Radiotherapy-induced trismus is present in up to 40% of patients treated radiotherapeutically for head and neck cancer (HNC) and impacts health-related quality of life (HRQL) negatively. This prospective study aimed to investigate the development of trismus and its influence on HRQL and trismus-related symptoms in HNC patients for up to 5 years post-radiotherapy completion as no such follow-up studies exist.n = 211) were followed prospectively from pre-radiotherapy to 12 and 60 months post-radiotherapy. At each follow-up, maximum interincisal opening (MIO) was measured, and patients filled in the European Organization for Treatment of Cancer Quality-of-Life Questionnaire Core-30 (EORTC QLQ-C30), Head and Neck-35 (EORTC QLQ-HN35), and Gothenburg Trismus Questionnaire (GTQ). Trismus was defined as an MIO ≤ 35 mm.Patients (At 1 year post-radiotherapy, a total of 27% met the trismus criterion, and at 5 years post-radiotherapy, the corresponding figure was 28%. Patients in the trismus group scored significantly worse compared to the patients without trismus on 8/15 domains at 1 year post-radiotherapy on EORTC QLQ-C30, further worsening in 11/15 domains at 5 years post-radiotherapy. Similar results were found for EORTC QLQ-HN35. Patients with trismus reported more trismus-related symptoms according to the GTQ at both timepoints compared to those without trismus.This study highlights that HNC patients suffering from radiotherapy-induced trismus report poorer HRQL and more trismus-specific symptoms compared to patients without trismus. These differences persist and increase up to at least 5 years following treatment completion. Hence, our results highlight that radiotherapy-induced trismus affects long-term HRQL, jaw symptoms, and pain, further stressing the need for early and structured intervention. Over the past 30 years, the epidemiology of head and neck cancer (HNC) has changed, with a decline seen in tobacco- and alcohol-related HNC and an increase in human papillomavirus (HPV)-related HNC. In Sweden, there has been a steady increase in the annual incidence of HNC with a 38% increase in new cases reported by the National Quality Registries in Swedish Health Care between 2008 and 2019 [Tumors of HNC are most commonly treated surgically or radiotherapeutically with or without the addition of chemotherapy . In genePrevious studies focusing on post-radiotherapy (RT) trismus have demonstrated that trismus impacts HRQL negatively and may cause pain as well as interference with normal daily activities such as speaking or eating –12. As nHence, this prospective observational cohort study aims to investigate the development of trismus and its influence on HRQL and trismus-related symptoms, comparing HNC patients who develop postradiation trismus to those who do not for up to 5 years post-RT.Patients were invited to participate in this study in connection with the weekly multidisciplinary tumor board meetings for all new cases of diagnosed HNC in the region of West Sweden at Sahlgrenska University Hospital in Gothenburg, between 2007 and 2012. The Sahlgrenska University Hospital is one of the major university hospitals in Northern Europe and the specialized center for HNC treatment for the Swedish county of Vastra Gotaland, populated by 1.7 million. Inclusion criteria were 18 years of age or older, receiving curatively intended RT, and cancer sites in the oral cavity, oropharynx, nasopharynx, salivary glands, paranasal sinuses, or cervical carcinoma of unknown primary (CCUP). Exclusion criteria included pre-treatment MIO of ≤ 35 mm, recurrent disease, surgical treatment alone, and insufficient cognitive abilities and Swedish language competency to independently complete the questionnaires and partake in examinations. Patients were followed prior to RT (baseline) and at 12 and 60 months post-RT. At each follow-up, MIO was measured, and the patients filled in patient-reported outcome instruments related to HRQL and trismus-specific symptoms, as described below. The Adult Comorbidity Index 27 (ACE27) and Karnofsky Performance Status Scale were filled in at baseline only , 14.n = 141).Tumors were classified according to the global standard, the TNM-staging system by the International Union Against Cancer (UICC), which includes tumor size (T), regional lymph nodes involvement (N), and distant metastasis (M) . CurativSurgery was performed with post-operative RT with or without the addition of chemotherapy for some tumor sites. Oral tumors stage III–IV were treated with surgery, including diagnostic and therapeutic neck dissections and radiotherapy. If the tumor was assessed to be unresectable, the patient received chemoradiotherapy only.Furthermore, primary site tumors were removed surgically, including neck dissection, followed by post-operative RT also if located in the salivary glands and sinonasal cancers. Neck dissections were also performed before administering non-surgical oncologic treatment in selected cases of those diagnosed with CCUP, depending on the status of their nodal metastasis. Non-surgical treatment was clinical practice for oropharyngeal and nasopharyngeal tumors.MIO was measured in millimeters with a ruler as the maximum distance between the upper and lower incisors at all three timepoints. The cut-off point defining trismus was an MIO of ≤ 35 mm . EdentulThe European Organization for Research and Treatment of Cancer Quality-of-Life Questionnaires (EORTC QLQ) were used to measure HRQL at all timepoints. Firstly, the EORTC QLQ Core-30 (QLQ-C30), which is a cancer-specific instrument, was utilized . In addiThe EORTC QLQ-C30 consists of five function scales, a global quality of life scale, three symptom scales, and six single items, totaling 30 items that describe the patients’ symptoms and functional level during the last week. The EORTC QLQ-HN35 consists of 35 items addressing symptoms specific to HNC and its treatments. Scores range from 0 to 100, where higher scores represent better function in the functioning domains and a higher global quality of life, whereas higher scores in the symptom domains equate to a higher symptom burden .The GTQ is the first comprehensive trismus-specific questionnaire and was developed as a complement to the objective measure of MIO. The GTQ is composed of three domains containing 13 items: jaw-related problems (six items), eating limitations (four items), and muscular tension (three items). Additionally, there are eight single items. The scores of the domains and single items range from 0 to 100, where a higher score indicates more symptoms and lower scores represent less symptoms .U test for continuous variables, and chi-square test for non-ordered categorical variables. All tests were two-sided and conducted at a 5% significance level. SAS version 9.4 was used for analyses.For categorical variables, number and percentages are presented. Standard deviation is presented for relevant variables related to sociodemographic data in Table The study was conducted according to the Declaration of Helsinki and was approved by the Regional Ethic Review Board in Gothenburg, Sweden. All participants gave their written informed consent before study inclusion.n=39), poor general health (n=4), death due to unknown cause (n=13) and unknown (n=26). The 129 patients completing the study had at baseline significantly higher Karnofsky scores, i.e. better performance status , less comorbidity as measured by ACE27 (p=0.006) and were younger  compared to the 82 patients who dropped out.A total of 211 patients were included. The baseline sociodemographic and clinical characteristics can be found in Table n = 211). At 1 year post-RT, however, a total of 27% (n = 49) met the trismus criterion, and at 5 years after finishing RT, the corresponding figure was 28%  at 5 years post-RT. At 1 year after RT completion, every symptom except for experiencing facial pain right now was statistically significantly worse in the trismus group. The GTQ results are presented in Table This study is, to the best of our knowledge, the longest follow-up study describing HRQL in HNC patients with post-RT trismus. Its large prospective cohort of patients and longitudinal design has yielded important findings in terms of HRQL prevalence and trismus-related symptoms.Firstly, the trend that patients suffering from trismus report generally worse HRQL scores compared to those without trismus is in line with previous findings of shorter-term studies, but highlights that these deteriorations persist long term , 20, 21.Other aspects known to contribute to HRQL might be found in the patient characteristics. Patients who live alone have been found more likely to report a negative impact on quality of life , 26. EveAdditional important findings in this material highlighted that the trismus group reported worse scores with regard to all pain modules in the EORTC QLQ-HN35 and the GTQ compared to those without trismus. Scores continued to deteriorate over time for patients with trismus, whereas on the other hand, the quantitative scores for patients without trismus improved at the 5-year follow-up. Thus, a statistically significant pattern regarding pain emerges over time, which appears disadvantageous for those suffering from trismus. These results are in line with a previous study regarding pain and its association with trismus, where structured exercise aiming to improve jaw-opening also resulted in reduced pain 3 years following oncologic treatment. This indicates that trismus is a prominent reason for post-RT pain . InteresOverall, the findings in this study highlight and further confirm the presence and persistence of long-term trismus, trismus-specific symptoms, and deteriorations in HRQL for those suffering from the condition. Previous research has demonstrated that patients who perform structured jaw exercises also report less trismus and better scoring regarding HRQL. A prospective interventional study by Karlsson et al. reported on 100 HNC patients with trismus of which 50 underwent a 10-week structured exercise program and the remaining constituted a control group. Patients were followed up to 3 years post-RT, and at all study timepoints, MIO was higher for the intervention group along with better reported HRQL scores . FurtherAs it is now known that trismus is a long-term complication severely affecting HRQL and that structured jaw training improves MIO, the importance of routinely introducing rehabilitative measures should continue to be emphasized. However, more recent studies have also focused on prophylactic intervention. A recent systematic review by Wang et al. covering prehabilitative interventions for trismus prevention identified a total of 11 studies, of which six contained sufficient information for analysis . ResultsThe strength of this study lies in its prospective, longitudinal design and in the size of the cohort. Furthermore, objective measurements have been used for MIO, and patient-reported outcome data have been obtained through validated, reliable, and widely used HRQL instruments. The study is limited by the patients who dropped out as these were in slightly worse overall health at baseline, raising the awareness of survival bias in long-term studies. Another further possible limitation includes the period that the data was collected. Since then, treatment methods and regimens have somewhat changed which may lead to an altered prevalence of post-RT trismus and hence associated HRQL data.This study highlights that HNC patients suffering from post-RT trismus report worse HRQL and trismus-specific symptoms compared to patients not suffering from post-RT trismus. These differences not only persist but increase up to at least 5 years following treatment completion. The results from the study highlight that RT-induced trismus affects long-term HRQL, jaw symptoms, and pain, further stressing the need for intervention in this patient group.


