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The affective pathway to psychosis implicates affective symptoms and neuroticism as mediating steps between childhood trauma and symptoms of schizophrenia. Prior research seldom examined the interplay between childhood trauma, resilience, personality, social functioning and symptoms in schizophrenia patients. This study recruited 290 schizophrenia patients, and constructed a regularized partial correlation network of childhood trauma, resilience, big-five personality traits, symptoms and social functioning. We further applied flow diagram and shortest path analysis to clarify how different childhood trauma types would contribute to and reach different symptoms. In the network, emotional and physical abuse showed the highest expected influence, and resilience showed the highest strength. In flow diagrams, all nodes together contributed two-thirds of variance of social functioning (which had highest predictability). Among childhood trauma types, emotional abuse contributed most to positive symptoms; physical neglect contributed most to negative, depressive and disorganized symptoms. Childhood abuse reached positive symptoms via neuroticism and depressive symptoms, yet it reached negative symptoms via physical neglect and social functioning. Childhood neglect reached positive symptoms via resilience, conscientiousness, neuroticism and depressive symptoms, yet it reached negative symptoms via social functioning. Our findings support that different childhood trauma types contribute to different symptoms, and interacts with resilience, personality and social functioning., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Introduction: The equity-focused ILANA study evaluated feasibility, acceptability, appropriateness of delivering on-label two-monthly cabotegravir and rilpivirine (CAB+RPV) injections for HIV-1 therapy in clinics and community settings., Methods: The study, which mandated inclusive recruitment, was conducted May-December 2022 at six UK sites. Injections were delivered in clinic (months 1-6), and in clinic or community setting according to patient choice (months 6-12). Surveys were completed at baseline, M4 and M12 using validated measures for feasibility (FIM), acceptability (AIM), and appropriateness (IAM). Primary endpoint: proportion of participants agreeing that the injection and community setting were feasible (FIM>4) at M12. Fourteen participants completed interviews at baseline and M12., Results: Community settings offered by sites included: home visits (n=3), HIV support organisations (n=2), community clinic (n=1). Of 114 participants,54% were female, 70% racially minoritised and 40% aged >50. 27/114 chose to receive injections in community settings. FIM/AIM/IAM scores at M12 were high for the injection (79.0-87.4%) and lower for the community setting (44.2-47.4%) overall. Subgroup analyses indicated differences in scores by gender and ethnicity. Among those who attended the community, FIM/AIM/IAM scores for the community setting at M12 were high (73.1-80.8%). Concerns about stigma, inconvenience, and losing access to trusted clinicians negatively influenced perceptions of receiving injections at community settings, amongst other factors., Conclusion: CAB+RPV injections were considered highly feasible, acceptable, and appropriate, however few chose community delivery. Those that chose community delivery found it highly acceptable and feasible. Further exploration of CAB+RPV delivery in alternative community sites not offered (e.g. primary care or pharmacies) is warranted., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Aims: To develop and externally test deep learning (DL) models for assessing the image quality of three-dimensional (3D) macular scans from Cirrus and Spectralis optical coherence tomography devices., Methods: We retrospectively collected two data sets including 2277 Cirrus 3D scans and 1557 Spectralis 3D scans, respectively, for training (70%), fine-tuning (10%) and internal validation (20%) from electronic medical and research records at The Chinese University of Hong Kong Eye Centre and the Hong Kong Eye Hospital. Scans with various eye diseases (eg, diabetic macular oedema, age-related macular degeneration, polypoidal choroidal vasculopathy and pathological myopia), and scans of normal eyes from adults and children were included. Two graders labelled each 3D scan as gradable or ungradable, according to standardised criteria. We used a 3D version of the residual network (ResNet)-18 for Cirrus 3D scans and a multiple-instance learning pipline with ResNet-18 for Spectralis 3D scans. Two deep learning (DL) models were further tested via three unseen Cirrus data sets from Singapore and five unseen Spectralis data sets from India, Australia and Hong Kong, respectively., Results: In the internal validation, the models achieved the area under curves (AUCs) of 0.930 (0.885-0.976) and 0.906 (0.863-0.948) for assessing the Cirrus 3D scans and Spectralis 3D scans, respectively. In the external testing, the models showed robust performance with AUCs ranging from 0.832 (0.730-0.934) to 0.930 (0.906-0.953) and 0.891 (0.836-0.945) to 0.962 (0.918-1.000), respectively., Conclusions: Our models could be used for filtering out ungradable 3D scans and further incorporated with a disease-detection DL model, allowing a fully automated eye disease detection workflow., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: Limited research has directly compared the effectiveness of aqua- and land-based exercises for postexercise recovery. This study aimed to fill this gap by comparing the effects of these 2 types of exercises on postexercise recovery., Methods: Sixteen male college athletes participated in an 8-day experimental study. The initial 2 days were dedicated to determining the intensity levels for the muscle-damaging exercise and recovery jogging. In a crossover design, participants underwent 2 sets of experimental trials. They were randomly assigned to either an aqua or land recovery intervention for days 3 to 5, and after a 1-week washout period they switched to the opposite intervention for days 6 to 8. Muscle soreness, creatine kinase, anaerobic performance, countermovement-jump height, and flexibility were assessed at different time points: baseline, immediately after downhill running, within 1 hour after jogging, and 24 hours and 48 hours after aqua or land jogging., Results: Significant group × time interaction effects were detected in the perceived soreness of the hamstring and quadriceps. However, the post hoc analysis showed no significant difference between aqua and land jogging groups. No significant group × time interaction effect was observed in creatine kinase, anaerobic performance, countermovement-jump height, or flexibility., Conclusion: Aqua and land jogging have similar recovery effects on muscle soreness and performance-based parameters.

