Clinical Research Network Research Articles

Fostering the international interoperability of clinical research networks to tackle undiagnosed and under-researched rare diseases

Clinical research is an essential component to advance diagnosis and therapeutic development. In 2022, the International Rare Diseases Research Consortium (IRDiRC) and the European Joint Programme on Rare Diseases (EJP RD) brought together key stakeholders from across the globe to discuss common themes in clinical research networks (CRNs) for rare diseases. Various topics were raised during discussions including current state of CRNs, the need for new CRNs, multi-stakeholder perspectives on value of CRNs, and ways to collaborate on a global scale. Communication and coordination between various groups, taking advantage of existing experiences, can expedite establishment and execution of complex collaborations that will be necessary for CRNs. In this perspective, we discuss opportunities and highlight key considerations for developing successful collaborative CRNs across the globe.

Abstract 4140180: The Effect of Benzodiazepine Use in Patients with Atrial Fibrillation and Obstructive Sleep Apnea

Introduction: Sleep apnea is a common sleep disorder that can worsen atrial fibrillation(AF) prognosis. Benzodiazepines(BZD) are commonly prescribed for insomnia, which often accompanies sleep apnea. However, BZDs have been associated with worsening of sleep apnea due to respiratory depression, pharyngeal muscle relaxation, and increase of arousal threshold, which all may lead to prolonged hypoxia. There is little research on the effect of BZD use in AF patients with sleep apnea. Therefore, the objective of this study is to investigate the effects of BZD usage on outcomes in the AF population with sleep apnea. Methods: Data from patients with AF and sleep apnea seen at Tulane Medical Center between 2010 and 2019 was obtained from Research Action for Health Network(REACHnet), a Clinical Research Network in PCORnet®. Patients with AF and sleep apnea were divided between those with a prescription of BZD and those without BZD. These two groups were compared using the Kaplan-Meier method for time-to outcome for all-cause mortality, ischemic stroke, myocardial infarction(MI), and hospitalizations in the five years following their AF diagnosis. Cox regression analysis was used to investigate proportional hazards and control for demographics, comorbidities, and medication use. Results: There were 524 total patients included with AF and sleep apnea. Of these, 413(78.8%) were not prescribed BZDs, while 111(21.1%) were taking BZDs. Use of BZDs was associated with worse outcomes. In the no BZD and the BZD group over the 5 years following AF diagnosis, the rate of mortality was 6.1% and 12.6%(p<.001), the rate of ischemic stroke was 16% and 23.4%(p=.008), the rate of MI was 11.9% and 22.5%(p<.001), and the rate of hospitalization was 51.8% and 59.5%(p<.001), respectively. In multivariate Cox regression, use of BZD was associated with higher mortality(HR: 2.65; CI: 2.26-3.05; p=.013) and hospitalization(HR: 2.15; CI: 1.99-2.31;p<.001). Conclusion: BZD use was associated with an over 2-fold increase in all-cause mortality and hospitalizations in patients with AF and sleep apnea. This suggests that BZDs should be used with caution in this patient population, and other treatment modalities for insomnia should be considered.

Differences in COVID-19 Outpatient Antiviral Treatment Among Adults Aged ≥65 Years by Age Group - National Patient-Centered Clinical Research Network, United States, April 2022-September 2023.

Adults aged ≥65 years experience the highest risk for COVID-19-related hospitalization and death, with risk increasing with increasing age; outpatient antiviral treatment reduces the risk for these severe outcomes. Despite the proven benefit of COVID-19 antiviral treatment, information on differences in use among older adults with COVID-19 by age group is limited. Nonhospitalized patients aged ≥65 years with COVID-19 during April 2022-September 2023 were identified from the National Patient-Centered Clinical Research Network. Differences in use of antiviral treatment among patients aged 65-74, 75-89, and ≥90 years were assessed. Multivariable logistic regression was used to estimate the association between age and nonreceipt of antiviral treatment. Among 393,390 persons aged ≥65 years, 45.9% received outpatient COVID-19 antivirals, including 48.4%, 43.5%, and 35.2% among those aged 65-75, 76-89, and ≥90 years, respectively. Patients aged 75-89 and ≥90 years had 1.17 (95% CI = 1.15-1.19) and 1.54 (95% CI = 1.49-1.61) times the adjusted odds of being untreated, respectively, compared with those aged 65-74 years. Among 12,543 patients with severe outcomes, 2,648 (21.1%) had received an outpatient COVID-19 antiviral medication, compared with 177,874 (46.7%) of 380,847 patients without severe outcomes. Antiviral use is underutilized among adults ≥65 years; the oldest adults are least likely to receive treatment. To prevent COVID-19-associated morbidity and mortality, increased use of COVID-19 antiviral medications among older adults is needed.