Countries making up the Nordic region – Denmark, Finland, Iceland, Norway, and Sweden – have minimal socioeconomic, cultural, and geographical differences between them, allowing for a fair comparative analysis of the health policy and economy trade-off in their national approaches towards mitigating the impact of the COVID-19 pandemic.This study utilized publicly available COVID-19 data of the Nordic countries from January 2020 to January 3, 2021. COVID-19 epidemiology, public health and health policy, health system capacity, and macroeconomic data were analysed for each Nordic country. Joinpoint regression analysis was performed to identify changes in temporal trends using average monthly percent change (AMPC) and average weekly percent change (AWPC).P < 0.001; 6.3, 95% CI = 3.5, 9.1, P < 0.001). Denmark had the highest number of COVID-19 tests per capita, consistent with their approach of increased testing as a preventive strategy for disease transmission. Iceland had the second-highest number of tests per capita due to their mass-testing, contact tracing, quarantine and isolation response. Only Norway had a significant increase in unemployment  while the percentage change in real Gross Domestic Product (GDP) was insignificant for all countries.Sweden’s health policy, being by far the most relaxed response to COVID-19, was found to have the largest COVID-19 incidence and mortality, and the highest AWPC increases for both indicators (13.5, 95% CI = 5.6, 22.0, There was no trade-off between public health policy and economy during the COVID-19 pandemic in the Nordic region. Sweden’s relaxed and delayed COVID-19 health policy response did not benefit the economy in the short term, while leading to disproportionate COVID-19 hospitalizations and mortality. Various strategies for containing and mitigating the COVID-19 pandemic have been implemented worldwide. Public health and response measures or non-pharmaceutical interventions (NPIs) have been utilized to varying degrees to contain and/or mitigate the pandemic, including face masks and hand hygiene, social distancing, border closures, lockdowns and stay-at-home mandates, closure of non-essential businesses and educational institutions, ban on mass gatherings, quarantine and patient isolation, mass screenings, and contact tracing .The Nordic countries have similar population density, climate and lifestyle, and are among the top twelve developed countries according to the Human Development Index of the United Nations. Around 27 million people live in the Nordic countries, with 38% living in Sweden (10.1 million), 20% in Norway (5.4 million), 21% in Denmark (5.8 million), 20% in Finland (5.5 million) and 1% in Iceland (0.36 million). The limited socioeconomic and cultural differences between and within these countries make them the ideal setting for comparing the effect of different strategies to tackle the COVID-19 pandemic.In these countries, the first COVID-19 cases were confirmed by the end of January 2020, with the first confirmed deaths occurring between March 11 and 23. While the “Swedish strategy” relied on the citizens’ responsibility for social distancing, working from home, hand washing and limiting non-essential travel, Norway, Finland, and Denmark implemented strict mitigation strategies with the main stated purpose of protecting the elderly and not overwhelming the health care system. Iceland had adopted a strict “test, trace and isolate” approach early on from March 2020 onwards.The aim of the study was to determine how the Nordic countries have balanced this trade-off between the restrictive COVID-19 health policy and response measures and their impact on the economy. The COVID-19 public health and response measures will be determined for each Nordic country and their effectiveness assessed by the epidemiology of COVID-19, public health and health care capacity, and the community response to the COVID-19 guidelines. The associated negative economic effects will be measured by comparing the macroeconomic indicators and trends for the Nordic region during the pandemic. The generalisability and application of the trade-off in the Nordic countries to comparable regions will provide evidence for better understanding and decision-making, thereby contributing to the science on how to save lives and support the economy during a pandemic.This study utilized publicly available COVID-19 data of the Nordic countries from January 2020 to January 3, 2021. Epidemiological COVID-19 data (relative numbers adjusted for population size unless otherwise mentioned) including incidence, mortality and case-fatality rate (CFR) were analysed using data sourced from the World Health Organization (WHO) Coronavirus (COVID-19) Dashboard and the European Centre for Disease Prevention and Control . The CFRPublic health and health system capacity was assessed by COVID-19 testing, test positivity rate , hospitaWe also evaluated the health policy measures in the Government Response Stringency Index, a composite measure rescaled to a value from 0 to 100 (100 = strictest response) based on indicators that included: school closures, workplace closures, cancellation of public events, restrictions on public gatherings, closures of public transport, stay-at-home requirements, public information campaigns, restrictions on internal movements, and international travel controls ,9.Quantitative data were collected to evaluate the population response to the government’s health policy measures. “Social Distancing” estimates based on change in mobility from anonymous cell phone data from the Institute for Health Metrics and Evaluation (IHME) were also examined . “Mask UThe data from macroeconomic indicators to evaluate the effect of COVID-19 pandemic and health policy control measures on the economy included “Economic growth, percent change in quarterly real GDP” and unemployment rate (monthly), both of which were sourced from Organization for Economic Co-operation and Development (OECD) and the data repository GlobalEconomy.com ,12.Corrections for populations were performed using 2020 mid-year population for the Nordic countries and standardizing data per 100 000 persons. A descriptive analysis was performed to determine the impact of COVID-19 in the Nordic countries utilizing the following variables: number of new COVID-19 cases, (per 100 000 persons), number of deaths, (per 100 000 persons), case-fatality (in percentage), COVID-19 tests conducted (per 100 000 persons), test positivity (in percentage), COVID-19 hospitalization (per 100 000 persons), COVID-19 intensive care unit (ICU) admissions (per 100 000 population).p-value of <0.05 was considered statistically significant.Joinpoint regression analysis was performed to identify changes of temporal trends of pandemic development and response indicators. Joinpoint allows for the identification of time points that are associated with statistically significant changes in trends using a Monte Carlo permutation method and calculates the monthly (MPC) and weekly percentage changes (WPC) (weighted least-squares method) for each key indicator. Additionally, the WPCs were weighted by length of interval and averaged to calculate the average weekly percent change (AWPC). The AWPC allows for the use of a single number to describe the average WPCs throughout the course of the year . It is vWe obtained AWPC and their 95% confidence intervals (CI) during the study period, across the Nordic countries for the epidemiological, public health and health system capacity, health policy measures, population response variables. For monthly unemployment rate (in percentage) we obtained average monthly percent change (AMPC). We obtained quarterly data for real GDP growth for which joinpoint regression analysis was not feasible. Instead, quarterly percentage change was calculated for real GDP growth.The COVID-19 mitigation strategies utilized by the Nordic countries are summarized in The country with the highest number of COVID-19 tests per 100 000 persons was Denmark, followed by Iceland. Iceland started large-scale testing the earliest, in March 2020, with sustained effort throughout the study period; Denmark had a gradual increase in COVID-19 tests starting in April and peaking in December 2020; Norway and Finland ramped up testing in July 2020; Sweden was the last to have an increase in testing during September 2020 (P < 0.05)  (P < 0.001) (P < 0.001) (P < 0.05) and Sweden’s  increases were significant and comparable. For ICU occupancy, only Norway showed a statistically significant decrease in AWPC . Decrease in percent mobility was analysed from March to the end of December 2020 for all countries. Each country saw a decrease in mobility; however, only Sweden’s was statistically significant . Mask usage was analysed from February to the end of December 2020 for all countries; all countries saw a significant increase in AWPCs, with Norway having the largest increase    response from April to mid-October 2020, despite large fluctuations in test positivity . This is comparable to a recent study that showed Sweden had the highest number of ICU hospitalizations [P < 0.001). Interestingly, while mask usage was the lowest, the Swedish population was the only one to exhibit an overall significant decrease in mobility [Among all Nordic countries, the number of cases and mortality per capita, as well the number of hospitalizations and ICU admissions were highest in Sweden. Case fatality was 0.9% on average (0.5%-5%) for the other Nordic countries, and 2.2% for Sweden. The test positivity ratio was around 10% for Sweden, and below 2% in all other Nordic countries (in line with other reports), also indicating restricted testing in Sweden and probably the largest proportion of un-diagnosed cases in the Nordic region . These rizations . Existinizations . The commobility ,22. All P < 0.009) performed significantly worse than Sweden in terms of unemployment. The similar macroeconomic performance of Sweden compared to other Nordic countries suggests that more stringent pandemic mitigation policies and containment can entail limited macroeconomic costs in the short run while enabling the aggregate economy to recover faster from a pandemic. Put differently, the results suggest that there is no trade-off between the restrictive COVID-19 policies to contain the COVID-19 pandemic and macroeconomic outcomes in the Nordic countries.From the macroeconomic perspective, the results do not reveal clear-cut benefits of the looser health policies adopted in Sweden when compared to the rest of the Nordic countries. For example, the trend in percentage change of real GDP was statistically insignificant for all Nordic countries. Compared with its Finnish and Danish neighbours, Sweden exhibits similar dynamics of the unemployment rate. Among these countries, only Norway  multiplied by the global number of COVID-19 deaths of 1 400 000), with US$10 trillion loss in the global GDP . SeveralFew studies have investigated the trade-off between the COVID-related health policies and the economy -28. EvenLimitations of the study include varying epidemiological definitions and methodologies that were reported by countries in the publicly available COVID-19 databases. The results were based on “recorded” COVID-19 cases, and therefore the “true number” is likely to be higher, depending on the definition used in each country to diagnose an active case. The hospitalization and ICU data for Iceland were not available at the time of analysis. Relying on multiple databases to collect the study variables may have led to timeline differences for data reporting. The macroeconomic indicators had fewer data points compared to the epidemiological indicators, leading to analytic differences, especially for the percent change in GDP. Also, factors affecting the economy besides the mitigation measures were not controlled for in this study.To conclude, this pandemic has demonstrated the variability of COVID-19 mitigation measures across the Nordic countries. Every country has shown a unique reaction, implementing measures based on socioeconomic and geographic factors, epidemiology, health, and politics. Although Sweden had chosen looser COVID-19 health policies to benefit its economy, there is no evidence that this had any short-term economic benefits, while costing disproportionate disease transmission and mortality numbers compared to neighbouring countries.


