N = 4731 in the SGLT2i arms; N = 4736 in the placebo arms). Compared to placebo, SGLT2i treatment was associated with a significant reduction in the risk of AF  and AF/AFL . Subgroup analysis showed that empagliflozin use resulted in a significant reduction in the risk of AF  and AF/AFL . By contrast, dapagliflozin use was not associated with a significant reduction in the risk of AF  or AF/AFL . Additionally, a “shorter” duration (< 1.5 years) of treatment with SGLT2i remained associated with a reduction in the risk of AF  and AF/AFL . In conclusion, SGLT2i therapy was associated with a significant reduction in the risk of AF and AF/AFL in patients with HFrEF. These results reinforce the value of using SGLT2i in this setting.Atrial fibrillation (AF) and atrial flutter (AFL) are associated with adverse outcomes in patients with heart failure and reduced ejection fraction (HFrEF). We investigated the effects of sodium-glucose cotransporter-2 inhibitors (SGLT2i) on the incidence of AF and/or AFL in HFrEF patients. PubMed and ClinicalTrials.gov were systematically searched until March 2022 for randomized controlled trials (RCTs) that enrolled patients with HFrEF. A total of six RCTs with 9467 patients were included (The online version contains supplementary material available at 10.1007/s10741-022-10281-3. Atrial fibrillation (AF) and heart failure with reduced ejection fraction (HFrEF) frequently coexist, and each affects the course and treatment of the other . In patiSodium-glucose cotransporter-2 inhibitors (SGLT2i) have been shown to reduce the risk of HF hospitalization and cardiovascular mortality in patients with HFrEF and represent an effective novel therapeutic modality for this condition –8. InterTherefore, a systematic review and meta-analysis of RCTs that enrolled patients with HFrEF was performed, examining serious adverse event reports of AF and/or AFL according to randomized assignment to SGLT2i or placebo. Furthermore, subgroup analyses were conducted to compare the SGLT2i treatment effect between different drug types and length of follow-up.This meta-analysis was conducted according to the Cochrane Handbook (Version 6.3) and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.PubMed and ClinicalTrials.gov were systematically searched for eligible studies from their inception to March 03, 2022. We screened published and unpublished RCTs using the following search strategy: (sodium-glucose cotransporter-2 inhibitors OR SGLT2 inhibitors OR SGLT-2 inhibitors OR SGLT 2 inhibitors OR empagliflozin OR dapagliflozin OR canagliflozin OR ertugliflozin OR tofogliflozin OR ipragliflozin OR luseogliflozin OR remogliflozin OR sergliflozin OR sotagliflozin) AND . No language restrictions were set. Reference lists of included studies were carefully checked to identify additional studies.Eligible RCTs had to meet the following criteria: (i) enroll patients aged 18 years or older with a diagnosis of HFrEF [left ventricular ejection fraction (LVEF) ≤ 40%]; (ii) compare SGLT2i with placebo; and (iii) report at least one of the predefined outcomes of interest. RCTs focused on conditions other than HFrEF were excluded. Trial eligibility was assessed by two independent reviewers (D.S. and T.L.). Discrepancies between reviewers were resolved by consensus or, if necessary, by a third investigator (P.K.).Primary outcomes of interest included the incidence of AF, AFL, and the composite of AF/AFL (new-onset and recurrent events of relevant arrhythmias) reported as serious adverse events according to Medical Dictionary for Drug Regulatory Activities (MedDRA). Prespecified subgroup analyses by SGLT2i agent used and follow-up duration were conducted to compare the SGLT2i treatment effect between different drug types and length of follow-up. Subgroup analysis by dosage was not performed because the included studies examined only the doses of 10 mg empagliflozin and 10 mg dapagliflozin.Two reviewers (D.S. and T.L.) independently performed data extraction using a standard form, including study characteristics, sample size, study design, follow-up duration, baseline characteristics of study population, interventions, comparisons, and outcomes of interest. Quality assessment of included RCTs was conducted using the Cochrane Risk of Bias Tool (performed by D.S. and T.L.). Discrepancies were resolved by consensus, or if necessary, by adjudication from a third investigator (P.K.).I2 before the meta-analysis. For the Q test, a P value < 0.1 was considered statistically significant. Additionally, I2 > 50% indicated at least moderate heterogeneity. If heterogeneity was present, as suggested by P value < 0.1 or I2 > 50%, the random-effects (RE) model was applied; otherwise, the fixed effects (FE) model was applied. All analyses were conducted using Review Manager .The collected raw data were used to calculate relative risks (RRs) and 95% confidence intervals (CIs), which were then pooled in meta-analyses. The pooled RRs and corresponding 95% CIs were used to present the incidence of AF, AFL, and the composite of AF/AFL. Heterogeneity was assessed using the Cochran Q statistic and Higgins and Thompson N = 4731 in the SGLT2i arms; N = 4736 in the placebo arms) matched the predefined inclusion criteria and were included in the final meta-analysis. The PRISMA flow diagram is presented in Supplementary material online, Appendix Fig. Among the 2164 records identified, six RCTs  includinN = 9467) and the outcome evaluation population (N = 9454). Since the difference between the two sets was very small , it was considered unlikely that it could have influenced the pooled results. Therefore, a low risk of bias was still considered.The results of the quality assessment are presented in Supplementary material online, Appendix Figs. N = 4725) and 88 in the placebo group (N = 4729). After pooling the six trials, treatment with SGLT2i was associated with a significant reduction in the risk of AF compared to placebo  . Visual inspection of the funnel plot suggested no apparent publication bias , whereas dapagliflozin use was not associated with a reduction in the risk of AF   remained associated with a significant reduction in the risk of AF .AF was reported in six RCTs , 16–19. N = 4231) and 14 in the placebo group (N = 4231). Since substantial heterogeneity was identified , the two trials were pooled using the random-effects model. Overall, there was no significant difference between the SGLT2i arm and the placebo arm in the incidence of AFL   . Visual inspection of the funnel plot suggested no apparent publication bias , whereas dapagliflozin use was not associated with a significant reduction in the risk of AF/AFL   was still associated with a significant reduction in the risk of AF/AFL . Interestingly, there was substantial heterogeneity between the subgroups of empagliflozin and dapagliflozin (I2 = 61%) and moderate heterogeneity between the subgroups of shorter and longer duration of follow-up (I2 = 48.5%).When AF and AFL were combined as a composite endpoint, treatment with SGLT2i was associated with a significant reduction in the risk of AF/AFL compared to placebo  Fig. . Given tAFL Fig. . In subgThe present meta-analysis demonstrated that SGLT2i treatment was associated with a significant reduction in the risk of AF and AF/AFL in patients with HFrEF. In subgroup analysis by SGLT2i agent used, the use of empagliflozin, but not dapagliflozin, resulted in a significant reduction in the risk of AF and AF/AFL. In subgroup analysis by follow-up duration, a “shorter” duration (< 1.5 years) of treatment with SGLT2i remained associated with a significant reduction in the risk of AF and AF/AFL. As far as AFL is concerned, no significant association was observed.AF, especially if new-onset or paroxysmal, confers a worse prognosis in patients with HFrEF , 20. In + and Ca2+ handling abnormalities in the atrial cardiomyocyte level, which may prevent the triggering and maintenance of AF [The results of the present meta-analysis suggest that SGLT2i may have a favorable impact on the mechanistic pathways of AF and AF/AFL in patients with HFrEF. Although a significant association between SGLT2i and AFL was not observed, the number of AFL events was low, and this might have contributed to a wide confidence interval. Nonetheless, AFL is considered to have similar clinical significance and consequences to AF, and the combined analysis of AF/AFL showing a significant risk reduction might eliminate possible publication bias for AFL. In support of the results of this meta-analysis, SGLT2i have recently been shown to mitigate adverse cardiac remodeling and fibrosis , 22–24. ce of AF –29. Evence of AF , 31. Alsce of AF , 31. Morce of AF , 32. Nevce of AF . Finallyce of AF , 33.This meta-analysis has several potential limitations. Firstly, AF and AFL were not the prespecified outcomes of the included trials; therefore, there might be ascertainment bias. Secondly, only AF or AFL events that were reported as serious adverse events according to MedDRA were included. Thirdly, the trials included were underpowered to study arrhythmia outcomes. Fourthly, the included trials examined only empagliflozin and dapagliflozin. Fifthly, most of the weight of the statistical analysis depended only on two studies, namely, EMPEROR-Reduced and DAPA-HF. Sixthly, most of the weight of the empagliflozin and dapagliflozin subgroups depended on the EMPEROR-Reduced and DAPA-HF trials, respectively, and therefore the results of subgroup analysis by agent used may have been influenced by the different populations included in them. Consequently, whether the use of empagliflozin results in a significant reduction in the risk of AF and AF/AFL, and dapagliflozin does not, needs to be further investigated. Seventhly, there were five RCTs that had shorter duration of follow-up (< 1.5 years), and only one RCT that had relatively longer duration of follow-up (> 1.5 years), restricting the significance of the results of subgroup analysis by follow-up duration. Finally, the included trials examined only the doses of 10 mg empagliflozin and 10 mg dapagliflozin, rendering subgroup analysis by dosage unfeasible. In this context, further research with adequately powered RCTs to study arrhythmia outcomes is needed.SGLT2i therapy was associated with a significant reduction in the risk of AF and AF/AFL in patients with HFrEF. These results reinforce the value of using SGLT2i in these patients. Further data with properly designed RCTs are needed to confirm the present findings, as well as to evaluate and elucidate the potential antiarrhythmic effects of SGLT2i in patients with HFrEF.Supplementary file1 (DOCX 39 KB) Supplementary material online, Appendix Figure S1: Prisma flow diagram of study selection processSupplementary file2 (PDF 238 KB) Supplementary material online, Appendix Figure S2: Results of the quality assessment (risk of bias graph)Supplementary file3 (PDF 263 KB) Supplementary material online, Appendix Figure S3: Results of the quality assessment (risk of bias summary)Supplementary file4 (PDF 257 KB) Supplementary material online, Appendix Figure S4: Forest plot comparing the incidence of AFL between SGLT2i and placebo. CI, confidence interval; AFL, atrial flutter; SGLT2i, sodium–glucose cotransporter-2 inhibitorsSupplementary file5 (PDF 28 KB) Supplementary material online, Appendix Figure S5: Funnel plot of meta-analysis for the incidence of AFL. RR, relative risk; AFL, atrial flutter; SE, standard errorSupplementary file6 (PDF 58 KB) Supplementary material online, Appendix Figure S6: Funnel plot of subgroup analysis by SGLT2i agent used comparing the incidence of AF/AFL between SGLT2i and placebo. RR, relative risk; AF, atrial fibrillation; AFL, atrial flutter; SE, standard errorSupplementary file7 (PDF 86 KB) Supplementary material online, Appendix Figure S7: Funnel plot of subgroup analysis by follow-up duration comparing the incidence of AF/AFL between SGLT2i and placebo. RR, relative risk; AF, atrial fibrillation; AFL, atrial flutter; SE, standard errorBelow is the link to the electronic supplementary material.