Developing an automated algorithm for identification of children and adolescents with diabetes using electronic health records from the OneFlorida+ clinical research network.

To develop an automated computable phenotype (CP) algorithm for identifying diabetes cases in children and adolescents usingelectronic health records (EHRs) from the UF Health System. The CP algorithm was iteratively derived based on structured data from EHRs (UF Health System 2012-2020). We randomly selected 536 presumed cases among individuals aged <18 years who had (1) glycated haemoglobin levels ≥ 6.5%; or (2) fasting glucose levels ≥126 mg/dL; or (3) random plasma glucose levels ≥200 mg/dL; or (4) a diabetes-related diagnosis code from an inpatient or outpatient encounter; or (5) prescribed, administered, or dispensed diabetes-related medication. Four reviewers independently reviewed the patient charts to determine diabetes status and type. Presumed cases without type 1 (T1D) or type 2 diabetes (T2D) diagnosis codes were categorized as non-diabetes/other types of diabetes. The rest were categorized as T1D if the most recent diagnosis was T1D, or otherwise categorized as T2D if the most recent diagnosis was T2D. Next, we applied a list of diagnoses and procedures that can determine diabetes type (e.g., steroid use suggests induced diabetes) to correct misclassifications from Step 1. Among the 536 reviewed cases, 159 and 64 had T1D and T2D, respectively. The sensitivity, specificity, and positive predictive values of the CP algorithm were 94%, 98% and 96%, respectively, for T1D and 95%, 95% and 73% for T2D. We developed a highly accurate EHR-based CP for diabetes in youth based on EHR data from UF Health. Consistent with prior studies, T2D was more difficult to identify using these methods.

Social Deprivation and Multimorbidity Among Community-Based Health Center Patients in the United States.

Multimorbidity - having 2 or more chronic diseases - is a national public health concern that entails burdensome and costly care for patients, their families, and public health programs. Adults residing in socially deprived areas often have limited access to social and material resources. They also experience a greater multimorbidity burden. We conducted a retrospective cohort analysis of electronic health record (EHR) data from 678 community-based health centers (CHCs) in 27 states from the Accelerating Data Value Across a National Community Health Center (ADVANCE) Network, a clinical research network, from 2012-2019. We used mixed-effects Poisson regression to examine the relationship of area-level social deprivation (eg, educational attainment, household income, unemployment) to chronic disease accumulation among a sample of patients aged 45 years or older (N = 816,921) residing across 9,362 zip code tabulation areas and receiving care in safety-net health organizations. We observed high rates of chronic disease among this national sample. Prevalence of multimorbidity varied considerably by geographic location, both within and between states. People in more socially deprived areas with Social Deprivation Index (SDI) scores in quartiles 2, 3, and 4 had greater initial chronic disease counts - 17.1%, 17.7%, and 18.0%, respectively - but a slower rate of accumulation compared with people in the least-deprived quartile. Our findings were consistent for models of the composite SDI and those evaluating disaggregated measures of area-level educational attainment, household income, and unemployment. Social factors play an important role in the development and progression of multimorbidity, which suggests that an assessment and understanding of area-level social deprivation is necessary for developing public health strategies to address multimorbidity.

Combining electronic health records data from a clinical research network with registry data to examine long-term outcomes of interventions and devices: an observational cohort study

ObjectivesTo assess the feasibility of assessing long-term outcomes of peripheral vascular intervention (PVI) by linking data from a clinical registry to electronic health records (EHR) data from a clinical research...

