BACKGROUND AND OBJECTIVE:Historic prediction models overestimate the risk of recurrence and progression for intermediate risk (IR) non-muscle-invasive bladder cancer (NMIBC). We report outcomes for patients with IR-NMIBC and the appropriateness of surveillance cystoscopy protocol using contemporaneous clinical trials. METHODS:Pooled individual IR-NMIBC patient data from four randomized controlled trials (RCT) were analyzed: HIVEC-II, PHOTO, BOXIT, and CALIBER. Patients with IR-NMIBC underwent complete tumor resection and were recommended to receive 6 weekly instillations of mitomycin C. Kaplan-Meier analyses were performed for oncological endpoints. Noncumulative distribution of recurrence was evaluated to determine the appropriateness of surveillance cystoscopy. KEY FINDING:A total of 578 patients with IR-NMIBC, with a median follow-up of 34 mo (interquartile range: 25-55 mo) were included for analysis. There was no meaningful increase in recurrence from 36 to 60 mo: overall recurrence-free rates at 12, 24, 36, and 60 mo were 73%, 61%, 56%, and 54%, respectively. In the multivariable model, the risk of recurrence was higher in patients with prior recurrences (hazard ratio [HR]: 1.75, 95% confidence interval [CI]: 1.16-2.64, p = 0.008), multifocality (HR: 1.49, 95% CI: 1.13-1.95, p = 0.004), and cancer grade (HR: 1.57, 95% CI: 1.08-2.28, p = 0.018). Grade or stage progression was uncommon (<5%), and cancer-specific survival (CSS) was 99% at 60 mo. The noncumulative risk of recurrences at 36 and 60 mo were 17% and <5%, respectively. CONCLUSIONS AND CLINICAL IMPLICATIONS:Patients with IR-NMIBC have a high recurrent risk within 36 mo, but grade/stage progression remains low. Patients could consider terminating/reducing the frequency of cystoscopy after 60 mo because of a low risk of subsequent recurrence.

Importance:Hospital-based ophthalmology faces increasing demand for long-term monitoring of neovascular age-related macular degeneration (nAMD). Safe redistribution of routine monitoring to community clinicians is relevant to integrated community (primary)-secondary care models. Objective:To examine whether community optometrist-led monitoring of nAMD is noninferior to hospital-based monitoring for detecting disease activity requiring treatment. Design, Setting, and Participants:This multicenter, noninferiority randomized clinical trial was conducted from October 8, 2019, to January 31, 2024, at secondary centers (17 hospitals) and primary centers (60 community optometry practices) with 12-month follow-up. Statisticians were masked to patient grouping. Adults 55 years or older with quiescent AMD in at least 1 eye (and quiescent or nonneovascular disease in the other) were recruited at participating hospitals. Data analysis was performed from October 2024 to March 2025. Interventions:Participants were randomized 1:1 to monitoring sessions once every 2 months in hospitals (control) or community practices (intervention). Trained and accredited optometrists performed optical coherence tomography imaging, clinical examination, patient management, and online reporting at each visit. Main Outcomes and Measures:The primary outcome (participant level) was a binary indicator of whether a false-negative clinical management decision occurred at any visit within 12 months (missed quiescent nAMD reactivation or new fellow-eye nAMD, adjudicated by a central reading-center reference standard). The noninferiority margin was a 10-percentage point absolute risk difference. Secondary outcomes were false-positive clinical management decisions, attendance adherence, visual acuity change, harms, loss to follow-up, suspicious classifications, and confirmation visit outcomes. Results:Of 704 randomized participants, 635 (90.2%) completed at least 1 follow-up visit, including 287 at community practices (mean [SD] age, 80.6 [8.1] years; 236 [67.4%] female) and 348 at hospitals (mean [SD] age, 80.1 [8.5] years; 203 [57.3%] female). False-negative clinical management decisions occurred in 11 of 287 community participants (3.8%) vs 27 of 348 hospital participants (7.8%) (risk difference, -3.9 percentage points; 95% CI, -7.4 to -0.3 percentage points; P = .04; adjusted odds ratio, 0.51; 95% CI, 0.24-1.07; P = .08), meeting noninferiority. False-positive clinical management decisions occurred in 24 of 287 community participants (8.4%) vs 12 of 348 hospital participants (3.5%) (risk difference, 4.9 percentage points; 95% CI, 0.9-9.0 percentage points). Findings were consistent across per-protocol, cluster-adjusted, and relative risk sensitivity analyses. No adverse event-related withdrawals occurred. Conclusions and Relevance:In this randomized clinical trial, community optometrist-led monitoring of quiescent nAMD was noninferior to hospital monitoring for detecting disease activity requiring treatment. These results provide evidence for its use in integrated clinical care models. Trial Registration:ClinicalTrials.gov Identifier: NCT03893474.

