Xpert MTB/RIF (Xpert) is an automated molecular test recommended by World Health Organization (WHO) for diagnosis of tuberculosis (TB). This study evaluated the effect of Xpert implementation on the detection of pulmonary TB (PTB) and rifampicin-resistant TB (RR-TB) cases in Shanghai, China.Xpert was routinely implemented in 2018 for all presumptive PTB patients. All PTB patients above 15 years-old identified within the Provincial TB Control Program during the first half of each of 2017 and 2018, were enrolled to compare the difference in proportions of bacteriological confirmation, patients with drug susceptibility test (DST) results for rifampicin  and RR-TB detection before and after Xpert’s implementation.p-values < 0.05). Among 1103 PTB patients who completed sputum smear, culture and Xpert testing in 2018, Xpert detected an additional 121 (11%) PTB patients who were negative by smear and culture, but missed 248 (23%) smear and/or culture positive patients. Besides, it accounted for an increase of 9% in DST coverage and 1% in RR-TB detection. The median time from first visit to a TB hospital to RR-TB detection was 62 days (interquartile range -IQR 48–84.2) in 2017 vs. 9 days (IQR 2–45.7) in 2018 . In the multivariate model, using Xpert was associated with decreased time to RR-TB detection .A total of 6047 PTB patients were included in the analysis with 1691 tested by Xpert in 2018. Percentages of bacteriological confirmation, DST coverage and RR-TB detection in 2017 and 2018 were 50% vs. 59%, 36% vs. 49% and 2% vs. 3%, respectively (all Integrating Xpert with smear, culture and culture-based DST in a routine setting significantly increased bacteriological confirmation, DST coverage and RR-TB detection with a dramatic reduction in the time to RR-TB diagnosis in Shanghai, China. Our findings can be useful for other regions that attempt to integrate Xpert into routine PTB and RR-TB case-finding cascade. Further study should focus on the identification and elimination of operational level challenges to fully utilize the benefit of rapid diagnosis by Xpert. China has the second highest tuberculosis (TB) and multidrug-resistant/rifampicin-resistant TB (MDR/RR-TB) incidence in the world . Early dMycobacterium tuberculosis (MTB) and resistance to rifampicin (RIF), providing results within 2 h. Clinical validation trials have demonstrated high sensitivity and specificity of the test for both MTB and RIF-resistance detection in different settings [Xpert® MTB/RIF assay  (Xpert) is a rapid test for TB diagnosis currently endorsed by the WHO , which ssettings –7. Seversettings , 9 and csettings , 11. Thesettings . The usesettings –15.In Shanghai, China, sputum specimens are collected for all presumptive PTB patients to perform smear microscopy and culture. Culture-based drug susceptibility test (DST) for isoniazid (H), rifampicin (R), ethambutol (E), and streptomycin (S) is routinely conducted for culture positive MTB strains to identify MDR-TB , 17. WitIn 2018, Shanghai launched a large scale project funded by the local government to test all presumptive PTB patients using Xpert at their first visit to designated TB hospitals. It aimed to increase bacteriological confirmation and DST coverage among TB patients and to shorten the delay of RR-TB detection. We conducted this study to evaluate the effect of Xpert implementation on the detection of PTB cases and RIF-resistance, including time to RR-TB detection and risk factors associated with RR-TB delay.Primarily, this was a cross-sectional study utilizing routinely collected programmatic data for secondary analysis. In addition, we performed a retrospective cohort  to identify time to RR-TB detection and the factors associated with it.There are 30 designated TB hospitals in Shanghai  in charge of TB diagnosis and treatment, and more than 240 community health centers in charge of patient management (ie. DOTS). The Xpert project (detailed below) was initiated on January 1st, 2018. By November 2018 when the analysis was performed, only data of the first half of 2018 was available. Therefore, all PTB patients 15 years of age and above identified within the Provincial TB Control Program in the first half of 2018 were included in this study. Patients identified in the first half of 2017 were also enrolled for comparison.All presumptive PTB patients  detected in a general hospital or a community health center are referred to the district TB hospital where sputum smear, liquid culture, chest radiograph and other necessary tests are carried out for diagnosis. Culture positive strains are transferred to the TB reference laboratory at Shanghai Center for Disease Control and Prevention (CDC) to conduct a Lowenstein-Jensen culture for species identification and DST for first-line drugs (H/R/E/S); while one referral TB hospital, Shanghai Pulmonary Hospital, conducts liquid culture for species identification and DST for first-line (H/R/E/S) and 3 sec-line drugs (Aminoglycoside/Ofloxacin/Cycloserine). The TB reference laboratory at Shanghai CDC is responsible for the quality control of all TB laboratories in the 30 surrounding TB hospitals.According to the national standard of diagnosis for PTB , confirmRR-TB patients are subject to an expert panel  for finaA total of 17 TB hospitals were equipped with Xpert platforms. Laboratory staff were trained by the reference laboratory of Shanghai CDC on the operation and reporting. Since January 1st, 2018, an Xpert test has been performed for all presumptive PTB patients along with sputum smear and culture at their first visit to one of these TB hospitals. Patients in hospitals without Xpert platforms were transferred to a nearby hospital where Xpert testing was available.The Global Laboratory Initiative (GLI) and the WHO , 22 suggData was extracted from the National TB management information system into Microsoft Excel® . A bacteriologically confirmed case was defined as a PTB case with positive results of smear, culture or Xpert. A DST covered case was defined as a PTB case with DST results for RIF. The delay of RR-TB detection was defined as time (days) from the date of first visit to a TB hospital to the date RIF-resistance was detected by either conventional DST or Xpert.p-value of less than 0.05 was considered significant.Analysis was performed using R® software (3.5.1). Demographic, clinical and diagnosis characteristics were analyzed and presented in frequencies and medians with an interquartile range (IQR) for categorical and continuous variables, respectively. Overall bacteriological confirmation and RR-TB detection was reported in frequencies. Comparison of frequencies was done using chi-square test, and medians using Wilcoxon rank-sum test. We estimated the probability of RR-TB detection using the Kaplan-Meier method and subgroups were compared using the log rank test. Cox proportional hazard model was used to investigate the factors associated with RR-TB detection. Unadjusted hazard ratios (HR) were calculated from a bivariate analysis. Adjusted hazard ratios were estimated by multivariate analysis. The final model was adjusted for all the variables from the bivariate analysis. A There were 6357 PTB patients registered in the first half of each of 2017 and 2018. After excluding patients under 15 years old (31 cases) and those diagnosed as nontuberculous mycobacteria , 6047 PTB patients were included in the analysis , with a median age of 44 years (IQR 27–62). The majority were male (68%), new patients (93%), local residents (54%) and registered in referral hospitals (69%), with no significant difference between 2017 and 2018.p-value < 0.05)  were new cases. Proportions of bacteriological confirmation, DST coverage and RR-TB detection were significantly higher in 2018 than in 2017 (Among 1691 (54%) PTB patients who underwent for Xpert in 2018, 909 (54%) were MTB positive, and 69 (8%) RIF-resistant . When Xpert was used, the delay to RR-TB detection was significantly shorter compared to conventional DST .The median of delay to RR-TB detection was 62 days IQR 48–84) in 2017 vs. 9 days (IQR 2–45) in 2018  .To our knowledge, this is the first real-world, population-based study that evaluates the effect of Xpert on PTB and RIF-resistance detection at a provincial level in China. The majority of research on Xpert in China has been confined to laboratories and hospitals –26, focuOur study found a significant increase (11%) in bacteriological confirmation when Xpert was offered to all presumptive patients. This was similar to studies in other countries and regions , 27–29, We also observed an increase in DST coverage and RR-TB detection in our study due to the use of Xpert, which was similar to other studies , 31. As In our study, the delay of RR-TB detection was dramatically reduced from 62 to 9 days after implementing Xpert. Findings in other countries , 32–34 hUniversal DST is one component of the End TB strategy. The WHO suggested that DST coverage reach 100 and 90% of TB patients be tested using a WHO-recommended rapid diagnostic (WRD) at the time of diagnosis by 2025 [Our findings provide critical insights about using Xpert in a routine setting in China. However, TB incidence and TB control resources vary significantly throughout the country. It is notable that the experience in Shanghai should be tailored to fit for other regions in the country accordingly.There are some limitations in our study. Due to the observational study design, the implementation of Xpert was not controlled, 45% patients did not undergo the test. This might underestimate the effect of Xpert on the detection of PTB and RR-TB. Factors associated with low Xpert implementation should be identified to strengthen the scaling-up in the next phase. Our Xpert project was funded by local government and free for patients. Whether this is sustainable still needs to be determined. Previous studies have indicated that cost-effectiveness varied in different settings and algorithms, e.g. initial use for all presumptive TB cases or use only in sputum smear microscopy negative cases –39. FinaThis study provided useful evidence regarding the potential use of Xpert in a high-burden country to increase PTB and RR-TB detection, as well as decrease RR-TB detection delay. It might be helpful for regions with similar settings when considering integrating this technique into routine PTB and RR-TB case-finding algorithms. Operational level problems should be identified and eliminated to fully utilize the benefit of rapid diagnosis by Xpert.


BACKGROUND: Disabilities among older adults are associated with cumulative adversities such as low socioeconomic status (SES), poor nutrition, and lack of access to medical care and education. However, there is little evidence on the long-term association between education and disability status among older adults in Iceland. The aim of the study was to examine the association between mid-life education and prevalence of disability in activities of daily living (ADL) and mobility disability in late-life using 25 years of longitudinal data. METHODS: A large community-based population residing in Reykjavik, Iceland participated in a longitudinal study with an average of 25 years of follow-up  Mid-life education was categorized into 2 groups (primary and secondary versus college and university). Disability status in late life was defined with ADL and mobility disability with a binary outcome (no difficulty versus any difficulty). Logistic regression analysis was used to examine the association. RESULTS: After controlling for age and gender, and midlife health risk factors, those who had high education at mid-life were less likely to have ADL disability (Odds Ratio (OR) = 0.75, 95% Confidence Interval (CI): 0.64 ~ 0.88, P ≤ 0.001) and mobility disability  compared with those who had low education in mid-life. CONCLUSION: People with high mid-life education were less likely to have ADL and mobility disability after 25 years later.