The sensitivity of HIV screening assays often leads to a high rate of false-positive results, requiring retests and confirmatory tests. This study aimed to analyze the capability of signal-to-cutoff (S/CO) ratios of HIV screening assay to predict HIV infection.A retrospective study on the HIV screening-positive population was performed at Zhongshan Hospital, Xiamen University, the correlation between HIV screening assay S/CO ratios and HIV infection was assessed, and plotted Receiver Operating Characteristic (ROC) curves were generated to establish the optimal cutoff value for predicting HIV infection.P < 0.001). The rate of confirmed HIV infection was increased with higher S/CO ratios in the screening assay. The ROC curve based on the HIV screening assay S/CO ratio achieved a sensitivity of 93.78% and a specificity of 93.12% with an optimal cutoff value of 14.09. The area under the ROC curve was 0.9612. Further analysis of the ROC curve indicated that the S/CO ratio thresholds yielding positive predictive values of 99%, 99.5%, and 100% for HIV infection were 26.25, 285.7, and 354.5, respectively.Out of 396,679 patients, 836 were confirmed to be HIV-infected, with an HIV prevalence of 0.21%. The median S/CO ratios in HIV infection were significantly higher than that in non-HIV infection (296.9 vs. 2.41, Using HIV screening assay S/CO ratio to predict HIV infection can largely reduce necessitating retests and confirmatory tests. Incorporating the S/CO ratio into HIV testing algorithms can have significant implications for medical and public health practices. Acquired immunodeficiency syndrome (AIDS), caused by infection with the human immunodeficiency virus (HIV), is one of the most prevalent sexually transmitted diseases throughout the world . Early aHIV screening assays are commonly reported as positive or negative based on a signal-to-cutoff (S/CO) threshold. Previous research has shown that the strength of the S/CO value is correlated with the likelihood of a positive confirmatory test result for certain HIV screening assays –6. By adThis retrospective study aims to analyze patients’ data from Zhongshan Hospital, Xiamen University, to evaluate the association between the S/CO ratio and HIV infection within the HIV screening-positive population. Additionally, Receiver operating characteristic (ROC) curves were generated based on the S/CO ratio. The primary objective of this investigation is to establish an optimal cutoff value for predicting HIV infection, thereby enhancing the efficiency of clinical decision-making and treatment processes. This will enable the broader implementation of the S/CO ratio as a predictive tool for HIV infection.This retrospective study was conducted at Zhongshan Hospital, Xiamen University, which is an affiliated comprehensive tertiary hospital of Xiamen University. The subjects included inpatients, outpatients and physical examination populations who had undergone HIV screening from January 1, 2016, to December 31, 2022. The inclusion criteria of subjects were available integrity information. No loss of participants occurred during the HIV testing process and no loss of results of tests received by the subjects. A detailed manual chart review was performed to obtain the patients’ clinical characteristics . Ethical approval for this study was obtained from the Research Ethics Committee of Zhongshan Hospital, Xiamen University (xmzsyyky2021-195), per national legislation and the Declaration of Helsinki Guidelines. Adult participants provided written consent to participate and minors provided written assent along with written consent from a parent/legal guardian.In this study, a chemiluminescent immunoassay  was used as a preliminary screening test for HIV detection. The optical density of the reaction system was measured and compared to the threshold value provided in the manufacturers’ instructions to calculate the S/CO ratio. A S/CO ratio of ≥ 1 was considered a positive result, while a S/CO ratio of < 1 was considered a negative result. If the initial HIV screening assay yielded a positive result, the sample was retested in duplicate using the same chemiluminescent immunoassay. Results were considered HIV-negative if both duplicate tests were negative. If at least one of the tests was positive, the sample was then referred to Xiamen Center for Disease Control and Prevention for further confirmatory using Western Blot . The determination of the positive, indeterminate, or negative status of the tested samples was based on the criteria specified in the manufacturers’ instructions. Indeterminate samples underwent further HIV nucleic acid detection. Determine the test results according to the kit instructions. A “reactive” test result is reported as positive for HIV nucleic acid detection. A “nonreactive” test result is reported as negative for HIV nucleic acid detection. Test results from Western Blot or HIV nucleic acid detection were regarded as the reference standard for diagnosing HIV infection. Finally, HIV screening-positive patients were categorized as HIV-infected if Western Blot or HIV nucleic acid detection was reactive.P < 0.05 was considered statistically significant.The statistical analyses were performed utilizing SPSS Statistics version 26 and GraphPad Prism version 8 . Normally distributed data were tested using the Student’s t-test. The Nonparametric Mann-Whitney U test was used when two non-normally distributed groups were compared. Categorical data were tested by Chi-square test and Chi-square test for trend. The Spearman rank correlation test was used to investigate the correlation between two variables. The ROC curve was plotted, the optimal cutoff point was determined using the ROC curve, and the area under the ROC curve (AUC) was calculated. A A total of 396,679 individuals underwent HIV screening assay, with 1,083 patients testing positive for HIV and subsequently undergoing Western Blot confirmatory testing. Of these, 247 patients exhibited a nonreactive result, while 796 patients were reactive. Additionally, 40 indeterminate samples were subsequently serologically reactive. Thus, of the 1083 samples that HIV screening-positive, 836 were confirmed to be HIV-infected, while 247 were not. The HIV prevalence rate was 0.21%  . According to the age group criteria in China and the age distribution of subjects, age was divided into following stages: minor (0–17 years), youth adult (18–28 years), adult (29–40 years), middle age (41–65 years) and old age (≥ 66 years). Comparing the proportion of diagnosed HIV-infected individuals among HIV screening-positive individuals in different age groups, the rate of diagnosed HIV infection among HIV screening-positive patients decreased with increasing age among those aged 18 years and older . Comparison of the proportion of HIV-infected patients among HIV screening-positive individuals revealed a statistical difference between the different years . This may be related to the different HIV prevalence status and HIV screening populations from year to year. Among HIV screening-positive patients, the rate of HIV infection was higher in males (84.7%) compared to females (51.4%)  (Table The mean age of HIV infection (39 years) was less than that of non-HIV infection (50 years) . In Fig. P < 0.001). Then, according to the statistical quartile method, the HIV screening-positive patients were divided into four groups based on HIV screening S/CO ratio: 1.0-10.6 (n = 271), 10.7–202.0 (n = 271), 202.1-431.6 (n = 271), > 431.6 (n = 270), and a Chi-square test for trend was performed to evaluate the association between HIV screening S/CO ratio and the rate of diagnosed HIV infection. The rates of diagnosed HIV infection of groups were presented in Fig. P for trend < 0.001).Figure 10.6 n = 71, 10.7–P < 0.001). Based on the Youden index, the optimal cutoff value of the S/CO ratio for predicting HIV infection was identified as 14.09, which corresponded with a positive predictive value (PPV) of 97.88%. As the cutoff value of the S/CO ratio increased, the PPV for HIV infection also increased. Further analysis of the ROC curve indicated that the S/CO ratio thresholds yielding PPVs of 99%, 99.5%, and 100% for HIV infection were 26.25, 285.7, and 354.5, respectively  test followed by an HIV-1/2 antibody (Ab) differentiation test and, if necessary, a diagnostic HIV-1 nucleic acid test (NAT) to resolve discordant or indeterminate results. In China, the “2020 National Guideline for Detection of HIV/AIDS” proposed a new diagnostic algorithm which included nucleic acid detection to resolve indeterminate HIV antibody test results. In this study, we reviewed the HIV test results of 396,679 individuals. HIV nucleic acid detection was performed on 40 patients with indeterminate Western Blot results, all of which were reactive. HIV nucleic acid detection is highly sensitive and can detect the window period of HIV infection in time. Thus, HIV nucleic acid detection can detect acute or early HIV infection, in which HIV antibody tests are likely to be negative or indeterminate . The likAmong 396,679 subjects, 1,083 screened positive for HIV, out of which 836 were HIV-infected or living with AIDS. The detection positivity rate of HIV was found to be low (0.21%). In areas with low HIV prevalence, HIV screening is prone to false positive results, which increases reagent and personnel costs . Based oIn our study, more than 80% of men who received positive HIV screening results were eventually diagnosed with HIV infection, while only about half of women were diagnosed with HIV infection, which is consistent with previous studies . In addiThis study also has some limitations. First, the sample source of this study was a single center. The prevalence of HIV infection was inconsistent across regions. The cutoff values used in our study did not apply to other organizations. We recommend that individual institutions research to determine their appropriate cutoff values. Second, for samples with inconsistent results between the HIV screening assay and the confirmatory test, we did not conduct further HIV nucleic acid amplification tests, which may compromise the accuracy in determining the HIV infection status of the samples.There is a positive correlation between HIV screening assay S/CO ratios and the likelihood of HIV infection. Using a S/CO ratio of 26.25 to predict HIV infection can largely reduce testing costs. For patients with S/CO ratios higher than this threshold, it can effectively accelerate the time for treatment initiation and enable early intervention. Utilizing the HIV screening assay S/CO ratio to promote updates of HIV testing algorithms will have significant value in medical and public health practice.