Background:In patients with a glioma, 50-80% will have seizures during their lifetime and half of these will be drug resistant. Seizure risk is increased perioperatively (around the time of surgery) at tumour progression and shortly before death. In seizure-naive patients with glioma undergoing surgery, existing guidelines do not recommend routine use of prophylactic antiseizure medication. Despite this, an antiseizure medication, levetiracetam, is frequently prescribed perioperatively in many neurosurgical units. Objectives:To determine whether in seizure-naive, newly diagnosed cerebral glioma patients undergoing surgery, prophylactic levetiracetam, pre-operatively and for at least 1 year post operatively, produces a meaningful (> 50%) reduction in the risk of developing seizures when compared with standard care (no prophylaxis) and is cost-effective. Design and methods:We undertook a two-arm, multicentre phase III randomised trial in 14 neurosurgery units across England and Scotland, with an embedded health economic evaluation, comparing 12 months of prophylactic antiseizure medication (levetiracetam) versus no antiseizure medication (comparator) in patients with suspected cerebral glioma undergoing surgery. The target samples size was 804 participants. Outcome measures:The primary outcome was the occurrence of a seizure within 12 months of randomisation. The secondary outcomes were time to first seizure, time to first tonic-clonic seizure, time to death (overall survival) and time to tumour recurrence (progression-free survival). The impact of prophylactic levetiracetam on mood, personality, fatigue and memory, severity of first seizure if it occurred and quality of life were assessed. The planned health economic outcomes were costs to the National Health Service and Personal Social Services and incremental cost per quality-adjusted life-year at 12 months and modelled over estimated survival. Analyses were carried out using the intention-to-treat principle. Results:Between 9 October 2019 and 30 August 2022, 94 patients were recruited, from 24 to 79 years of age and randomised to prophylactic levetiracetam (n = 49) or no prophylaxis (n = 45). Due to slow accrual, the trial closed early. Thirteen patients in the prophylactic levetiracetam arm and 9 in the no prophylaxis group died within 1 year of randomisation and did not have a seizure. Of the patients who survived for at least 1 year, 17 (47%) of 36 prophylactic levetiracetam patients had a seizure when compared with 15 (41%) of 36 no prophylaxis patients (odds ratio 1.25, 95% confidence interval 0.49 to 3.21, p = 0.64). Median time to first seizure was 5.0 months in the prophylactic levetiracetam group and 2.5 months in the no prophylaxis group. In the prophylactic levetiracetam group, 20 (41%) of 49 patients died within 12 months (median overall survival 6.8 months; range 0.2-11.9), and in the no prophylaxis group, 14 (31%) of 45 patients died within 12 months (median 4.6 months; range 0.1-12.0). At the 3-month and 6-month data collection points, the mean healthcare costs were lower in the prophylactic levetiracetam group (£1175 and £1278) compared with the no prophylaxis group (£2703 and £2767). At the 9-and 12-month data collection points, the mean healthcare costs were higher in the prophylactic levetiracetam group (£1916 and £1238) as compared with the no prophylaxis group (£1597 and £686). Health-related quality of life as measured by the EuroQol-5 Dimensions, five-level version was similar in the two intervention arms across all time points. Limitations:The trial was underpowered and closed early due to slow recruitment impacted by the COVID-19 pandemic. Approximately one quarter of patients died within 12 months and did not reach the primary outcome of 1-year risk of seizure. Conclusions:Given the trial was underpowered, there was no evidence of a difference in the 12-month seizure risk between the randomised groups and limited evidence regarding potential cost-effectiveness. The role of prophylactic antiseizure medication in glioma surgery remains undefined. Future work:SPRING provides the highest quality data available for a future, individual patient data meta-analysis. A definite trial is still needed to answer this clinical question. Funding:This synopsis presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number 16/31/136.

