GWAS of longitudinal trajectories at biobank scale.

Biobanks linked to massive, longitudinal electronic health record (EHR) data make numerous new genetic research questions feasible. One among these is the study of biomarker trajectories. For example, high blood pressure measurements over visits strongly predict stroke onset, and consistently high fasting glucose and Hb1Ac levels define diabetes. Recent research reveals that not only the mean level of biomarker trajectories but also their fluctuations, or within-subject (WS) variability, are risk factors for many diseases. Glycemic variation, for instance, is recently considered an important clinical metric in diabetes management. It is crucial to identify the genetic factors that shift the mean or alter the WS variability of a biomarker trajectory. Compared to traditional cross-sectional studies, trajectory analysis utilizes more data points and captures a complete picture of the impact of time-varying factors, including medication history and lifestyle. Currently, there are no efficient tools for genome-wide association studies (GWASs) of biomarker trajectories at the biobank scale, even for just mean effects. We propose TrajGWAS, a linear mixed effect model-based method for testing genetic effects that shift the mean or alter the WS variability of a biomarker trajectory. It is scalable to biobank data with 100,000 to 1,000,000 individuals and many longitudinal measurements and robust to distributional assumptions. Simulation studies corroborate that TrajGWAS controls the type I error rate and is powerful. Analysis of eleven biomarkers measured longitudinally and extracted from UK Biobank primary care data for more than 150,000 participants with 1,800,000 observations reveals loci that significantly alter the mean or WS variability.

Trajectories of BMI before and after diagnosis of type 2 diabetes in a real-world population.

AIMS/HYPOTHESIS: Few studies have examined the clinical characteristics associated with changes in weight before and after diagnosis of type 2 diabetes. Using a large real-world cohort, we derived trajectories of BMI before and after diabetes diagnosis, and examined the clinical characteristics associated with these trajectories, including assessing the impact of pre-diagnosis weight change on post-diagnosis weight change. METHODS: We performed an observational cohort study using electronic medical records from individuals in the Scottish Care Information Diabetes Collaboration database. Two trajectories were calculated, based on observed BMI measurements between 3 years and 6 months before diagnosis and between 1 and 5 years after diagnosis. In the post-diagnosis trajectory, each BMI measurement was time-dependently adjusted for the effects of diabetes medications and HbA1c change. RESULTS: A total of 2736 individuals were included in the study. There was a pattern of pre-diagnosis weight gain, with 1944 individuals (71%) gaining weight overall, and 875 (32%) gaining more than 0.5 kg/m2 per year. This was followed by a pattern of weight loss after diagnosis, with 1722 individuals (63%) losing weight. Younger age and greater social deprivation were associated with increased weight gain before diagnosis. Pre-diagnosis weight change was unrelated to post-diagnosis weight change, but post-diagnosis weight loss was associated with older age, female sex, higher BMI, higher HbA1c and weight gain during the peri-diagnosis period. When considering the peri-diagnostic period (defined as from 6 months before to 12 months after diagnosis), we identified 986 (36%) individuals who had a high HbA1c at diagnosis but who lost weight rapidly and were most aggressively treated at 1 year; this subgroup had the best glycaemic control at 5 years. CONCLUSIONS/INTERPRETATION: Average weight increases before diagnosis and decreases after diagnosis; however, there were significant differences across the population in terms of weight changes. Younger individuals gained weight pre-diagnosis, but, in older individuals, type 2 diabetes is less associated with weight gain, consistent with other drivers for diabetes aetiology in older adults. We have identified a substantial group of individuals who have a rapid deterioration in glycaemic control, together with weight loss, around the time of diagnosis, and who subsequently stabilise, suggesting that a high HbA1c at diagnosis is not inevitably associated with a poor outcome and may be driven by reversible glucose toxicity.

Impact of COVID-19 pandemic on depression incidence and healthcare service use among patients with depression: an interrupted time-series analysis from a 9-year population-based study.