Early hospital readmissions or deaths are key healthcare quality measures in pay-for-performance programs. Predictive models could identify patients at higher risk of readmission or death and target interventions. However, existing models usually do not incorporate social determinants of health (SDH) information, although this information is of great importance to address health disparities related to social risk factors. The objective of this study is to examine the impact of social determinants of health on predictive models for potentially avoidable 30-day readmission.We extracted electronic health record data for 19,941 hospital admissions between January 2015 and November 2017 at an academic medical center in New York City. We applied the Simplified HOSPITAL score model to predict potentially avoidable 30-day readmission or death and examined if incorporating individual- and community-level SDH could improve the prediction using cross-validation. We calculated the C-statistic for discrimination, Brier score for accuracy, and Hosmer–Lemeshow test for calibration for each model using logistic regression. Analysis was conducted for all patients and three subgroups that may be disproportionately affected by social risk factors, namely Medicaid patients, patients who are 65 or older, and obese patients.The Simplified HOSPITAL score model achieved similar performance in our sample compared to previous studies. Adding SDH did not improve the prediction among all patients. However, adding individual- and community-level SDH at the US census tract level significantly improved the prediction for all three subgroups. Specifically, C-statistics improved from 0.70 to 0.73 for Medicaid patients, from 0.66 to 0.68 for patients 65 or older, and from 0.70 to 0.73 for obese patients.Patients from certain subgroups may be more likely to be affected by social risk factors. Incorporating SDH into predictive models may be helpful to identify these patients and reduce health disparities associated with vulnerable social conditions. Early hospital readmissions are both common and costly . For exaHealth disparities are of particular relevance to hospital readmissions because patients with low socioeconomic status (SES) and those living in disadvantaged neighborhoods are more likely to be readmitted –7. Low SHowever, from the care delivery perspective, there is little doubt that accurately identifying patients who will be readmitted due to social risk factors can help reduce unnecessary healthcare utilization , 15. HosOne avenue that holds the potential to improve these strategies and programs is the inclusion of SDH in predictive models for 30-day readmission. Improved predictive modeling can be particularly helpful in low-resource settings, allowing community hospitals to effectively identify and target patients at high risk for potentially avoidable readmissions. A recent review identified 73 unique readmission prediction tools developed between 2011 and 2015 for a variety of patient populations and health conditions . Health We hypothesized that the performance of a widely used hospital readmission risk prediction model would improve with the inclusion of individual-level and community-level SDH. We additionally hypothesized that the effects of adding SDH to predictive models would be greatest among the most vulnerable patient subgroups without resources to compensate for social risk factors. We therefore examined the performance of the model, and the impact of incorporating SDH, for three subgroups: patients receiving Medicaid , obese patients, and patients 65 or older. Compared to other patients, these three groups of patients appeared likely to be disproportionately affected by vulnerable social conditions due to their low income, multiple chronic conditions, or disability.This is a retrospective cohort study. Our goal was to update the Simplified HOSPITAL score, which predicts 30-day readmissions across disease conditions, with the inclusion of SDH data , 22. To Using existing institutional infrastructure for secondary use of electronic health record (EHR) data , we extrThe study was approved by Weill Cornell Medicine’s Institutional Review Board with a waiver of consent.Our outcome is the potentially avoidable hospital readmission or death 30 days after an eligible hospital admission. We added death as part of our composite outcome, as early death after discharge also indicates adverse quality of care . To idenWe applied the Simplified HOSPITAL score model to predict potentially avoidable 30-day hospital readmission or death , 22. TheWe extracted individual-level SDH from the EHR, including sex, race , ethnicity , primary language , marital status , and insurance type . Prior studies have found that these variables are associated with increased risk of readmission –38. For For community-level SDH, we first reviewed the relevant literature to identify SDH with a theoretical basis for potential association with readmission ; felony rate, walkability score, Gini income inequality coefficient, a composite score reflecting household composition and disability, and a composite score for minority status and language. S2 Table in the We first compared differences in demographics, comorbidities, and SDH between admissions with and without 30-day readmission or death. Demographic characteristics include age, age categories, and all the individual-level SDH . Comorbidities include Charlson comorbidity score , HOSPITAWe first tested the performance of the Simplified HOSPITAL score using logistic regressions. We then ran three SDH-augmented models by adding: (1) all individual-level SDH drawn from the EHR; (2) Census tract-level neighborhood SDH; (3) All individual- and community-level SDH together. We ran these models using all patients, then performed subgroup analyses on Medicaid patients, patients 65 and older, and obese patients (BMI > 30). We used cross-validation to examine the predictive value of SDH. For each patient cohort , we first randomly split the entire dataset into training set (75%) and testing set (25%). We conducted 3-fold cross-validation using training set. The whole training set was first partitioned into three near-equal parts. Three iterations of training and validation were then performed. Within each iteration, a model was trained on two parts, and then the fitted model was applied to the held-out part. The area under the receiver operating characteristic curve (AUC) was calculated on the held-out part. The model with the highest AUC on the held-out set was chosen as the final model. This model, with the same regression coefficients, was then applied to the remaining 25% of data to examine the performance of the model. We presented the regression results of models with both individual- and community-level SDH in the S3 Table in p value ≥ 0.05 for the significance test means that the predicted and observed outcomes are consistent, implying goodness of fit for the predictive model [For each model, we calculated the C-statistic for discrimination (> 0.7 indicates good discrimination), which refers to the ability to differentiate between admissions followed versus not followed by a 30-day potentially avoidable readmission or death . We alsove model , 22. Finve model , 47. Forve model .All analyses were completed using Stata/MP version 14 (StataCorp).Our study included 19,941 index admissions from 12,537 unique patients during the study period . Among aCompared to patients without potentially avoidable 30-day readmission or death, those with potentially avoidable 30-day readmission or death were older (63.5 versus 62.2), more likely to be black (19.5% versus 17.7%) and Hispanic (16.8% versus 14.9%), more likely to speak English as a primary language (78.8% versus 75.6%), more likely to be dually enrolled in Medicare and Medicaid (33.9% versus 27.0%), more likely to be admitted from the ED (85.9% versus 83.5%), and more likely to have a BMI over 30 (20.3% versus 18.6%). Patients with avoidable 30-day readmission or death also had higher Charlson comorbidity scores (5.0 versus 3.9), and higher HOSPITAL scores (3.6 versus 2.6). Patients with avoidable 30-day readmission or death also had higher proportion of foreign-born residents, lower walkability score, and poorer conditions in household composition and disability in their neighborhood.The Simplified HOSPITAL score performed similarly on our data set as compared to the original paper , with a In accordance with our second hypothesis, we examined performance of the predictive model in the three vulnerable subgroups .Within vulnerable subgroups, the Simplified HOSPITAL score produced better discrimination (C-statistic: 0.66–0.70) and fairly similar accuracy (Brier score: 0.09–0.11) as compared to the overall population. Calibration was poor for all subgroups (Hosmer-Lemeshow goodness-of-fit P < 0.05). Adding individual-level SDH made statistically significant improvements in the C-statistic for patients 65 or older and calibration for Medicaid patients without affecting the Brier score. Adding community-level SDH produced greater improvements in the C-statistic among obese patients .Incorporating both individual and community-level SDH significantly improved discrimination among all subgroups but had little impact on accuracy or calibration.Collinearity diagnostics indicated sufficiently low multicollinearity in all models. The highest VIF value is 4.2, which is lower than the widely used threshold of 10 to indicate multi-collinearity .For all patients and patients in each subgroup, the event NRI (for readmission or death) was positive when adding individual SDH, community SDH, or both , indicatDespite evidence that SDH are significantly associated with health outcomes, we found that incorporating individual- or community-level SDH did not meaningfully improve the prediction of potentially avoidable 30-day readmission for a general patient population. However, adding individual- or community-level SDH improved model performance among patient subgroups who may not be able to compensate for social risk factors, namely Medicaid patients, patients who are 65 or older, and obese patients.Our results are consistent with previous literature, which found that adding SDH information did not significantly improve the prediction of some health-related outcomes , 50. It It is also plausible that readmission is primarily determined by clinical factors captured in the HOSPITAL score, or by other process factors not captured in our model, such as care delivery processes and provider-level variables , 52. ExiWe found adding SDH improved readmission risk prediction for vulnerable subgroups, including Medicaid patients, patients who are 65 or older, and obese patients. Medicaid patients with low income are disproportionately likely to have health-related unmet social needs, such as food and housing . In addiThis study has several limitations. First, we used EHR data from a single academic medical center. Patients might have been readmitted to hospitals other than the index hospital, artificially deflating readmission counts. This would create particularly strong biases if patients with disadvantaged social conditions are more likely to be readmitted to other hospitals, which, if true, would be likely to bias our analyses toward the null. Second, this study was based on a group of patients from New York City, and our results may not be generalizable to other populations. For example, a key transportation variable in New York City is proximity to public transportation. In other regions of the US, access to a car may be a more important variable. Third, some important individual-level SDH, such as income, education, and occupation were not available in this study. Adding these SDH may have a different impact on model performance. Fourth, SDH and clinical factors may be associated with readmissions in interactive ways. Using machine learning-based methods may be able to identify important interaction terms. Fifth, capture of post-discharge mortality is poor in EHR data. Further research may focus on supplementing the data set with other sources, including both insurance claims data and data from other NYC healthcare system, such as organizations participating in centralized clinical data research networks , to addrWe examined the value of SDH in predicting potentially avoidable 30-day readmission and we found SDH did not improve risk prediction for the overall patient population. However, SDH improved the performance of models for three vulnerable patient populations, namely, Medicaid patients, obese patients, and patients 65 and older. Future studies may examine more SDH that are related to readmission and develop the prediction model based on other feature selection methods.S1 Appendix(DOCX)Click here for additional data file.