Use of electronic health records to characterize patients with uncontrolled hypertension in two large health system networks

BackgroundImproving hypertension control is a public health priority. However, consistent identification of uncontrolled hypertension using computable definitions in electronic health records (EHR) across health systems remains uncertain.MethodsIn this retrospective cohort study, we applied two computable definitions to the EHR data to identify patients with controlled and uncontrolled hypertension and to evaluate differences in characteristics, treatment, and clinical outcomes between these patient populations. We included adult patients (≥ 18 years) with hypertension (based on either ICD-10 codes of hypertension or two elevated blood pressure [BP] measurements) receiving ambulatory care within Yale-New Haven Health System (YNHHS; a large US health system) and OneFlorida Clinical Research Consortium (OneFlorida; a Clinical Research Network comprised of 16 health systems) between October 2015 and December 2018. We identified patients with controlled and uncontrolled hypertension based on either a single BP measurement from a randomly selected visit or all BP measurements recorded between hypertension identification and the randomly selected visit).ResultsOverall, 253,207 and 182,827 adults at YNHHS and OneFlorida were identified as having hypertension. Of these patients, 83.1% at YNHHS and 76.8% at OneFlorida were identified using ICD-10-CM codes, whereas 16.9% and 23.2%, respectively, were identified using elevated BP measurements (≥ 140/90 mmHg). A total of 24.1% of patients at YNHHS and 21.6% at OneFlorida had both diagnosis code for hypertension and elevated blood pressure measurements. Uncontrolled hypertension was observed among 32.5% and 43.7% of patients at YNHHS and OneFlorida, respectively. Uncontrolled hypertension was disproportionately higher among Black patients when compared with White patients (38.9% versus 31.5% in YNHHS; p < 0.001; 49.7% versus 41.2% in OneFlorida; p < 0.001). Medication prescription for hypertension management was more common in patients with uncontrolled hypertension when compared with those with controlled hypertension (overall treatment rate: 39.3% versus 37.3% in YNHHS; p = 0.04; 42.2% versus 34.8% in OneFlorida; p < 0.001). Patients with controlled and uncontrolled hypertension had similar incidence rates of deaths, CVD events, and healthcare visits at 3, 6, 12, and 24 months. The two computable definitions generated consistent results.ConclusionsWhile the current EHR systems are not fully optimized for disease surveillance and stratification, our findings illustrate the potential of leveraging EHR data to conduct digital population surveillance in the realm of hypertension management.

Novel eicosanoid signature in plasma provides diagnostic for metabolic dysfunction-associated steatotic liver disease

There is a clinical need for a simple test implementable at the primary point of care to identify individuals with metabolic dysfunction-associated steatotic liver disease (MASLD) in the population. Blood plasma samples from adult patients with varying phenotypes of MASLD were used to identify a minimal set of lipid analytes reflective of underlying histologically confirmed MASLD. Samples were obtained from the NIDDK Nonalcoholic Steatohepatitis Clinical Research Network (NASH CRN) NAFLD Database prospective cohort study (MASLD group; N = 301). Samples of control subjects were obtained from cohort studies at the University of California San Diego (control group; N = 48). Plasma samples were utilized for targeted quantitation of circulating eicosanoids, related bioactive metabolites, and polyunsaturated fatty acids by ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) lipidomics analysis. Bioinformatic approaches were used to discover a panel of bioactive lipids that can be used as a diagnostic tool to identify MASLD. The final panel of fifteen lipid metabolites consists of 12 eicosanoid metabolites and 3 free fatty acids that were identified to be predictive for MASLD by multivariate area under the receiver operating characteristics curve (AUROC) analysis. The panel was highly predictive for MASLD with an AUROC of 0.999 (95% CI = 0.986–1.0) with only one control misclassified. A validation study confirmed the resulting MASLD LIPIDOMICS SCORE, which may require a larger-scale prospective study to optimize. This predictive model should guide the development of a non-invasive “point-of-care” test to identify MASLD patients requiring further evaluation for the presence of metabolic dysfunction-associated steatohepatitis.

Prevalence of subclinical hypothyroidism and longitudinal thyroid stimulating hormone changes in youth with metabolic dysfunction-associated steatotic liver disease: an observational study.