BACKGROUND: Most studies on the impact of the COVID-19 pandemic on depression burden focused on the earlier pandemic phase specific to lockdowns, but the longer-term impact of the pandemic is less well-studied. In this population-based cohort study, we examined the short-term and long-term impacts of COVID-19 on depression incidence and healthcare service use among patients with depression. METHODS: Using the territory-wide electronic medical records in Hong Kong, we identified all patients aged ≥ 10 years with new diagnoses of depression from 2014 to 2022. We performed an interrupted time-series (ITS) analysis to examine changes in incidence of medically attended depression before and during the pandemic. We then divided all patients into nine cohorts based on year of depression incidence and studied their initial and ongoing service use patterns until the end of 2022. We applied generalized linear modeling to compare the rates of healthcare service use in the year of diagnosis between patients newly diagnosed before and during the pandemic. A separate ITS analysis explored the pandemic impact on the ongoing service use among prevalent patients with depression. RESULTS: We found an immediate increase in depression incidence (RR = 1.21, 95% CI: 1.10-1.33, p < 0.001) in the population after the pandemic began with non-significant slope change, suggesting a sustained effect until the end of 2022. Subgroup analysis showed that the increases in incidence were significant among adults and the older population, but not adolescents. Depression patients newly diagnosed during the pandemic used 11% fewer resources than the pre-pandemic patients in the first diagnosis year. Pre-existing depression patients also had an immediate decrease of 16% in overall all-cause service use since the pandemic, with a positive slope change indicating a gradual rebound over a 3-year period. CONCLUSIONS: During the pandemic, service provision for depression was suboptimal in the face of increased demand generated by the increasing depression incidence during the COVID-19 pandemic. Our findings indicate the need to improve mental health resource planning preparedness for future public health crises.

Development and Implementation of a Dynamically Updated Big Data Intelligence Platform Using Electronic Medical Records for Secondary Hypertension.

Background: The accurate identification and diagnosis of secondary hypertension is critical,especially while cardiovascular heart disease continues to be the leading cause of death. To develop a big data intelligence platform for secondary hypertension using electronic medical records to contribute to future basic and clinical research. Methods: Using hospital data, the platform, named Hypertension DATAbase at Urumchi (UHDATA), included patients diagnosed with hypertension at the People's Hospital of Xinjiang Uygur Autonomous Region since December 2004. The electronic data acquisition system, the database synchronization technology, and data warehouse technology (extract-transform-load, ETL) for the scientific research big data platform were used to synchronize and extract the data from each business system in the hospital. Standard data elements were established for the platform, including demographic and medical information. To facilitate the research, the database was also linked to the sample database system, which includes blood samples, urine specimens, and tissue specimens. Results: From December 17, 2004, to August 31, 2022, a total of 295,297 hypertensive patients were added to the platform, with 53.76% being males, with a mean age of 59 years, and 14% with secondary hypertension. However, 75,802 patients visited the Hypertension Center at our hospital, with 43% (32,595 patients) being successfully diagnosed with secondary hypertension. The database contains 1458 elements, with an average fill rate of 90%. The database can continuously include the data for new hypertensive patients and add new data for existing hypertensive patients, including post-discharge follow-up information, and the database updates every 2 weeks. Presently, some studies that are based on the platform have been published. Conclusions: Using computer information technology, we developed and implemented a big database of dynamically updating electronic medical records for patients with hypertension, which is helpful in promoting future research on secondary hypertension.

Noninvasive Risk Prediction Models for Heart Failure Using Proportional Jaccard Indices and Comorbidity Patterns.

Background: In the post-coronavirus disease 2019 (COVID-19) era, remote diagnosis and precision preventive medicine have emerged as pivotal clinical medicine applications. This study aims to develop a digital health-monitoring tool that utilizes electronic medical records (EMRs) as the foundation for performing a non-random correlation analysis among different comorbidity patterns for heart failure (HF). Methods: Novel similarity indices, including proportional Jaccard index (PJI), multiplication of the odds ratio proportional Jaccard index (OPJI), and alpha proportional Jaccard index (APJI), provide a fundamental framework for constructing machine learning models to predict the risk conditions associated with HF. Results: Our models were constructed for different age groups and sexes and yielded accurate predictions of high-risk HF across demographics. The results indicated that the optimal prediction model achieved a notable accuracy of 82.1% and an area under the curve (AUC) of 0.878. Conclusions: Our noninvasive HF risk prediction system is based on historical EMRs and provides a practical approach. The proposed indices provided simple and straightforward comparative indicators of comorbidity pattern matching within individual EMRs. All source codes developed for our noninvasive prediction models can be retrieved from GitHub.