H test was used for continuous variables since they were not normally distributed. Moreover, the Spearman rank correlation coefficient (rho) was used to determine the relationship between different variables. There was a significantly positive correlation between the vaccine coverage (%) and both of total cases per one million populations  and deaths per one million populations . Moreover, there was a significant correlation between different income groups and each of vaccine coverage (%) , total cases per one million populations , and deaths per one million populations . All claims regarding the possible protective effect of Polio vaccination do not have any support when analyzing the related data. Polio vaccination efforts should be limited to eradicate the disease from endemic countries; however, there is no evidence to support the immunization with live-attenuated vaccines for the protection against COVID-19.We conducted the current analysis to determine the potential role of polio vaccination in the context of the spread of COVID-19. Data were extracted from the World Health Organization’s (WHO) Global Health Observatory data repository regarding the polio immunization coverage estimates and correlated to the overall morbidity and mortality for COVID-19 among different countries. Data were analyzed using R software version 4.0.2. Mean and standard deviation were used to represent continuous variables while we used frequencies and percentages to represent categorical variables. The Kruskal-Wallis The online version contains supplementary material available at 10.1007/s11356-021-12861-6. As of December 2019, a significant number of patients with “unknown viral pneumonia” connected to a local Seafood Wholesale Market were identified in Wuhan City, China  and inactivated poliovirus vaccine (IPV) have been used to eradicate poliovirus. In addition to the protective properties of live-attenuated vaccines against specific microorganisms, various vaccines have been shown to induce non-specific immune effects. Recent epidemiological data suggest that the use of live-attenuated vaccines , measles vaccine, and OPV) may result in the induction of non-specific effects in the immune system  Global Health Observatory data repository regarding the polio immunization coverage estimates   were used to represent continuous variables while we used frequencies and percentages to represent categorical variables. The skewness and Kurtosis tests were used for testing the normal distribution of continuous variables. The Kruskal-Wallis p-value < 0.001) and deaths per one million populations   and a negative one with deaths per one million populations ; however, these correlations were not statistically significant  and COVID-19 statistics in different countries Tables . There w1) Figs. . On furtnt Figs. .Table 1p-value < 0.001), total cases per one million populations , and deaths per one million populations  , total cases per one million populations , and deaths per one million populations    .Fig. 5TOral poliovirus vaccine (OPV) and inactivated poliovirus vaccine (IPV) are the two major types of vaccines that protect individuals against poliovirus. Polio is now recognized as the main vaccine-preventable disease after receiving the required attention and support for its complete eradication  compared to countries that implemented polio vaccination policies at later a date. This indicates that the earlier the universal polio vaccination policy was deployed, the greater the number of COVID-19 cases as well as the greater the number of mortality cases per one million populations.Countries were divided into low, low-middle, upper-middle, and high-income countries based on the World Bank classification. We noted that low-income countries had the lowest mean poliovirus (3rd dose) vaccination coverage rates of 60% compared to the 92% mean coverage rate of high-income countries. Surprisingly, these low-income countries had much lower mortality cases compared to high-income countries (mean deaths per 1 million populations: 0.66 vs 89.16). In the same context, the total number of COVID-19 cases was dramatically lower in low-income countries compared to high-income ones (mean: 16.43 vs 1493.04 new cases per one million populations). These differences were noted to be highly significant, indicating that coverage of polio vaccination policies is not correlated with a protective effect against COVID-19 infection. However, it should be noted that a considerable proportion of low-income countries did not report the rates of mortality or report no deaths due to COVID-19, while nearly half low-income countries reported mortality rates < 1 per one million populations. Therefore, the aforementioned differences based on the income of countries could be attributed to the underreporting of these countries.On 28 March 2020, Miller et al.  was the main contributor to our results because these data were not available. Notably, underreporting in low-income countries is a potential limitation to our findings. Therefore, our results should be interpreted with caution. Although the data regarding the immunization data quality—in low- and middle-income countries—are limited in the literature, coverage values were found to be inflated and adjusted in the official reports


The feasibility and safety of same-day discharge after transvenous implantable cardioverter-defibrillator implantation is well-established. However, subcutaneous ICDs (S-ICDs) are now increasingly being implanted, and the feasibility, safety, and potential cost savings associated with same-day discharge after S-ICD placement has not been widely investigated. In a small cohort of patients (n = 24) who underwent S-ICD implantation at our institution, 54% were successfully discharged on the same day as their implant procedure. Procedure-related complications were not apparent in this sampling and the reduction in health care costs was high, suggesting this protocol has immense benefit in today’s health care environment. As such, same-day discharge of S-ICD patients is appropriate to consider and should receive further attention. Historically, however, S-ICD patients have not been discharged on the day of implantation secondary to the use of general anesthesia to facilitate implantation. However, it may be reasonable to consider same-day discharge in select patients.Implantable cardioverter-defibrillators (ICDs) have been demonstrated to reduce the incidence of sudden cardiac death in select patients. The feasibility and safety of same-day discharge after transvenous ICD systems is well-established; same-day discharge after transvenous ICD implantation improves patient satisfaction, increases bed availability, and facilitates overall hospital cost savings without adversely affecting readmission rates.To our knowledge, the feasibility, safety, and potential cost savings associated with same-day discharge after S-ICD placement have not been investigated. Therefore, this study sought to evaluate the safety, feasibility, and cost reductions associated with same-day discharge after S-ICD implantation for primary prevention in comparison with those among patients observed overnight after implantation.We prospectively analyzed 24 consecutive patients who presented to our institution to solely undergo S-ICD implantation for a primary prevention indication over an eight-month period. This study was reviewed by the Office of Human Subjects Protection of our research institute and was deemed to be a quality improvement study and not a human research study so therefore did not require institutional review board approval. Patients were excluded if they were scheduled for a lead or device revision, lived more than 30 miles from an emergency department, did not have a driver or responsible party to stay with them overnight, developed a postprocedure complication while in the hospital, or the procedure was completed after 1:00 PM.A protocol was developed and implemented for same-day discharge of S-ICD patients. The implanting physician, rounding nurse practitioner, electrophysiology laboratory staff, and device clinic staff were all assigned specific responsibilities to ensure smooth same-day discharge and coordination for follow-up. The nurse practitioner was responsible for evaluation of the patient prior to discharge, reviewing the same-day device interrogation and chest X-ray, and providing device education including activity restrictions and follow-up details to the patient. The patient also received a follow-up telephone call from the nurse practitioner the next day. The patient was scheduled to undergo an incision check one week after at the practice device clinic and an in-clinic device interrogation three months after device implantation, respectively.The 24 patients were 17% female and 83% male, with ages ranging from 23 to 82 years (average age: 62.1 years). As stated, all devices were implanted for a primary prevention indication. Fifteen (62.5%) patients had a diagnosis of nonischemic cardiomyopathy (NICM) and nine (37.5%) had that of ischemic cardiomyopathy (ICM). The average ejection fraction for these patients was 27.8% (range: 15%–35%). One patient had a prior ICD, extracted in a previous setting.The study participants were divided into two groups: group A consisted of patients successfully discharged on the same day (n = 13 patients) and group B consisted of patients observed overnight after implantation (n = 11 patients). Same-day discharge was defined as discharge home prior to 9:00 PM on the same calendar day as implantation.For patients in both groups, electronic medical records were reviewed three months postimplantation. Outpatient and inpatient records during this time frame were reviewed to identify any complications potentially related to S-ICD implantation, including as surgical site bleeding, hematoma, lead dislodgement, infection, or cardiac injury.Of the 24 patients included in this study, 54% were successfully discharged on the same day. Patients who were not discharged on the same day experienced excessive postprocedural pain and/or the patient/implanting physician preference mandated an overnight stay. No postprocedural complications were reported in the initial three-month period postimplantation for patients in either group. Of note, two patients in group A were readmitted within 30 days of discharge (one for an acute heart failure exacerbation at 20 days postimplantation and one for symptoms of fatigue at 15 days postimplantation). Neither of these readmittances were thought to be directly related to device implantation or would have necessarily been avoided had these patients stayed overnight after their procedure. Device interrogation or reprogramming prior to the initial three-month interrogation was not required in either group..The demographics of the two groups were very similar. In group A, 53.8% of patients had NICM and 46.2% had ICM. In group B, 72.7% patients had NICM and 27.2% had ICM. Age, gender, and average ejection fraction were not a factor in predicting which patients were discharged on the day of implantation. The average ages in groups A and B were 60 years and 64.3 years, respectively, while the average ejection fractions were 27.4% and 25.4% . This improved hospital bed access by 17.5 hours per patient. The overall hospital savings achieved by discharging patients on the same day were calculated by comparing hospital costs and hospital charges. This calculation demonstrated a modest reduction of 5.3% in the cost of care per patient with discharge on the same day, or an average of $1,664.48 per patient . A reduction in nursing costs largely accounted for these savings.Separately, the average time spent in the hospital per patient following S-ICD implantation demonstrated a time savings of 63% when patients were discharged on the same day Current procedural billing and coding protocols for ICD implants classifies S-ICD implantation as an outpatient procedure, and, therefore, overnight resource utilization cannot be charged for . Consequently, all ICD implants are billed and coded the same regardless of the length of stay even though resource utilization is significantly less when a patient is discharged on the same day.In an environment of increasingly strained health-care resources, it is paramount to recognize best practices that improve efficiency and economics. Implementing structured postprocedure protocols can reduce unnecessary hospitalizations. The use of telephone and telemedicine monitoring can further provide virtual follow-up to ensure patients’ postprocedural recovery is progressing as anticipated and no lingering questions remain. A potentially novel role for a postprocedure navigator may allow for expansion of same-day protocols and could improve the overall patient experience and care.It is appropriate to consider same-day discharge in select patients who are determined as eligible for such per institution discretion after undergoing S-ICD implantation for a primary prevention indication. In a small cohort of patients undergoing S-ICD implantation over an eight-month period, same-day discharge was safe and feasible. Procedure-related complications were not apparent, and a reduction in costs associated with health care may be realized as a result.