BACKGROUND:Atypical haemolytic uraemic syndrome (aHUS) is a rare but severe condition caused by complement dysregulation. Eculizumab prophylaxis prevents recurrence and improves survival, yet the benefits of lifelong treatment for patients are uncertain and the long-term costs for health services are substantial. This economic evaluation applied the results from the Stopping Eculizumab Treatment Safely in aHUS (SETS aHUS) trial and assessed the cost-effectiveness of replacing lifelong eculizumab with a disease monitoring strategy over the long term. METHODS:A Markov model was used to estimate cost and quality-adjusted life years (QALYs) for a treatment withdrawal and disease monitoring strategy over the long term. Results from the SETS aHUS trial informed the risk of relapse diagnosis or progression, utility values and additional healthcare use. Time to relapse diagnosis was extrapolated using parametric survival functions. RESULTS:The treatment withdrawal and disease monitoring strategy increased average patient QALYs by 0.08 [95% credible interval (CrI) -0.33-0.53], and reduced patient costs by £4 234 196 (95% CrI -£684 495 to -£6 403 694) compared with the lifelong delivery of eculizumab. The impact on survival estimates was low, as withdrawal patients had an average reduction of 0.0005 patient life years (LYs) (95% CrI -0.0029-0) over an 80-year time horizon. Withdrawal and monitoring had a 64% likelihood of being more effective and less costly than lifelong treatment. Results remained robust across multiple scenarios exploring uncertainties. CONCLUSION:Treatment withdrawal and disease monitoring was cost-effective compared with lifelong eculizumab therapy. Its adoption is expected to substantially reduce costs per patient and may improve average patient quality of life.

Objectives To assess and compare the diagnostic accuracy of non-ophthalmologist-led diabetic retinopathy screening (DRS) at health and wellness centres (HWCs) and offline artificial intelligence (AI)-assisted community-based screening, using specialist grading as the reference standard in India.Design, settings and participants Pragmatic diagnostic accuracy study in primary healthcare settings. The settings included HWCs and community-based screening sites in rural Block Boothgarh, Mohali District, Punjab, India. A total of 600 people with diabetes aged ≥30 years were enrolled across three screening models: (1) non-ophthalmologist-led DRS at the HWC, (2) AI-assisted smartphone-based DRS in the community and (3) standard referral-based care. Retinal images were captured using non-mydriatic fundus cameras and independently graded by two masked human graders; a senior retina specialist resolved any disagreements. The AI was assessed for its ability to detect diabetic retinopathy (DR) and referable diabetic retinopathy (RDR). Diagnostic performance metrics were reported.Results The non-ophthalmologist-led model demonstrated 86.4% sensitivity (95% CI 65.1% to 97.1%) and 94.3% specificity (95% CI 88.5% to 97.7%) for DR detection, with an ungradability rate of 8%. For RDR, sensitivity reached 95.8% (95% CI 78.9% to 99.9%) and specificity was 93.1% (95% CI 88.0% to 96.5%). The offline AI-assisted model achieved 93.3% sensitivity (95% CI 68.1% to 99.8%) and 85.1% specificity (95% CI 76.9% to 91.2%) for RDR, but with a higher ungradability rate (38%), mainly due to cataracts and poor image quality. Both approaches effectively identified referable cases; however, the non-ophthalmologist-led model demonstrated greater accuracy and operational feasibility.Conclusions This study demonstrates that non-ophthalmologist-led DRS at HWCs can enhance access to primary care. Offline AI-enabled screening demonstrates potential for community use but is currently limited by image quality and binary classification outputs. Integrating both approaches may strengthen DRS coverage in resource-limited settings.Clinical trials registry of India CTRI/2022/10/046283.