Health Data Sciences and Cardiovascular Diseases in South Asia: Innovations and Challenges in Digital Health.

PURPOSE OF REVIEW: Health data sciences can help mitigate high burden of cardiovascular disease (CVD) management in South Asia by increasing availability and affordability of healthcare services. This review explores the current landscape, challenges, and strategies for leveraging digital health technologies to improve CVD outcomes in the region. RECENT FINDINGS: Several South Asian countries are implementing national digital health strategies that aim to provide unique health account numbers for patients, creating longitudinal digital health records while others aim to digitize healthcare services and improve health outcomes. Significant challenges impede progress, including lack of interoperability, inadequate training of healthcare workers, cultural barriers, and data privacy concerns. Leveraging digital health for CVD management involves using big data for early detection, employing artificial intelligence for diagnostics, and integrating multiomics data for health insights. Addressing these challenges through policy frameworks, capacity building, and international cooperation is crucial for improving CVD outcomes in region.

Three-phase generalized raking and multiple imputation estimators to address error-prone data.

Validation studies are often used to obtain more reliable information in settings with error-prone data. Validated data on a subsample of subjects can be used together with error-prone data on all subjects to improve estimation. In practice, more than one round of data validation may be required, and direct application of standard approaches for combining validation data into analyses may lead to inefficient estimators since the information available from intermediate validation steps is only partially considered or even completely ignored. In this paper, we present two novel extensions of multiple imputation and generalized raking estimators that make full use of all available data. We show through simulations that incorporating information from intermediate steps can lead to substantial gains in efficiency. This work is motivated by and illustrated in a study of contraceptive effectiveness among 83 671 women living with HIV, whose data were originally extracted from electronic medical records, of whom 4732 had their charts reviewed, and a subsequent 1210 also had a telephone interview to validate key study variables.

Effectiveness of patient reminders on influenza vaccination coverage among adults with chronic conditions: A feasibility study in Australian general practices.

BACKGROUND: Influenza vaccination is recommended for Australians 18+ years old with medical risk factors, but coverage is suboptimal. We aimed to examine whether automatic, opportunistic patient reminders (SMS and/or printed) before appointments with a general practitioner increased influenza vaccination uptake. METHODS: This clustered non-randomised feasibility study in Australian general practice included patients aged 18-64 years with at least one medical risk factor attending participating practices between May and September 2021. Software installed at intervention practices identified unvaccinated eligible patients when they booked an appointment, sent vaccination reminders (SMS on booking and 1 h before appointments), and printed automatic reminders on arrival. Control practices provided usual care. Clustered analyses adjusted for sociodemographic differences among practices were performed using logistic regression. RESULTS: A total of 12,786 at-risk adults attended 16 intervention practices (received reminders = 4066; 'internal control' receiving usual care = 8720), and 5082 individuals attended eight control practices. Baseline influenza vaccination uptake (2020) was similar in intervention and control practices (∼34%). After the intervention, uptake was similar in all groups (control practices = 29.3%; internal control = 30.0%; intervention = 31.6% (p-value = 0.203). However, SMS 1 h before appointments increased vaccination coverage (39.3%, adjusted OR = 1.65; 95%CI 1.20;2.27; number necessary to treat = 13), especially when combined with other reminder forms. That effect was more evident among adults with chronic respiratory, rheumatologic, or inflammatory bowel disease. CONCLUSION: These findings indicate that automated SMS reminders delivered at proximate times to appointments are a low-cost strategy to increase influenza vaccination among adults at higher risk of severe disease attending Australian general practices.

Topical amitriptyline in burning mouth syndrome: A retrospective real-world evidence study.