Studies on adults have shown an association between overt or subclinical hypothyroidism (SH) and metabolic dysfunction-associated steatotic liver disease (MASLD). The goal of this study was to assess the relationship between thyroid-stimulating hormone (TSH) levels and the histological characteristics of MASLD in youth. This observational study used prospectively collected liver biopsy and clinical data from youth enrolled in two pediatric clinical trials in the Nonalcoholic Steatohepatitis Clinical Research Network (NASH CRN). Thyroid assays were compared between youth with MASLD and population-based controls aged ≤18 years from the National Health and Nutrition Examination Survey (NHANES). Individuals with overt hypothyroidism, abnormal anti-thyroid antibody, or thyroid-related medications were excluded. SH was defined as TSH between 4.5-10.0uIU/L. Multinomial logistic regression was used to test the association between TSH and MASLD histological changes at baseline, adjusting for age, sex, race/ethnicity, and body mass index. Mixed-effect models, including treatment and time, were used for the longitudinal analysis. Mean TSH, total thyroxine (T4), total triiodothyronine (T3), and free T4 levels were higher (p<0.001) in the NASH CRN cohort (n=218; 421 observations) than in the NHANES cohort (n=2,198). TSH levels were positively associated with increased steatosis over time (p=0.03). SH was associated with borderline or definite metabolic-associated steatohepatitis on histology at baseline (p=0.03) and with changes in fibrosis over time (p=0.01). The association between TSH and steatosis severity in individuals with normal thyroid hormone concentrations suggests an independent role of TSH in MASLD.

Prevalent Metformin Use in Adults With Diabetes and the Incidence of Long COVID: An EHR-Based Cohort Study From the RECOVER Program.

Studies show metformin use before and during SARS-CoV-2 infection reduces severe COVID-19 and postacute sequelae of SARS-CoV-2 (PASC) in adults. Our objective was to describe the incidence of PASC and possible associations with prevalent metformin use in adults with type 2 diabetes mellitus (T2DM). This is a retrospective cohort analysis using the National COVID Cohort Collaborative (N3C) and Patient-Centered Clinical Research Network (PCORnet) electronic health record (EHR) databases with an active comparator design that examined metformin-exposed individuals versus nonmetformin-exposed individuals who were taking other diabetes medications. T2DM was defined by HbA1c ≥6.5 or T2DM EHR diagnosis code. The outcome was death or PASC within 6 months, defined by EHR code or computable phenotype. In the N3C, the hazard ratio (HR) for death or PASC with a U09.9 diagnosis code (PASC-U09.0) was 0.79 (95% CI 0.71-0.88; P < 0.001), and for death or N3C computable phenotype PASC (PASC-N3C) was 0.85 (95% CI 0.78-0.92; P < 0.001). In PCORnet, the HR for death or PASC-U09.9 was 0.87 (95% CI 0.66-1.14; P = 0.08), and for death or PCORnet computable phenotype PASC (PASC-PCORnet) was 1.04 (95% CI 0.97-1.11; P = 0.58). Incident PASC by diagnosis code was 1.6% metformin vs. 2.0% comparator in the N3C, and 2.1% metformin vs. 2.5% comparator in PCORnet. By computable phenotype, incidence was 4.8% metformin and 5.2% comparator in the N3C and 24.7% metformin vs. 26.1% comparator in PCORnet. Prevalent metformin use is associated with a slightly lower incidence of death or PASC after SARS-CoV-2 infection. PASC incidence by computable phenotype is higher than by EHR code, especially in PCORnet. These data are consistent with other observational analyses showing prevalent metformin is associated with favorable outcomes after SARS-CoV-2 infection in adults with T2DM.