Background: Dietary weight-loss interventions often fail among migrant populations. We investigated the practicability and acceptability of a culturally adapted dietary weight-loss intervention among Ghanaian migrants in Berlin. Methods: The national guidelines for the treatment of adiposity were adapted to the cultural characteristics of the target population, aiming at weight-loss of ≥2.5 kg in 3 months using food-based dietary recommendations. We invited 93 individuals of Ghanaian descent with overweight or obesity to participate in a 12-weeks intervention. The culturally adapted intervention included a Ghanaian dietician and research team, one session of dietary counselling, three home-based cooking sessions with focus on traditional Ghanaian foods, weekly smart-phone reminders, and monthly monitoring of diet and physical activity. We applied a 7-domains acceptability questionnaire and determined changes in anthropometric measures during clinic-based examinations at baseline and after the intervention. Results: Of the 93 invitees, five participants and four family volunteers completed the study. Reasons for non-participation were changed residence (13%), lack of time to attend examinations (10%), and no interest (9%); 64% did not want to give any reason. The intervention was highly accepted among the participants . Over the 12 weeks, median weight-loss reached −0.6 kg ; the diet was rich in meats but low in convenience foods. The median contribution of fat to daily energy intake was 24% (range: 16–40%). Conclusions: Acceptance of our invitation to the intervention was poor but, once initiated, compliance was good. Assessment centers in the participants’ vicinity and early stakeholder involvement might facilitate improved acceptance of the invitation. A randomized controlled trial is required to determine the actual effects of the intervention. For abdominal obesity (waist circumference > 102 cm for men and >88 cm for women), these figures are 15% in men and 71% in women [Adiposity is a growing public health problem, already affecting more than 2 billion adults worldwide. Of these, over 650 million individuals have obesity (body mass index (BMI) ≥ 30.0 kg/m2) . Current2) [2) . Among t2) [2)  and thei2) [2) . Ghanaia2) [2) ,10. In f2) [2)  of whom in women .Lifestyle modification constitutes the first-line treatment for obesity because it is safe and usually effective , but dieGiven the obesity-related health problems and no previous interventions targeting migrants from sub-Saharan Africa in Germany, this feasibility study aimed at evaluating the practicability and the acceptability of a culturally adapted dietary weight-loss intervention among a group of well-characterized Ghanaian adults in Berlin. As a secondary objective, we aimed at exploring the weight-loss effect on changes in cardio-metabolic risk factors.n = 547) who were eligible (n = 93). Shopping vouchers (10 €) were offered for each completed examination visit as incentives to participate. In brief, the RODAM study was implemented between 2012 and 2015 and comprised Ghanaians aged 25–70 years living in rural and urban Ghana as well as in Amsterdam, Berlin and London. The study used standardized instruments for data collection at all the study sites, comprising questionnaire-based interviews, physical examination, and biological sample collection.For the present ADAPT study , participants of the multi-center, cross-sectional Research on Obesity and Diabetes among African Migrants (RODAM) study  were re-2 or waist circumference >94 cm for men or >80 cm for women, Ghanaian migrant status (defined as being born in Ghana or having two parents born in Ghana), age ≥ 25 years, and the cooperation of the family cook or volunteer supporting the participant’s behavioral change. The exclusion criteria were known diabetes, receiving long-term oral corticosteroids or weight-loss medication, and current pregnancy.The inclusion criteria were BMI ≥ 25.0 kg/mThe study protocol was reviewed and approved by the Ethics Committee of Charité-Universitaetsmedizin Berlin (EA1/151/17). The study was registered retrospectively at the German Registry for Clinical Trials (DRKS00013767). Prospective registration was not performed, because the study has not been planned as a randomized controlled trial. Therefore, the study was registered after the participants were recruited. The authors confirm that all ongoing and related trials for this intervention are registered. In order to finish the program before Christmas, the baseline assessments started on 2 October 2017, and the last visit was performed on 18 December 2017. All participants gave informed written consent prior to their enrolment.We adapted the guidelines for the treatment of adiposity by the German Society of Adiposity  Table 1Table 1. Linguistic, constituent-involving and socio-cultural adaptations seem to be the most successful for weight-loss and dietary changes ,16,23. Tn = 547) [n = 93). We invited them by phone. Reasons for non-participation were documented. Upon agreement, an appointment at the study center was scheduled for the baseline examination. The individual schedule for interviews and physical examinations is presented in We used documented contact details of previous RODAM participants in Berlin (n = 547)  who fulfTrained personnel conducted questionnaire-based interviews with the active study participants but not the family volunteers. These were performed in the participant’s preferred language, either English or a local Ghanaian language. Demographic characteristics included age and sex.Affective attitude: I enjoyed the diet and sports program;Burden: I easily integrated the diet and sports program in my daily life;Ethicality: The diet and sports program was important for me;Intervention coherence: I easily understood the diet and sports program;Opportunity costs: I am convinced by the diet and sports program;Perceived effectiveness: The diet and sports program will improve my health;Self-efficacy: The diet and sports program will help me to change my lifestyle.The acceptability questionnaire was administered in weeks 7 and 12. We used a questionnaire that was based on the theoretical framework of acceptability, comprising seven component constructs :AffectivThere were six response categories to avoid the possibility of neutral answering, ranging from “strongly disagree” to “strongly agree”.For information about the baseline habitual diet, we used data of the previous RODAM study, that had been collected with the semi-quantitative Ghana-Food Propensity Questionnaire (Ghana-FPQ) . The GhaAgain, we used self-reported physical activity data of the previous RODAM study as our baseline information. Physical activity had been assessed by means of the WHO STEPwise approach to chronic disease risk factor Surveillance (STEPS) questionnaire . The samSimilar to the questionnaire-based interviews, physical examinations were conducted only among the active study participants but not their family volunteers. A trained nutrition scientist conducted the physical examinations among participants in light clothes and without shoes. The measurements comprised body weight , height , waist circumference (cm) and hip circumference (cm) using a measuring tape. Systolic and diastolic blood pressures (mmHg) were measured  in triplicates after an appropriate resting time. The mean of the last two measurements was used for analysis.Baseline characteristics are presented as median and range for continuous variables and as percentage for categorical data. We calculated differences between baseline and follow-up data for secondary outcomes, i.e., weight-loss and lifestyle factors. All analyses were performed using Microsoft Excel 2016 .2 (range: 23.3–35.1 kg/m2) and the median waist circumference was 98.3 cm (range: 86.0–100.0 cm).Two men and four women attended the ADAPT baseline examination. We contacted 93 eligible individuals by phone. As depicted in The changes in anthropometric measures, lifestyle characteristics and clinical variables between baseline examination and follow-up are shown in After 12 weeks, the median weight-loss was −0.6 kg , and median BMI and median waist circumference tended to be lower . For lifThis feasibility study examined the practicability and the acceptability of a 12-weeks culturally adapted, dietary weight-loss intervention among Ghanaian migrants with overweight in Berlin. Our study was the first attempt in Germany to provide a culturally adapted lifestyle intervention for West-African migrants. Innovative adaptations comprised linguistic, constituent-involving and socio-cultural components: a Ghanaian research team and an ethnically matched dietician to facilitate culturally appropriate communication and culinary knowledge to deliver nutrition education, respectively. Nudging, through regular text and image messaging, enhanced self-empowering and frequent assessments of dietary behavior and physical activity during the intensive intervention period facilitated self-contracting to achieve the individual weight-loss goals.For ethnic minorities in the United States, Nierkens et al. have reported response rates ranging from 31% to 97% for culturally adapted interventions aiming at smoking cessation, diet, and physical activity . The lown = 46), few respondents associated hypertension with adiposity, even though many had overweight [Still, this target population appears to be highly mobile as indicated by the proportions of individuals who moved (8/93) or traveled (3/93). The poor intervention uptake may also stem from unawareness in the target population for adiposity as a risk factor of chronic diseases. In fact, in a qualitative study with Ghanaian migrants in Amsterdam  over a period of 6 months [The present feasibility study indicates that the culturally adapted dietary intervention may reduce body weight, BMI and waist circumference in this population over a period of 12 weeks, although the study lacks a comparison group. This corroborates previous findings that culturally tailored and facilitated interventions produce better outcomes than generalized interventions ,16,17,366 months . To estaRegarding the dietary behavior among Ghanaian migrants, core food items of the traditional diet are maintained even several years after migration, including starchy roots and tubers, bread, rice, and leafy vegetables . These tSince the study did not aim to test an effect of the intervention, no sample size calculations were performed. Owing to the small sample size, which impairs external validity of our findings, we refrained from concluding any effects of the intervention regarding biomedical data. The lack of a comparison group limits the interpretation of our acceptability results, because the poor participation rate could either result from the intervention program per se or from the reported reasons. Selection bias might have occurred, if study participants differ from non-participants in unobserved characteristics. The acceptability questionnaire used in this study may involve subjectivity bias in which the participants might have different interpretations of items resulting in different endorsements of ratings. For the assessment of dietary intake, detailed information about eating times, portion sizes, recipes and their preparations were gathered by culture-specific assessment tools . HoweverThis feasibility study examined the practicability and the acceptability of a 12-weeks culturally adapted, dietary weight-loss intervention among Ghanaian migrants with overweight in Berlin. The study showed a low participation rate, but 5 out of 6 enrolled participants completed the intervention and rated the program as highly convenient. The dietary behavior during the intervention period still relied on starchy foods and animal-based products and was low in fruit consumption. Yet, the proportions of consumed vegetables and the contributions of macronutrients to energy intake adhered to international dietary guidelines.The present culturally adapted dietary weight-loss intervention for Ghanaian migrants in Germany has the potential to reduce adiposity and, thus, to prevent cardio-metabolic conditions in this vulnerable population group. In future studies, early stakeholder involvement, advocacy by community leaders, and sensitization of the Ghanaian community prior to the implementation are key factors for the success of this program. For the establishment of the actual weight-loss and its cardio-metabolic effects, a randomized, controlled trial is required.