Patients with inflammatory bowel disease (IBD) are at increased risk of herpes zoster (HZ). We evaluated the incidence of HZ in ulcerative colitis (UC) and Crohn’s disease (CD) patients and compared this with HZ incidence in a non-IBD population.We conducted a retrospective cohort study (GSK study identifier: VEO-000043) of adults aged ≥18 years with UC and CD and without IBD who were identified from claims recorded in a US healthcare database between October 2015 and February 2020. Crude HZ incidence rates/1,000 person-years (PY) were calculated, and comparisons of HZ incidence rates between UC or CD and non-IBD cohorts were made using adjusted generalized linear models.The study population comprised a total of 29,928 UC, 25,959 CD, and 11,839,329 non-IBD patients. Crude overall HZ incidence rates were 13.64/1,000 PY (UC), 15.94/1,000 PY (CD), and 7.95/1,000 PY (non-IBD). UC and CD patients had increased HZ incidence rates, with adjusted incidence rate ratios of 1.35  and 1.66 , respectively, compared with non-IBD patients. Stratified analysis indicated increased relative rates of HZ in progressively younger age strata in the UC and CD patients compared with non-IBD patients. HZ incidence rates were higher in UC and CD patients who had previously received thiopurines or methotrexate, TNF-inhibitors, or corticosteroids than in UC and CD patients who did not take those medicines.UC and CD patients had increased HZ incidence rates compared with patients without IBD, demonstrating the importance of HZ prevention in IBD patients.  Herpes zoster (HZ) is an acute, painful, and debilitating condition that results from the reactivation of latent varicella–zoster virus (VZV) infection . This reStudies evaluating HZ incidence in patients with inflammatory bowel disease (IBD) compared with HZ incidence in non-IBD or general populations have also reported a higher incidence of HZ in IBD patients , with a IBD medication use can also influence HZ risk. Most studies consistently reported a higher risk of HZ in IBD patients receiving systemic corticosteroids  and thosPrevious studies in the USA evaluating HZ incidence in patients with IBD were conducted prior to more widespread use of anti-TNF agents and newer immunosuppressive agents  or chiefThis was a retrospective longitudinal cohort study (GSK study identifier: VEO-000043) using patient-level medical and pharmacy claims data sourced from the Optum’s de-identified Clinformatics Data Mart Database. This contains healthcare information on 15–19 million annual covered lives insured by commercial or Medicare Advantage plans across all 50 states in the USA. The database captures enrolment, demographics, health plan eligibility, and medical and prescription-drug claims arising from inpatient stays and outpatient care, identifiable via diagnostic and medication codes.The study utilized data spanning the period from 1 October 2015 to 28 February 2020 to estimate HZ incidence rates in UC and CD patients, evaluated as separate and mutually exclusive cohorts, with each compared with a single non-IBD patient cohort .Eligible individuals were patients ≥18 years of age with ≥6 months of continuous enrolment prior to the index date (which marked the beginning of observation for incident HZ) and ≥18 months of continuous enrolment after the index date. Patients were assigned to one of three mutually exclusive study cohorts  on the basis of claims associated with relevant International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes. For the UC cohort, patients were required to have at least two claims associated with a UC diagnosis  on separate days within a 12-month period, or at least one claim associated with a UC diagnosis and at least one pharmacy claim for an IBD-related medication  within 30 days after the UC diagnosis. The index date was the date of the first UC diagnosis claim or the 6-month point from the start of continuous enrolment, whichever was latest. CD cohort inclusion followed a similar approach, with patients identified using ICD-10-CM diagnosis code K50 . For patBaseline patient demographics, i.e. age, sex, region, and insurance plan type, were identified as of the index date. Clinical characteristics were assessed during the 6-month baseline period prior to the index date. For all cohorts this included an assessment of co-morbidities, conditions associated with a potentially increased risk of HZ, and immunosuppressive medication use (identified via relevant ICD-10-CM and medication codes). Overall co-morbidity burden was estimated using the modified Charlson–Quan co-morbidity index (CCI) . MarkersAll patients were followed up for ≥18 months post-index date or until incident HZ (event) or HZ vaccination (censor). Patients with neither HZ nor HZ vaccination were censored at the end of their continuous enrolment period. Incident HZ was defined as at least one claim associated with an HZ diagnosis  occurring during the observation period.The study objectives were to (i) estimate crude and age-stratified HZ incidence rates per 1,000 PY in the UC, CD, and non-IBD cohorts, and (ii) compare incidence rates  in patients with UC or with CD vs those patients without IBD. For the UC and CD cohorts, an additional objective was to estimate HZ incidence rates in patients receiving specific IBD medications.Descriptive analyses were performed for all study variables for each cohort. For continuous variables, mean values ± standard deviations (SD) and medians were calculated, while frequency counts and percentages were calculated for categorical variables. The balance of baseline characteristics across cohorts was assessed using standardized differences, where standardized differences of 20%, 50%, and 80% suggest small, medium, and large differences between cohorts, respectively .HZ incidence rates were calculated as the number of patients with incident HZ divided by the person-time observed and expressed per 1,000 PY. Incidence was calculated for each cohort , both overall and stratified by age. Adjusted incidence rate ratios (aIRRs) were estimated to compare HZ incidence rates between UC and non-IBD cohorts, and between CD and non-IBD cohorts, using generalized linear models with a Poisson distribution, and log link, and accounting for differences in patients’ baseline characteristics using doubly-robust propensity score adjustment. In this approach, propensity scores were estimated using logistic regression with IBD status as the outcome, i.e. UC vs non-IBD and, separately, CD vs non-IBD. Key baseline demographics  and clinical variables  were included in the propensity score models as predictors . In thisThe study employed a retrospective cohort study design using a large administrative claims database. Data were de-identified and comply with the requirements of the Health Insurance Portability and Accountability Act. Institutional Review Board review and approval were therefore not required, as per the United States Department of Health and Human Services regulation for the protection of human subjects in research (45 CFR 46) . The stuBetween 1 October 2015 and 28 February 2020, the database included 32,157,116 patients, of whom 279,220 (0.9%) had at least one claim for IBD (either UC or CD) at any time and 113,805 had a confirmed UC or CD diagnosis. After applying the eligibility criteria of the study, the final cohorts included 29,928 patients with UC, 25,959 patients with CD, and 11,839,329 patients without IBD . SelecteThe majority of patients in the UC and CD cohorts had an index date in 2017  or 2018 , whereas 69.2% of the non-IBD cohort had a 2016 index date. Of the UC cohort, 54.1% were female, with a mean age (± SD) of 60.0 ± 17.4 years. For the CD cohort, 56.9% were female, with a mean age of 56.2 ± 17.9 years; for the non-IBD cohort, 52.1% were female, with a mean age of 54.0 ± 19.0 years. The co-morbidity burden was similar in the UC and CD cohorts (mean CCI 0.8 ± 1.4) and greater than that observed in the non-IBD cohort (0.4 ± 1.0). The prevalence of specific co-morbidities varied between cohorts, although for most co-morbidities, standardized differences were <20% . PropensBaseline use of IBD-related medications (as assessed during the 6-month period prior to the index date) was common, with nearly half of the patients in the UC cohort (49.9%) and slightly more in the CD cohort (53.3%) using IBD-related medications. The use of specific classes of medications was slightly lower in the UC cohort than in the CD cohort: thiopurines , anti-TNF biologics , and corticosteroid use  . RelativPatients with UC were followed up for a mean time (± SD) of 25.3 ± 7.0 months and those with CD were followed up for 26.4 ± 7.6 months; the non-IBD cohort was followed up for 34.3 ± 11.2 months. The study included a total of 33,939,920 PY of observation time, with 62,986 PY for the UC cohort, 57,141 PY for the CD cohort, and 33,819,793 PY for the non-IBD cohort. A total of 270,629 cases of incident HZ were identified with 859 in the UC cohort, 911 in the CD cohort, and 268,859 HZ cases in the non-IBD cohort. The overall crude incidence rate for HZ was 13.64 per 1,000 PY in the UC cohort, 15.94 per 1,000 PY in the CD cohort, and 7.95 per 1,000 PY in the non-IBD cohort . In all P < 0.001). Age-specific aIRRs were higher in UC patients aged <50 years, with an aIRR of 1.85  in patients aged 18–29 years and 1.80  in those aged 30–39 years (P < 0.001). aIRRs were higher still in younger patients, with aIRRs of 3.35  and 2.29 , respectively, in patients aged 18–29 and 30–39 years (both P < 0.001).After adjustment for baseline covariates, compared with non-IBD patients, the aIRR for incident HZ in UC patients was 1.35  of 1.81  for UC patients and 1.56  for CD patients compared with a non-IBD cohort, although the risk differences between the UC and CD cohorts were not significant [In this retrospective claims-database analysis, we evaluated HZ incidence rates in patients with IBD, stratified into mutually exclusive UC and CD patient cohorts, and evaluated the risk of HZ compared with a large, non-IBD population using adjusted multivariate analyses. We found that the HZ incidence rate was higher in both UC and CD patients  than in the patients without IBD . UC and CD were associated with an increased risk of HZ, with a 1.35-fold greater incidence of HZ in UC patients and a 1.66-fold greater incidence of HZ in CD patients than in the non-IBD population, after adjusting for baseline differences between cohorts. These findings are consistent with previous studies reporting a higher HZ incidence rate and greater relative risk of HZ in IBD patients , 21. We In previous studies , 3, the We also evaluated the HZ incidence associated with IBD medication use. HZ incidence rates were lower among patients receiving conservative treatment  than among patients receiving other therapies—a pattern seen in both the UC and CD cohorts. HZ incidence rates were higher in patients receiving TNF-inhibitors, even higher in those receiving thiopurines or methotrexate, and highest in those also receiving corticosteroids. In contrast to some previous US studies that evaluated HZ risk associated with medication exposure time or compared HZ risk in IBD patients receiving specific medications relative to those IBD patients receiving only 5-ASA , 9, our This study has several limitations. It was conducted using administrative claims data and thus has limitations common to all such retrospective database analyses, such as billing record miscoding, missing data, and a lack of detailed clinical data. While we used ICD-10-CM codes to identify patients with HZ, this may have failed to identify some eligible patients, including those patients with less severe HZ who did not seek medical care. As such, HZ case numbers and the