Environmental toxicants modulate disease severity in pediatric metabolic dysfunction-associated steatohepatitis.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is common in children. We hypothesized environmental toxins could drive progression to metabolic dysfunction-associated steatohepatitis (MASH), and assayed serum toxins and metabolites in children with histologically characterized MASLD/MASH. Environmental chemicals, common in household items, perfluoroalkyl substances (PFAS), brominated flame retardants (PBDEs), and metabolic profiles were assayed in children enrolled in the multicenter NASH Clinical Research Network Pediatric Database 2. Mixture models, using repeated holdout weighted quantile sum regression (WQSrh) were run in addition to single chemical/metabolite logistic regression. For metabolomic analyses, random subset version of WQSrh was used for the large number of predictors versus participants. Nominal and false discovery rate (FDR) p-values (two-sided) were computed. Four hundred and thirty-five children distributed across MASH (n = 293) and MASLD (n = 142), with 304 (69.9%) males. Mean (standard deviation) for Nonalcoholic Steatohepatitis Score (NAS) and alanine aminotransferase (ALT) for MASLD were 3.1 (1.0), 67.9 (43.4), and for MASH 4.2 (1.4), 144 (121). There was an inverse association between PFAS/PBDE mixture and MASH versus MASLD, lobular inflammation (p = 0.026), NAS (p = 0.009, FDR p = 0.04), and log-transformed ALT (p = 0.005, FDR p = 0.025) driven by perfluorohexane sulfonate (PFHxS). Metabolites from positive hydrophilic interaction liquid chromatography mode, biliverdin (p = 0.002) and 1-methylhistidine (associated with meat ingestion, p = 0.02) and reverse phase negative mode, hippuric acid (solvent exposure, p = 0.022) significantly associated with MASH. Significant negative PFAS/PBDE mixture effect and odds of MASH were dominated by PHFXS. Several metabolites are significantly associated with MASH which inform mechanistic pathways and could drive key therapeutic and diagnostic strategies in children.

Body mass index changes and their association with SARS-CoV-2 infection: a real-world analysis.

To study body mass index (BMI) changes among individuals aged 18-99 years with and without SARS-CoV-2 infection. Using real-world data from the OneFlorida+ Clinical Research Network of the National Patient-Centered Clinical Research Network, we compared changes over time in BMI in an Exposed cohort (positive SARS-CoV-2 test between March 2020-January 2022), to a contemporary Unexposed cohort (negative SARS-CoV-2 tests), and an age/sex-matched Historical control cohort (March 2018-January 2020). BMI (kg/m2) was retrieved from objective measures of height and weight in electronic health records. We used target trial approaches to estimate BMI at start of follow-up and change per 100 days of follow-up for Unexposed and Historical cohorts relative to the Exposed cohort by categories of sex, race & ethnicity, age, and hospitalization status. The study sample consisted of 249,743 participants (19.2% Exposed, 61.5% Unexposed, 19.3% Historical cohort) of whom 62% were women, 21.5% Non-Hispanic Black, 21.4% Hispanic and 5.6% Non-Hispanic other and had an average age of 51.9 years (SD: 18.9). At start of follow-up, relative to the Unexposed cohort (mean BMI: 29.3 kg/m2 [95% CI: 29.1, 29.4]), the Exposed (0.07 kg/m2 [95% CI; 0.01, 0.12]) had higher mean BMI and Historical controls (-0.20 kg/m2 [95% CI; -0.25, -0.15]) had lower mean BMI. Over 100 days, BMI did not change (0 kg/m2 [95% CI: -0.03, 0.03]) for the Exposed cohort, decreased (-0.04 kg/m2 [95% CI; -0.05, -0.02]) for the Unexposed cohort and increased (0.03 kg/m2 [95% CI; 0.01, 0.04]) for the Historical cohort. Observed differences in BMI at start of follow-up and over 100 days were consistent between Unexposed and Exposed cohorts for most subgroups, except at start of follow-up period among Males and those 65 years or older who had lower BMI among Exposed. In a diverse real-world cohort of adults, mean BMI of those with and without SARS-CoV2 infection varied in their trajectories. The mechanisms and implications of weight retention following SARS-CoV-2 infection remain unclear.

Bevacizumab First in DRCR Protocol AC vs Real-World Physician Treatment Choice for Diabetic Macular Edema: Two-Year Cost Analysis.