Abstract Background Localised renal cell carcinoma is treated with radical nephrectomy (RN) or partial nephrectomy (PN). Nephron-sparing PN increases preservation of renal function, reducing incidence of end stage renal failure and associated cardiovascular events. In patients with exophytic T1a (≤ 4 cm) tumours and normal contralateral kidney, PN is standard of care. In patients with T1b (> 4–7 cm) or endophytic T1a tumours and normal contralateral kidney, the benefits of PN over RN are less clear as there are increased surgical complications and more tissue may be excised reducing the preservation of renal function. There are no high-quality studies to address if PN is superior to RN in these more complex cases. Methods PARTIAL is a pragmatic randomised controlled parallel group unblinded superiority trial with embedded internal pilot and economic and process evaluation. A total of 420 participants will be recruited in UK NHS centres with expertise in minimally invasive nephrectomy techniques. Eligible consenting adults with a single T1 renal cell carcinoma, normal contralateral kidney and equipoise within the multidisciplinary team confirming suitability to receive both interventions by minimally invasive approaches are randomised 1:1 to PN or RN. Patients with metastatic disease, existing chronic kidney disease, solitary functioning kidney, congenital renal abnormality, inherited kidney cancer syndrome, who lack capacity to consent or are pregnant or breast feeding are excluded. Primary outcomes are gains in preservation of renal function at 2 years and surgical complications over the peri-operative period. Secondary outcomes are quality of life and recovery, cost and cost-effectiveness, rates of positive surgical margin, recurrence and cardiovascular events, overall survival, progression to chronic kidney disease and end stage renal failure, operative conversion and patient acceptability. Participants are followed up for 2 years with outcomes collected from medical records and participant questionnaires. Discussion PARTIAL will determine if gains from PN are superior to RN and offset the potential harms and costs in complex T1 renal tumours suitable for either approach. If PN is not found to provide clinically significant gains and excess complications are confirmed, then a practice-changing case for RN as standard of care could be made. Trial registration ISRCTN 11293415. Registered prospectively on 19 January 2023.

Metabolic-dysfunction associated steatotic liver disease (MASLD) is a progressive chronic liver condition characterised by substantial inter-patient variation in disease severity, with the probability of progressing to hepatic fibrosis, cirrhosis or hepatocellular carcinoma. The prevalence of MASLD is increasing rapidly and may have a significant impact on health-related quality of life (HRQoL). A novel non-preference-based Patient-Reported Outcome Measure (PROM) called NASH-CHECK has been developed to assess outcomes in metabolic dysfunction-associated steatohepatitis (MASH), previously called non-alcoholic steatohepatitis (NASH). Preference-based outcome measures are needed to generate quality adjusted life years (QALYs) for economic evaluation. The aim of this study was to generate mapping algorithms to predict EQ-5D-5L utility scores from the NASH-CHECK in a MASLD population. A large dataset comprising 1,971 MASLD cases from seven European countries (France, Italy, Portugal, Netherlands, Spain, Sweden and UK) was used to generate the mapping algorithms. Regression results from a number of popular candidate models were compared against each other in terms of statistical and visual fit, including more conventional models (OLS, Tobit, Two-Part) and the more recently developed Adjusted Limited Dependent Variable Mixture Model (ALDVMM). Mapping was conducted separately for each of the seven countries. The ALDVMM with higher numbers of components provided the best visual fit across all samples, especially at the low end (representing very poor health states and worse-than-death health states) and high end (representing fairly good health states and full health) of the EQ-5D-5L distributions. The ALDVMM also produced predicted estimates which had the best statistical fit (in terms of mean absolute error, root mean square error and information criteria where applicable) for samples with relatively large number of observations. Using an ALDVMM with higher numbers of components provides estimates across the whole distribution for the prediction of EQ-5D-5L as a function of NASH-CHECK scores for people with MASLD in several European countries. This enables QALYs to be indirectly calculated in this patient population when a preference-based measure such as the EQ-5D-5L has not been collected.