Lancet on October 17th. The accompanying announcement by the Institute for Health Metrics and Evaluation (IHME) described GBD2019 as “the largest and most comprehensive effort to quantify health loss across places and over time”, including “more than 3.5 billion estimates of … 369 diseases and injuries … in 204 countries and territories” [The capstone papers on the Global Burden of Disease study 2019 (GBD2019), delayed by a diversion of resources to mapping covid-19, appeared in IHME had previously announced its move to a 3-year cycle of major model updates for most non-fatal causes and risk factors (but not causes of death) . Each fuNevertheless, headache disorders in 2019 ranked 14th among global causes of DALYs  . Seven nWhat about YLDs? In separate on-line estimates, headache disorders were the cause in 2019 of 46.6 million YLDs globally, 5.4% of total YLDs, with 88.2% of these attributable to migraine [There were variations according to World Bank region and country income level. Headache disorders were third cause of YLDs in East Asia & Pacific and in Middle East & North Africa, but second in Europe & Central Asia, fourth in South Asia and in sub-Saharan Africa, fifth in Latin America & Caribbean and (surprisingly) sixth in North America. They were third in countries classed by the World Bank as lower- or upper-middle-income, but fourth in low-income countries and fifth in those classed as high income. The association between headache and socioeconomic status has never been clear!GBD is wholly dependent on data. It applies highly sophisticated modelling to fill data gaps, “borrowing strength between locations and over time” . But extThe level-3 grouping of headache disorders in GBD2019 includes only specific diseases: migraine and tension-type headache (TTH), each with medication-overuse headache (MOH) as a sequela factored in according to the proportion of MOH attributed to it  (Table 2New to GBD2019 were bias adjustments to make allowance for low-quality sampling and survey methods, and for a range of other methodological deficiencies in data sources . This iscri de coeur [The authors of the GBD2019 report wrote: “The prominent position of headache disorders in the DALY rankings in the 10-24-year and 25-49-year age groups has received little attention in global health policy debates” . A similde coeur . They adde coeur . The disde coeur  – is conde coeur .


Introduction: Nearly all cervical cancer cases are caused by one of several high-risk strains of the human papillomavirus (hr-HPV). Transmasculine (TM) individuals  have low adherence to standard cervical cancer screening modalities. Introduction of self-collected vaginal swabs for hr-HPV DNA testing may promote initiation and adherence to cervical cancer screening among TM individuals to narrow screening disparities. The purpose of this study was to assess the rate of cervical cancer screening among TM individuals following the introduction of self-collected swabbing for hr-HPV DNA testing in comparison to clinician-administered cervical specimen collection.Methods: Rates of uptake and adherence to cervical cancer screening among TM individuals were assessed before and after the clinical introduction of self-collected swab testing in October 2017. Rates were compared with the rates of cervical cancer screening among cisgender women at a colocated Comprehensive Health Program during the time period of review.Results: Of the 121 TM patients seen for primary care in the 6-month baseline period before the October 2017 introduction of self-collected swabbing for hr-HPV DNA testing, 30 (25%) had cervical cancer screening documented in the electronic medical record. Following the implementation of self-swabbing, of 193 patients, 98 (51%) had a documented cervical cancer screening, a two-fold increase in the rates of adherence to cervical cancer screening (p<0.001).Conclusion: Self-collected swab testing for hr-HPV can increase rates of adherence to screening recommendations among an otherwise under-screened population. Food and Drug Administration as an alternative strategy to cytology-based cervical cancer screening methods. Clinician-collected cervical swab has a sensitivity for high-grade cervical squamous intraepithelial lesions (SILs) and invasive cervical cancer that is parallel or superior to that of a Pap smear.5–8 However, when validated with transgender men, vaginal self-swabs for HPV have been found to be 71.5% as sensitive as provider-collected swabs.9Papanicolaou (Pap) cytologic testing is the recommended screening modality for cervical abnormalities in individuals with a cervix from 21 to 65 years of age, with screening every 3 years if Pap cytology test results are normal.11 recent research suggests that TM patients experience the same level of risk relative to cisgender women for hr-HPV infection and associated progression of cervical abnormalities.12–14Despite myths that TM individuals are at low risk for sexually transmitted infections, including HPV and associated cervical abnormalities,15–17 However, available data precede widespread insurance coverage for these procedures, and the number of TM individuals who retain their uterus and cervix may change in the future. Routine preventive health screening including screening for cervical cancer, like for cisgender women, is recommended for TM patients who retain their cervix.9 Nationally, however, as many as one-third of all TM patients are not up-to-date with screening per U.S. clinical guidelines and TM individuals are more likely to have never undergone cervical cancer screening.19The majority (>80%) of TM individuals do not undergo gender-affirming genital surgery or removal of reproductive tract organs, and therefore retain a cervix.21 Self-collection has led to improved rates of adherence to specified American College of Obstetricians and Gynecologists (ACOG) and Centers for Disease Control and Prevention (CDC) screening recommendations among historically under-screened women, suggesting that it could be used as a viable and less invasive screening option.22–24 The practice of self-collected swabbing involves the use of a swab by the individual patient to collect a specimen from the patient's own vaginal canal, without the use of a speculum. Introduction of self-collected vaginal swabs for hr-HPV testing and cervical cancer screening for TM patients with retained female reproductive tract organs may promote increased cervical cancer screening and narrow screening disparities if offered after a traditional speculum exam is refused.9Among cisgender women, self-collected vaginal swabbing for hr-HPV testing as a primary method for cervical cancer screening has been found to be more acceptable than cervical cytological screening.25 to date there are no reports contrasting self- and clinician-collected swabs for hr-HPV testing in TM patients with respect to rates of uptake and adherence to preventive screening protocols.Although past research has confirmed the general acceptability of self-collected hr-HPV swabs over clinician-collected hr-HPV or Pap tests for TM individuals in the clinical setting,The purpose of this study was to assess rates of cervical cancer screening uptake and adherence among TM individuals before and after the clinic-wide introduction of a self-collected swab testing intervention. The self-swab option was offered once a traditional speculum exam with cytology collection was refused in patients ages 21–30 and as a primary screening modality in those over 30 with a history of no abnormal Pap testing.The study was conducted at the Center for Transgender Medicine and Surgery (CTMS) at Mount Sinai in New York City as part of an ongoing quality improvement project. Approval for publication was obtained from the Institutional Review Board at Mount Sinai.Eligibility for the study was determined by both patient interview and medical records. Those TM individuals ages 21–30 years who could not recall or document cervical cancer screening within the past 2–3 years with a history of no screening or negative screening along with those ages 30–65 years who could not recall or document screening within the past 5 years were considered eligible if they refused screening with a traditional speculum exam.The intervention consisted of medical providers offering self-swabs for HPV once a conventional speculum exam for cytology collection was declined. This process included discussion of follow-up options for cytology with hr-HPV screening. Providers instructed those declining conventional screening to insert a cotton-tipped swab into the vagina as far as comfortable, move it in a circular motion, and withdraw the swab. The swab was then vigorously agitated in a conventional ThinPrep™ preparation and sent to the Mount Sinai Health System clinical laboratory for processing.Rates of uptake and adherence to cervical cancer screening among TM individuals were assessed before and after the implementation of a self-collected swab testing intervention, introduced clinic-wide in October 2017. The baseline historical rate of cervical cancer screening was extracted from an electronic medical record through retrospective chart review of the TM patients who retained a cervix and attended at least one primary care visit from January 2017 through June 2017. Cervical cancer screening rates among TM patients with a cervix and who attended primary care appointments from April 2018 through September 2018, after introduction of the intervention, were determined. Both rates were compared with those among cisgender women at a colocated Comprehensive Health Program during the time period of review. These periods were chosen to avoid provider biases either while the intervention was under discussion and some providers may have adopted early, or heightened sensitivity to the need for cervical cancer screening immediately after implementing the new screening tool.t-test was completed with R to confirm the statistical significance of the difference between hr-HPV testing coverage in the baseline group and the rate of screening among the group examined after the self-swab intervention was implemented and clinically normalized.A Welch two sample A total of 394 TM patients received primary care at the CTMS at Mount Sinai during the period studied. Of those patients, 80 had undergone hysterectomy before the study, meaning that there were 314 who required cervical cancer surveillance. The baseline rate of cervical cancer screening was determined through retrospective chart review of the 121 TM patients who retained a cervix and attended at least one primary care visit during the 6-month period from January 2017 through June 2017. This retrospective review addressed all documentation in the patient's chart where a cervical cancer screen would be documented, including progress note free text.Following the introduction of the self-swab protocol, the intervention cervical cancer screening rate among TM patients was determined from a review of the 193 TM patients with a cervix who presented for primary care appointments during the 6-month period from April 2018 through September 2018.Among the 314 eligible TM patients, 73 had medical appointments during both the historical and intervention periods. Of the 73, 16 were screened only during the baseline period, and 34 were screened only during the intervention period. The remaining 15 of the 73 patients had cervical cancer screening done in both the pre- and postintervention periods. Without the 73 patients seen in both periods, there were 241 unique TM patients whose appointments did not overlap between the baseline and sample time periods and whose experiences could be cleanly compared.The patient sample assessed had a mean age of 32 years (range 21–62 years). Of the sample, 58% identified as White, 21% as Black or African American, 12% as Hispanic/Latinx, and 6% as another race or ethnicity. There were 4% unknown or unreported.The most common terms patients used to describe their gender identities were transgender man (91% of patients) and nonbinary . The