Elevated levels of testosterone and fibroblast growth factor 23 (FGF-23) are both independently associated with a higher risk of cardiovascular disease (CVD). However, the relationship between sex hormones and FGF-23 is not well established. We explored the association between sex hormones and FGF-23 among middle-aged to older men and women in MESA. We studied 3,052 men and 2,868 postmenopausal women free of CVD at the time of enrollment with baseline serum sex hormones  and intact FGF-23. In sex-stratified analyses, we examined the cross-sectional associations between log-transformed sex hormones (per 1 SD) and log-transformed FGF-23 using multiple linear regression adjusted for socio-demographics, CVD risk factors, estimated glomerular filtration rate and mineral metabolites . The mean (SD) age of study participants was 64 (10) years. The median (IQR) of FGF-23 was similar in women and men [38 (30–46) vs 38 (31–47) pg/mL]. In adjusted analyses, among women, 1 SD increment in free T was associated with 3% higher FGF-23 while SHBG was associated with 2% lower FGF-23. In men, 1 SD increment in E2 was associated with 6% higher FGF-23 whereas total T/E2 ratio was associated with 7% lower FGF-23. In conclusion, this exploratory analysis found that a more androgenic sex hormone profile was directly associated with FGF-23 in women and inversely associated with FGF-23 in men. Longitudinal studies are required to determine whether FGF-23 mediates the relationship between sex hormones and CVD risk. Fibroblast growth factor-23 (FGF-23) is an endocrine hormone, produced by osteocytes, that exerts its effects on the kidneys by stimulating urinary excretion of phosphate in addition to inhibiting the synthesis as well as promoting the degradation of calcitriol  . MoreovePostmenopausal women with a more androgenic sex hormone profile [higher endogenous free testosterone and lower sex hormone binding globulin (SHBG) levels] have a more adverse cardiovascular phenotype . This phObservations from prior animal studies suggest a relationship between sex hormones and FGF-23. For example, FGF-23 levels decreased following orchiectomy of a male rat model from an acute loss of endogenous testosterone (hypo-androgenic state) and testosterone supplementation restored FGF-23 levels . LikewisGiven the sparsity of research showing the link between these two hormones, the aim of this study was to conduct an exploratory analysis of the relationship between sex hormones and FGF-23 among middle-aged to older men and women from a multi-ethnic population free of clinical CVD at baseline and determine whether this relationship is independent of sociodemographic characteristics, CVD risk factors, and other mineral metabolites. We hypothesized that a more androgenic sex hormone profile will be associated with higher levels of FGF-23 among postmenopausal women but not among men of similar age.https://biolincc.nhlbi.nih.gov/studies/mesa/. Additionally, other researchers can apply to the MESA Coordinating Center to become new investigators after signing a Data Use Agreement (DUA); more details are available at https://www.mesa-nhlbi.org/. Upon receipt of the DUA by the MESA Coordinating Center, access to the de-identified MESA databases would be made available to other researchers with approved proposals. The findings of our study should be easily reproducible through the methods described in this paper.The Multi-Ethnic Study of Atherosclerosis (MESA) participates in the NIH BioLincc Open program and requests for access to MESA data can be submitted to: The Multi-Ethnic Study of Atherosclerosis (MESA) is a prospective cohort study of 6,814 women and men without a history of clinical CVD at time of enrollment. Study participants aged 45 to 84 years were recruited from six field centers in the United States  between the years 2000 and 2002 . MESA exBaseline data were used for the present analysis. As shown in the flowchart of study participants in The MESA study protocol was approved by the institutional review boards (IRB) at the aforementioned field centers and written informed consent was given by all participants . At JohnThe measurement of sex hormones as reported in previously published research from MESA is described as follows –30. DuriThe measurement of FGF-23 has been previously described in prior research from MESA , 32, 33.MESA study personnel collected data on the covariates included in this study at baseline examination from standardized questionnaires, physical examinations and laboratory testing . We consWe stratified all analyses by sex because of the differences in sex hormones between women and men. We reported continuous variables as means with standard deviation (SD) or medians with interquartile range (IQR) for skewed distributions. Additionally, we reported categorical variables as frequencies with percentages. We logarithmically transformed the sex hormones and FGF-23 because of their skewed distributions and modeled both as continuous variables. The sex hormones and T/E2 ratio expressed per 1 SD were the independent variables and FGF-23 was the dependent variable. Using multiple linear regression models, we reported the exponentiated beta-coefficients with 95% confidence intervals of the association between each sex hormone and FGF-23 as well as the association between the T/E2 ratio and FGF-23. We presented four progressively adjusted models. Model 1 was adjusted for age, race/ethnicity and MESA field center. Model 2 was adjusted for education and CVD risk factors such as smoking, BMI and physical activity. In model 3, we adjusted for additional CVD risk factors such as total cholesterol, HDL-C, systolic blood pressure, diabetes, eGFR, use of antihypertensive and lipid-lowering medications. For women, we also adjusted for years since menopause and current use of hormone therapy in model 3. The final model (model 4) was additionally adjusted for the related mineral metabolites of 25-hydroxyvitamin D, calcium, phosphorus and parathyroid hormone.Furthermore, we used restricted cubic splines adjusted for model 4 covariates to assess for non-linear relationships between logarithmically transformed sex hormones and the differences in logarithmically transformed FGF-23. In separate analysis for women and men, we tested whether race/ethnicity was an effect modifier of the association between sex hormones and FGF-23 by including interaction terms in the fully adjusted model. Where interaction was significant, we performed stratified analysis by subgroups. Lastly, we conducted a sensitivity analysis among women stratified by current use of hormone therapy and we adjusted for model 4 covariates. We performed all our analyses using STATA version 15.0 . In view of the higher probability of false positive findings from multiple comparisons, a Bonferroni corrected two-sided P-value <0.0021 [0.05 divided by 24 (6 exposure variables x 1 outcome variable x 4 models)] was considered statistically significant.The baseline characteristics of study participants  stratified by sex are presented in The adjusted cross-sectional associations between sex hormones and FGF-23 in women are shown in In this exploratory analysis of a large multi-ethnic cohort of postmenopausal women and men free of clinical CVD at baseline, we found that among women, higher levels of free testosterone were independently associated with higher FGF-23 and higher levels of SHBG were associated with lower FGF-23. Since free testosterone reflects testosterone that is unbound to SHBG and albumin, the relationships of free testosterone and SHBG with FGF-23 in opposite directions are consistent. In men, higher levels of estradiol were associated with higher FGF-23 and higher levels of T/E2 ratio were associated with lower FGF-23. These aforementioned relationships were all independent of CVD risk factors and other markers of mineral metabolism such as serum 25-hydroxyvitamin D, calcium and phosphate, which are influenced by FGF-23 levels.The few studies that have examined the relationship between sex hormones and FGF-23 reported conflicting findings , 37. BurSaki and colleagues in an experimental study investigating the effect of testosterone and letrozole on 1, 25-dihydroxyvitamin D and FGF-23 in male rats reported a significant reduction in 1, 25-dihydroxyvitamin D and FGF-23 in orchiectomized rats compared to the control group , 39.Furthermore, an experimental study conducted by Carrillo-Lopez and colleagues to investigate the factors and mechanisms involved in the effect of estrogens on the parathyroid gland found that female rats treated with estrogen had significantly higher serum and bone FGF-23 levels as well as significantly lower serum calcitriol, phosphorus and parathyroid hormone levels . In our Given that the relationship between endogenous sex hormones and FGF-23 from population studies has not been previously well established, we undertook this study to better understand the potential mechanism that might explain why both sex hormone profiles  and FGF-23 are associated with elevated CVD risk , 16. HowThis study has some strengths. We used data from a large, diverse, community-based population of women and men who did not have clinical CVD at the time of study enrollment. The availability of data on a large number of variables with standardized measurements enabled us to examine five different sex hormones and reduce the effect of potential confounding factors. We were also able to account for other important mineral metabolite markers. Nevertheless, our study has some limitations. We cannot prove causality or show whether a temporal relationship exists between sex hormones and FGF-23 because this study was observational with a cross-sectional design. In addition, residual confounding may still be present even though we accounted for numerous confounding factors in our analysis. We used only one baseline measurement of sex hormones to determine the hormonal status of study participants instead of serial measurements, although previous studies suggest a single assessment of sex hormones is reliable , 44. LasIn this exploratory analysis, we found that a more androgenic sex hormone profile was directly associated with FGF-23 in women while inversely associated with FGF-23 in men. In light of the fact that CVD is the leading cause of morbidity and mortality globally, a thorough understanding of the different biological pathways underlying the incidence of CVD is of considerable importance to facilitate the development of improved prevention and therapeutic options . There iS1 Table(DOCX)Click here for additional data file.