Background: Time-resolved magnetic resonance fingerprinting (MRF), or 4D-MRF, has been demonstrated its feasibility in motion management in radiotherapy (RT). However, the prohibitive long acquisition time is one of challenges of the clinical implementation of 4D-MRF. The shortening of acquisition time causes data insufficiency in each respiratory phase, leading to poor accuracies and consistencies of the predicted tissues' properties of each phase., Purpose: To develop a technique for the reconstruction of multi-phase parametric maps in four-dimensional magnetic resonance fingerprinting (4D-MRF) through the optimization of local T1 and T2 sensitivities., Methods: The proposed technique employed an iterative optimization to tailor the data arrangement of each phase by manipulation of inter-phase frames, such that the T1 and T2 sensitivities, which were quantified by the modified Minkowski distance, of the truncated signal evolution curve was maximized. The multi-phase signal evolution curves were modified by sliding window reconstruction and inter-phase frame sharing (SWIFS). Motion correction (MC) and dot product matching were sequentially performed on the modified signal evolution and dictionary to reconstruct the multi-parametric maps. The proposed technique was evaluated by numerical simulations using the extended cardiac-torso (XCAT) phantom with regular and irregular breathing patterns, and by in vivo MRF data of three health volunteers and six liver cancer patients acquired at a 3.0 T scanner., Results: In simulation study, the proposed SWIFS approach achieved the overall mean absolute percentage error (MAPE) of 8.62% ± 1.59% and 16.2% ± 3.88% for the eight-phases T1 and T2 maps, respectively, in the sagittal view with irregular breathing patterns. In contrast, the overall MAPE of T1 and T2 maps generated by the conventional approach with multiple MRF repetitions were 22.1% ± 11.0% and 30.8% ± 14.9%, respectively. For in-vivo study, the predicted mean T1 and T2 of liver by the proposed SWIFS approach were 795 ms ± 38.9 ms and 58.3 ms ± 11.7 ms, respectively., Conclusions: Both simulation and in vivo results showed that the approach empowered by T1 and T2 sensitivities optimization and sliding window under the shortened acquisition of MRF had superior performance in the estimation of multi-phase T1 and T2 maps as compared to the conventional approach with oversampling of MRF data., (© 2024 American Association of Physicists in Medicine.)