resultant incidence estimations may be underestimates. It is also possible that some patients identified as having HZ were misdiagnosed based on the presentation of disease, which could have resulted in misclassification in the study. While we adjusted for potential confounders using measures of patients’ baseline clinical and demographic characteristics using a doubly-robust approach (by including both propensity score and baseline variables in our models for comparisons of incidence rates), residual confounding may have influenced our findings. For example, studies from Taiwan have found that HZ risk is higher in patients following appendectomy or splenectomy, and with other co-morbidities such as varicocele . While set al., although any such risk was non-significant [et al., who found a significantly higher risk in both UC and CD patients receiving 5-ASA than in non-IBD patients [Our pragmatic approach to medication groupings has some limitations. For example, we grouped patients receiving no therapy or receiving budesonide or 5-ASA as a single category, where our goal was to look at those patients receiving no or only limited immunosuppressive therapy. However, 5-ASA may carry some additive risk for HZ, as reported in previous US studies, e.g. by Long nificant , and morpatients .The study included a relatively high number of patients in our UC and CD cohorts characterized as receiving no IBD medications during the 6-month period prior to the index date (50% of UC patients and 47% of CD patients). While this proportion of patients is relatively large, previous US studies using insurance claims data have reported similarly large proportions of IBD patients receiving no therapy , 26. WhiWe grouped vedolizumab and ustekinumab together, in part to distinguish these agents from other medication classes with recognized HZ risk (e.g. JAK inhibitors). However, vedolizumab and ustekinumab have different mechanisms of actions, and may also differ in their potential impact on risk for HZ. In the present study, our findings that the crude HZ incidence rates in our UC and CD cohorts for patients receiving vedolizumab and/or ustekinumab were lower than that observed for the ‘no therapy or receiving budesonide or receiving 5-ASA’ category would be consistent with previous data indicating little additive risk  and may A further limitation of our medication analyses was in only addressing medication use at the end of the observation period for incident HZ, and we did not account for exposure to other medications preceding this, or for therapy switching or medication adherence.A key strength of the present study is that our analysis was conducted across a large adult population that included a high proportion of patients <50 years of age  and with a slight majority of female patients in each cohort (ranging from 52% to 57%). In this respect, our study is complementary to other recent US studies, which focused on predominantly male (>90%) and slightly older populations . In addiThe higher HZ incidence rates and increased risk of HZ in UC and CD patients that we reported may provide support for the broader use of HZ vaccination in adult patients with IBD . A recomet al. reported that no HZ cases were observed in a total of 655 IBD patients aged 50–60 years after receiving a complete two-dose RZV schedule, while 69 HZ cases were observed in a total of 5,995 unvaccinated IBD patients (with a resultant HR for HZ of 0) [Recent observational studies in the USA evaluating RZV use in IBD patients have provided initial evidence of substantial reductions in HZ risk , 39. In HZ of 0) . For thoHZ of 0) . It shouHZ of 0) . Safety HZ of 0) , 41. In Previous studies were conducted prior to the recent recommendations for RZV use in younger immunodeficient or immunosuppressed patients . Based ogoad016_Supplementary_DataClick here for additional data file.


Coronary artery disease (CAD) usually coexists with subclinical cerebrovascular diseases given the systematic nature of atherosclerosis. In this study, our objective was to predict the progression of white matter hyperintensity (WMH) and find its risk factors in CAD patients using the coronary artery calcium (CAC) score. We also investigated the relationship between the CAC score and the WMH volume in different brain regions.n = 66) and nonprogressive groups (n = 71) by the change in WMH volume from the first to the second MRI. We collected demographic, clinical, and imaging data for analysis. Independent risk factors for WMH progression were identified using logistic regression. Three models predicting WMH progression were developed and assessed. Finally, patients were divided into groups based on their total CAC score  to compare their WMH changes in nine brain regions.We evaluated 137 CAD patients with WMH who underwent coronary computed tomography angiography (CCTA) and two magnetic resonance imaging (MRI) scans from March 2018 to February 2023. Patients were categorized into progressive (p < 0.05). The logistic regression model with all four variables performed best . An increased CAC risk grade came with significantly higher WMH volume in the total brain, corpus callosum, and frontal, parietal and occipital lobes (p < 0.05).Alcohol abuse, maximum pericoronary fat attenuation index (pFAI), CT-fractional flow reserve (CT-FFR), and CAC risk grade independently predicted WMH progression (This study demonstrated the application of the CCTA-derived CAC score to predict WMH progression in elderly people (≥60 years) with CAD. White matter hyperintensity (WMH) is a prevalent manifestation in cerebral small vessel disorders. The pathogenesis of WMH is interconnected with various pathological conditions that impact the small arteries, capillaries, and small veins that perfuse brain tissue, causing damage to both gray and white matter . This tyCardiovascular disease, including coronary artery disease (CAD), is the primary cause of mortality in developed nations . It is eThe coronary artery calcium (CAC) score is a non-invasive metric derived from non-contrast coronary computed tomography angiography (CCTA) images. It measures the volume of calcium in coronary arteries to assess individual plaque accumulation . The CACThe complex and multifactorial relationship between the CAC score and WMH remains unclear. It is critical to monitor changes in WMH in patients with coronary atherosclerosis, since such changes may affect their prognosis and treatment. Our preliminary research discovered a linear correlation between the CAC score and the volume of WMH in elderly populations with high clinical risk factors, which suggested that the CAC score could serve as an imaging biomarker predicting the progression of WMH . TherefoThis study was approved by the Ethics Committee of ZJPP Hospital. Due to the retrospective application of imaging data, the need for informed consent was waived. The investigation complied with the principles set out in the Declaration of Helsinki.This retrospective study gathered data from 1,452 patients who had both CCTA and brain MRI at Zhejiang Provincial People’s Hospital between March 2018 and February 2023. Of these, 364 patients had WMH and underwent a second brain MRI after a 12-month interval. Among them, 137 patients met the inclusion criteria and were allocated to the training and validation models. The inclusion criteria were as follows: (1) WMH seen on T2 FLAIR and T2 weighted MR images; (2) age 60 or above; (3) absence of stroke (not counting lacunar infarction) on the DWI sequence; (4) no neurological symptoms such as Alzheimer’s disease, multiple sclerosis, or major brain injuries; (5) no history of heart attack or coronary stenting; and (6) symptoms of typical or atypical angina persisting for at least 3 months. Exclusion criteria: (1) intracranial infection or inflammation; (2) heart valve disease or irregular heart rhythm; (3) past cerebral infarction or mini-stroke; (4) inability to provide full baseline information; and (5) poor quality of MRI and CCTA images. Demographic and clinical data of all study participants were gathered, including age, sex, body mass index (BMI), hypertension, hyperlipidemia, diabetes, smoking, and alcohol abuse. The calculation of BMI involved dividing weight (in kgs) by the square of height (in meters). The criteria for hypertension included a systolic blood pressure not less than 140 mmHg, a diastolic blood pressure at least 90 mmHg, or the regular use of hypertension medication. Hyperlipidemia was identified if the participants had total cholesterol ≥240 mg/dL, had low-density lipoprotein cholesterol ≥160 mg/dL, or were taking lipid-lowering drugs. The presence of diabetes was determined by the intake of diabetic pills or an HbA1c level of 6.5% or more . All theCCTA was done by using a third-generation dual-energy CT (DECT) scanner . The patient was told to fast before the examination, and the patient’s heart rate, height and weight were measured. After acquisition of the localization image, the contrast agent iohexol (350 mg I/mL) was injected via the right median vein at a rate of 5.0 mL/s using a high-pressure syringe, and the contrast agent injected was 30 mL of contrast agent plus 40 mL of saline. The scan was triggered using bolus tracking, with the region of interest (ROI) placed in the ascending aorta at a threshold of 100 Hounsfield units (HU) and a 4-s delay in initiating the scan. The image quality imaging conditions were 100 kVp, 288 mAs, other scan parameters: prospective cardiac gating, 65% RR interval, pitch 3.2, 0.25 s/r, detector collimation width 192 × 0.6 mm, reconstruction layer thickness and interval 3 mm.3, spread across at least three neighboring pixels, were detected using 3D-based tools. The areas of calcium in each slice, approximately 3 mm thickness, were bolstered by an intensity factor and added up across slices to calculate the CAC score through the Agatston method. With this method, the CAC volume was measured by multiplying the area of each lesion by a weighted attenuation score, which depends on the maximum attenuation within the lesion. Two radiologists  reviewed and corrected the presence and amount of CAC independently, both blinded to the clinical information of all patients. The total CAC score was grouped into low-risk (score under 100), medium-risk (score between 100 and 400) and high-risk categories (score over 400). The measurement of CAC score is depicted in The non-contrast image sets were reconstructed (B35f HeartView medium CaScore), and CAC was identified and quantified using syngo.via calcium scoring software . The four key coronary arteries assessed included the left main artery (LM), left anterior descending artery (LAD), right coronary artery (RCA), and left circumflex artery (LCX). We defined the total CAC score as the sum of the CAC burden of the four coronary vessels. Lesions going beyond the calcium threshold of 130 HU within a volume of 1 mmWe used the PHIgo workstation  to measure the CT-FFR value and pFAI value of the target lesion based on threshold values for a high risk of CAD (CT-FFR ≤ 0.80 and pFAI ≥ −70.1 HU) . ArteriaAll brain MRI scans were carried out at a local hospital using a 3.0-tesla MRI scanner . This scanner was equipped with an eight-channel head coil. Consistent MRI parameters were maintained during scans, including T1 FLAIR, T2-weighted imaging, diffusion-weighted imaging (DWI), and T2 FLAIR sequences. The T2 FLAIR sequence was used to observe WMH, applying parameters such as a repetition time/echo time/inversion time of 9,000 ms/120 ms/2,412 ms, a field of view of 256 × 256 mm, a matrix of 256 × 256, a flip angle of 160°, an echo chain of 18, a bandwidth of 50 kHz, a 5 mm section thickness, and a zero interslice gap. T1 FLAIR was used for white matter segmentation, with