To explore the attitude towards COVID-19 vaccination among healthcare workers in the US, we surveyed three groups of individuals . We found surprisingly high portions of healthcare workers with COVID-19 vaccine hesitancy/resistance, with 23% of correctional healthcare workers and 17% general healthcare workers (as compared to 12%) refusing to be vaccinated against COVID-19. Multivariate regression models suggest that current season flu vaccination (aOR = 3.34), relying on employer for COVID-19 information (aOR = 3.69), and living in the Midwest (aOR = 5.04) to be strongly associated with COVID-19 vaccine acceptance among essential workers and general healthcare workers. Current season flu vaccination (aOR = 7.52) is also strongly associated with COVID-19 vaccine acceptance among correctional healthcare workers. Potential mechanisms of vaccine hesitancy/resistance among healthcare workers involves low health literacy and employer mistrust. Our findings are highly relevant as we try to reach COVID-19 vaccination goals in the US. Coronavirus disease COVID-19) is an infectious disease caused by the SARS-CoV-2 virus 9 is an i–5. In paA growing body of literature shows that COVID-19 vaccines are safe and effective .Despite the clear and documented benefits of COVID-19 vaccines, there continues to be resistance to vaccination among many individuals in the US, including health care workers. Reasons for vaccine hesitancy include vaccine-specific concerns (safety and effectiveness), need for more evidence/information, antivaccine beliefs, and lack of institutional trust . SeveralTherefore, in this exploratory pilot study, we aimed to assess correctional health care workers,’ general healthcare workers’ and essential workers’ willingness to receive, refuse or express hesitancy towards the COVID-19 vaccine; reasons for getting or not getting the COVID-19 vaccine; and sources of COVID-19 information. In addition, we compare our results from the correctional health care staff to healthcare workers in non-jail environments and general essential workers over the COVID-19 pandemic . These results are designed to provide data for developing a larger study of a representative sample of correctional health care staff in multiple regions of the US.®, a probability-based ongoing panel of about 35,000 households designed to be representative of the US household population. Over the same general time frame (spring of 2021) as the jailed-based health care worker survey, we selected all general healthcare workers (n = 65) and a random sample of self-reported essential workers (n = 100) during the COVID-19 pandemic but outside of the health field from AmeriSpeak’s ongoing panel of surveys. All general healthcare workers had either “healthcare practitioner and technical occupations” or “healthcare support occupations,” and reported patient contact during work.This exploratory study includes a cross-sectional random sample of participants drawn from two main sources. The first sample (n = 78) was a group of healthcare professional (mostly nurses) from 65 local jail facilities across eight states . All eligible jail healthcare professional staff (mostly nurses) were offered the survey and 80% completed the survey. The research team coordinated the distribution of the survey with the medical director of the health care staff. Potential participants, all adults, were emailed a link to the online survey by the medical director. The second data source was AmeriSpeak® panel, a stratified random sample of U.S. households are selected and sampled using area probability and address-based sampling, with a known, nonzero probability of selection from the NORC at the University of Chicago (NORC) National Sample Frame. These sampled households are then contacted by U.S. mail, telephone, and field interviewers (face-to-face) to capture harder to reach cases. The panel provides sample coverage of approximately 97% of the U.S. household population [For the AmeriSpeakpulation  and comppulation , 24. Thepulation . AmeriSppulation . The AmeFor this study, our team implemented our survey under AmeriSpeak’s monthly Omnibus survey program. AmeriSpeak staff sent an email to a randomly-selected group of panel members describing the study, covering informed consent and inviting them to participate in the survey. One-quarter of the contacted participants from the AmeriSpeak panel of 3,900 invited adult panelists completed this project’s survey . For this study, we selected all general healthcare workers (n = 65) and a random sample of essential workers (n = 100) during the COVID-19 pandemic but outside of the health field from AmeriSpeak to participate in this study.Participation in the survey was strictly voluntary and informed consent was required before a participant was allowed to work on a survey. The study was approved by one of the author’s organization’s Institutional Review Board  for the conducting of human subject’s research. All survey participants completed the survey in English. Sample participants who did not respond to the initial invitation were contacted about three to four times by email to complete the survey.Medical staff responsible for providing healthcare in a jail environment across eight states were invited to complete an 85-item survey on perceptions of COVID-19 related risk, experiences with COVID-19 risk mitigation strategies, and willingness to participate in COVID-19 vaccination campaigns from the end of March 2021 to May 31, 2021. Next, a cross-sectional sample of AmeriSpeak participants completed surveys during a data collection period from February 10, 2021 to March 22, 2021 . Participants were given a subset of 40 of the same 85-item survey items covering COVID-19 protective behavior including vaccinations and demographic/background questions. The survey items in common for the two samples were used in this paper .Survey items covered the nature of the participants’ work, work environment, COVID-19/flu vaccination history and vaccination hesitancy, reasons for getting or not getting the COVID-19 vaccine, and sources of COVID-19 information. We also included a series of demographic and background questions such as age, biological sex at birth , region of US the person works within , and education .Our main outcome of interest was willingness to be vaccinated against COVID-19. In the surveys, participants reported their COVID-19 vaccine status. To be considered “willing”, a participant had to be either already vaccinated (one dose or more), or willing to be vaccinated as soon as possible. If a participant expressed disapproval or reluctance of receiving the vaccine, they were considered “unwilling”.In addition to vaccine willingness, we also asked for reasons why individuals chose to be vaccinated or not. For those unvaccinated participants, we also asked participants about factors that would make them reconsider being vaccinated. Participants could report more than one reason/factor.The first covariate was flu vaccination status. Participants were asked whether they were ever vaccinated against seasonal flu, and whether they had been vaccinated for the current flu season.Each participant was asked where they obtained most of their information on COVID-19 within the past month. Sources of information included newspaper , television (broadcast and cable), online news, social media, friends and family, employer, government , scientific journals, and other sources . Participants could report more than one source of information.We also asked participants whether or not anyone they knew had died from COVID-19, including people within the participants’ household, friends, family members, acquaintances, and coworkers.Lastly, we collected the participants’ demographic information, including current age, sex, state of residence, and education level.We first assessed the distribution of COVID-19 vaccine status, and associated reasons for vaccine willingness or refusal. We compared the distribution across all three groups, as well as within the two AmeriSpeak groups, using chi-square tests. We repeated the analysis with sources of COVID-19 information.To assess factors contributing to vaccine willingness, we constructed multivariable logistic regression models. The outcome was the dichotomous variable of vaccine willingness (yes/no), and we included several covariates which potentially influence COVID-19 vaccination acceptance in the model, including flu vaccination status, source of COVID-19 information, and demographic variables . We first tested the model within the correctional healthcare group. Then we tested the model within the two AmeriSpeak groups , with employment type (group assignment) as an additional covariate. Coefficients were exponentiated to obtain adjusted odds ratios (aOR).Participant demographics are shown in Overall, 15% of essential non-healthcare workers, 54% of general healthcare workers, and 65% of correctional healthcare workers reported receiving their COVID-19 vaccination . Among tAmong participants in all three samples who reported not willing to receive a COVID-19 vaccine, common reasons included potential side effects, not being concerned about becoming seriously ill from COVID and COVID-19 vaccines being promoted by politicians to win votes without sufficient testing. Among general healthcare workers, another common reason participants endorsed for not being vaccinated against COVID-19 was the belief that the COVID-19 pandemic is not as severe as many people think. A greater proportion of participants in the general healthcare worker group and in the jail-based healthcare worker group indicated that nothing would make them reconsider being vaccinated against COVID-19 . In contrast, only 19% of the essential non-healthcare workers expressed a similar unwillingness to reconsider their vaccination status.The main sources of COVID-19 information, stratified by COVID-19 vaccination status and sample group, are shown in In the AmeriSpeak sample , flu vaccination in the current season was associated with willingness to receive COVID-19 vaccinations. Those vaccinated for flu were three times as likely to be willing to receive COVID-19 vaccines, as compared to those not vaccinated for flu in the current season . Participants who obtained most of their COVID-19 information from their employers in the past month were almost 4 times as likely to be willing to receive COVID-19 vaccination, as compared to those who didn’t obtain COVID-19 information from their employer . In addition, participants from the Midwest were 5 times as likely to be willing to receive COVID-19 vaccination, as compared to participants in the South .In the jail-based healthcare worker sample, flu vaccination in the current season was the only factor significantly associated with willingness to receive COVID-19 vaccinations. Those vaccinated for flu were over seven times as likely to be willing to receive COVID-19 vaccines, as compared to those not vaccinated for flu in the current season .Considering how strong influenza vaccination is associated with COVID-19 vaccine willingness, we conducted sensitivity analyses where we ran the regression models without influenza vaccination variables. After omitting influenza vaccination, several other factors become statistically significant . Among eHealthcare workers are at higher risk of COVID-19 infection because of continuous exposure to patients. It is crucial for healthcare workers to achieve high COVID-19 vaccination rates for the protection of themselves and for people, especially patients, around them. Healthcare workers in correctional settings are an especially important population to be vaccinated, because they work in closed environments filled with extremely vulnerable populations . The risk is further exacerbated by poor conditions within correctional facilities  and high turnover rates of people who are incarcerated in jail settings . COVID-1There were significantly more healthcare workers in our sample, as compared to essential non-healthcare workers, who have already received vaccines for COVID-19. However, a larger portion of healthcare workers  reported that they would not consider getting the COVID vaccine, as compared to essential workers (12%); surprisingly, the majority of healthcare workers who refused to be