QuestionIs community optometrist-led monitoring of quiescent neovascular age-related macular degeneration noninferior to hospital monitoring for identifying disease activity requiring treatment?FindingsIn this randomized clinical trial of 635 adults, false-negative clinical management decisions occurred in 3.8% in the community group and 7.8% in the hospital group for a difference of -3.9 percentage points, meeting the criterion for noninferiority.MeaningThis study's results support the use of community optometrist-led monitoring of quiescent neovascular age-related macular degeneration for detecting disease activity requiring treatment in integrated clinical care models. This randomized clinical trial examines whether community-based monitoring of neovascular age-related macular degeneration is noninferior to hospital monitoring for identifying disease activity requiring treatment. ImportanceHospital-based ophthalmology faces increasing demand for long-term monitoring of neovascular age-related macular degeneration (nAMD). Safe redistribution of routine monitoring to community clinicians is relevant to integrated community (primary)-secondary care models.ObjectiveTo examine whether community optometrist-led monitoring of nAMD is noninferior to hospital-based monitoring for detecting disease activity requiring treatment.Design, Setting, and ParticipantsThis multicenter, noninferiority randomized clinical trial was conducted from October 8, 2019, to January 31, 2024, at secondary centers (17 hospitals) and primary centers (60 community optometry practices) with 12-month follow-up. Statisticians were masked to patient grouping. Adults 55 years or older with quiescent AMD in at least 1 eye (and quiescent or nonneovascular disease in the other) were recruited at participating hospitals. Data analysis was performed from October 2024 to March 2025.InterventionsParticipants were randomized 1:1 to monitoring sessions once every 2 months in hospitals (control) or community practices (intervention). Trained and accredited optometrists performed optical coherence tomography imaging, clinical examination, patient management, and online reporting at each visit.Main Outcomes and MeasuresThe primary outcome (participant level) was a binary indicator of whether a false-negative clinical management decision occurred at any visit within 12 months (missed quiescent nAMD reactivation or new fellow-eye nAMD, adjudicated by a central reading-center reference standard). The noninferiority margin was a 10-percentage point absolute risk difference. Secondary outcomes were false-positive clinical management decisions, attendance adherence, visual acuity change, harms, loss to follow-up, suspicious classifications, and confirmation visit outcomes.ResultsOf 704 randomized participants, 635 (90.2%) completed at least 1 follow-up visit, including 287 at community practices (mean [SD] age, 80.6 [8.1] years; 236 [67.4%] female) and 348 at hospitals (mean [SD] age, 80.1 [8.5] years; 203 [57.3%] female). False-negative clinical management decisions occurred in 11 of 287 community participants (3.8%) vs 27 of 348 hospital participants (7.8%) (risk difference, -3.9 percentage points; 95% CI, -7.4 to -0.3 percentage points; P = .04; adjusted odds ratio, 0.51; 95% CI, 0.24-1.07; P = .08), meeting noninferiority. False-positive clinical management decisions occurred in 24 of 287 community participants (8.4%) vs 12 of 348 hospital participants (3.5%) (risk difference, 4.9 percentage points; 95% CI, 0.9-9.0 percentage points). Findings were consistent across per-protocol, cluster-adjusted, and relative risk sensitivity analyses. No adverse event-related withdrawals occurred.Conclusions and RelevanceIn this randomized clinical trial, community optometrist-led monitoring of quiescent nAMD was noninferior to hospital monitoring for detecting disease activity requiring treatment. These results provide evidence for its use in integrated clinical care models.Trial RegistrationClinicalTrials.gov Identifier: NCT03893474

PURPOSE:The diagnostic performance of artificial intelligence (AI) in real-world settings remains uncertain, particularly across different fundus camera systems. This study evaluates the diagnostic accuracy of three AI algorithms for diabetic retinopathy (DR) detection using two nonmydriatic fundus cameras, assessing image gradability and DR severity. METHODS:A prospective diagnostic accuracy study was conducted at a primary health center, Khijrabad, Punjab, India (March-July 2021). The study evaluated three commercially available artificial intelligence algorithms for DR detection using two nonmydriatic fundus cameras. Participants underwent two-field, nonmydriatic fundus imaging with both cameras. Image quality and DR presence were independently assessed by masked human graders, including optometrists and a retina specialist. Diagnostic performance was measured using sensitivity, specificity, and positive and negative predictive values. RESULTS:A total of 272 images from 136 participants (mean age 67.7 years; 62% female) were analyzed. Human graders classified more than 97% of images as gradable, with DR detected in 47% of the images. AI-1 demonstrated the highest sensitivity (Forus: 97.5% (0.956-0.994); Intuvision: 81.7% (0.768-0.867)) but comparatively low specificity: 62.7% (58.6-66.8) and 53.8% (0.474-0.602). AI-2 displayed a balanced performance (sensitivity 80.0% and 77.0%; specificity 95.7% and 92.0%). AI-3 had a moderate sensitivity (73-80%) with the specificity ranging from 82% to 86%. CONCLUSION:AI performance varied across camera platforms, highlighting the need for context-specific validation to ensure safe integration into primary care and guide DR screening guidelines.