patients reported the following sexual orientations: 25% heterosexual, 11% homosexual, 7% bisexual, 20% queer, and 18% some other sexual orientation. There were 19% unknown or unreported. The patients reported gender identities of their sexual partners as predominantly cisgender women (69%), followed by cisgender men (23%), transgender men (16%), and transgender women (16%).The majority of the sample (95%) reported ever using masculinizing hormone replacement therapy , with 24% of those patients reporting that they had been taking masculinizing hormones for at least 5 years. Seventy-five percent of patients had commercial insurance coverage, while 23% had Medicaid/Medicare, and 2% were uninsured .There were no statistically significant intergroup differences in age, race/ethnicity, gender identity, or sexual orientation between the baseline and the intervention groups .Of the 121 TM patients seen for primary care during the baseline period, 30 (25%) had cervical cancer screening following the recommended timeline documented in their chart. All were clinician-administered Pap tests . The majFollowing the introduction of self-collected swabs for hr-HPV, 98 (51%) of the 193 TM patients seen for primary care had a documented cervical cancer screening in their chart, indicating a two-fold increase in adherence to cervical cancer screening recommendations among TM patients . The ratAll samples collected from the Pap tests performed by clinicians during the baseline period were determined to be satisfactory for evaluation. All testing in the baseline period was negative for either intraepithelial lesions or malignancy. Of the 15 specimens co-tested for hr-HPV during the baseline period, 4 (27%) were positive for HPV 31/33/35/39/45/51/52/56/58/59/66/68.Of the 51 cervical cancer screening procedures completed during the 6-month intervention period, 4 (8%) were determined to be unsatisfactory for evaluation with indeterminate results. All 4 unsatisfactory specimens were clinician-collected cytology tests, comprising 17% of the 23 clinician-collected tests. Of the remaining clinician-collected cytology specimens, 1 (5%) detected SILs requiring follow-up, and 1 (8%) of the 13 specimens co-tested for hr-HPV tested positive for HPV genotypes 31/33/35/39/45/51/52/56/58/59/66/68.All hr-HPV self-swabs were satisfactory for laboratory analysis. HPV genotypes 31/33/35/39/45/51/52/56/58/59/66/68 were detected in 2 (7%) of the self-swab samples. All abnormal results were referred for colposcopy, but adherence data and results were not available at the time of the chart review.t-test was completed with R and confirmed the statistical significance of the difference between the 25% cervical cancer screening in the baseline period and the 51% rate of screening in the intervention period .A Welch two sample 22 Self-collected swabs for hr-HPV DNA testing improved rates of participation and engagement in cervical cancer screening among TM patients and, consequently, detection of hr-HPV.To our knowledge, this is the first assessment of increased hr-HPV testing and cervical cancer screening coverage among TM patients receiving primary care in an urban center following the introduction of self-collected swabbing as the primary hr-HPV DNA testing strategy. The increase is consistent with literature reporting self-swab to be a preferred method of cervical cancer screening for TM individuals.During the baseline period, we were able to successfully screen only 25% of patients. While we were able to screen 51% of patients in the intervention period with either provider- or patient-collected specimens, the lower sensitivity of hr-HPV self-swabs in TM would mean that 44% of primary care patients received an accurate screening test, still a significant improvement over the preintervention period. However, the lower sensitivity of self-swabs among TM individuals calls into question the proper screening interval with the use of primary hr-HPV screening in this population. There are not enough data available on TM individuals and cervical cancer to make a recommendation at this time.26 Previous studies have also found that TM individuals have lower lifetime rates of Pap test adherence and are significantly less likely to be current with cervical cancer screening. For example, one study at a similar center showed 74% adherence to screening among cisgender female patients and 64% among TM patients.19 Another showed 84% for cisgender female patients and 69% among TM patients.18 Notably, the rates of adherence exceed that of the rates accomplished here and suggest additional examination of barriers impeding access to cervical cancer screening for TM individuals at Mount Sinai.The observed increase in cervical cancer screening among TM patients after the introduction of self-swabbing, from 25% in 2017 to 51% in 2018, is still lower than the 76% screening coverage of cisgender women in the colocated Comprehensive Health Program, and the national rate of 85% of insured cisgender women who are historically up-to-date with cervical cancer screening.27 The literature documents multiple barriers to consistent engagement with cervical cancer screening for TM individuals. The biggest barrier is the lack of access to affordable, affirming, and quality care.28 Barriers to health care include those that are direct—economic instability, unemployment, being victims of violence, and lack of health insurance28–34—along with those that are indirect , such as the paucity of knowledgeable health care providers.31–43 Despite several clinical practice guidelines,44–47 scarcity of competent clinicians continues to represent the greatest barrier reported by TGNB individuals.34–37Transgender and gender non-binary (TGNB) individuals are the subject of very little focused health research.48 and are likelier to have unmet routine medical care needs due to cost, compared to cisgender individuals.50 With broad coverage for transgender care, New York state serves as an excellent setting to examine disparities in care among TGNB individuals beyond lack of coverage for care. In states without expanded Medicaid coverage, access to cervical cancer screening is still limited for the uninsured or underinsured. Only 2% of the TM patients in our sample were uninsured. TGNB-competent care training should include discussion of the unique primary care and preventive screening service needs of TGNB patients to promote the ongoing development of clinical recommendations from evidence-based observational and intervention studies throughout all levels of care.51Nationally, TGNB individuals are significantly less likely to have health insurance, with a 14% un-insurance rate,52–54This study utilized a convenience sample, a weakness for generalizability. We examined a patient sample of TM individuals already well-engaged in primary care at an academic medical center specializing in TGNB health care who may have been more motivated than average to engage in general medical care and follow clinician recommendations to adhere to preventive screening procedures. Relatedly, our study likely suffered clinician bias in that introduction of the self-swab protocol may have increased clinician vigilance with regard to screening recommendations and surveillance. Clinicians were not aware that there would be a change in protocol during the baseline period. The stability of cervical cancer screening rates among the cisgender women after increased surveillance suggests that the effect was modest. Given the importance of provider recommendation for motivating cisgender people to undergo cancer screening, the role of the relationship between provider and patients should be further investigated in TGNB samples.Self-collected swab testing to screen for hr-HPV can increase rates of uptake and adherence to screening recommendations among an under-screened and underserved patient population. Self-collected swab testing could prove a key element to shrink screening disparities and progress toward more optimal care for TGNB individuals. Future research should continue to explore less invasive, patient-empowering, and gender-affirming screening strategies within primary care for TGNB individuals and focus on increasing the sensitivity of self-swab specimens in TM individuals.


An efficient tool that can accurately recognize important clinical concepts of COVID-19 from free text in electronic health records (EHRs) will be valuable to accelerate COVID-19 clinical research. To this end, this study aims at adapting the existing CLAMP natural language processing tool to quickly build COVID-19 SignSym, which can extract COVID-19 signs/symptoms and their 8 attributes  from clinical text. The extracted information is also mapped to standard concepts in the Observational Medical Outcomes Partnership common data model. A hybrid approach of combining deep learning-based models, curated lexicons, and pattern-based rules was applied to quickly build the COVID-19 SignSym from CLAMP, with optimized performance. Our extensive evaluation using 3 external sites with clinical notes of COVID-19 patients, as well as the online medical dialogues of COVID-19, shows COVID-19 SignSym can achieve high performance across data sources. The workflow used for this study can be generalized to other use cases, where existing clinical natural language processing tools need to be customized for specific information needs within a short time. COVID-19 SignSym is freely accessible to the research community as a downloadable package ( Rich patient information, such as signs/symptoms together with their attributes, is recorded in clinical narratives, which is critical for COVID-19 surveillance, diagnosis and prognosis, and treatment effectiveness research. Therefore, natural language processing (NLP) techniques are needed to automatically extract important clinical information efficiently and accurately from clinical text. Clinical NLP communities, such as the OHDSI NLP working group and the N3C NLP working group, have quickly reacted and built tools such as COVID-19 TestNorm14 for lab testing normalization and MedTagger COVID-19 pipeline.16Despite that several large consortia have been formed to construct large clinical data networks for COVID-19 research, such as Open Health Data Science and Informatics (OHDSI),18 to quickly respond to the urgent need of developing NLP pipelines for specific disease areas, such as COVID-19. Given that the datasets and annotations originally used to build the general-purpose clinical NLP systems are not dedicated to COVID-19 signs/symptoms, the learnt distributions of linguistic features and semantic types may not be sufficient to model the specific set of COVID-19 signs/symptoms, which leads to dropped performance for this specific task. To improve it, unique contextual patterns and lexicons may need to be created to tailor the existing clinical NLP system for COVID-19 information.Nevertheless, 1 common question worth answering is how to leverage existing general-purpose clinical NLP systems17 The extracted entities were also normalized to standard terms in the OHDSI Observational Medical Outcomes Partnership (OMOP) common data model (CDM)19 automatically. The tool was originally developed and evaluated on the MIMIC-III dataset. It was then evaluated using clinical notes of COVID-19 patients from 3 external institutions, including UT Physicians (UTP), University of Kansas Medical Center (KUMC), and Johns Hopkins Hospital. In addition, we also examined and adapted it to social media data—online medical dialogues of COVID-19. Evaluations on clinical notes and medical dialogues demonstrate promising results. We believe this tool will provide great support to the secondary use of EHRs to accelerate clinical research of COVID-19.To address this question, in this study, we describe how to quickly build COVID-19 SignSym, which extracts COVID-19 signs/symptoms and 8 attributes  by adapting existing components in the Clinical Language Annotation, Modeling, and Processing (CLAMP) NLP tool.Five clinical datasets were used