settings such as a 1,750 ms repetition time, a 24 ms echo time, a 256 × 256 mm field of view, a 256 × 256 resolution, a 111° flip angle, a 10 echo chain, a 31.25 kHz bandwidth, a 5 mm section thickness, and a zero interslice gap.All T1 FLAIR and T2 FLAIR baseline images were imported into SPM12 softwareThe clinical details of patients with progressive WMH were divided into two categories in each dataset. We then compared the differences in CAC score between these categories to identify potential predictive variables. Univariate logistic regression was applied to each predictive factor in the training set. Next, three models were developed using multivariable logistic regression to assess WMH progression: Model 1 incorporated traditional cardiovascular risk factors; Model 2 included CT-FFR and pFAI on top of Model 1; and Model 3 was Model 2 plus the CAC index. Internal validation of the three models was performed with the validation set.3 with default settings. To ensure accurate capture of WMH, all LPMs were visually inspected against the FLAIR images and manually corrected by an experienced radiologist according to published standards . We further compared the WMH variations across the different brain regions between the three CAC risk groups.WMH from each participant were segmented using LPA. Lesion probabilities were estimated for each voxel to segment WMH lesions observed in FLAIR images, and then local spatial lesion probability maps (LPMs) were calculated. The LPM was binarized (threshold = 0.5) with a minimum clustering range of 15 mmtandards . We usedp < 0.05 was significant.The statistical processing was done with SPSS 23.0 , MedCalc 19.3.1, and Excel 2019 (Microsoft). Categorical variables are presented as n (%), and parametric data are reported as mean ± SD, following the application of the Kolmogorov–Smirnov test for normality. The chi-square test or Fisher’s exact test was used for categorical variable comparisons, while Student’s t test was utilized for continuous variable comparisons. After a comparative analysis of the CAC score between the two datasets per risk factor, significant risk factors were incorporated into the univariate logistic regression to calculate their association with WMH progression. Three predictive models were formulated based on multivariable logistic stepwise regression in a training set to evaluate WMH progression. The models’ efficiency was validated using the receiver operating characteristic (ROC) curve, sensitivity, specificity, accuracy, precision, and F1-score. Finally, we compared the differences in WMH outcomes in different brain regions among patients in different CAC risk groups.p < 0.05). No significant differences were observed in the other clinical factors, including sex, time interval, BMI, hypertension, diabetes mellitus, and smoking history . Further analysis showed significant differences in maximum pFAI and CT-FFR between the groups (p < 0.05), though total pFAI was similar (p > 0.05). The CAC scores of LM, LAD, LCX, and RCA and the total CAC score showed statistically significant differences (p < 0.05). The CAC risk grade also differed between the groups (p < 0.05). The findings are detailed in The study included 137 patients with WMH , of whom 66 were put into the progression group  and 71 patients  were put into the nonprogression group. Statistical analysis revealed significant differences in age, hyperlipidemia, and alcohol abuse between the two groups (p = 0.310), while other variables were significantly different (p < 0.05). In the internal validation set, all CAC scores were different between the WMH progressive and nonprogression groups (p < 0.05).A sample of 50 out of 137 cases was first randomly selected as the internal validation set, including 25 progression WMH and 25 nonprogression WMHs, and the remaining 87 cases were taken as the training set, which were 41 progressive and 46 nonprogressive cases . In the p = 0.014]. The maximum pFAI  was positively associated with progression, whereas the larger the CT-FFR was, the more likely WMH showed a nonprogressive trend . The CAC risk grade was a strong predictor of WMH volume progression: With grade 1 as the reference, the ORs for grades 2 and 3 were 5.614  and 9.985 , respectively . The AUC further improved upon adding the CAC risk grade in Model 3, underscoring its enhanced predictive ability over Models 1 and 2 .The progression of WMH was evaluated using three models developed from multivariable logistic regression analysis. Model 1 incorporated alcohol abuse, Model 2 included alcohol abuse and the maximum pFAI and CT-FFR, and Model 3 added the CAC risk grade. The predictive accuracies of these models are demonstrated in r < 0.4) (p < 0.05), greater changes becoming evident as the CAC risk grade increased . Links were observed between CAC risk grade and the WMH volume changes in the corpus callosum (p = 0.045), frontal lobe (p < 0.05), parietal lobe (p < 0.05), and occipital lobe (p = 0.047). No link was found between the WMH volume change and CAC risk grade in the deep white matter, temporal lobe, insula, brain stem or cerebellum (p > 0.05). More specific observations are detailed in Using the Pearson correlation coefficient to evaluate the quantitative correlation between CAC score and WMH progression volume, we found that there was no significant correlation between any individual CAC score and WMH progression volume in any individual brain region (r < 0.4) . Signifip < 0.05). (2) The combined model with alcohol abuse, maximum pFAI, CT-FFR and CAC risk grade showed the best performance in predicting the progression of WMH . (3) As the CAC risk grade increased, the volume change in the total WMH (p < 0.05), corpus callosum (p = 0.045), frontal lobe (p < 0.05), parietal lobe (p < 0.05), and occipital lobe (p = 0.047) became more significant.Identifying reliable biomarkers for predicting WMH progression is clinically significant, as it enables early identification and intervention in high-risk patients. The present study evaluated the utility of the CAC score as a predictor of the progression of WMH in patients with CAD. We conducted both univariate and multivariate logistic regression analyses to identify independent risk factors for WMH progression and developed three predictive models from them. We compared the predictive performance of traditional clinical risk factors, CCTA-derived markers (CT-FFR and pFAI) and CAC markers. Finally, we partitioned the regions of WMH progression to compare the progression of WMH volumes in different brain regions between different CAC risk grade subgroups. Our study had three major findings: (1) Alcohol abuse, maximum pFAI, CT-FFR and CAC risk grade were independent predictors of WMH progression  features, and run-length matrix (RLM) features, to predict the progression of any, periventricular, and deep WMH. The area under the curve (AUC) values for the training and testing datasets were 0.697–0.758 . Our resExplaining the clinical significance of research results is an important aspect of scientific studies. As a retrospective study, this cross-sectional design cannot definitively draw causal links between CAC scores and WMH progression. However, these preliminary statistical results reflect the correlation between CAC scores and WMH progression. In the future, it is necessary to explore the expected variations in the progression of WMH across different CAC risk tiers through prospective design. Understanding these variations can help improve risk assessment and guide treatment decisions. In practical settings, utilizing automated software for CAC scoring can reduce the subjectivity of manual assessments. Combining machine learning models for automated prediction of WMH progression can provide medical professionals with valuable tools. Medical professionals can categorize patients into different risk categories based on CAC scores, allowing for more informed decisions regarding treatment strategies. For instance, patients with higher CAC scores indicate a significant plaque burden and may require more aggressive interventions such as lipid-lowering medications or invasive procedures. Meanwhile, incorporating CAC scores into early screening strategies can help identify high-risk individuals with cerebral small vessel disease. Furthermore, investigating whether the progression of WMH at different risk grades is associated with specific clinical outcomes, such as cognitive decline or the occurrence of related cardiovascular events, can guide personalized treatment plans and improve patient prognosis.This study has several limitations. First, the patients were elderly adults with CAD, and they appeared to have more vascular risk factors, so the applicability of the findings to younger demographics or those without CAD may be limited. And the sample size of 137 patients was relatively small, potentially affecting the generalizability. Furthermore, the WMH volume changed excessively in some patients, which could affect the comparison of results between patients. However, the results demonstrated the potential for the CAC score to predict the progression of WMH, and in the future, we will include more individuals to validate the accuracy of these findings. Second, the lack of publicly available datasets related to our aims lowers its credibility. Unfortunately, we were unable to access relevant data for this purpose during the study. Our data suggested that the time interval between the two MRI scans did not significantly impact the progression of WMH, possibly due to the small sample size and short time intervals. The progression value of WMH in this study was an absolute increment, without considering the influence of the baseline size of WMH, and the measurement errors of the quantitative values may have potential effects on the experimental results, which makes it necessary to further improve the precision of WMH segmentation. Finally, as with all traditional machine learning methods, our developed model may be enhanced further if radiomics or deep learning features are incorporated. To improve the model’s robustness and generalizability, we plan to extract radiomics features of plaques and leverage deep learning algorithms to train the data.In conclusion, the CCTA-derived CAC score, along with specific risk factors, can predict the progression of WMH in patients with coronary artery disease. In the future, we may be able to identify people at increased risk for catastrophic vascular events by deploying a CAC score to achieve early detection of and intervention against WMH.2857865081@qq.com; XG, gong.xy@vip.163.com.The datasets presented in this article are not readily available because legal restrictions, imposed by the ethical committee, prevent us from publicly sharing the dataset due to sensitive patient information. Requests to access the datasets should be directed to HJ, The studies involving humans were approved by the Ethics Committee of ZJPP Hospital. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required from the participants or the participants’ legal guardians/next of kin in accordance with the national legislation and institutional requirements.HJ: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing. JH: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing. XQ: Data curation, Formal analysis, Investigation, Writing – review & editing. XD: Data curation, Investigation, Writing – review & editing. GZ: Formal analysis, Investigation, Writing – review & editing. YM: Data curation, Formal analysis, Writing – review & editing. ZS: Software, Writing – review & editing. YW: Formal analysis, Software, Resources, Writing – review & editing. XG: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Supervision, Writing – review & editing.