vaccinated stated that nothing would make them reconsider COVID-19 vaccines .The main reason for not vaccinating, across all three groups, were potential side effects (73%-94%). All three COVID-19 vaccines in the US, approved by the Food and Drug Administration, have been proven safe and effective against severe COVID-19 infections . MillionIn addition to potential side effects, many unvaccinated healthcare workers were not concerned about getting severely ill from COVID-19 ; and approximately one-third of general healthcare workers and essential workers believed that COVID-19 vaccines were being promoted by politicians only to win election votes even when these vaccines were not sufficiently tested for effectiveness or safety. These findings go hand-in-hand with skepticism about COVID-19 vaccine safety/effectiveness. Some healthcare workers in our sample believe that vaccines are more harmful than COVID-19, despite witnessing all the illness and deaths at work from COVID-19. These concerns need to also be incorporated into education and messaging about COVID-19 vaccines in order to dispel misinformation. In addition, there are two potential factors that may be highly influential: health literacy and employer trust.Health literacy is defined as “the degree to which individuals and groups can obtain process, understand, evaluate, and act upon information needed to make public health decisions that benefit the community” . When a In our study, the majority of correctional healthcare workers relied on their employer for COVID-19 information, including those refusing to be vaccinated. We suspect some level of employer mistrust leads to vaccine hesitancy among correctional healthcare workers. Employer mistrust has long existed in correctional settings due to understaffing, low pay, high workload, and many other factors . Such miBased on our regression analyses, current influenza vaccination is also a key predictor of COVID-19 vaccination willingness—those who were currently vaccinated against influenza were 3 to 7 times more likely to be willing to receive COVID-19 vaccines, as compared to those who were not currently vaccinated against influenza. Up-to-date influenza vaccination may be an indicator of higher health literacy . In futuThe study has several limitations. First, the sample size is relatively small . The sample is also fairly homogeneous  which limits our ability to examine effectively demographic factors as predictors for vaccine willingness. Second, the study uses two existing cross-sectional surveys, and we were limited to data collected by the survey. There are potentially unadjusted confounders in our regression models. Third, the study faces the usual limitations of relying on self-reports from surveys  and future research should consider integrating medical records on actual vaccine acceptance to the research.This study has several policy implications. First, our data indicate the significance of accurate and transparent COVID-19 information, especially on social media platforms and online news sites. This aligns with the CDC’s emphasis on finding credible vaccine information—it is crucial for the general public, as well as health care workers, to be exposed to credible and accurate COVID-19 information, in order to make informed healthcare decisions . Second,In this exploratory study, we surveyed three groups of individuals  on their attitude towards COVID-19 vaccination. We found surprisingly high portions of healthcare workers with vaccine hesitancy/resistance. We also found that flu vaccination, source of COVID-19 information, and region of residence to be strongly associated with COVID-19 vaccine acceptance. Potential mechanisms of vaccine hesitancy/resistance among healthcare workers may involve low health literacy and employer mistrust. Findings of this study inform a follow-up larger study to explore the merits of recommending policy changes including better COVID-19 information dissemination and improvement of working conditions at correctional facilities.S1 File(XLSX)Click here for additional data file.


Structured analyses of hospital administrative data may detect potentially preventable adverse drug events (ADE) and therefore are considered promising sources to prevent future harm and estimate cost savings. Whether results of these analyses indeed correspond to ADE that may be preventable in clinical routines needs to be verified. We exemplarily screened all adult inpatients admitted to a German University Hospital  for International Classification of Diseases-10th revision (ICD-10) diagnoses coding for drug-induced kidney injury (AKI). In a retrospective chart review, we checked the coded adverse events (AE) for inhospital occurrence, causality to drug exposure, and preventability in all identified cases and calculated positive predictive values (ppv). We identified 69 inpatient cases of whom 41 cases (59.4%) experienced the AE in the hospital (ppv-range 0.43–0.80). Causality assessment revealed a rather likely causal relationship between AE and drug exposure in 11 cases  whereby preventability measures could be postulated for seven cases . Focusing on drug-induced AKI, this study exemplarily underlines that ICD-10-code-based ADE prevention efforts are quite limited due to the small identification rate and its high proportion of primarily outpatient events. Furthermore, causality assessment revealed that cases are often too complex to benefit from generic prevention strategies. Thus, ICD-10-code-based calculations might overestimate patient harm and economic losses. Clinical administrative data (CAD) are a widely used data source for research questions, including the identification of adverse drug events (ADE) by using ICD-9 or ICD-10 codes  ,5,6,7,8.Indeed, as several studies show, inhospital ADE load is high and has a crucial impact on patient outcomes and economic burden ,11,12. HIn a previous analysis, we compiled a list of ICD-10 codes referring to ADE that were suspected of typically occurring during the hospital stay and might be preventable. We performed propensity score analyses in order to estimate the clinical relevance of the respective codes with respect to the prolongation of the length of stay of the affected patients [The aims of this study were, therefore, (i) to confirm the actual inhospital occurrence of the coded adverse events (AE), (ii) to assess the causality between suspected drugs and the AE, and (iii) to analyse the causes and conditions leading to inhospital drug-induced renal failure in order to determine whether common prevention strategies could have avoided them.All adult inpatients admitted to Heidelberg University Hospital, Germany, in 2012, whose stays were covered by German health insurance , were screened for predefined ICD-10 codes that are typically used for coding drug-induced nephropathy (N14.1 or N14.2) or postprocedural renal failure  if any of the following conditions were present: an increase in serum creatinine (SCr) by ≥0.3 mg/dl within 48 h; an increase in SCr to ≥1.5 times baseline, which is known or presumed to have occurred within the prior seven days, or a urine volume <0.5 mL/kg/h for six hours . InhospiFor causality assessment, all relevant information was summarized in a standardized form. We collected information about the patient ), the pWe used the updated Bégaud score for the causality assessment of AE to drug exposure . BrieflyWe have adapted techniques of Root Cause Analysis to our data set  ,21 in orMetric and normally distributed variables were reported as mean ± standard deviation (SD), range, and median. Categorical variables were presented as frequency and percentage. To quantify the validity of the three previously assessed ICD-10 codes , the posData management was performed with MS Access 2010, data analysis by MS Excel 2010 , SPSS 22.0, 2013 , and GraphPad Prism 5.01, 2007 .The records of all 69 identified inpatients  with ICD-10 codes coding for drug-induced renal failure were analyzed. The mean patient age was 62 years and the mean length of stay was 22.1 days. Ten patients exceeded the maximum hospital stay that is fully reimbursed by insurance companies .Based on the course of their SCr values, 41 patients developed an inhospital AKI while the remaining 28 patients turned out to have a known history of renal failure already at admission. The ppv of all codes for an inhospital event was 0.59, and was highest for N99.0 , corresponding to seven inpatient cases 23%, .Preventive strategies could be hardly elaborated for the four cases with buprenorphine, methotrexate, cisplatin, or ciclosporin. Buprenorphine triggered hypotension, subsequently lowered renal perfusion, and was considered a previously unknown intolerance of this patient and therefore rated as not preventable. In the latter three cases recommended precautions  were already set in place as far as assessable from the documentation in the chart. The ppv for preventable inhospital AKI was thus 0.10 for all codes together and highest for N14.1 , defined as an intrinsic imputability score of at least I4. In many cases, the AE was not likely caused by a drug or at least not by a drug alone. Most often, patients had severe underlying diseases and other individual contributing risk factors suggesting that the causes for AKI were likely multi-factorial, thus precluding the deduction of a straightforward and generic prevention strategies. Another study reported a much higher ppv of 0.79 for ICD-10-codes coding for inhospital ADE but based the causality assessment on expert opinion alone, not considering contributing factors or other non-drug causes for respective AE . Hence, Furthermore, the prevalence of drug-induced AKI coded with the respective ICD-10 code was lower compared to prospective studies assessing AKI in inpatients. Typically, the incidence of drug-induced AKI concerned 0.49–1.3% of the patients ,31, wherOur data set did not allow calculating sensitivity rates for our ICD-10 codes indicative for ADE. Studies that report sensitivity rates for ICD-10 codes showed rather low sensitivity rates of ICD-10 codes indicative for an ADE (6.8%) , or ICD-Thus, our study clearly underlines the fact that CAD-driven ADE analysis may not be a useful tool to derive potential cost savings as the ADE might not be easily preventable in the first place. Nevertheless, there are several studies calculating clinical and economic risks on the basis of ICD-10 codes, among others there are also codes for renal failure ,9,10,12.The applied study design has several limitations. First of all, the inevitably retrospective design partly impeded the preventability assessment as, for instance, no interviews of involved health care professionals or patients were possible. Hence, proposed measures might have even been set in place but not documented in detail. Thus, postulated preventability and proposed prevention strategies need to be seen as first suggestions, and then would need prospective verification in routine care. Second, while incidence rates of ICD-10 codes indicative for ADE are in line with other studies, we report results of a single-center analysis in a university hospital setting. Coding habits may have differed between our various departments, and such differences may be of greater importance between different centers with various administrative databases, patient records, and clinical decision support systems, which all might influence the incidence rates.Within the limitations of a single center study, this study emphasises that ADE analyses based on hospital discharge data carry the risk of overestimating potential cost savings by generalizing treatment-related problems and ignoring patient- and context-relevant factors. Moreover, it also outlines that the few identified ADE are often too complex to be easily caught by the few and generic prevention measures. To more reliably estimate preventable inhospital AE and its economic burden on the basis of ICD-10-codes, we strongly recommend the use of appropriate causality assessment or fitting ppv of the respective ICD-10 codes. For this, our study adds another, probably more realistic ppv of ICD-10 codes coding for inhospital and drug-induced AKI, showing that administrative data-based calculations of patient harm and economic loss are insufficient.