Large language models (LLMs) underlie remarkable recent advanced in natural language processing, and they are beginning to be applied in clinical contexts. We aimed to evaluate the clinical potential of state-of-the-art LLMs in ophthalmology using a more robust benchmark than raw examination scores. We trialled GPT-3.5 and GPT-4 on 347 ophthalmology questions before GPT-3.5, GPT-4, PaLM 2, LLaMA, expert ophthalmologists, and doctors in training were trialled on a mock examination of 87 questions. Performance was analysed with respect to question subject and type (first order recall and higher order reasoning). Masked ophthalmologists graded the accuracy, relevance, and overall preference of GPT-3.5 and GPT-4 responses to the same questions. The performance of GPT-4 (69%) was superior to GPT-3.5 (48%), LLaMA (32%), and PaLM 2 (56%). GPT-4 compared favourably with expert ophthalmologists (median 76%, range 64-90%), ophthalmology trainees (median 59%, range 57-63%), and unspecialised junior doctors (median 43%, range 41-44%). Low agreement between LLMs and doctors reflected idiosyncratic differences in knowledge and reasoning with overall consistency across subjects and types (p>0.05). All ophthalmologists preferred GPT-4 responses over GPT-3.5 and rated the accuracy and relevance of GPT-4 as higher (p<0.05). LLMs are approaching expert-level knowledge and reasoning skills in ophthalmology. In view of the comparable or superior performance to trainee-grade ophthalmologists and unspecialised junior doctors, state-of-the-art LLMs such as GPT-4 may provide useful medical advice and assistance where access to expert ophthalmologists is limited. Clinical benchmarks provide useful assays of LLM capabilities in healthcare before clinical trials can be designed and conducted., Competing Interests: AM is a member of the Panel of Examiners of the Royal College of Ophthalmologists and performs unpaid work as an FRCOphth examiner. DSWT holds a patent on a deep learning system to detect retinal disease. DSJT authored the book used in the study and receives royalty from its sales. The other authors have no competing interests to declare., (Copyright: © 2024 Thirunavukarasu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Clinical practice guidelines on limitation of life-sustaining treatments (LST) in the intensive care unit (ICU), in the form of withholding or withdrawal of LST, state that there is no ethical difference between the two. Such statements are not uniformly accepted worldwide, and there are few studies on LST limitation in Asia. This study aimed to evaluate the predictors and outcomes of withholding and withdrawal of LST in Singapore, focusing on the similarities and differences between the two approaches., Methods: This was a multicentre observational study of patients admitted to 21 adult ICUs across 9 public hospitals in Singapore over an average of three months per year from 2014 to 2019. The primary outcome measures were withholding and withdrawal of LST (cardiopulmonary resuscitation, invasive mechanical ventilation, and vasopressors/inotropes). The secondary outcome measure was hospital mortality. Multivariable generalised mixed model analysis was used to identify independent predictors for withdrawal and withholding of LST and if LST limitation predicts hospital mortality., Results: There were 8907 patients and 9723 admissions. Of the former, 80.8% had no limitation of LST, 13.0% had LST withheld, and 6.2% had LST withdrawn. Common independent predictors for withholding and withdrawal were increasing age, absence of chronic kidney dialysis, greater dependence in activities of daily living, cardiopulmonary resuscitation before ICU admission, higher Acute Physiology and Chronic Health Evaluation (APACHE) II score, and higher level of care in the first 24 h of ICU admission. Additional predictors for withholding included being of Chinese race, the religions of Hinduism and Islam, malignancy, and chronic liver failure. The additional predictor for withdrawal was lower hospital paying class (with greater government subsidy for hospital bills). Hospital mortality in patients without LST limitation, with LST withholding, and with LST withdrawal was 10.6%, 82.1%, and 91.8%, respectively (p < 0.001). Withholding (odds ratio 13.822, 95% confidence interval 9.987-19.132) and withdrawal (odds ratio 38.319, 95% confidence interval 24.351-60.298) were both found to be independent predictors of hospital mortality on multivariable analysis., Conclusions: Differences in the independent predictors of withholding and withdrawal of LST exist. Even after accounting for baseline characteristics, both withholding and withdrawal of LST independently predict hospital mortality. Later mortality in patients who had LST withdrawn compared to withholding suggests that the decision to withdraw may be at the point when medical futility is recognised., (© 2024. The Author(s).)