Diabetic retinopathy (DR) is a leading cause of preventable vision loss. While DR screening is critical, evidence on the reach and implementation of different screening models in primary healthcare settings is limited. This study evaluated the reach and implementation of DRS models in northern India using the RE-AIM framework. A pragmatic three-arm observational study was conducted between February 2023 and January 2024 in Block Boothgarh, a rural block in District Mohali, Punjab, comprising 30 villages with an estimated 120,000 residents. Household line listing was performed to identify individuals aged 30 years or older with diabetes. Participants (n = 600) were equally allocated to three screening models: facility-based screening at Health and Wellness Centres (HWC) by non-ophthalmologists, community-based AI-assisted screening at home, and standard care. Reach and implementation were assessed through quantitative data, field observations, and qualitative interviews with healthcare providers. Refusal for screening was higher in facility-based screening (40%, 135/340) and lower in community-based screening (13%, 31/240). Older individuals were more likely to decline participation, with a mean age of 62.0 years for males and 60.3 years for females. Reported barriers included existing medical conditions, mobility limitations, perceived good eye health, travel distance, and transportation difficulties. Concerns regarding long-term medication adherence also reduced uptake. Technical issues, including power outages, hardware or software malfunctions, suboptimal image quality, and lack of cooperation, further declined implementation. Adaptations, including the use of backup power generators, on-site troubleshooting, and provision of transport support, mitigated these barriers and improved overall implementation fidelity. Assessing reach is essential for the success of public health interventions. Using the RE-AIM framework, this study identified key barriers and adaptive strategies in DRS, enhancing both reach and implementation within primary healthcare settings. These findings can inform the integration of DRS models into comparable resource-constrained contexts, thereby improving overall effectiveness. Clinical Trial Registry of India (CTRI): 2022/10/046283.

Background Diabetic retinopathy (DR) is a leading cause of blindness globally. DR has increasingly affected both individuals and health care systems as the population ages. Objective This study aims to explore factors and identify barriers associated with nonadherence to referral recommendations among older adult participants after DR screening (DRS) during the COVID-19 pandemic. Method This paper presents findings from a pilot study on artificial intelligence–enabled DRS conducted in two districts in Punjab, India (Moga and Mohali) during the COVID-19 pandemic. The screenings were conducted from March to June 2022 at community health center Badhani Kalan in Moga and from March to June 2021 in community settings (homes) in Block Boothgarh, Mohali. Participants were referred to the district hospital for an ophthalmological review based on artificial intelligence–enabled screening. After 1 month, the participants were contacted by telephone to assess adherence to the referral recommendations. Participants who did not adhere to the referral were then interviewed alongside health care providers to understand the barriers explaining their nonadherence. Results We aimed to recruit 346 and 600 older adult participants from 2 sites but enrolled 390. Key challenges included health facility closures due to COVID-19, low motivation among health personnel for recruitment, incomplete nonparticipation data, and high participant workloads. Approximately 45% of the participants were male and 55% female. Most participants (62.6%) were between 60 and 69 years old, while 37.4% were 70 or older, with a mean age of 67.2 (SD 6.2) years. In total, 159 participants (40.8%) were referred, while 231 participants (59.2%) were not. Only 23 (14.5%) of those referred followed through and visited a health facility for ophthalmological review, while 136 (85.5%) did not pursue further evaluation. Our analysis revealed no significant differences in the characteristics between adherent and nonadherent participants, suggesting that demographic and health factors alone do not predict adherence behavior in patients with DR. Interviews identified limited knowledge about DR, logistical challenges, financial constraints, and attitudinal barriers as the primary challenges. Conclusions This study, conducted during the COVID-19 pandemic, showed suboptimal adherence to referral recommendations among older adult patients due to knowledge gaps, logistical challenges, and health system issues. Quantifying and understanding adherence factors are crucial for targeted interventions addressing barriers to referral recommendations after DRS. Integrating teleophthalmology into and strengthening infrastructure for artificial intelligence–enabled diabetic retinopathy screening to enhance access and outcomes.