OBJECTIVE: To evaluate the effectiveness, tolerability, and safety of topical amitriptyline as a potential route of administration for the management of burning mouth syndrome. BACKGROUND: Burning mouth syndrome is a complex, idiopathic, and debilitating orofacial pain disorder that impairs quality of life, with a prevalence of up to 18% in menopausal women. Available drugs to alleviate its burning sensation have inconsistent and limited efficacy. Given its physicochemical properties, excellent tolerability, and ability to target peripheral pathways, topical amitriptyline seems a promising mechanistically specific analgesic drug for burning mouth syndrome. METHODS: In this retrospective cross-sectional real-world evidence study, patients with burning mouth syndrome who were prescribed topical amitriptyline for 8 weeks were identified. Eligibility criteria stemmed from ICHD-3, ICOP, and consensus definitions. The primary outcome measure was mean daily pain intensity (on a 0-10 scale); secondary outcomes included adverse events and patient global impression of improvement. Data are given as the mean ± SD. RESULTS: A total of 15 patients fulfilling the eligibility criteria were included and analyzed. Mean daily pain was 6.7 ± 2.1 at baseline and 3.7 ± 2.3 after treatment, with a mean reduction of 3.1 ± 2.8 (p = 0.002). Half of the patients experienced a decrease in pain by at least 50% (p = 0.008). Several mild adverse events were reported, such as somnolence or dry mouth. CONCLUSIONS: Topical amitriptyline may be a safe and potent route of administration in the treatment of burning mouth syndrome, a hypothesis to be tested in further controlled trials.

Standardizing visual display of gastrointestinal pathology results for improved clinical interpretation.

OBJECTIVES: Pathology is an essential component of disease diagnosis and management in pediatric gastroenterology. Pathology reports have not been standardized in some areas of pediatric gastrointestinal pathology and pathology reporting varies. Development of electronic medical record (EMR) pathology synoptic report templates (PSRT) enables pathology data collection in a specific format and can help standardize pathology reporting. We developed, implemented, and evaluated EMR PSRTs for eosinophilic esophagitis (EoE) and inflammatory bowel disease (IBD). METHODS: PSRTs were developed by a multidisciplinary team of pediatric experts of allergy, gastroenterology, and pathology for both EoE and IBD based on available literature and validated scales. Likert surveys (range 1 low acceptance to 5 high acceptance) based on the Technology Acceptance Model assessed user acceptance of the developed PSRTs. The use of PSRTs was monitored via control charts. RESULTS: Overall, evaluation questionnaires achieved >80% response rates. Clinicians and pathologists reported moderate-to-high levels of Perceived Usefulness (median (interquartile range) for EoE PSRT: clinicians 4.0 (4.0, 5.0) and pathologists 3.5 (3.5, 4.0); and IBD PSRT: clinicians 4.0 (3.0, 4.0) and pathologists 4.0 (4.0, 5.0)) and Perceived Ease of Use (EoE PSRT: clinicians 4.5 (4.0, 5.0) and pathologists 4.0 (4.0, 4.0); and IBD PSRT: clinicians 4.0 (4.0, 5.0) and pathologists 4.0 (4.0, 5.0)) of the developed PSRTs. Control charts demonstrated 100% utilization by 2-5 months from launch. CONCLUSIONS: We demonstrate successful implementation of synoptic reporting for both pediatric EoE and IBD pathology. EMR synoptic reporting provides standardization of pathology reporting and improved methods of pathology data presentation, which could potentially optimize provider efficiency, clinician interpretation of pathology results and disease trajectory, patient care, and clinician satisfaction.

Proxy endpoints - bridging clinical trials and real world data.

OBJECTIVE: Disease severity scores, or endpoints, are routinely measured during Randomized Controlled Trials (RCTs) to closely monitor the effect of treatment. In real-world clinical practice, although a larger set of patients is observed, the specific RCT endpoints are often not captured, which makes it hard to utilize real-world data (RWD) to evaluate drug efficacy in larger populations. METHODS: To overcome this challenge, we developed an ensemble technique which learns proxy models of disease endpoints in RWD. Using a multi-stage learning framework applied to RCT data, we first identify features considered significant drivers of disease available within RWD. To create endpoint proxy models, we use Explainable Boosting Machines (EBMs) which allow for both end-user interpretability and modeling of non-linear relationships. RESULTS: We demonstrate our approach on two diseases, rheumatoid arthritis (RA) and atopic dermatitis (AD). As we show, our combined feature selection and prediction method achieves good results for both disease areas, improving upon prior methods proposed for predictive disease severity scoring. CONCLUSION: Having disease severity over time for a patient is important to further disease understanding and management. Our results open the door to more use cases in the space of RA and AD such as treatment effect estimates or prognostic scoring on RWD. Our framework may be extended beyond RA and AD to other diseases where the severity score is not well measured in electronic health records.