Postoperative delirium (POD) is a common complication in elderly patients after hip fracture surgery. Our study was to investigate whether intraoperative mean arterial pressure variability (MAPV) was associated with POD in elderly patients after hip fracture surgery.In this retrospective cohort study, patients aged 65 years and older undergoing hip fracture surgery were included. The correlation between MAPV and POD was investigated using univariate and multivariate logistic regression. Covariate-related confounding effects were eliminated with propensity score matching (PSM) analysis. Then, a subgroup analysis was conducted to further examine the associations between MAPV and POD.P < 0.001). All covariates between the two groups were well balanced after PSM adjustment. A significant correlation between MAPV and POD was found in the PSM analysis .Nine hundred sixty-three patients with a median age of 80 years (IQR: 73–84) were enrolled. POD occurred in 115/963 (11.9%) patients within 7 days after surgery. According to multivariate regression analysis, MAPV > 2.17 was associated with an increased risk of POD (OR: 2.379, 95% CI: 1.496–3.771, An increased intraoperative MAPV may be a predictor for POD.The online version contains supplementary material available at 10.1186/s12877-023-04425-9. Postoperative delirium (POD) is a common complication of hip fracture surgery , 2. The Several factors may contribute to POD , 10. ResIn this study, we proposed an indicator, namely, intraoperative mean arterial pressure variability (MAPV), for quantifying blood pressure fluctuations. We hypothesized that high MAPV is associated with a higher risk of POD.In this retrospective cohort study, patients aged 65 and older who underwent hip fracture surgery at the First Medical Centre of the Chinese PLA General Hospital between January 1, 2014, and December 31, 2018, were included. The Chinese PLA General Hospital's Ethics Committee Board approved this study (protocol number: S2019-311–03) and waived informed consent requirements.The inclusion criteria were as follows: 1) patients aged 65 years and older; and 2) patients who underwent hip fracture surgery. A person who underwent a second surgery for hip fracture was considered a new patient. The exclusion criteria were as follows: 1) missing data on intraoperative blood pressure; and 2) missing information on primary medical records.Data were collected from the anesthesia information management system. A manual filter was applied to the raw data values in which either the systolic blood pressure or the diastolic blood pressure was 0 mmHg. The electronic hospital information system was used to collect demographic, preoperative and postoperative data and data on medication use. Laboratory tests were performed within three days before the surgery.The patient’s arterial blood pressure was measured from the time they entered the operating room to the time they left. Invasive blood pressure measurements were collected continuously, and non-invasive blood pressure measurements were collected every three or five minutes. All blood pressure values were recorded every 30 s.The MAP was calculated as follows: (systolic blood pressure−diastolic blood pressure)/3 + diastolic blood pressure. Continuous invasive measurements as well as non-invasive measurements were used to extract the MAP. If both the invasive and non-invasive blood pressure measurements were available at a given time point, the information from the invasive measurement was used in the analysis since it is a direct measurement of the MAP as opposed to an estimation derived from the oscillometric measurement.The variability in a patient's blood pressure record was calculated to quantify fluctuations in blood pressure during surgery. Consequently, a patient with more blood pressure fluctuations has greater blood pressure variability than a patient with a relatively constant blood pressure during surgery. We developed an indicator of intraoperative MAPV to measure blood pressure fluctuation. MAPV was calculated as follows:The primary outcome was the incidence of POD within seven days after surgery. Neurologists confirmed the diagnosis based on descriptive words in the medical records. The diagnostic criteria were proposed and demonstrated in a previous study . The detAccording to the available literature and clinical plausibility, we selected the following potential confounding variables: age, sex, body mass index (BMI), American Society of Anesthesiologists (ASA) physical status, diabetes mellitus, hypertension, cardiovascular disease, cerebrovascular disease, chronic obstructive pulmonary disease (COPD), dementia, alcohol consumption, fracture type, white blood cell (WBC) count, hemoglobin level, red blood cell (RBC) count, albumin level, anesthesia method, duration of surgery, use of benzodiazepines, dexmedetomidine, or glucocorticoids, and emergency surgery.Receiver operating characteristic (ROC) curves were used to determine the optimal MAPV cutoff value for predicting POD. Multivariate and univariate logistic analyses were then conducted to investigate the correlation between MAPV  and POD. Univariate logistic regression analysis was performed for the correlation between MAPV and POD in model 1. In the multivariate logistic regression analysis, model 2 was adjusted for age, sex, BMI, ASA, hypertension, diabetes mellitus, cardiovascular disease, cerebrovascular disease, COPD, dementia and alcohol consumption. Model 3 was adjusted for WBC count, RBC count, hemoglobin level, albumin level, anesthesia method, duration of surgery, and use of benzodiazepines, dexmedetomidine or glucocorticoids. In model 4, all variables in models 2 and 3 were accounted for.We used propensity score matching (PSM) to pair the treatment and control patients with similar propensity scores. A multivariate logistic regression model was used to compute propensity scores based on the probability that patients had a different MAPV level . MatchinTo investigate the correlation between MAPV and POD by sex, age, cerebrovascular disease status, ASA physical status, and anesthesia method, subgroup analyses were conducted after logistic regression analysis of model 4. Subgroup predictions of POD by the MAPV value were summarized in a forest plot.P value < 0.05.Each statistical model was run using R 4.0.5 . Missing data were imputed using the random forest method in the ‘mice’ package. The median and interquartile range (IQR) are presented for continuous data and were compared with the Mann‒Whitney test. Frequencies with percentages are expressed for categorical variables and were compared with the χ2 test or Fisher’s exact test. For all tests, statistical significance was determined by a two-sided Retrospective analyses were conducted on 973 patients over 65 years old who underwent hip fracture surgery at the Chinese PLA General Hospital's First Medical Center between January 2014 and December 2018. In the final analysis, 963 patients were included after excluding 8 patients due to a lack of records and 2 patients due to a lack of blood pressure values  and high MAPV . The baseline characteristics of the groups are presented in Table When conducting ROC analysis, the appropriate cutoff value was selected to maximize the sum of sensitivity and specificity in Supplementary Fig. P < 0.001 (model 1)). The ORs of MAPV in multivariate logistic regression were 1.277 (model 2), 1.375 (model 3), and 1.246 (model 4). Therefore, MAPV played an independent role in POD  of 1.385  . In total, 471 patients MAPV ≤ 2.17 group) were matched with 157 patients (MAPV > 2.17 group). As shown in Fig. .17 groupP < 0.05, Fig. Additionally, in each subgroup, the MAPV ORs were significant for sex and anesthesia method .