Data on the risk of developing diabetes in patients with systemic lupus erythematosus (SLE) are limited and have yielded mixed results. We conducted a nationwide cohort study to investigate the risk of subsequent type 2 diabetes in patients with SLE compared with matched non-SLE controls.Data were collected from the Taiwan National Health Insurance Research Database. Adult patients newly diagnosed with SLE between 2003 to 2010 were identified as the study cohort. The non-SLE group was matched for age, gender, and date of initial diagnosis as the comparison cohort.A total of 6159 SLE patients  were identified during this period. Of these, 206 (3.34%) developed type 2 diabetes. The 3-year incidence of type 2 diabetes was significantly higher in the SLE cohort than in the control group , with an adjusted hazard ratio of 1.22 , after adjusting for age, gender, underlying comorbidities, and monthly income. Stratified analyses showed that women with SLE and low-income SLE patients  had a higher risk of type 2 diabetes than non-SLE controls, with adjusted hazard ratios of 1.21 (95% CI 1.01–1.45) and 1.36 (95% CI 1.10–1.69), respectively.Patients with newly diagnosed SLE had a 22% increased risk of developing type 2 diabetes during the 3-year follow-up period compared with matched controls. Diabetes is one of the modifiable cardiovascular risk factors for cardiovascular disease. Previous studies have shown an increased prevalence of diabetes in patients with SLE, ranging from 5% to 15.11%, compared with age- and gender-matched controls.–4Systemic lupus erythematosus (SLE) is a systemic autoimmune disease that primarily affects women of childbearing age, and is characterized by autoantibody production, immune complex deposition, and a wide range of clinical manifestations. Patients with SLE are at an increased risk of cardiovascular disease, which is a major cause of mortality. This higher risk is multifactorial, including traditional cardiovascular risk factors, SLE disease activity, SLE-related immunological factors, and SLE-related medications.,6 Hemminki et al used data from 3 Swedish health databases to estimate the risk of subsequent type 2 diabetes in patients with autoimmune diseases. The study included a total of 12,206 patients with SLE and found that patients with SLE had a higher risk of type 2 diabetes . Both men and women had an increased risk of type 2 diabetes, without significant gender differences . In contrast, in a nationwide population-based study using data from the UK Clinical Practice Research Datalink, 1605 patients with SLE had no increased risk of developing diabetes .However, there is a paucity of data on the risk of diabetes in newly diagnosed SLE patients, with mixed results.In this study, we used a nationwide database to assess the risk of incident type 2 diabetes in patients newly diagnosed with SLE compared with matched non-SLE controls to clarify the conflicting results in the literature.This nationwide cohort study used data from the Taiwan national health insurance research database (NHIRD). The National Health Insurance Program is a nationwide health insurance system launched in 1995, and more than 99% of Taiwanese people are currently enrolled in the program. Data in this study were obtained from the longitudinal health insurance database 2000 (LHID2000), which is a representative subset of NHIRD containing records from a random sample of 1 million people in 2000 from the entire population of National Health Insurance beneficiaries. Another database acquired from the NHIRD was the Registry of Catastrophic Illness database, which included information on all 23 million Taiwanese people. Patients with proven catastrophic illnesses including SLE were exempt from copayments. The issue of a catastrophic illness certificate to patients with major rheumatic diseases was validated by rheumatologists commissioned by the Bureau of National Health Insurance by reviewing the medical records as well as laboratory and imaging studies. Because NHIRD contains de-identified secondary data released to the public for research purposes, this study was exempt from full review by the Institutional Review Board.th revision, clinical modification [ICD-9-CM] code 710.0) from 2003 to 2010 were included in the study cohort. For higher diagnostic accuracy, a case of SLE was defined by the possession of a catastrophic illness certificate for SLE. The index date for the study cohort was determined as the date of the first ambulatory care visit for a diagnosis of SLE. To identify new SLE cases, those with index dates before January 1, 2003, were excluded. The comparison cohort comprised subjects without SLE (3 for every patient in the SLE cohort) randomly selected from the LHID2000 and frequency matched by age, gender, and year of the index date. To confirm new-onset type 2 diabetes, patients in both cohorts with a diagnosis of diabetes (ICD-9-CM code 250) before the index date were excluded. A flowchart of the study subject selection is presented in Figure Study patients were categorized into SLE and non-SLE cohorts. Patients aged ≥ 20 years newly diagnosed with SLE . Patients were defined as having type 2 diabetes if the diagnosis was repeated at least 3 times either with outpatient claims or upon hospitalization. Incident type 2 diabetes was identified during the follow-up and the 3-year incidence rate was calculated. Incidence rates were estimated for each cohort separately and then stratified by age, gender, monthly income, and underlying comorbidities. The selected baseline comorbidities included hypertension (ICD-9-CM codes 401–405), hyperlipidemia (ICD-9-CM code 272), coronary artery disease (ICD-9-CM codes 410–414), cerebrovascular accident (ICD-9-CM codes 430–438), and chronic renal disease (ICD-9-CM code 585). These comorbidities were determined based on at least 1 in-patient claim or 3 out-patient claims before the SLE diagnosis. All study patients were followed up for 3 years or until December 31, 2010.t-test for continuous variables. The adjusted HRs and 95% CIs were calculated using the Cox proportional hazard regression model to identify significant predictors of type 2 diabetes. The Kaplan–Meier method was used to estimate the cumulative incidence, and the differences between curves were tested with a 2-tailed log-rank test. All statistical tests were 2-tailed, and only associations with a P-value < 0.05 were considered statistically significant.All statistical analyses were performed using Statistical Package for Social Sciences for Windows . Mean values were reported as standard deviation. Comparisons of groups with or without SLE were performed using the chi-square test for categorical variables and Student’s P-value < 0.0001).Table Table P-value = 0.0023).Figure This study used a national database to examine the risk of developing type 2 diabetes in newly diagnosed SLE patients. Our study showed that patients with SLE had a 22% higher risk of type 2 diabetes within 3 years compared with matched controls. In a study of 44 nondiabetic women with SLE, the incidence of insulin resistance was higher in patients with SLE than in age-matched controls. Although patients using steroids had lower insulin sensitivity, insulin sensitivity was still significantly reduced in those who did not use steroids compared with controls. A cross-sectional study in Spain reported higher rates of insulin resistance in patients with SLE compared with controls. This difference remained statistically significant after adjustment for classical cardiovascular risk factors and prednisone use. These findings suggested that SLE independently increases insulin resistance, which over time progresses to type 2 diabetes.The higher risk of type 2 diabetes in patients with SLE might be due to increased insulin resistance caused by SLE itself and medications used to treat SLE. Insulin resistance plays a major role in the development of glucose intolerance and type 2 diabetes.,11 A UK study reported that glucocorticoid use was associated with a strong dose-dependent increase in the incidence of type 2 diabetes in SLE patients, regardless of body mass index, family history of diabetes, or disease duration, even after adjustment for systemic inflammatory activity. Calcineurin inhibitors  are commonly used in induction and maintenance therapies for lupus nephritis. Calcineurin inhibitors can cause glucose intolerance and lead to diabetes by reducing insulin secretion and increasing insulin resistance. Therefore, regular diabetes risk assessment and screening are essential during glucocorticoid and calcineurin inhibitor therapy, regardless of the prescribed dose.Medications used to treat SLE, including glucocorticoids and calcineurin inhibitors, are associated with an increased risk of diabetes. Glucocorticoids are frequently used to treat SLE owing to their potent anti-inflammatory and immunosuppressive effects. Glucocorticoids are known to cause hyperglycemia through a variety of mechanisms, including inducing or worsening preexisting insulin resistance, increasing hepatic gluconeogenesis, causing islet cell dysfunction, and, in the long term, stimulating appetite and weight gain. A study found a gender difference in glucocorticoid use in patients with SLE; the frequency and dose of glucocorticoids were significantly higher in male SLE patients. Therefore, men with SLE are more likely than women to be treated with high-dose glucocorticoids, which may lead to the development of insulin resistance or type 2 diabetes. The gender difference in diabetes risk in our study may be due to the relatively small sample size of males with SLE, which results in a wider confidence interval with a larger margin of error. Further research is needed to understand the effect of the male gender on diabetes risk in patients with SLE.In this study, women with SLE had a significantly higher risk of type 2 diabetes than non-SLE controls. Men with SLE also had a higher incidence of type 2 diabetes than controls. However, this difference did not reach statistical significance . SLE typically affects women at far higher rates than men. However, males were associated with more active disease at diagnosis, regardless of age or ethnicity.,17 In a longitudinal study of the Hopkins Lupus Cohort, low income was also associated with cardiovascular risk factors (including diabetes), myocardial infarction, and stroke compared with individuals in the highest income category. It is well known that low income is associated with a higher incidence of diabetes and diabetes-related complications. The mechanisms by which low income is associated with type 2 diabetes are not clear. Our findings suggest that low-income SLE patients are at a particularly high risk of developing diabetes, emphasizing the importance of regular diabetic risk assessment and testing in these patients.In the present study, low-income SLE patients had a significantly higher risk of type 2 diabetes than non-SLE controls. Previous studies have shown that low income is independently associated with higher morbidity, increased damage accumulation, and worse prognosis in patients with SLE. Fasting plasma glucose and glycated hemoglobin levels should be tested regularly to screen for prediabetes or diabetes. Studies have shown that lifestyle interventions such as a healthy diet, regular exercise, and weight control in high-risk individuals are effective in preventing type 2 diabetes and are considered first-line preventive therapies.,22 Furthermore, it is well known that glucocorticoid use increases the risk of diabetes; therefore, in patients with SLE, it is strongly recommended to reduce steroid exposure and use steroid-sparing agents to minimize adverse effects. Hydroxychloroquine, an antimalarial drug, is widely used to treat SLE. Hydroxychloroquine has been