Time to next treatment in patients with chronic lymphocytic leukemia initiating first-line ibrutinib or acalabrutinib.

Aim: To investigate real-world time to next treatment in patients with chronic lymphocytic leukemia initiating first-line (1L) ibrutinib or acalabrutinib. Materials & methods: US specialty pharmacy electronic medical records (21/11/2018-30/4/2022) were used; patients initiated 1L on/after 21/11/2019 (acalabrutinib approval). Results: Among 710 patients receiving ibrutinib, 5.9% initiated next treatment (mean time to initiation = 9.2 months); among 373 patients receiving acalabrutinib, 7.5% initiated next treatment (mean time to initiation = 5.9 months). Adjusting for baseline characteristics, acalabrutinib-treated patients were 89% more likely to initiate next treatment (hazard ratio = 1.89; p = 0.016). Conclusion: This study addresses a need for real-world comparative effectiveness between 1L ibrutinib and acalabrutinib and shows that next treatment (a clinically meaningful measure for real-world progression) occurred less frequently with 1L ibrutinib.

Ibrutinib and acalabrutinib are oral medications taken once-daily and twice-daily, respectively. They are recommended as initial treatment for chronic lymphocytic leukemia (CLL). The goal of this study was to compare the efficacy of these treatments as initial treatment for CLL. To meet this goal, real-world US specialty pharmacy electronic medical records between 11/21/2018­4/30/2022 were used. Patients treated with ibrutinib or acalabrutinib as initial treatment for CLL were studied. Treatment had to be started on or after the date of acalabrutinib approval for CLL (11/21/2019). Time to next treatment was used to estimate real-world disease progression. It was defined as the time from the initiation of initial treatment with ibrutinib or acalabrutinib to the initiation of a next treatment. Study results showed that patients were observed for a median of up to 1.5 years. Over this period, next treatment was more likely for acalabrutinib (7.5%) compared with ibrutinib (5.9%). After adjusting for differences in patient characteristics, next treatment was 89% more likely with acalabrutinib than ibrutinib. This study addresses a need to compare the effectiveness of initial treatment with ibrutinib and acalabrutinib in the real-world. It helps better contextualize results from clinical trial data and shows that next treatment occurred less frequently with ibrutinib.

Assessing the implementation of a tertiary care comprehensive pediatric asthma education program using electronic medical records and decision support tools.

BACKGROUND: Self-management education is integral for proper asthma management. However, there is an accessibility gap to self-management education following asthma hospitalizations. Most pediatric patients and their families receive suboptimal or no education. OBJECTIVE: To implement a comprehensive pediatric asthma education program and evaluate subsequent self-management knowledge in patients as well as behavior change outcomes reflected in the frequency of asthma related repeat emergency department visits and hospitalization. The program implementation was informed by the Knowledge to Translation Action Framework and the i-PARIHS model for quality improvement and involved several iterative stages. METHODS: We implemented a comprehensive asthma education program for the families of all children 0-18 years old who had been admitted for an asthma exacerbation to the Children's Hospital of Eastern Ontario (CHEO), beginning on April 1, 2018. The program was adapted to the stages of the Knowledge Translation to Action Framework including undertaking an environmental scan, expert stakeholder feedback, reviews, addressing barriers, and tailoring the intervention, along with evaluating knowledge and health outcomes. Education was delivered over 1-2 h in personalized individual or small group settings, within 4 wk of hospital discharge. All education was provided by registered nurses or respiratory therapists who were also certified asthma educators. The EPIC electronic medical record was used to facilitate referral and scheduling of asthma education sessions, and to track subsequent acute asthma visits. We compared the frequency of a repeat asthma emergency department (ED) visit or hospitalization within 1-year following an initial asthma hospitalization for children who would have received comprehensive asthma education, to a historical cohort of children who were hospitalized between April 9, 2017 - Apr 8, 2018, and did not receive asthma education. RESULTS: The program had a high enrollment, capturing nearly 75% of the target population. Most families found the program to be acceptable and reported increased knowledge of how to manage asthma. We identified a crude overall 54% reduction in repeat hospitalizations among children 1 year after implementation of the asthma education program (i.e. 10.2% (23/225) repeat hospitalization rate pre- implementation versus 4.8% (11/227) post-implementation). In adjusted time-to event analysis, this reduction was prominent at 3 months among those who received comprehensive asthma education, relative to those who did not, but this improvement was not sustained by 1 year (HR =1.1, 95% CI =0.55- 2.05; p-value = 0.6). DISCUSSION: Although we did not find long-term improvements in ED visits, or hospitalizations, in children of caregivers who participated in comprehensive asthma education, the asthma education program holds potential given that most patients found it to be acceptable and that it increased asthma management knowledge. A future asthma education program should include multiple sessions to ensure that the knowledge and behavior change will be sustained, leading ultimately to long-term reductions in repeat ED visits and hospitalizations.