Purpose: To compare the modeled costs of the Protocol AC bevacizumab-first treatment protocol (with a switch to aflibercept for sub-responders) with real-world costs for treatment-naïve patients with diabetic macular edema (DME) over a 2-year period. Methods: Published data from the Diabetic Retinopathy Clinical Research Network (DRCR) Protocol AC bevacizumab-first arm (154 eyes) were used to model 2-year treatment costs. Real-world costs were modeled using data from the Vestrum Health electronic medical records database from a 2016 to 2018 cohort of treatment-naïve eyes with DME (n = 1062) treated with antivascular endothelial growth factor monotherapy. The visual acuity (VA) before treatment in the real-world cohort was matched to Protocol AC. A secondary cost analysis further matched VA gains after treatment in the real-world cohort (n = 346) to Protocol AC. Results: In Protocol AC, the modeled 2-year DME treatment cost in the bevacizumab-first arm was $18,952, with a mean of 16.1 injections over 22.5 visits and 70% of eyes being switched to aflibercept by year 2. (Within 2 years, 57% of injections were bevacizumab and 43% were aflibercept.) Over the same period, the modeled 2-year real-world cost ($11,459) was 40% lower, with a mean of 8.6 injections over 13.8 visits (42% bevacizumab, 45% aflibercept, 13% ranibizumab). Even when matched for baseline VA and a 14-letter VA gain over 2 years, the real-world cost ($15,394) was still 19% lower than the modeled cost in the Protocol AC bevacizumab-first arm. Conclusions: The real-world cost of treating DME over 2 years was significantly lower than the Protocol AC bevacizumab-first cost. Application of Protocol AC findings into real-world utilization, as with step therapy mandates, should only be considered if the same intensive protocol could be followed. These data suggest that existing real-world costs that reflect physician choice are already significantly lower than protocol-mandated step therapy, even when controlling for similar VA outcomes.

Development of Lung Cancer Risk Prediction Machine Learning Models for Equitable Learning Health System: Retrospective Study.

A significant proportion of young at-risk patients and nonsmokers are excluded by the current guidelines for lung cancer (LC) screening, resulting in low-screening adoption. The vision of the US National Academy of Medicine to transform health systems into learning health systems (LHS) holds promise for bringing necessary structural changes to health care, thereby addressing the exclusivity and adoption issues of LC screening. This study aims to realize the LHS vision by designing an equitable, machine learning (ML)-enabled LHS unit for LC screening. It focuses on developing an inclusive and practical LC risk prediction model, suitable for initializing the ML-enabled LHS (ML-LHS) unit. This model aims to empower primary physicians in a clinical research network, linking central hospitals and rural clinics, to routinely deliver risk-based screening for enhancing LC early detection in broader populations. We created a standardized data set of health factors from 1397 patients with LC and 1448 control patients, all aged 30 years and older, including both smokers and nonsmokers, from a hospital's electronic medical record system. Initially, a data-centric ML approach was used to create inclusive ML models for risk prediction from all available health factors. Subsequently, a quantitative distribution of LC health factors was used in feature engineering to refine the models into a more practical model with fewer variables. The initial inclusive 250-variable XGBoost model for LC risk prediction achieved performance metrics of 0.86 recall, 0.90 precision, and 0.89 accuracy. Post feature refinement, a practical 29-variable XGBoost model was developed, displaying performance metrics of 0.80 recall, 0.82 precision, and 0.82 accuracy. This model met the criteria for initializing the ML-LHS unit for risk-based, inclusive LC screening within clinical research networks. This study designed an innovative ML-LHS unit for a clinical research network, aiming to sustainably provide inclusive LC screening to all at-risk populations. It developed an inclusive and practical XGBoost model from hospital electronic medical record data, capable of initializing such an ML-LHS unit for community and rural clinics. The anticipated deployment of this ML-LHS unit is expected to significantly improve LC-screening rates and early detection among broader populations, including those typically overlooked by existing screening guidelines.

Digital quantitation of bridging fibrosis and septa reveals changes in natural history and treatment not seen with conventional histology.