Additionally, method comparison demonstrated that the magnetic probes were beneficial for sensitivity improvement due to the matrix effect reduction after magnetic separation, and the MNP–ICA is eight times higher sensitive than ICA based on colloidal gold nanoparticles. The developed MNP–ICA will provide sensitive, convenient, and efficient technical support for biomarkers rapid screening in cancer diagnosis and prognosis.Immunochromatographic assay (ICA) plays an important role in in vitro diagnostics because of its simpleness, convenience, fastness, sensitivity, accuracy, and low cost. The employment of magnetic nanoparticles (MNPs), possessing both excellent optical properties and magnetic separation functions, can effectively promote the performances of ICA. In this study, an ICA based on MNPs (MNP–ICA) has been successfully developed for the sensitive detection of carcinoembryonic antigen (CEA). The magnetic probes were prepared by covalently conjugating carboxylated MNPs with the specific monoclonal antibody against CEA, which were not only employed to enrich and extract CEA from serum samples under an external magnetic field but also used as a signal output with its inherent optical property. Under the optimal parameters, the limit of detection (LOD) for qualitative detection with naked eyes was 1.0 ng/mL, and the quantitative detection could be realized with the help of a portable optical reader, indicating that the ratio of optical signal intensity correlated well with CEA concentration ranging from 1.0 ng/mL to 64.0 ng/mL (R Point-of-care testing (POCT) is an economical, rapid, and reliable medical in vitro diagnostic technology that provides results in a short time to save detection time under limited resources with the help of portable diagnostic tools. It has gradually penetrated people’s lives for self-health monitoring and disease diagnosis in many developing countries and remote areas ,2. AccorStreptococcus pneumoniae detection, suggesting it was nearly 1000 times more sensitive than ICA based on quantum dots [Among them, MNPs have attracted extensive attention in the fields of medicine and biology, such as in vitro diagnosis, drug tracking and targeted administration, targeted therapy, and magnetic resonance imaging ,16. To dtum dots . In geneICA methods in POCT can be used as supplementary means of medical diagnosis to relieve pressure on the health care system and patients. This is of great significance for assisting in early screening and diagnosis, efficacy prediction, and prognosis . CarcinoTheoretically, the MNPs modified with abundant carboxyl groups, exhibiting good dispersion with an average diameter at about 300 nm A, were cIn order to obtain better performances of the MNP–ICA, the parameters have been optimized by using a single variable method. Results are presented in Because MNPs exhibit both excellent optical properties (bright brown) and unique magnetic separation performance, the prepared MNP–mAbI can be employed to enrich CEA in the serum samples and reduce the influence of the matrix effect for the MNP–ICA detection. As shown in T and ODC) were obtained and recorded by a portable reader, of which alteration tendencies were consistent with the results observed by the naked eye. It is reported that the ODT/ODC ratio can effectively offset the effects of the inherent heterogeneity of test strips and the matrix containing the samples [T/ODC ratios were calculated and exhibited better precision than ODT 1.056) (R2 = 0.9997). The limit of detection (LOD) of MNP–ICA was calculated according to the regression equation and formula: minI = minI is the ODT/ODC ratio corresponding to the LOD, T/ODC ratio of 11 blank serum samples, σ is the standard deviation [CEA standard solution was diluted with human serum to a series concentration  and detected by the developed MNP–ICA under the optimal parameters. The brown color on the T lines deepened, but that on the C lines weakened as the concentration increased because more and more MNP–mAbI were bound with CEA and captured by the mAbII coated on the T line. And the brown band on the T line can be clearly distinguished by the naked eye even though the CEA concentration was as low as 1.0 ng/mL A. The co samples . The ODTthan ODT . A sigmoeviation . As calcSeveral common tumor biomarkers in serum, such as AFP, Cyfra21-1, GDF-15, NSE, CEA, CA125, and CA153, have been detected by the MNP–ICA to investigate the specificity. As displayed in Blank serum samples spiked with CEA at high (64.0 ng/mL), medium (16.0 ng/mL), and low (1.0 ng/mL) concentrations have been tested three times a day for three days, and the relative standard deviation (RSD) was calculated to evaluate the intra-assay and inter-assay variations of the MNP–ICA. As presented in GCNPs are the common and stable labels in the ICA method; an ICA method base on homemade GCNPs (characterized in 1.056); as plotted in Serum samples from five healthy people and five liver cancer patients were tested by the MNP–ICA. The results shown in CEA antigen was purchased from Novoprotein Scientific Co., Ltd. . Monoclonal antibodies I and II against CEA (mAbI and mAbII) were purchased from Hefei Kangruixiang Biotechnology Co., Ltd. . Goat Anti-Mouse IgG was purchased from Jackson ImmunoResearch Laboratories, Inc. . Carboxylated MNPs , N-(3-Dimethylaminopropyl)-N’-ethylcarbodiimide hydrochloride (EDC), N-Hydroxysuccinimide (NHS), Polyethylene glycol, Tween-20, and Potassium carbonate were acquired from Aladdin Reagent Co., Ltd. . 2-(N-morpholino) ethanesulfonic acid (MES) was supplied by Vdo Biotechnology Co., Ltd. . Borate buffer solution was purchased from Coolaber Science & Technology Co., Ltd. . Sodium chloride was purchased from Sinopharm Chemical Reagent Co., Ltd. . Bovine serum albumin (BSA), ProCline-300, Tetronic 1307, Sucrose, D-(+)-Trehalose dihydrate, and Polyvinylpyrrolidone were obtained from Sigma-Aldrich Chemical Corporation . Phosphate Buffer Saline Tablets and Tris-HCl buffer were purchased from Solarbio Science & Technology Co., Ltd. . GCNPs (~40 nm) solution was prepared in our laboratory . PolyvinThe microcomputer automatic cutting machine (ZQ2402), CNC cutting machine (CTS300), and XYZ 3D film spraying instrument (HM3035) were supplied by Kinbio Tech Co., Ltd. . Ultrapure water was purified with Milli-Q system from Millipore Corp. . Electronic balance was purchased from Mettler Toledo Instruments Co., Ltd. . Portable reader was supplied by HYK Gene Technology Co., Ltd. ; the principle of portable reader for signal readout is as follows: a high-performance LED with a wavelength of 500–520 nm was used as light source, and the light was focused on the MNP–ICA test strip by optical lens. According to reflectance spectroscopy, the MNPs on the test strip would produce optical reflection signal due to the strong absorbance of MNPs. The produced reflective optical signal was converted into photoelectrical signals by conversion module.The magnetic detection probes (MNP–mAbI) were prepared by MNPs covalently conjugating with mAbI. Briefly, 0.5 mg of MNPs were dissolved in 250 μL of MEST buffer (MES buffer containing 0.05% Tween-20) after washing three times. Moreover, 50 μL of NHS (3 mg/mL) and EDC (3 mg/mL) were added in succession to activate the carboxyl groups on the surface of MNPs. Stirring continuously for 30 min at room temperature, the MNPs were washed three times with 5 mM BBT buffer  and then resuspended with 250 μL of BBT buffer. Then, 100 μL of mAbI (0.1 mg/mL) was added and agitated at room temperature for 1 h. BBT buffer was removed with magnetic separation, 250 μL of 1% PEG solution containing 0.05% Tween-20, and 250 μL of 10% BSA solution containing 0.05% Tween-20 were added to block the nonspecific sites. After 30 min, with the help of external magnetic field, the supernatant was discarded, and the precipitate was redispersed in 100 μL of 0.02 M Tris-HCl buffer , stored at 4 °C until use.The mAbII and goat anti-mouse IgG were diluted with PBS buffer , sprayed on the NC membrane with 0.8 μL/cm as the test (T) and control (C) lines, and then dried at 37 °C for 12–16 h. The structure of MNP–ICA test strip is illustrated in As illustrated in The processes of GCNP–ICA were described in the In this work, a rapid and sensitive ICA method based on MNPs has been successfully established for CEA detection, in which the prepared magnetic probes MNP–mAbI exhibited excellent magnetic responsiveness and optical property and were employed for target enrichment and signal output, allowing the qualitative and quantitative detection of CEA in serum to be finished within 15 min. The sensitivity of the MNP–ICA was eight times higher than that of the GCNP–ICA developed with the same antibody pair in our work, attributing to (1) the magnetic probes can effectively reduce the serum matrix effect by magnetic separation and (2) the optical signal intensity of MNPs is stronger than that of GCNPs. The results demonstrated that the developed MNP–ICA is convenient, high-efficiency, sensitive, specific, and accurate for CEA in serum determination, and it is also suitable for screening other disease markers, which has potential applications for social and economic benefits.


Congenital scoliosis(CS) is associated with multiple organs defect, and cardiac abnormalities have been reported commonly associated with CS. Hemivertebra is caused by the failure of vertebral formation, which is a major constitute of CS. Till now, few studies focus on the incidence and interrelationship of hemivertebra and concomitant cardiac abnormalities in congenital scoliosis. We aimed to analyze the cardiac defect in CS patients with or without hemivertebra, and further explore the incidence of cardiac defect between different types of hemivertebra.The ultrasonic cardiography (UCG) results of surgically treated congenital scoliosis (CS) patients between 2015 and 2018 were retrospectively analyzed. Patients were divided into hemivertebra group and non-hemivertebra group according to preoperative CT. Patients with hemivertebra was further divided into sub-group by single/multiple or fully/partially/mixed segmented hemivertebra. Demographic information, radiographic data and cardiac abnormalities were statistically compared between groups.A total of 329 patients were analyzed, including 216 patients with hemivertebra and 113 patients without hemivertebra. UCG results were abnormal in 89 cases (27.1%), including 41 males(12.5%) and 48 females(14.6%). Hemivertebra group had comparable incidence of cardiac abnormalities with non-hemivertebra group (p = 0.517). No significant difference in the incidence of UCG abnormalities between single and multiple hemivertebra group (P = 0.246). Binary logistic regression analysis showed that female sex with multiple hemivertebra was a risk factor for abnormal UCG . Cardiac abnormalities was comparable among fully, partially and mixed segmented hemivertebra group(P = 0.264). In abnormal UCG, 33 patients with hemivertebra had non-valvular abnormalities, and 48.5% (16/33) were septal defects. 28 patients had valvular abnormalities, most of them were mitral valve abnormalities, especially mitral valve redundancy, prolapse and insufficiency. No significant difference between the incidence of non-valvular and valvular abnormalities in patients with hemivertebra (P = 0.581).The incidence of abnormal UCG results was approximately 28.2% in CS patients with hemivertebra. Female patients with multiple hemivertebra had a higher risk of UCG abnormalities. Mitral valve abnormalities were the most common abnormality of UCG found in CS patients with hemivertebra.retrospectively registered. Hemivertebra are caused by one side of the vertebral body developing while the other side does not during embryonic development, and its incidence is approximately 1–10/per 1000 live infants . HemiverInstitutional Review Board (IRB) approval of our institution was obtained for the study. We retrospectively reviewed the medical records and radiographic data of CS patients who underwent posterior spinal correction surgery in our hospital between January 2015 and December 2018. The inclusion criteria were as follows: (1) age ≤ 18 years; (2) full clinical and radiographic data from which we could determine the classification of the patients’ hemivertebra; and (3) detailed ultrasonic cardiography (UCG) examination results.A total of 329 patients were enrolled, including 216 CS patients with hemivertebra and 113 patients without hemivertebra. In hemivertebra group, the mean age was 8.1 ± 5.0 years  and the mean coronal Cobb angle of the major curve was 54.8 ± 12.2 degrees . According to McMaster’s classification of hemivertebra, 152 patients had single hemivertebra, of which 94 cases were fully segmented .SPSS 17.0 for Windows was used for statistical analysis. Student’s T test was used for the comparison of continuous variables, and the chi-square test and ANOVA test was used for categorical variables. A difference was statistically significant if P < 0.05.A total of 329 patients were analyzed, including 216 patients with hemivertebra and 113 patients without hemivertebra. In hemivertebra group, 61 (28.2%) cases had abnormal UCG results, and 31 (14.3%) were male and 30 (13.9%) were female. In non-hemivertebra group, 28(24.8%) cases had abnormal UCG results. No significant difference in the incidence of UCG between hemivertebra group and non-hemivertebra group (P = 0.517). There were no significant differences in sex, curve direction or location between groups (P > 0.05) . Binary logistic regression analysis showed that female sex with multiple hemivertebra was a risk factor for abnormal UCG . There were no significant differences in sex, curve direction or location between groups (P > 0.05) . No significant difference in sex, curve direction or curve location among the three groups (P > 0.05) Table .Among the 61 hemivertebra patients with abnormal UCG results, 33 of them with non-valvular lesions. Septal defects, which included atrial septal defects/patent foramen ovale and ventricular septal defects, composed nearly half of the abnormalities 48.5%, 16/33) , segmentation of the hemivertebra, curve direction and location did not affect the occurrence of cardiac abnormalities. This is consistent with the report by Bollini et al. . HoweverAmong the types of cardiac abnormalities, non-valvular lesions are the main ones reported –5. In 20There are few reports about valve lesions on the UCG of patients with hemivertebra malformations. Forrester et al. reported that 1 of 42 patients with hemivertebra malformation had pulmonary atresia and stenosis  . In the This study had some limitations. First, its retrospective nature gives it inherent shortcomings. Second, in the patient group with valvular abnormalities, we included patients with simple mitral valve redundancy (9 patients), which may not have been analyzed in some studies. Third, this study only analyzed surgically treated patients with hemivertebra, and those without surgical treatment were not included.In summary, to our knowledge, this is the largest case study of UCG analysis in patients with congenital scoliosis caused by hemivertebra deformity. In 216 patients with hemivertebra, the incidence of abnormal UCG results was 28.2%. The number of hemivertebra, the segmentation and the curve direction and location did not affect the occurrence of UCG abnormalities. Female sex along with multiple hemivertebra was a risk factor for UCG abnormalities. In patients with UCG abnormalities, mitral valve abnormalities are the most common type.