Utilizing electronic medical records alert to improve documentation of neonatal acute kidney injury.

BACKGROUND: Neonatal acute kidney injury (AKI) is a common yet underdiagnosed condition in neonates with significant implications for long-term kidney health. Lack of timely recognition and documentation of AKI contributes to missed opportunities for nephrology consultation and follow-up, potentially leading to adverse outcomes. METHODS: We conducted a quality improvement (QI) project to address this by incorporating an automated real-time electronic medical record (EMR)-AKI alert system in the Neonatal Intensive Care Unit (NICU) at Le Bonheur Children's Hospital. Our primary objective was to improve documentation of neonatal AKI (defined as serum creatinine (SCr) > 1.5 mg/dL) by 25% compared to baseline levels. The secondary goal was to increase nephrology consultations and referrals to the neonatal nephrology clinic. We designed an EMR-AKI alert system to trigger for neonates with SCr > 1.5 mg/dL, automatically adding AKI diagnosis to the problem list. This prompted physicians to consult nephrology, refer neonates to the nephrology clinic, and consider medication adjustments. RESULTS: Our results demonstrated a significant improvement in AKI documentation after implementing the EMR-AKI alert, reaching 100% compared with 7% at baseline (p < 0.001) for neonates with SCr > 1.5 mg/dL. Although the increase in nephrology consultations was not statistically significant (p = 0.5), there was a significant increase in referrals to neonatal nephrology clinics (p = 0.005). CONCLUSIONS: Integration of an EMR alert system with automated documentation offers an efficient and economical solution for improving neonatal AKI diagnosis and documentation. This approach enhances healthcare provider engagement, streamlines workflows, and supports QI. Widespread adoption of similar approaches can lead to improved patient outcomes and documentation accuracy in neonatal AKI care.

Delirium is frequently underdiagnosed among older hospitalised patients despite available information in hospital medical records.

BACKGROUND: In-hospital delirium is associated with adverse outcomes and is underdiagnosed, limiting research and clinical follow-up. OBJECTIVE: To compare the incidence of in-hospital delirium determined by chart-based review of electronic medical records (D-CBR) with delirium discharge diagnoses (D-DD). Furthermore, to identify differences in symptoms, treatments and delirium triggers between D-CBR and D-DD. METHOD: The community-based cohort included 2,115 participants in the Hordaland Health Study born between 1925 and 1927. Between 2018 and 2022, we retrospectively reviewed hospital electronic medical records from baseline (1997-99) until death prior to 2023. D-DD and D-CBR were validated using The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, criteria for delirium. RESULTS: Of the 2,115 participants, 638 had in-hospital delirium. The incidence rate (IR) of D-CBR was 29.8 [95% confidence interval 28, 32] per 1,000 person-years, whereas the IR by D-DD was 3.4 [2.8, 4.2]. The IR ratio was 9.14 (P < 0.001). Patients who received pharmacological treatment for delirium (n = 121, odds ratio (OR) 3.4, [2.1, 5.4], P < 0.001), who were affected by acute memory impairment (n = 149, OR 2.8, [1.8, 4.5], P < 0.001), or change in perception (n = 137, OR 2.9, [1.8, 4.6] P < 0.001) had higher odds for D-DD. In contrast, post-operative cases (OR 0.2, [0.1, 0.4], P < 0.001) had lower odds for D-DD. CONCLUSION: Underdiagnosis of in-hospital delirium was a major issue in our study, especially in less severe delirium cases. Our findings emphasise the need for integrating systematic delirium diagnostics and documentation into hospital admission and discharge routines.