Background Artificial intelligence (AI) algorithms offer an effective solution to alleviate the burden of diabetic retinopathy (DR) screening in public health settings. However, there are challenges in translating diagnostic performance and its application when deployed in real-world conditions. Objective This study aimed to assess the technical feasibility of integration and diagnostic performance of validated DR screening (DRS) AI algorithms in real-world outpatient public health settings. Methods Prior to integrating an AI algorithm for DR screening, the study involved several steps: (1) Five AI companies, including four from India and one international company, were invited to evaluate their diagnostic performance using low-cost nonmydriatic fundus cameras in public health settings; (2) The AI algorithms were prospectively validated on fundus images from 250 people with diabetes mellitus, captured by a trained optometrist in public health settings in Chandigarh Tricity in North India. The performance evaluation used diagnostic metrics, including sensitivity, specificity, and accuracy, compared to human grader assessments; (3) The AI algorithm with better diagnostic performance was integrated into a low-cost screening camera deployed at a community health center (CHC) in the Moga district of Punjab, India. For AI algorithm analysis, a trained health system optometrist captured nonmydriatic images of 343 patients. Results Three web-based AI screening companies agreed to participate, while one declined and one chose to withdraw due to low specificity identified during the interim analysis. The three AI algorithms demonstrated variable diagnostic performance, with sensitivity (60%-80%) and specificity (14%-96%). Upon integration, the better-performing algorithm AI-3 (sensitivity: 68%, specificity: 96, and accuracy: 88·43%) demonstrated high sensitivity of image gradability (99.5%), DR detection (99.6%), and referral DR (79%) at the CHC. Conclusions This study highlights the importance of systematic AI validation for responsible clinical integration, demonstrating the potential of DRS to improve health care access in resource-limited public health settings.

Restricted and repetitive behaviours vary greatly between autistic people. Some are a source of pleasure or create opportunities for learning; others may be detrimental in day-to-day life or cause harm. We have developed, in close collaboration with parents/carers, the Understanding Repetitive Behaviours programme, designed for families of young autistic children, to help them recognise, understand and respond sensitively to their child's impactful restricted and repetitive behaviours. This study is a clinical and cost-effectiveness, multi-site randomised controlled trial of the Understanding Repetitive Behaviours parent programme versus a psychoeducation programme (equivalent to current best practice), learning about autism. Participants were parents/carers, with an autistic child aged between 3-9 years and 11 months. The study was delivered across three sites in England and Scotland. Analyses were completed using intention-to-treat principles. Two hundred and twenty seven families were randomised (113 in LAA; 114 in Understanding Repetitive Behaviours arm). No differences were found between the arms on the primary outcome measure (The Clinical Global Impression - Improvement scale). Analysis of secondary outcomes indicated that children in the Understanding Repetitive Behaviours arm were more likely to be rated as responders in target impactful restricted and repetitive behaviours at 24 weeks but that this effect was not maintained at 52 weeks. Improvements in parent and family functioning were apparent, with no evidence of differences between the arms. The study reconfirms that it is important that clinicians consider both restricted and repetitive behaviours and social communication needs of autistic children with parents when planning appropriate support.Lay abstractAutistic children, frequently repeat the same behaviours over and over, have specific interests or like things to stay the same. These behaviours and interests are often fun and helpful. However, sometimes they can impact negatively on day-to-day life or put the child at risk of harm. Working closely with parents of autistic children, we developed an 8-week programme (Understanding Repetitive Behaviours) to help them recognise and understand these behaviours. This study aimed to find out whether the understanding repetitive behaviour programme was helpful and good value for money. Two hundred and twenty seven families were allocated by chance to receive either Understanding Repetitive Behaviours or a learning about autism programme. When experts made judgements about whether children showed positive changes across various measures, and these were analysed, there were no differences between the programmes. However, parents who attended the Understanding Repetitive Behaviours programme reported improvement in one of their child's specific repetitive behaviour (selected to be the main focus of the Understanding Repetitive Behaviours programme) at 24 weeks after the end of the programme. Parents who attended either programme reported more confidence, greater wellbeing and less stress up to 1 year after the end of the study.

[This corrects the article DOI: 10.1016/j.eclinm.2024.102662.].