Neurofibromatosis type 1 (NF1) is a genetic disease that alters neurodevelopment. We aimed to analyze the sleep macrostructure of a sample of children affected by NF1 without neurocognitive co-morbidities and MRI reports of unidentified bright objects (UBOs).A 100 pre-pubertal children participated in the cross-sectional study: 50 subjects were children diagnosed with NF1 and 50 subjects were typically developing healthy children (TDC). All participants underwent polysomnographic evaluation through which conventional sleep parameters were collected: Total sleep time (TST), Sleep latency (SOL), first REM latency (FRL), number of stage shifts/h (SS/h), number of awakenings/h (AWN/h), wake after sleep onset (WASO%), sleep efficiency percentage (SE%), percentage of sleep time spent in sleep stages 1 (N1%) and 2 (N2%), slow-wave sleep (N3%), and REM sleep (REM%). Additionally, nocturnal respiratory events such as apnea/hypopnea index (AHI), oxygen desaturation index (ODI), and periodic limb movement index (PLMI) were recorded.p < 0.001), sleep efficiency , and stage N2% (p < 0.001). Moreover, the number of awakenings per hour (AWN/h), wake after sleep onset (WASO%), and respiratory events such as AHI, ODI, and PLMI resulted higher in NF1 vs. TDC children.Neurofibromatosis type 1 children showed a reduction in sleep duration parameters (TST; The data showed that the sleep macrostructure differs between NF1 and TDC children. These findings suggest that the evaluation of sleep may provide useful support in corroborating the diagnosis and offers additional therapeutic management perspectives in NF1 and genetic neurodevelopmental disorders in general. Among others, the central nervous system (CNS) is frequently affected in these children with many manifestations including cognitive, behavioral, neurodevelopmental disorders, speech disorders and motor impairment , migrainAmong the NF1-related neurological morbidities, sleep disorders  are very frequently seen in clinical practice. However, a limited number of studies focusing on NF1-related sleep disorders have been described .p ≤ 0.05) in the NF1 group than in the general population (p < 0.05). Patients with NF1 and IQ < 85 showed higher prevalence rates of daytime sleepiness (20 vs. 6.7%) and of sleep hyperhidrosis (11 vs. 0%).To date, in fact, only a few data on the sleep habits of NF1 patients have been reported such as a single case report of an old man suffering from sleep apnea syndrome due to the mechanical superior vena cava obstruction , or two pulation . The oveMoreover, the sleep disturbance rate among children with NF1 has been estimated to range from 13 to 86% vs. 11–37% among typical control children .To the best of our knowledge, polysomnographic evaluation reports in pediatric NF1 have been extremely rare, with a lack of reference data to guide clinical practice in the management of sleep problems in children and adolescents with NF1.We aimed to systematically assess sleep macrostructure, nocturnal respiratory events, and periodic limb movements index in a sample of children affected by NF1 in comparison to TCD.2.2.1.The clinical retrospective study was conducted according to the principles of the Declaration of Helsinki . The Eth2.2.The present experimental design consisted of a retrospective cross-sectional analysis between two independent groups of subjects. NF1 subjects were recruited during the period 2003–2013 and compared with a historical control group of typical developing healthy children (TDC).2.3.The NF1 subjects group consisted of 50 pre-pubertal children , which underwent overnight full polysomnography (PSG) after at least one night of adaptation to avoid the first night effect accordingly to international criteria for PSG  Supplem.The diagnosis of NF1 for all subjects was based on the National Institute of Neurological Disorders and Stroke (NIH) criteria .The second group, the control group, consisted of 50 typically developing children , which were all part of a historical control group collected among inpatient subjects, admitted for assessment of recurrent episodes of headache and abdominal pain, that resulted negative for neuropsychiatric disorders and pediatric screenings during hospitalization.All subjects enrolled in this study were Caucasian, Italian native speakers, and comparable for socio-economic and educational status.UBOs).We considered as exclusion criteria for all participants: obesity and overweight, epilepsy, psychiatric disorders , cognitive disability , plexiform neurofibromas involving head or neck, psychotropic drugs treatment and MRI report of unidentified bright objects : Total sleep time (TST), Sleep latency (SOL), first REM latency (FRL), Number of stage shifts/h (SS/h), Number of awakenings/h (AWN/h), Sleep efficiency (SE%), Percentage of sleep time spent in sleep stages 1 (N1%) and 2 (N2%), slow-wave sleep (N3%), and REM sleep (REM%).All variables were analyzed by Hypnolab 1.2 sleep software analysis . All full overnight PSGs were recorded with 19 electrodes  referenced to the contralateral mastoid (A1 and A2), left and right electrooculogram (ROC and LOC), chin electromyogram (EMG), left and right tibialis EMG, electrocardiogram (one derivation), nasal cannula, thorax and abdominal effort, peripheral oxygen saturation, and pulse and position sensors.Respiratory nocturnal events were identified according to the criteria of the American Academy of Sleep Medicine  and the For the assessment of limb movement events (PLMs), a PLMs index (number of PLMs per hour of sleep) higher than ≥5 was considered clinically significant .2.5.U). Cohen’s d was calculated to establish clinical differences. A value of p ≤ 0.05 was considered statistically significant. The software Statistica version 8.1  was used for all statistical tests.Assumption of normality was performed with Kolmogorov–Smirnov test. Considering the violation of the normal distribution, descriptive statistics were expressed as medians and interquartile ranges (IQR) for continuous variables. Comparisons of categorical data were performed with the chi-squared test and Fisher’s exact test, while continuous data were analyzed with the nonparametric Mann–Whitney U test , sleep efficiency percentage , and N2 percentage (p < 0.001). Moreover, we found that NF1 children had an increase in the number  and duration of wake periods  in comparison to TDC. Furthermore, respiratory events such as AHI (p < 0.001), ODI (p < 0.001), and PLMI (p < 0.001) were higher in NF1 vs. TDC group.Children with NF1 have severe sleep-disordered breathing, i.e., 6.9 ± 4.5 AHI, with all having an AHI > 1. 42% of the control children have an AHI > 1. None of the control children had a PLMI≥5 but 56% of NF1 had. While 66.67% of the NF1 children had an AHI > 5 and PLMI ≥ 5.Post hoc comparisons between the clinical groups within the NF1 sample showed that clinical groups were different for N2%. Particularly, those with periodic leg movements but moderate sleep-disordered breathing spent more time in N2% compared to those with severe sleep-disordered breathing. IQ (p = 0.5019) and BMI z-score (p = 0.7375) were not different across these clinical groups  and PLMS might determine the worsening of already poor attentional and executive functioning as well as learning difficulties in NF1 children , 36. NamMost of the previous studies in children with NF1 have been based on questionnaires. Reporting alterations in disturbances of initiating and maintaining sleep, arousal, sleep–wake transition, and hyperhidrosis, but not reported abnormal sleep breathing or excessive daytime somnolence , 24. Ournucleus accumbens (NAc)  .Finally, sleep-related breathing disorders have been rarely reported in questionnaire-based studies, differently from nocturnal hyperhidrosis, which seems to have a high prevalence among NF1 children despite that this nocturnal sign is strongly associated with nocturnal respiratory disorders , 50. TheIn general, our findings are in line with some animal studies. In fact, experimental data about abnormalities of the circadian clock control in Drosophila models of NF1  and on tWe moreover would like to specify that the choice of recruiting pre-pubertal children with NF1 has been made to avoid sleep alterations due to hormonal abnormalities during adolescence , 61.The limited availability of children to undergo PSG is mainly due to the necessity of hospitalization. This limitation joined to the relative rarity of NF1, seems to well explain the relatively small size of the recruited population. Another limitation of the present study may be identified in the PSG evaluation restricted to the children with NF1 without UBOs as well as the retrospective nature of our investigation. Lastly, the control group is a presumed healthy group without any medical diagnosis fitting the exclusion criteria.Notwithstanding these limitations, the present study may be considered the first investigation reporting PSG data in pre-pubertal NF1 children. We confirmed some previous findings, however, we added knowledge on a series of new aspects of sleep disorders in NF1 children, specifically in NF1 children without any other neurocognitive comorbidity . Considemarco.carotenuto@unicampania.it.The datasets presented in this article are not readily available because of ethical and privacy restrictions. Requests to access the datasets should be directed to MC, The studies involving human participants were reviewed and approved by the Ethics Committee at the Università degli Studi della Campania “Luigi Vanvitelli” Protocol number 0015908/i; May 21, 2021. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.MC and KS: conceptualization and draft preparation. GM, ME, and CS: data collection. DI: statistical analysis and data elaboration. KS: paper final revision. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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