Metabolic dysfunction-associated steatohepatitis (MASH) with bridging fibrosis is a critical stage in the evolution of fatty liver disease. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy with artificial intelligence (AI) provides sensitive and reproducible quantitation of liver fibrosis. This methodology was applied to gain an in-depth understanding of intra-stage fibrosis changes and septa analyses in a homogenous, well-characterised group with MASH F3 fibrosis. Paired liver biopsies (baseline [BL] and end of treatment [EOT]) of 57 patients (placebo, n = 17 and tropifexor n = 40), with F3 fibrosis stage at BL according to the clinical research network (CRN) scoring, were included. Unstained sections were examined using SHG/TPEF microscopy with AI. Changes in liver fibrosis overall and in five areas of liver lobules were quantitatively assessed by qFibrosis. Progressive, regressive septa, and 12 septa parameters were quantitatively analysed. qFibrosis demonstrated fibrosis progression or regression in 14/17 (82%) patients receiving placebo, while the CRN scoring categorised 11/17 (65%) as 'no change'. Radar maps with qFibrosis readouts visualised quantitative fibrosis dynamics in different areas of liver lobules even in cases categorised as 'No Change'. Measurement of septa parameters objectively differentiated regressive and progressive septa (p < .001). Quantitative changes in individual septa parameters (BL to EOT) were observed both in the 'no change' and the 'regression' subgroups, as defined by the CRN scoring. SHG/TPEF microscopy with AI provides greater granularity and precision in assessing fibrosis dynamics in patients with bridging fibrosis, thus advancing knowledge development of fibrosis evolution in natural history and in clinical trials.

Exploring General Practitioners' Management of Self-Harm in Young People: A Qualitative Study.

General practitioners (GPs) are key to the frontline assessment and treatment of young people after self-harm. Young people value GP-led self-harm care, but little is known about how GPs manage young people after self-harm. This study aimed to understand the approaches of GPs to self-harm in young people and explore their perspectives on ways they might help young people avoid repeat self-harm. We conducted semi-structured interviews with GPs from the National Health Service in England in 2021. GPs were recruited from four geographically spread clinical research networks and a professional special interest group. Data were analysed using reflexive thematic analysis. The study's patient and public involvement and community of practice groups supported participant recruitment and data analysis. Fifteen interviews were undertaken with a mean age of participants being 41 years and a breadth of experience in practice ranging from 1 to 22 years. Four themes were generated: GPs' understanding of self-harm; approaches to managing self-harm; impact of COVID-19 on consultations about self-harm; and ways to avoid future self-harm. Negative attitudes towards self-harm within clinical settings are well documented, but GPs said they took self-harm seriously, listened to young people, sought specialist support when concerned and described appropriate ways to help young people avoid self-harm. GPs felt that relationship-based care is an important element of self-harm care but feared remote consultations for self-harm may impede on this. There is a need for brief GP-led interventions to reduce repeat self-harm in young people. A study advisory group consisting of young people aged 16-25 years with personal experience of self-harm and parents and carers of young people who have self-harmed designed the recruitment poster of this study, informed its topic guide and contributed to its findings.

Lessons from the pandemic: An innovative scheme to support research in the North West Coast

In 2021, a Clinical Research Fellow (CRF) scheme was created to serve the North West Coast (NWC) region in line with the key health priorities set out by the Clinical Research Network. Five doctors in pre-specialist training were placed in NHS trust research departments across the NWC. The scheme aimed to provide early career research experience while also enhancing the provision of research across the region. The CRFs were involved in writing clinical trial grant applications and study protocols, with the scheme providing additional experience in leadership roles and time management. In addition, the CRF scheme has had a positive impact in adopted NHS trusts, which have seen their overall research capacity and capability improve, through increased flexibility and medical oversight. Research departments have benefited from increased financial income and improved national reputations. Overall, this real-world experience provided a vital ‘foot in the door’, which is essential for research-interested medics to advance in a future academic career. In the wider NWC region, the CRF scheme successfully delivered achievable and financially sustainable research. Innovative programmes such as this one should be seen as a viable option for research provision through the NHS, in the UK.

Review and analysis of history and utilization of panretinal photocoagulation and ranibizumab after publication of protocol S.