shown to reduce the incidence of diabetes in patients with SLE. Patients with higher cumulative doses (≥ 129 g) had a significantly lower risk of diabetes than patients not receiving hydroxychloroquine. A Canadian cohort study also found that patients with SLE who adhered to antimalarial therapy had a 39% lower risk of developing type 2 diabetes than those who discontinued therapy. However, the protective effect was lost when less than 90% of the prescribed dose was taken.Because of the increased risk of developing type 2 diabetes in patients with SLE, effective screening and monitoring strategies should be employed for prevention and timely detection. Guidelines for the management of SLE recommend screening for diabetes at baseline and at least annually thereafter.This study has 3 advantages. First, it is a national, population-based study using an administrative database that removes selection bias. Second, the presence of a large number of study subjects and age- and gender-matched controls can estimate the risk of type 2 diabetes in patients with SLE. Third, more than 98% of Taiwan’s population is Han Chinese. Homogenous populations reduce the confounding effects of ethnicity.Our study has several limitations. First, using ICD codes from claims data to diagnose SLE, type 2 diabetes, and other comorbid medical conditions may impair accuracy. To address this concern, for the SLE cohort, we only recruited subjects with a catastrophic illness certificate for SLE, which would minimize the probability of recruiting non-SLE patients. Likewise, subjects were considered to have type 2 diabetes only if the diagnosis was repeated at least 3 times at the time of outpatient claims or hospitalization. Thus, the possibility of miscoding errors was minimized in this study. Second, information about family history of diabetes, weight and height, physical activity status, smoking habits, alcohol consumption, and education level is not recorded in NHIRD, which may also influence diabetes risk. Therefore, the variables used for adjustment may be limited.Patients with newly diagnosed SLE had an increased risk of developing type 2 diabetes compared with matched controls. Therefore, diabetes screening and prevention strategies should be implemented to improve SLE care.The authors would like to thank the Taiwan National Health Research Institute for permission and authorization to use this dataset. This study does not represent the official viewpoint of the Taiwan National Health Research Institute.Conceptualization: Yeong-Jang Lin, Chih-Chiang Chien, Hung-An Chen.Data curation: Chung-Han Ho.Investigation: Yeong-Jang Lin, Chih-Chiang Chien, Chung-Han Ho, Chao-Yu Chen.Methodology: Yeong-Jang Lin, Chih-Chiang Chien, Chung-Han Ho, Hung-An Chen.Software: Chung-Han Ho.Writing – original draft: Yeong-Jang Lin.Writing – review & editing: Yeong-Jang Lin.


Tuberculosis remains the leading cause of death from a single infectious disease worldwide. Trials evaluating digital adherence technologies for tuberculosis in low- and middle-income countries are urgently needed. We aimed to assess whether a digital medication event reminder and monitor (MERM) device-observed self-administered therapy improves adherence and treatment outcomes in patients with tuberculosis compared with the standard in-person directly observed therapy (DOT).TM urine colorimetric isoniazid test, and adherence self-report), and clinical measures . The intention-to-treat (ITT) primary endpoints were (1) individual-level percentage adherence over the two-month intensive phase measured by adherence records compiled from MERM device vs. DOT records that also considered all take-home doses as having been ingested and (2) sputum smear conversion following the standard two-month intensive phase treatment. Secondary endpoints were (1) individual-level percentage adherence over the two-month intensive phase measured by adherence records compiled from the MERM device vs. DOT records that considered all take-home doses as not ingested, (2) negative IsoScreen urine isoniazid test, (3) adverse treatment outcome , and (4) self-reported adherence. The MERM device has an electronic module and a medication container that records adherence, stores medication, emits audible and visual on-board alarms to remind patients to take their medications on time and refill, and enables providers to download the data and monitor adherence.We did a two-arm, attention-controlled, effectiveness-implementation type 2 hybrid, randomized controlled trial in ten healthcare facilities in Addis Ababa, Ethiopia. We included adults with new or previously treated, bacteriologically confirmed, drug-sensitive pulmonary tuberculosis who were eligible to start anti-tuberculosis therapy. Participants were randomly assigned (1:1) to receive a 15-day tuberculosis medication supply in the evriMED500® MERM device to self-administer and return every 15 days (intervention arm) or visit the healthcare facilities each day to swallow their daily dose with DOT by healthcare providers (control arm). Both arms were followed throughout the standard two-month intensive treatment phase (2RHZE). For control participants, some provider-approved take-home doses might be allowed for extenuating circumstances in real-world practice. Data were collected on patient information , medication adherence measures , MR 1.27 (95% CI 1.33–1.43)]. Urine isoniazid testing was done on 443 (97%) samples from 114 participants; 13 participants had at least one negative result; a negative test was significantly more common among the control group compared with the intervention group . There was no significant difference between the control and intervention arms for smear conversion , adverse treatment outcomes , and self-report non-adherence .Participants were enrolled into the study between 02 June 2020 and 15 June 2021, with the last participant completing follow-up on 15 August 2021. A total of 337 patients were screened for eligibility, of whom 114 were randomly assigned and included in the final analysis [57 control and 57 intervention participants]. Participants were 64.9% male, 15% with HIV, 10.5% retreatment, and 5.3% homeless. Adherence to TB medication was comparable between the intervention arm  and the control arm  and was within the prespecified margin for non-inferiority [mean ratio (MR) 1.00 (95% CI 0.99–1.01); In this randomized trial of patients with drug-sensitive pulmonary tuberculosis, medication adherence among participants assigned to MERM-observed self-administered therapy was non-inferior and superior by some measures when compared with the standard in-person DOT. Further research is needed to understand whether adherence in the intervention is primarily driven by allowing self-administered therapy which reduced challenges of repeated clinic visits or by the adherence support provided by the MERM system. To avoid contributing to patient barriers with DOT, tuberculosis medical programs should consider alternatives such as medication event monitors.ClinicalTrials.gov, NCT04216420.The online version contains supplementary material available at 10.1186/s12916-022-02521-y. Tuberculosis (TB) continues to be a leading cause of death from a single infectious disease worldwide, with an estimated 10 million people falling ill and 1.5 million people dying from TB each year –5. In-peDigital adherence technologies (DATs) are emerging as promising patient-centered solutions to avert the problems with in-person DOT by remotely monitoring and reminding patients to take their TB medications in a convenient location. Electronic medication monitors are attracting attention in this regard and efforts are underway to establish robust efficacy and effectiveness profiles across different population groups. A pragmatic stepped-wedge cluster-randomized trial reported a similar odds of TB treatment success with a 99DOTS-based electronic medication monitor compared with DOT largely provided by family treatment supporters . AnotherEthiopia, the second-most populous country in Africa with a population of 120 million 2022), is among the 30 high-burden countries for TB and HIV-associated TB according to the WHO Global TB report 2021 , is amon. As a reIn this trial, we aimed to test the hypothesis that the use of a digital medication event reminder and monitor device-observed self-administered therapy provides a non-inferior medication adherence and treatment outcomes for patients with TB compared with the standard in-person DOT in Ethiopia, one of the low-income countries with the highest burden of TB.This is a multicenter, two-arm randomized, attention-controlled, non-inferiority, effectiveness-implementation type 2 hybrid trial done in 10 healthcare facilities in Ethiopia. The trial is registered with ClinicalTrials.gov, NCT04216420, and a full description of the study protocol  , evriMED500®, manufactured by Wisepill Technologies, South Africa . The evrConsented participants were randomly assigned (1:1) to either MERM (intervention arm) or DOT standard care (control arm) using a computer-generated random number sequence developed by a trial expert who did not participate in recruitment. Permuted block randomization method was used to randomly allocate participants and maintain a balance of the number of participants assigned to each arm. The study investigators who were responsible for assessing study outcomes and writing the report were blinded to group allocation until the manuscript was completed. Because of the scope of the trial, participants and the other study staff were not blinded to group allocation. A statistician masked to group allocation performed the analyses. No stratification was needed for key variables.TM test, GFC Diagnostics Ltd, Bicester, England  and acid-fast bacillus smear microscopy [44 (38.6%) participants]. Among the participants diagnosed with pulmonary TB using smear microscopy, 16 (38.1%) were graded 3+ and 15 (35.7%) 2+. The mean monthly income was Ethiopian Birr (ETB) 2959.21 , 6 (5.3%) were homeless, 72 (63.2%) lived in a house with a single bedroom, and 20 (17.5%) smoked cigarettes. Baseline characteristics and HIV status were balanced between the two groups (Table Of 57 participants in the control (DOT) arm, 30 (52.6%) requested to take home some doses, of which the providers allowed this procedure for extenuating circumstances and provided doses for 29 (97%) participants on at least one occasion. These periods of take-home doses ranged from 3 to 15 days. There were 77 requests from the 29 participants on different occasions, with a minimum of one and a maximum of eight requests per participant. Among these, the providers agreed and provided doses for 74 (96%) of the requests. Of the total 3420 tablets expected to be administered in-person within the healthcare facilities, 1004 (29.4%) were taken home for self-administration.p = 0.954)  in the control arm and 99.01% GSD 1.02) in the intervention arm, with a non-significant difference between the two arms , and all participants had achieved an adherence threshold ≥ 80% .A general linear model regression was used to determine the effect of sociodemographic, behavioral, and health characteristics of participants on their levels of adherence, with adjustments made by controlling other covariates. Results of the multivariable regression model revealed that HIV co-infection, at least one negative urine isoniazid test, and occupation were associated with level of adherence and the level of adherence was higher among HIV-negative compared with HIV-positive participants. The level of adherence was higher among participants who were employed compared with those unemployed. The level of adherence was higher among participants who had no negative urine isoniazid test compared with those with at least one negative result Table . The GM −0.23 