for building and evaluating the pipeline; these included MIMIC-III  and clinical notes data from UTP, KUMC, and Johns Hopkins, as well as Medical Dialogs. The external clinical datasets were annotated independently at each site . Cohen’s Kappa score was reported for interannotator agreement of each dataset between at least 2 annotators.MIMIC-III: Given that no public EHR dataset of COVID-19 is available and that signs/symptoms of COVID-19 are a subset of general signs/symptoms, the MIMIC-III dataset was used for building the pipelines of information extraction and normalization in COVID-19 SignSym. MIMIC-III contains clinical notes from intensive patient care. 200 discharge summaries were randomly selected, with 50% for adapting the pipeline and 50% for open test. The reported interannotator agreement was 0.947. In total, the selected dataset contained 17 208 sentences and 329 044 tokens.Clinical notes from UTP: UTP is the clinical practice of McGovern Medical School at The University of Texas Health Science Center at Houston. The dataset contained a sample of 20 patients who were tested for COVID-19 at UTP from 03/2020 to 06/2020. For those patients, 100 encounter notes were randomly selected. The gold standard labels were manually annotated for validating COVID-19 SignSym. Based on performance in an initial evaluation using a small set of clinical notes, 25 notes were used for tuning the pipeline, and 75 notes were used for open test. The reported interannotator agreement was 0.955. Overall, the annotated corpus contained 1357 sentences and 5682 tokens.Clinical notes from KUMC: The dataset contained a sample of 20 hospitalized patients who were tested for COVID-19 and admitted to KU Hospital from 03/2020 to 08/2020. For those patients, 100 clinical notes were randomly selected from progress, history and physical examination (H&P), and emergency department (ED) notes, which were created 72 hours prior to or after hospital admission. All the notes were extracted from KUMC’s EHR system (Epic), which has record boundaries limitations that could break 1 clinical note across multiple database records. Therefore, we performed a preprocessing step to concatenate broken records into complete notes and restored missing line breaks. The gold standard labels were manually annotated for validating COVID-19 SignSym. The interannotator agreement reported for the KUMC dataset is 0.892. Overall, the annotated corpus contained 4746 sentences and 45 832 tokens.Clinical notes from Johns Hopkins Hospital: This dataset contained 334 clinical notes of 40 patients and includes relevant note types such as H&P, Critical Care Notes, Progress Notes, and ED Notes focusing specifically on the notes created within 48 hours before and after hospital admission.20 Notes were preprocessed by Hopkins in-house section identification tools, and only the relevant narrative parts, particularly the chief complaint and history of the present illness sections, were extracted. For each of the 40 patients, each symptom was labeled as present or not present, resulting in over 467 manually annotated symptoms. These gold standard labels were then used to validate COVID-19 SignSym. The reported interannotator agreement was 0.970. In total, the clinical notes in this dataset contained 13 397 sentences and 121 802 tokens.Medical dialogues: This dataset contained medical dialogues related to COVID-19 collected from an online website dialog between patients and doctors.21 Initially, 50 dialogues were randomly selected for external evaluation. However, a sharp performance drop was observed on several attributes, such as temporal information, due to unique patterns in medical dialogues. Therefore, these 50 dialogues were used for tuning the pipeline and another 50 dialogues were used for an open test of COVID-19 SignSym. The reported interannotator agreement was 0.914. In total, the selected dataset contained 1162 sentences and 22 324 tokens.The following datasets were used for external evaluation:The statistics of data sources used for evaluation in this study are summarized in 22: (1) Severity: indicates the severity degree of a sign/symptom; (2) Negation: indicates a sign/symptom was negated; (3) Temporal information: indicates the time period or specific time the sign/symptom started; (4) Subject: indicates who experienced the sign/symptom; (5) Uncertainty: indicates a measure of doubt in a statement about a sign/symptom; (6) Condition: indicates conditional existence of sign/symptoms under certain circumstances; (7) Body location: represents an anatomical location of the sign/symptom; (8) Course: indicates progress or decline of a sign/symptom. Examples of attribute values are illustrated in The information model followed by the COVID-19 SignSym is illustrated in 23 (2) N3C: 15 signs and symptoms were collected from the diagnosis table shared by the N3C as phenotyping information.12 (3) MedTagger Lexicon: 17 signs and symptoms together with their 136 synonyms were collected from the lexicon in MedTagger.16 (4) Lexicon from Johns Hopkins: 14 signs and symptoms, and 337 synonyms were collected from an in-house lexicon of Johns Hopkins. (5) UMLS CUIs of these signs and symptoms were also assigned manually, with their UMLS synonyms collected. After removing redundancy, 55 signs and symptoms  and 3213 synonyms were collected from these sources. Notably, the reason why 55 signs and symptoms have 153 UMLS CUIs is that some signs/symptoms are represented by multiple semantic concepts with finer-granularities in UMLS. For example, productive cough is represented as productive cough—green sputum (CUI: C0425504), productive cough—clear sputum (CUI: C0425505), and productive cough—yellow sputum (CUI: C0425506) in UMLS.Leveraging the community efforts, COVID-19 signs and symptoms were collected from 5 sources: (1) World Health Organization (WHO) case record form: 26 signs and symptoms were collected from the SIGNs AND SYMPTOMS ON ADMISSION section of the case record form provided by WHO.2418 was adapted for COVID-19 information extraction in this study. This pipeline was built to automatically extract mentions of problems and their 8 attributes from clinical text. The definition of problems follows that used in the i2b2 2010 shared task, which consisted of 11 semantic types in UMLS .25 The definitions of attributes follow those used in the SemEval 2015 shared task 14.22The problem-attribute pipeline in CLAMP26 In particular, a novel joint-learning framework was designed to recognize attributes and their relations with problems simultaneously by integrating problem mentions as features into the deep learning architecture.27 To balance the time efficiency and performance in a practical clinical NLP tool28, the deep learning-based Bi-directional Long Short-Term Memory Conditional Random Fields (BiLSTM-CRF) algorithm26 was used to recognize mentions of clinical concepts, with 200-dimension word embeddings of MIMIC-III as the initial input.The pipeline used a hybrid approach to recognize mentions of problems and their attributes by combining the deep learning-based method, domain lexicons, and rules. Both the recognition of problems and attributes were represented as a sequential labeling task.The lexicons previously collected were used in an additional step of dictionary-lookup to improve the coverage of recognized COVID-19 signs and symptoms. Regular expressions and rules were also applied in a postprocessing step to boost the performance of attribute recognition.29 Both CUIs and preferred terms in UMLS were output for each recognized entity.Mentions of problems and attributes were normalized to standard concepts using the UMLS encoder module of CLAMP, which were built on a hybrid method of semantic similarity-based ranking and rules of concept prevalence in UMLS.Once medical problems were automatically recognized and normalized to UMLS CUIs, they were filtered by the precollected lexicons and CUIs of COVID-19 signs and symptoms.30The remaining signs/symptoms and their attributes were also mapped to standard concepts in the OMOP CDM. The OMOP encoder module of CLAMP was used for this purpose, which applied a similar approach as in the UMLS encoder module with a different scope of standard concepts and identifiers. Finally, COVID-19 SignSym outputs tab-delaminated files of normalized clinical concepts, with a format ready for importing into the Note_NLP table of OMOP CDM.External evaluation on COVID-19 data: the tool was evaluated on 100 clinical notes of patients tested for COVID-19 in UTP. In addition, it was evaluated on 100 posts of COVID-19-related dialogues between patients and doctors online as an external test. Notably, an initial evaluation was carried out on each external source with a small set of data to determine if the SignSym pipeline needs to be fine-tuned to adapt to the external data for better performance. If adaptation was needed, the initial data was used for error analysis, so that common patterns in each data source could be summarized for performance improvement. As a result, 25 clinical notes from UTP were used for fine-tuning the pipeline and 75 were used for open test. In addition, 50 medical dialogues were used for fine-tuning the pipeline and another 50 were used for open test.As mentioned above, COVID-19 SignSym is a pipeline adapted from existing clinical information extraction pipelines in CLAMP. To tune this pipeline, 200 discharge summaries were randomly selected from MIMIC-III based on lexicons of COVID-19 signs/symptoms; 100 of them were used for error analysis and optimizing the SignSym pipeline; after that, the information extraction performance was evaluated on another 100 discharge summaries as the open test. (2) Errors present in the outputs of COVID-19 SignSym are analyzed carefully for adapting the pipeline to external datasets. As illustrated in Supplementary Table 1, common causes of errors can be categorized into several major types:For UTP notes: (1) False positive signs and symptoms within wrong context: since a dictionary lookup method using sign/symptom lexicons of COVID-19 is carried out to improve the recall, some lexicons are matched in a wrong context, such as flu in “flu shot” and influenza in “Influenza vaccine.” Semantic types in UMLS were used to filter out such false positives. (2) Semistructure list: some attributes, such as conditions, are modifying signs/symptoms in a list of multiple items. Regular expressions were designed to parse common semistructure patterns.For medical dialogues: (3) New temporal patterns: some temporal expressions have new patterns and contexts uncovered in previous training datasets, such as in “Saturday February 29th—diarrhea.” To address this problem, new temporal terms and pattern-based rules were added to the pipeline.For both UTP notes and medical dialogues: (4) New synonyms of signs/symptoms: for example, “breathing harder,” “cannot breathe”  are mentions of “shortness of breath.” Another error is caused by partial recognition of named entities: For example, “cough” is recognized instead of “cough productive of yellow sputum.” Unseen mentions were used to enrich the lexicon to improve its coverage. (5) Question marks as false positive uncertainty: both clinical text and medical dialogues contain questions about patients’ signs and symptoms. According to our current annotation guideline, if the question has answers along with it, then the question mark will not be considered as a mention of uncertainty; or else, it will be labeled as an uncertainty attribute. (6) New patterns of subjects: many subjects in medical dialogues are family members of the question asker, different from the common cases in clinical text, such as in “my daughter is 3 and a half… has had pneumonia.” Besides, false positives also occur when the family member’s statement is cited in the clinical text, such as in “Per his wife he had an episode of confusion.” Since the subject attribute is of low frequency in the text, it is hard to capture the complex context of it. Syntactic structures will be applied in the next step in attempt to resolve this problem.1000 terms were randomly selected from the UTP notes and manually reviewed to evaluate the performance of clinical concept normalization.A use case of identifying patients’ signs/symptoms at presentation from notes generated within 72/48 hours before and after admission at KUMC/Johns Hopkins Hospital was used to validate the effectiveness of COVID-19 SignSym. Specifically, the task was to recognize signs and symptoms of the patient, in order to assist in future COVID-19 diagnosis and research. Specifically, once signs and symptoms were recognized in clinical text and normalized, they were also determined as negated, possible, or positive using attributes in their context. Only positive signs/symptoms were kept, and they were aggregated into the patient level to compare with the gold standard annotations of signs and symptoms manually recorded for each patient.