Background: Cardiovascular disease is a leading cause of global death. Prospective population-based studies have found that changes in retinal microvasculature are associated with the development of coronary artery disease. Recently, artificial intelligence deep learning (DL) algorithms have been developed for the fully automated assessment of retinal vessel calibres., Methods: In this study, we validate the association between retinal vessel calibres measured by a DL system (Singapore I Vessel Assessment) and incident myocardial infarction (MI) and assess its incremental performance in discriminating patients with and without MI when added to risk prediction models, using a large UK Biobank cohort., Results: Retinal arteriolar narrowing was significantly associated with incident MI in both the age, gender and fellow calibre-adjusted (HR=1.67 (95% CI: 1.19 to 2.36)) and multivariable models (HR=1.64 (95% CI: 1.16 to 2.32)) adjusted for age, gender and other cardiovascular risk factors such as blood pressure, diabetes mellitus (DM) and cholesterol status. The area under the receiver operating characteristic curve increased from 0.738 to 0.745 (p=0.018) in the age-gender-adjusted model and from 0.782 to 0.787 (p=0.010) in the multivariable model. The continuous net reclassification improvements (NRIs) were significant in the age and gender-adjusted (NRI=21.56 (95% CI: 3.33 to 33.42)) and the multivariable models (NRI=18.35 (95% CI: 6.27 to 32.61)). In the subgroup analysis, similar associations between retinal arteriolar narrowing and incident MI were observed, particularly for men (HR=1.62 (95% CI: 1.07 to 2.46)), non-smokers (HR=1.65 (95% CI: 1.13 to 2.42)), patients without DM (HR=1.73 (95% CI: 1.19 to 2.51)) and hypertensive patients (HR=1.95 (95% CI: 1.30 to 2.93)) in the multivariable models., Conclusion: Our results support DL-based retinal vessel measurements as markers of incident MI in a predominantly Caucasian population., Competing Interests: Competing interests: CYC, DX, MLL and TYW are the coinventors of the SIVA-DLS system. TYW is an inventor, hold patents and is a cofounder of start-up companies EyRiS and Visre, which have interests in and develops digital solutions for eye diseases including diabetic retinopathy. In addition, personal consulting fees were made from the following companies: Aldropika Therapeutics, Bayer, Boehringer Ingelheim, Carl Zeiss, Genentech, Iveric Bio, Novartis, Oxurion, Plano, Roche, Sanofi and Shanghai Henlius., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Diabetic macular edema (DME) is the leading cause of vision loss in people with diabetes. Application of artificial intelligence (AI) in interpreting fundus photography (FP) and optical coherence tomography (OCT) images allows prompt detection and intervention., Purpose: To evaluate the performance of AI in detecting DME from FP or OCT images and identify potential factors affecting model performances., Data Sources: We searched seven electronic libraries up to 12 February 2023., Study Selection: We included studies using AI to detect DME from FP or OCT images., Data Extraction: We extracted study characteristics and performance parameters., Data Synthesis: Fifty-three studies were included in the meta-analysis. FP-based algorithms of 25 studies yielded pooled area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity of 0.964, 92.6%, and 91.1%, respectively. OCT-based algorithms of 28 studies yielded pooled AUROC, sensitivity, and specificity of 0.985, 95.9%, and 97.9%, respectively. Potential factors improving model performance included deep learning techniques, larger size, and more diversity in training data sets. Models demonstrated better performance when validated internally than externally, and those trained with multiple data sets showed better results upon external validation., Limitations: Analyses were limited by unstandardized algorithm outcomes and insufficient data in patient demographics, OCT volumetric scans, and external validation., Conclusions: This meta-analysis demonstrates satisfactory performance of AI in detecting DME from FP or OCT images. External validation is warranted for future studies to evaluate model generalizability. Further investigations may estimate optimal sample size, effect of class balance, patient demographics, and additional benefits of OCT volumetric scans., (© 2024 by the American Diabetes Association.)

Introduction: To evaluate eye growth of children wearing spectacle lenses with highly aspherical lenslets (HAL), slightly aspherical lenslets (SAL) and single-vision lenses (SVL) compared to eye growth patterns in non-myopes in Wenzhou, China., Methods: The randomised trial had 170 myopic children (aged 8-13 years) randomly assigned to the HAL, SAL or SVL group. Normal eye growth was examined using 700 non-myopic schoolchildren (aged 7-9 years) in the Wenzhou Medical University-Essilor Progression and Onset of Myopia (WEPrOM) cohort study using logistic function models. Slow, normal and fast eye growth was defined as range of values <25th, 25th-75th and >75th percentiles, respectively., Results: The predicted upper limits of slow eye growth (25th percentile) among non-myopes aged 7-10 years and 11-13 years were 0.20-0.13 and 0.08-0.01 mm (after 2-year period; 0.37-0.33 and 0.29-0.14 mm), respectively, while the upper limits of normal eye growth (75th percentile) were 0.32-0.31 and 0.28-0.10 mm (after 2-year period; 0.58-0.55 and 0.50-0.24 mm), respectively. The 2-year trial had 157 children, 96 of whom wore their lenses full time (everyday ≥12 h/day). The mean 2-year axial length change for HAL, SAL and SVL was 0.34, 0.51 and 0.69 mm (0.28, 0.46 and 0.69 mm in full-time wear), respectively. Slow eye growth was found in 35%, 17% and 2% (44%, 29% and 3% in full-time wear); normal eye growth in 35%, 26% and 12% (44%, 32% and 9% in full-time wear) and fast eye growth in 30%, 57% and 86% (12%, 39% and 88% in full-time wear), respectively (p < 0.001)., Conclusions: The eye growth pattern in approximately 90% wearing HAL full time (compared with about 10% wearing SVL full time) was similar or slower than that of non-myopic children both after 1- and 2-year periods., (© 2023 The Authors. Ophthalmic and Physiological Optics published by John Wiley & Sons Ltd on behalf of College of Optometrists.)