Rethinking the clinical research protocol: Lessons learned from the COVID-19 pandemic and recommendations for reducing noncompliance.

BACKGROUND/AIMS: Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, 103.4 million cases and 1.1 million deaths have occurred nationally as of November 2023. Despite the benefit of mitigating measures, the pandemic's effect on participant safety is rarely documented. METHODS: This study assessed noncompliance occurring from July 2019 to August 2021 that were stratified by the date of noncompliance (before or after restrictions). Events were described by size, site, noncompliance type, primary category, subcategory, and cause. In addition, noncompliance associated with COVID-19 was analyzed to determine characteristics. RESULTS: In total, 323 noncompliance events occurred across 21,146 participants at risk in 35 protocols. The overall rate of noncompliance increased from 0.008 events per participant to 0.022 events per participant after the COVID-19 restrictions (p < 0.001). For onsite protocols, the median within protocol change in rates was 0.001 (interquartile range = 0.141) after the onset of COVID-19 restrictions (p = 0.54). For large-sized protocols (n ≥ 100), the median within protocol change in rates was also 0.001 (interquartile range = 0.017) after COVID-19 restrictions (p = 0.15). For events related to COVID-19 restrictions, 160/162 (99%) were minor deviations, 161/162 (99%) were procedural noncompliance, and 124/162 (77%) were an incomplete study visit. CONCLUSION: These noncompliance events have implications for clinical trial methodology because nonadherence to trial design can lead to participant safety concerns and loss of trial data validity. Protocols should be written to better facilitate the capture of all safety and efficacy data. This recommendation should be considered when changes occur to the protocol environment that are outside of the study team's control.

Patients with hidradenitis suppurativa are associated with risk of new-onset glaucoma: a propensity-score-matched cohort study.

Background: Ocular comorbidities of hidradenitis suppurativa (HS) has been widely evaluated; however real-world evidence was scarce. Moreover, risk of glaucoma in HS patients remained unclear. This study aimed to evaluate the 5-year glaucoma risk in HS patients. Methods: This retrospective cohort study used the TriNetX database covering 2005-2017. In total, 53,281 HS patients were propensity score matched 1:1 to controls based on demographics, including comorbidities, medications, healthcare utilization, etc. Patients were followed for 5 years post-index date. Glaucoma risks were calculated based on hazard ratios and 95% confidence intervals (95% CI). Stratified analyses by sex and age were performed. Results: After matching, baseline characteristics were similar between groups. HS was associated with a 1.25 times higher 5-year glaucoma risk (95% CI, 1.10-1.42). The risk was significant within 1 year (HR=1.37; 95% CI, 1.03-1.82), 3 years (HR=1.31; 95% CI, 1.12-1.54), and 5 years post-index. In subgroup analysis, women had a 1.28 times higher risk (95% CI, 1.10-1.49). Patients aged 18-64 years (HR=1.33; 95% CI, 1.14-1.55) and ≥65 years (HR=1.33; 95% CI, 1.05-1.67) also presented elevated glaucoma risks. Conclusion: This real-world data analysis demonstrated a significantly increased 5-year glaucoma risk in HS patients versus matched controls. Ocular complications should be concerned while managing HS patients.

Association between hidradenitis suppurativa and atopic diseases: a multi-center, propensity-score-matched cohort study.

Background: Cross-sectional evidence has suggested a high prevalence of atopic diseases in patients with hidradenitis suppurativa (HS). However, there is a lack of evidence based on longitudinal studies. This study aimed to assess the risk of different atopic diseases, including asthma, atopic dermatitis, and allergic rhinitis, in patients with HS. Methods: In this retrospective cohort study, data from the TriNetX research network were obtained. Patients with HS were enrolled, and a 1:1 propensity score matching was performed to select a non-HS control group. Matching covariates included age, sex, race, comorbidities, comedications, socioeconomic status, lab data, and medical utilization status. Hazard ratios (HR) for atopic diseases were assessed. Results: Over a 15-year follow-up period, patients with HS were found to be at a higher risk for atopic dermatitis (HR = 1.65; 95% CI, 1.44-1.90), asthma (HR = 1.41; 95% CI, 1.33-1.49), and allergic rhinitis (HR = 1.08; 95% CI, 1.03-1.13). A similar trend was observed in shorter follow-up periods. The association between HS, atopic dermatitis, and asthma was consistent across different age and sex subgroups. Conclusion: Atopic diseases including atopic dermatitis, asthma and allergic rhinitis are associated with HS. Further investigation is needed to assess the necessity of early screening for atopic diseases in patients with HS.