as the data were log-transformed in the case of the count model. The assumed average adherence was 79% (47.4 pill count) vs 99% (59.4 pill count) within the given range of 20% non-inferiority. Assuming all take-home doses were not ingested, the GM percentage adherence as prescribed (standard DOT) was 77.71 (GSD 1.57), having a significant difference with the intervention arm . With this analysis, the intervention showed superiority over the DOT control when considering all take-home doses were not ingested. The intervention demonstrated that it was non-inferior to DOT with both assumptions . In detail, (1) assuming no take-home doses were ingested, the intervention was superior to the DOT control, and (2) assuming all take-home doses were ingested, the intervention was not superior but was non-inferior to the DOT control   as the outcome, assuming all take-home doses with the control arm were ingested. Poisson and negative binomial regression were done to identify factors that determine participants’ level of adherence. The Poisson regression was selected as it has the smallest Akaike information criterion (AIC = 678.911) compared with the negative binomial regression (AIC = 680.911) and the dispersion parameter in negative binomial regression was not significantly different from zero. None of the variables were found to be potential candidates for the multiple regression. The regression revealed that the intervention was non-inferior to the control arm with rate ratio (RR) of 1.00 (95% CI: 0.95–1.05), given a non-inferiority margin of 0.82 (= e−0.2), the intervention demonstrates superiority as well as non-inferiority  compared with the Poisson regression (AIC = 933.443), and the dispersion parameter in negative binomial regression was significantly different from zero. The multiple regression revealed that study arm, occupation, and at least one negative urine isoniazid test result were significant factors determining participants’ level of adherence. Given the non-inferiority margin of 0.82 (= ety Table .Table 6NUrine isoniazid colorimetric assay was performed on 443 (97%) samples out of the expected 456, of which 430 (97%) tested positive, indicating that the drug was taken within the 24–30 h prior to the urine test. There were 14 negative results, of which 12 were from control and two from intervention arms. The urine test was performed four times for 106 (93%) of the 114 participants, while the remaining eight participants missed a total of 13 samples: two participants from the control arm missed three samples each; one participant from the intervention arm missed two samples; and five participants, one from control and four from intervention arms, missed one sample each.p = 0.022). Participants in the DOT arm were more likely to have a negative isoniazid urine test, and the risk of having at least one negative urine isoniazid test in the DOT arm was 5.50 times more likely compared with the intervention arm (Table Thirteen (11.4%) participants had at least one negative result [control 11 (19.3%) vs intervention 2 (3.5%)]. Log binomial regression was done to estimate the risk of study arms for a negative ionized urine test. There was a significant association between the urine isoniazid test and study arms . Twenty (18.5%) participants felt stressed about meeting their TB treatment schedule, with no significant difference between the two arms . The adherence self-report had a significant association with the actual adherence result (p = 0.013) but not with the urine isoniazid test (p>0.99).Adherence self-report data were captured at the end of the intensive phase for 109 (95.6%) of the total 114 participants to identify the relationship between self-report and objective adherence measures over this 2-month period. Six (5.6%) reported they often forgot to take their TB medications; the difference between the two arms did not reach statistical significance .Smear conversion data were captured at the end of the intensive phase. Microscopy was performed for 108 (94.7%) participants, of whom 107 (99.1%) were negative with smear microscopy and were transitioned into the four-month continuation phase, while one (1%) remained positive and was treated for Xpert MTB/RIF-proven drug-resistant-TB per the national guidelines. There was no statistically significant difference between the arms on smear negativity following the intensive phase .Adverse treatment outcomes data were captured from enrolment. One participant from the intervention arm was lost-to-follow-up. The participant  was lost to follow-up after completing the first month of treatment and taking 15 days of doses for the second month. Her two urine isoniazid tests were positive, and based on the data downloaded from the pillbox device, she had taken her first month of treatment as prescribed. There was no statistically significant difference between the arms for the adverse treatment outcome measures including death [control 0 vs intervention 1 (1.9%), In this randomized controlled trial of patients with drug-susceptible pulmonary TB, MERM-enabled self-administered therapy showed non-inferior treatment adherence compared with the standard in-person DOT. This suggests that the use of electronic MERM, which holds TB medication supply, reminds patients using audible and visual alarms to self-administer their daily medication and refill medications and records medication intake events is a good alternative to in-person DOT. There was a significant association between the urine isoniazid test results and treatment adherence. Patients in the intervention arm were less likely to have a negative isoniazid urine test. The risk of having at least one negative urine isoniazid test was more likely for participants receiving in-person DOT compared with MERM-enabled self-administered therapy. There was a significant association between overall self-report adherence and actual adherence; however, there was no statistically significant difference between the two arms for self-report adherence. There was no statistically significant difference between the two arms for smear negativity following the intensive phase or on adverse treatment outcomes including lost-to-follow-up and death. This was likely due to the routinely practiced take-home of doses for participants in the control arm when the provider approved these exceptions for extenuating circumstances. Based on their experience, providers believed that denying these requests and insisting on strict DOT would lead to missed doses and thus result in lower rates of smear conversion and successful treatment.To our knowledge, this trial is the first study to apply a randomized trial design to investigate the effectiveness of a MERM-observed self-administered therapy for patients with TB in an African setting and the second such study globally. Only one other pragmatic cluster-randomized trial has been published and reported a significantly improved medication adherence with the use of MERM in China , which wIn this trial, treatment adherence in the intervention arm was non-inferior compared with the control arm, suggesting that it is possible to monitor participants during their treatment but without the need for daily visits to a healthcare facility. Daily facility visits are conducted during the 2-month intensive phase where their early disease condition, travels, and economic status could be barriers and interrupt treatment. Compared with the intensive phase, the 4-month continuation phase may present less of a burden as visits are weekly. Forgetfulness, lack of support, fear of drug side-effects, and lack of hope were major reasons for non-adherence. The findings revealed a significant association between urine isoniazid test and treatment adherence, unlike a previous prospective cohort study in India that reported a suboptimal accuracy of 99DOTS-based electronic medication monitor compared with urine isoniazid partly due to poor patient engagement with 99DOTS .This trial revealed a suboptimal implementation of in-person DOT, which concurs with previous studies conducted in Ethiopia , 26. We Adherence self-report data were captured at the end of the intensive phase for 109 participants, and the analysis showed a significant association between adherence self-report and the actual adherence result. This implies that self-report can be a potential option to measure medication adherence in this setting. Self-report adherence was high in both arms, with only six (5.6%) participants from both arms reported they often forget to take their TB medication, and with no significant difference between the two arms. Moreover, 20 (18.5%) participants overall felt stressed about meeting their TB treatment schedule, but there was no significant difference between groups.This trial also demonstrated that TB is predominantly a disease of the disadvantaged and that comprehensive economic and social protection is required to ensure successful treatment adherence and completion. The participants’ mean monthly income was ETB 2959.21, which was lower than the national average of ETB 8074 . AdditioThe vast majority of TB research studies were at least partially affected by the COVID-19 pandemic. In Ethiopia, the COVID-19 pandemic significantly interrupted routine TB care and treatment services and reduced the rate of TB case-detection. Several articles have been published informing local governments of interventions to retain patients with TB in care , the impOur study has several limitations. The overall sample size was modest. The approaches followed to measure the primary outcome differed according to the study arm (MERM data versus DOT records) that may lead to ascertainment bias. However, this is the conventional approach used for comparing medication event monitors data to standard of care in clinical trial settings. This study was carried out in Addis Ababa, Ethiopia, and this limits the generalizability of our results. Adherence is a multidimensional phenomenon determined by multiple sets of factors that may have biased our findings. Patients are given a fixed-dose combination of anti-TB medication where the findings may not apply in locations that do not use this. We did not use pre-existing scales to measure adherence self-report which may hinder the validity of the measurement. Blinding was not feasible. End-of-treatment outcomes are necessary to demonstrate the impact of DAT among patients with TB more broadly. The use of an individual participant randomized trial, instead of a pragmatic trial, may limit the findings to inform decision-making. However, despite these limitations, we trust the study reveals important findings. We used multiple measurement tools to assess medication adherence, which strengthened the findings. Furthermore, we conducted the study in Ethiopia, one of the countries with the highest burden of TB but poorly represented in such clinical trials. In our recent systematic review of the literature , we founIn this randomized trial of patients with drug-sensitive pulmonary TB, medication adherence among participants assigned to MERM-observed self-administered therapy was non-inferior and superior by some measures when compared with standard in-person DOT. Further research is needed to understand whether adherence in the intervention is primarily driven by allowing self-administered therapy which reduced challenges of repeated clinic visits or by the adherence support provided by the MERM system. To avoid contributing to patient barriers with DOT, TB medical programs should consider alternatives such as medication event monitors.Additional file 1. Study protocol.Additional file 2. CONSORT checklist.Additional file 3. Baseline questionnaire for TB patients.Additional file 4. Patients user leaflet of evriMED500.Additional file 5. Treatment adherence monitoring tool.