(1) The end-to-end performances of extracting signs, symptoms, and their attributes were evaluated using precision, recall, and F-measure (F1) by exact match between manual and automatic annotations. (2) The performance of concept normalization was evaluated using accuracy. (3) The performances of patient-level extraction of COVID-19 signs/symptoms were evaluated using precision, recall, and F-measure.Internal evaluation performances for COVID-19 information extraction on MIMIC-III are reported in External evaluation performances on clinical notes of UTP and the medical dialogue are illustrated in Based on manual check of 1000 gold standard entities annotated in the UTP notes and their automatically assigned OMOP concepts, COVID-19 SignSym obtained an accuracy of 91.8% for concept normalization.(1) COVID-19 sign/symptom presentation of patients at KUMC: In comparison with manually assigned signs/symptoms of each patient, the tool yielded a precision of 0.908, a recall of 0.917, and an F-measure of 0.909. (2) COVID-19 sign/symptom presentation of patients at Johns Hopkins Hospital: In comparison with manually assigned signs/symptoms of each patient, the tool yielded a precision of 0.928, a recall of 0.957, and an F-measure of 0.942.https://clamp.uth.edu/covid/nlp.php).18 A visualization of the pipeline output is illustrated in This tool is freely accessible to the research community as a downloadable package  were available for developing data-driven approaches . Therefore, rule-based approaches that leverage knowledge from domain experts or existing knowledge bases could be built quickly and our results also show that such methods could achieve good performance on sign and symptom recognition. Moreover, our results also show that previously existing clinical corpora of similar diseases  could be useful for developing methods for the new disease. Additionally, the deep learning-based disease-modifier models in the CLAMP tool also demonstrated reasonable performance when they were applied to COVID-19 signs and symptoms, indicating the adaption process could be mainly focused on defining postprocessing rules (instead of reannotating text and retraining models), thus saving the development time for the new NLP pipelines.Nevertheless, the developed COVID-19 SignSym pipeline did not always perform well when applied to different sites. For example, it worked well on KU and Johns Hopkins corpora; but direct application to UTP notes showed a drop in performance and required local customization, especially for certain types of entities and probably due to the intrinsic syntactic and semantic variance of clinical notes from different sites. As indicated from the error analysis, attributes with low frequencies in medical text suffer from a relatively sharper performance drop when applying the pipeline to a new dataset, probably because of new patterns uncovered in the previous training data. Also, the low frequencies make their performances vulnerable. For example, if an attribute has only 20 occurrences in the dataset, 1 false positive will yield a 5% drop in precision. Despite using pretrained language models of clinical text and deep learning-based methods for model building, there is still space for improvement, such as increasing the scale and coverage of the unlabeled clinical text used to build the pretrained language model and automatically adapting the current pipelines to new datasets.It would be interesting to investigate the lexicon variations of COVID-19 signs/symptoms among multiple sites. After removing lexical redundancies, the overlap among signs/symptoms annotated on MIMIC-III, UTP notes, and medical dialogues are illustrated in the Venn diagram of Limitations and future work: this work has several limitations and future work is needed in several areas. While performance on 5 COVID-19 datasets is evaluated and reported, additional evaluations are needed to further refine the tool and increase its generalizability. At this stage, lexicon and pattern-based rules are used for a fast adaptation of the pipeline to new datasets, based on detailed error analysis. This will serve as a foundation for later automatic adaptation such as semisupervised learning and automatic pattern detection when external datasets of larger sizes are available. Note that extracted phenotyping information representations will be applied in downstream clinical applications in our collaborator’s site. Currently, only sign/symptoms and their attributes are extracted; additional work will be conducted for more related information such as comorbidities and medications. Finally, the output information will also be mapped to other clinical data standards, such as FHIR, in the near future to facilitate clinical operations and other applications.This article presents an automatic tool, COVID-19 SignSym, to extract and normalize signs/symptoms and their 8 attributes from clinical text by adapting a general clinical NLP tool (CLAMP) to COVID-19 information. COVID-19 SignSym achieved great performance in external evaluation using clinical notes of COVID-19 patients from 3 institutions and a social media dataset of medical dialogues and has been used to facilitate COVID-19 research. The workflow used for this study may be generalized to other use cases, where existing clinical NLP tools need to be customized for specific information needs within a short time.


Congenital heart disease (CHD) is the commonest birth defect. Studies estimating the prevalence of CHD in school-age children could therefore contribute to quantifying unmet health needs for diagnosis and treatment, particularly in lower-income countries. Data at school age are considerably sparser, and individual studies have generally been of small size. We conducted a literature-based meta-analysis to investigate global trends over a 40-year period.p = 0.001). Between 1970–1974 and 1995–1999, there was no significant change in the prevalence of unrepaired CHD at school age; subsequently there was an approximately 2.5-fold increase from 1.985 (95% CI 1.074–3.173)/1000 in 1995–1999 to 4.832 (95% CI 3.425–6.480)/1000 in 2010–2014, (p = 0.009). Among all CHD conditions, atrial septal defects and ventricular septal defects chiefly accounted for this increasing trend. The summarised prevalence (1970–2017) of CHD diagnoses first made in childhood was 1.384 /1000; during this time there was a fall from 2.050 /1000 pre-1995 to 0.848 /1000 in 1995–2014 (p = 0.04).Studies reporting on CHD prevalence in school-age children (4–18 years old) from 1970 to 2017 were identified from PubMed, EMBASE, Web of Science and Google Scholar. According to the inclusion criteria, 42 studies including 2,638,475 children, reporting the prevalence of unrepaired CHDs (both pre-school diagnoses and first-time school-age diagnoses), and nine studies including 395,571 children, specifically reporting the prevalence of CHD first diagnosed at school ages, were included. Data were combined using random-effects models. The prevalence of unrepaired CHD in school children during the entire period of study was 3.809 /1000. A lower proportion of male than female school children had unrepaired CHD  recognised at birth/infancy or early childhood, but remaining unrepaired at school-age. In parallel there has been a decrease of first-time CHD diagnoses in school-age children. These together imply a favourable shift of CHD recognition time to earlier in the life course. Despite this, substantial inequalities between higher and lower income countries remain. Increased healthcare resources for people born with CHD, particularly in poorer countries, are required. Congenital heart disease (CHD) is the commonest birth defect. The advent of modern cardiological and cardiac surgical care has transformed the prognosis for even critical types of congenital heart disease in high-income countries. Approximately 85% of children born with CHD now survive to adulthood in high income countries; over 1 million adults are now thought to be living with CHD in the USA /1000 pre-1995 to 0.848 /1000 in 1995–2014, was shown in these nine studies, albeit with a small total number of CHD cases /1000, suggesting these represented 36.3%  of unrepaired CHDs in the period. Analyses grouping studies by income status showed a higher prevalence of childhood diagnosed CHD in lower-middle than upper-middle income countries  and PDA in Asia and particularly in Africa. Many of the newly diagnosed children with these milder forms of CHD (e.g. VSD spontaneous closures) do not necessarily need surgeries or interventions, but specialist practitioners providing the lifelong follow-up these patients may require are insufficient in countries of the Global South . IncreasThe increasing trend of unrepaired CHD prevalence in school-age children corresponds with our previous results in a global meta-analyses of birth prevalence; both suggests that substantially increased numbers of diagnoses in infancy and childhood are being made in LMICs . Improvep = 0.001). The incidence of CHD among males and females at birth is similar; previous studies have shown a higher CHD mortality rate among males in infancy than females which could account for our result [We found significantly fewer males with unrepaired CHD among school children  to draw inferences beyond the statistically significant fall over time of CHD diagnoses made as a result of participating in prevalence surveys at school age. A second limitation is that we cannot translate the prevalence of unrepaired CHDs in our dataset directly into estimates of unmet need for surgical or interventional cardiological care, since some CHDs  may not require correction or may resolve spontaneously. Nevertheless, best practice would require these children to have a periodic follow-up with specialist paediatric, and later with adult congenital cardiologists; access to these services is known to be severely limited in poorer countries. We excluded post-operative cases, as the principal aim of the work was to comment upon unrepaired lesions. Of course, patients who have undergone palliation or incomplete correction for complex lesions also contribute significantly to the burden of CHD morbidity in children and young adults; further studies will be necessary to assess the degree to which the needs of these patients are met in different socio-economic conditions, and at different ages.The reported prevalence of unrepaired CHDs in low-income countries is increasing in recent decades, especially in Africa. The similar increasing trends of recognised CHDs in both school-age children and live births, and corresponding reductions in first-time CHD diagnoses in school-age children, indicate a beneficial shift in CHD recognition time from school-age to earlier stages. Additional resources are needed to be allocated to the care of the increasing number of children recognised to be living with unrepaired CHDs.Additional file 1. Review protocol and supplementary tables for inclusion and exclusion criteria and classification of severe CHDs.Additional file 2. List of included studies and extracted original data for meta-analyses.