Depression risk in chronic tonsillitis patients underwent tonsillectomy: a global federated health network analysis.

Background: Tonsillectomy is a common surgery in the US, with possible postoperative complications. While small studies indicate postoperative depressive symptoms may occur, large-scale evidence is lacking on the tonsillectomy-depression link. Methods: We conducted a retrospective cohort study using the TriNetX US collaborative network, offering de-identified electronic health data from 59 collaborative healthcare organizations (HCOs) in the United States. In this study, people being diagnosed of chronic tonsillitis between January 2005 and December 2017 were enrolled. Patients deceased, with previous record of cancers or psychiatric events before index date were excluded. 14,874 chronic tonsillitis patients undergoing tonsillectomy were propensity score matched 1:1 to controls for age, sex, and race. New-onset depression risks were evaluated over 5 years post-tonsillectomy and stratified by age and sex. Confounders were adjusted for including demographics, medications, comorbidities and socioeconomic statuses. Results: After matching, the difference of key baseline characteristics including age, sex, comedications status and obesity status was insignificant between tonsillectomy and non-tonsillectomy groups. Tonsillectomy had a 1.29 times higher 5-year depression risk versus matched controls (95% CI, 1.19-1.40), with elevated risks seen at 1 year (HR=1.51; 95% CI, 1.28-1.79) and 3 years (HR=1.30; 95% CI, 1.18-1.43). By stratifications, risks were increased for both males (HR=1.30; 95% CI, 1.08-1.57) and females (HR=1.30; 95% CI, 1.18-1.42), and significantly higher in ages 18-64 years (HR=1.37; 1.26-1.49), but no significance observed for those 65 years and older. After performing sensitivity analyses and applying washout periods of 6, 12, and 36 months, the outcome remained consistent with unadjusted results. Conclusion: This real-world analysis found tonsillectomy was associated with a 30% higher 5-year depression risk versus matched non-tonsillectomy patients with chronic tonsillitis. Further mechanistic research is needed to clarify the pathophysiologic association between depression and tonsillectomy. Depression is not commonly mentioned in the current post-tonsillectomy care realm; however, the outcome of our study emphasized the possibility of these suffering condition after operation. Attention to psychological impacts following tonsillectomy is warranted to support patient well-being, leading to better management of post-tonsillectomy individuals.

Hidradenitis suppurativa as a potential risk factor of periodontitis: a multi-center, propensity-score-matched cohort study.

Background: Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease associated with systemic symptoms. Periodontitis, a prevalent dental disease, shares immune-mediated inflammatory characteristics with HS. This cohort study aims to evaluate the association between HS and periodontitis. Methods: Using the TriNetX research network, a global-federated database of electronic health records, we conducted a retrospective cohort study. People being diagnosed of HS were identified and propensity score matching was performed to identify proper control group, via balancing critical covariates Within the follow-up time of 1 year, 3 year and 5 years, hazard ratios were calculated to assess the risk of periodontitis in HS patients compared to controls. Results: Within the 53,968 HS patients and the same number of matched controls, the HS patients exhibited a significantly increased risk of developing periodontitis compared to controls after 3 years of follow-up (HR: 1.64, 95% CI: 1.11, 2.44) and 5 years of follow-up (HR: 1.64, 95% CI: 1.21, 2.24) of follow-up. Sensitivity analyses supported these findings under various matching models and washout periods. While comparing with patients with psoriasis, the association between HS and periodontitis remained significant (HR: 1.73, 95% CI: 1.23, 2.44). Conclusion: The observed increased risk suggests the need for heightened awareness and potential interdisciplinary care for individuals with HS to address periodontal health.