We describe the history, utilization, and series results of panretinal photocoagulation (PRP) and ranibizumab and provide an analysis of PRP and ranibizumab usage before versus after the publication of the 2-year and 5-year results of the Diabetic Retinopathy Clinical Research Network (DRCR.net) Protocol S trial. Number of ranibizumabs performed began to increase and number of PRPs performed began to decrease in 2016. After publication of the 2-year results, there was significant negative trend in PRP services and significant positive trend in ranibizumab services (both P < 0.001). After publication of the 5-year results, there was significant negative trend in PRP services (P = 0.003). There were significant negative trends (all P < 0.001) in reimbursement factors for PRP from 2013 to 2020: average work RVU (wRVU), nonfacility physical expense RVU, facility PE RVU, malpractice RVU (MP RVU). Both PRP and ranibizumab have undergone numerous trials comparing their efficacy to other treatment options or no treatment at all. The publication of the 2-year results of Protocol S was associated with an increase in utilization of ranibizumab and decrease in utilization of PRP, with continued decrease after the publication of the 5-year results.

Validation of a whole slide image management system for metabolic-associated steatohepatitis for clinical trials.

The gold standard for enrollment and endpoint assessment in metabolic dysfunction-associated steatosis clinical trials is histologic assessment of a liver biopsy performed on glass slides. However, obtaining the evaluations from several expert pathologists on glass is challenging, as shipping the slides around the country or around the world is time-consuming and comes with the hazards of slide breakage. This study demonstrated that pathologic assessment of disease activity in steatohepatitis, performed using digital images on the AISight whole slide image management system, yields results that are comparable to those obtained using glass slides. The accuracy of scoring for steatohepatitis (nonalcoholic fatty liver disease activity score ≥4 with ≥1 for each feature and absence of atypical features suggestive of other liver disease) performed on the system was evaluated against scoring conducted on glass slides. Both methods were assessed for overall percent agreement with a consensus "ground truth" score (defined as the median score of a panel of three pathologists' glass slides). Each case was also read by three different pathologists, once on glass and once digitally with a minimum 2-week washout period between the modalities. It was demonstrated that the average agreement across three pathologists of digital scoring with ground truth was noninferior to the average agreement of glass scoring with ground truth [noninferiority margin: -0.05; difference: -0.001; 95% CI: (-0.027, 0.026); and p < 0.0001]. For each pathologist, there was a similar average agreement of digital and glass reads with glass ground truth (pathologist A, 0.843 and 0.849; pathologist B, 0.633 and 0.605; and pathologist C, 0.755 and 0.780). Here, we demonstrate that the accuracy of digital reads for steatohepatitis using digital images is equivalent to glass reads in the context of a clinical trial for scoring using the Clinical Research Network scoring system.

Psychometric evaluation of clinician- and caregiver-reported clinical severity assessments for individuals with CDKL5 deficiency disorder.

The CDKL5 Clinical Severity Assessment (CCSA) is a comprehensive, content-validated measurement tool capturing the diverse challenges of cyclin-dependent kinase-like 5 (CDKL5) deficiency disorder (CDD), a genetically caused developmental epileptic encephalopathy (DEE). The CCSA is divided into clinician-reported (CCSA-Clinician) and caregiver-reported (CCSA-Caregiver) assessments. The aim of this study was to evaluate the factor structure of these measures through confirmatory factor analysis (CFA) and evaluate their validity and reliability. Participants were recruited from the International CDKL5 Clinical Research Network to take part in an in-clinic CCSA-Clinician evaluation (n = 148) and/or complete the CCSA-Caregiver questionnaire (n = 198). CFA was used to determine domains, and factor loadings and validity were assessed. For the CCSA-Clinician, inter-rater reliability was assessed by nine CDD experienced clinicians via 14 pre-recorded evaluations. Eight clinicians re-viewed and re-scored the videos after 4 weeks to evaluate intra-rater reliability. The CCSA-Caregiver was completed on a second occasion by 34 caregivers after 2-4 weeks to assess test-retest reliability. CFA resulted in three domains for the CCSA-Clinician (motor and movement, communication, vision) and four domains for the CCSA-Caregiver (seizures, behavior, alertness, feeding), with good item loadings across both measures. Structural statistics, internal consistency, discriminant validity, and reliability were satisfactory for both measures, and scores were consistent between known groups. This study provides strong evidence that the CCSA measures are suitable to assess the clinical severity of individuals with CDD, supporting their use in clinical trials. Further evaluation of responsiveness to change in a longitudinal assessment is planned. Use may also be appropriate in similar DEEs but would require validation in those populations.