Background:Suicide prevention is a national priority for United Kingdom government policy, and autistic people have recently been identified as a high-risk group in both the Department of Health and Social Care suicide prevention strategy and National Institute for Health and Care Excellence suicide prevention guidelines. No suicide prevention interventions have been developed specifically for autistic people. Safety plans are a simple, cost-effective, potentially life-saving intervention. Aims:To evaluate the feasibility and acceptability of the use of Autism Adapted Safety Plans for autistic adults and to undertake an external pilot to explore whether a larger future definitive trial is achievable. Methods:Stage 1 involved focus groups with autistic adults (n = 15), family members (n = 5) and service providers (n = 10) to inform adaptations to the Autism Adapted Safety Plans. Stage 2 was an interventional single-arm feasibility trial where autistic adults (n = 8) completed an Autism Adapted Safety Plans with a supporter (n = 8). Data on recruitment, completion of study measures and participant feedback informed final adaptations to the Autism Adapted Safety Plans and research methods prior to stage 3. Stage 3 was a pilot feasibility randomised controlled trial of Autism Adapted Safety Plans. Autistic adults were recruited via non-National Health Service organisations and self-referral. Participants were randomised without stratification to usual care ± Autism Adapted Safety Plans. The Autism Adapted Safety Plan was completed by the autistic adults with someone trained to support them. Research staff completing follow-up assessments were blind to participant allocation. Primary outcomes were feasibility and acceptability of the Autism Adapted Safety Plans to inform the parameters of a definitive randomised controlled trial. Participants were assessed at baseline, 1 and 6 months. Results:Stage 1 and 2 interviews highlighted the conditions needed to make the process of creating the Autism Adapted Safety Plans acceptable for autistic adults. Stage 2 also informed modifications to recruitment (to include self-referral) in stage 3. In stage 3, 53 participants consented, 49 were randomised to either Autism Adapted Safety Plans + usual care (n = 25) or usual care (n = 24). Sixty-eight per cent of participants were satisfied with the Autism Adapted Safety Plans and 41% rated it as usable. Feedback on the Autism Adapted Safety Plans and study processes employed in the trial were positive with suggested minor adaptations to some outcome measures. Retention of those randomised was 95% at 6-month follow-up. Completion rates for outcome measures were generally high (> 85%). Fidelity ratings for delivery of the Autism Adapted Safety Plans were 94% for therapeutic components and 91% for adherence to content. Conclusion:Autism Adapted Safety Plans are a potentially valuable intervention for autistic adults, provided that the process of creating it is flexible and sensitive to individual needs. The parameters of a future definitive trial of the clinical and cost-effectiveness of Autism Adapted Safety Plans are achievable, with minor recommended adaptations. Further testing of the Autism Adapted Safety Plans to assess its clinical and cost-effectiveness in National Health Service clinical services is urgently needed. Limitations:The sample size was below the initially intended sample of 70 participants due to difficulties with recruitment during the COVID-19 pandemic. As autistic participants self-referred into the study, data are not available regarding how many participants were approached to take part in the study. The majority of the study sample was White. Future work:A full definitive trial testing the clinical and cost-effectiveness of Autism Adapted Safety Plans in National Health Service clinical services is warranted. This fully powered trial will need to recruit a more diverse sample than was possible in the pilot trial. Results suggest that minor adaptations to the Autism Adapted Safety Plans could make this more personalised and accessible, such as through an app or website. Funding:This synopsis presents independent research funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme as award number NIHR129196.

50-80% of all glioma patients will have seizures. Guidelines recommend against prophylactic anti-seizure medication, but levetiracetam is frequently prescribed. Our aim was to determine the effectiveness of 12-months prophylactic levetiracetam at reducing seizure risk. Seizure-naïve patients undergoing glioma surgery were randomised (1:1) to 12-months levetiracetam or no prophylaxis and followed until death or maximum 18-months. The primary outcome was one-year risk of first seizure. Patients who died within 12-months of randomisation without experiencing a seizure were excluded from the primary outcome analysis. Target accrual was 804 participants. The trial was registered ( ISRCTN 49474281 and EudraCT 2018-001312-30). Between Oct 10, 2019 and Aug 30, 2022, 96 patients, from 24 to 79 years of age, were randomised to levetiracetam (n=49) or no prophylaxis (n=47). The trial closed early due to slow accrual and the Covid pandemic. In the levetiracetam group 17 patients had a seizure and 32 did not (19 survived ≥ 12-months, 13 died within 12-months). In the no prophylaxis group 15 patients had a seizure and 30 did not (21 survived ≥12-months, 9 died within 12-months). Seventeen of the 36 evaluable levetiracetam patients (47%) had a seizure, compared with 15 of 36 evaluable no prophylaxis patients (41%) (OR 1.25, 95%CI 0.49-3.21, p=0.64). There were no levetiracetam related serious adverse events. The SPRING trial provides no evidence of a difference between levetiracetam and no prophylaxis in the 12-month seizure risk in patients undergoing glioma surgery, but the study was underpowered. The role of prophylactic anti-seizure medication remains undefined.