medRxiv : serveur de preprint pour les sciences médicales

Purpose: In this study, we analyzed correlations between 28-day mortality and hemodynamic changes, measured using polymyxin B-immobilized fiber column direct hemoperfusion initiation time, in patients with cancer with refractory septic shock. Materials and methods: We retrospectively analyzed 45 patients with cancer who received polymyxin B-immobilized fiber column direct hemoperfusion due to refractory septic shock. Patients were categorized into early (<12 h between refractory septic shock and initiation of polymyxin B-immobilized fiber column direct hemoperfusion) and late (>12 h) initiation groups. Changes in vasoactive inotrope scores, sequential organ failure assessment scores, and PaO2/FiO2 ratios before and 24 h after polymyxin B-immobilized fiber column direct hemoperfusion, were compared. Results: Univariable analysis showed that 28-day mortality risk was associated with diabetes mellitus (odds ratio=3.081; 95% confidence interval =1.290-7.360; p=0.011), lactic acid (odds ratio=1.010; 95% confidence interval =1.005-1.014; p<0.0001), and sequential organ failure assessment score (odds ratio=1.190; 95% confidence interval =1.044-1.357; p=0.009). Multivariable analysis showed that 28-day mortality risk was associated with diabetes mellitus (odds ratio=2.718; 95% confidence interval =1.013-7.291; p=0.047), early initiation (odds ratio=0.268; 95% confidence interval =0.094-0.765; p=0.014), and lactic acid (odds ratio=1.009; 95% confidence interval =1.004-1.014; p<0.0001). Overall survival was slightly higher in the early than in the late initiation group (p=0.0515). Comparisons of variables before and 24 h after polymyxin B-immobilized fiber column direct hemoperfusion revealed that vasoactive inotrope scores decreased in both the early and late groups ({Delta}318 vs. {Delta}114; p=0.001 and p=0.005, respectively), whereas the PaO2/FiO2 ratio slightly increased ({Delta}127.5 vs. {Delta}95.6; p=0.350 and p=0.390, respectively) over time. Conclusions: In patients with cancer with refractory septic shock, early initiation of polymyxin B-immobilized fiber column direct hemoperfusion reduced inotrope-vasopressor requirement and 28-day mortality.

Coronavirus infectious Disease 2019 (COVID-19) was first reported in Wuhan, China, and with its rapidly mutating variants, it soon became a global concern. In response to the pandemic, intensive research and development efforts led to the development of six vaccines approved by the World Health Organization (WHO). Coronavirus is divided into four genera: alpha, beta, gamma and delta. Its unstable ssRNA resulted in multiple strains in a short period, which acted as a selection pressure for transmissibility. Sequelae of COVID-19 infection include multiple syndromes which have been reported at high incidence globally. Using the Cochrane guidelines and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), we present a systematic review of the most common syndromes reported. A total of 12 eligible studies were included in this review. Syndromes reported in the literature include immune thrombocytopenic purpura (ITP), viral encephalomyelitis, hemophagocytic lymphohistiocytosis, thrombotic thrombocytopenic purpura (TTP), Guillain-Barre syndrome (GBS) and postural orthostatic tachycardia syndrome (POTS). We cover the hypothesized pathophysiology, presenting symptoms and treatment for each respective syndrome. We aim to discuss coronavirus and its variants to provide a foundation on which to examine the syndromes manifested after COVID-19 infection (post-COVID-19 syndrome).

A fundamental question of any program focused on the testing and timely diagnosis of a communicable disease is its effectiveness in reducing community transmission. Unfortunately, direct estimation of this effectiveness is difficult in practice, elevating the value of mathematical modeling that can predict it from first principles. Here, we introduce testing effectiveness (TE), defined as the fraction by which transmission is reduced via testing and post-diagnosis isolation at the population scale, and develop a mathematical model that estimates it from the interactions of tests, within-host pathogen dynamics, and arbitrarily complex testing behaviors. While our model generalizes across pathogens, we demonstrate its flexibility through an analysis of three respiratory pathogens, influenza A, respiratory syncytial virus (RSV), and both pre-vaccine and post-vaccine era SARS-CoV-2, quantifying TE across post-exposure, post-symptom, and routine testing scenarios. We show that TE varies considerably by strategy and pathogen, with optimal testing depending on the number of tests available and when they are used. This work quantifies tradeoffs about when and how to test, providing a flexible framework to guide the use and development of current and future diagnostic tests to control transmission of infectious diseases.

Background: Despite the reported increased antenatal care (ANC) utilization in Ethiopia, large numbers of women give birth at home without skilled personnel attendance, even after attending an adequate antenatal care schedule (>= four antenatal visits) as recommended by the World Health Organization (WHO). This study aimed to assess individual and community-level factors associated with home delivery after adequate antenatal care visits in Ethiopia. Methods: We analyzed the 2019 Ethiopian mini demographic and health survey data. A total weighted sample of 1,643 women who had full antenatal care visits for their last childbirth/index birth was included in the analysis. Model comparison was done by using intra-cluster correlation, median odds ratio, and proportional change in variance. A multivariable multilevel logistic regression analysis was conducted to identify the effect of individual and community-level factors on the outcome variable (home delivery). Adjusted odds ratios (AOR), along with a 95% confidence interval (CI) were used to estimate the strength of the associations. Results: The intra cluster correlation (ICC) in the null model was 59%, showing that there was a significant difference in the prevalence of home delivery after adequate antenatal care at the community level, and the variability declined to 36.5% in the final model. Therefore, multilevel logistic regression model was utilized. At individual-level, secondary educational level was negatively associated with home delivery [AOR = 0.37; 95%CI: (0.17, 0.80)], and having a household of >= 5 members [AOR = 1.70; 95%CI: (1.09, 2.66)], poorest (vs. richest) wealth index [AOR = 6.98; 95%CI (2.89, 16.83)], poorer (vs. richest) wealth index [AOR = 2.77, 95%CI :(1.19,6.45)], and 2-3 birth order [AOR = 2.48; 95% CI(1.45, 4.21)] were associated with home delivery after attending the required adequate ANC visits. Community-level variables associated with home delivery after full antenatal care visits included: poor communities [AOR = 2.13; 95%CI (1.03, 4.40)], and living in a rural area [AOR = 2.74; 95%CI (1.19, 6.30)]. Conclusion: The findings of the current study indicate that in women who had the required number of ANC visits, having a larger household and poorest and poorer (vs. rich) wealth index, being the 2nd or 3rd birth, residing in a rural area, and living in poor communities were predictors of home delivery. Having a secondary education was supportive, against delivering at home. Strategies to improve households socioeconomic empowerment were recommended.

Background Distinguishing diseases into distinct subtypes is crucial for study, effective treatment, and the discovery of potential cures. The Open Targets Platform integrates biomedical, genetic, and biochemical datasets with the goal of empowering disease ontologies and gene targets. However, many disease annotations remain incomplete, necessitating laborious expert medical input. This is particularly painful for rare and orphan diseases, where resources are limited. Results We present a machine learning approach to identifying diseases with potential subtypes, using the approximately 23,000 diseases documented in Open Targets. We derive and describe novel features for predicting diseases with subtypes, using direct evidence. Machine learning models were applied to analyze feature importance and evaluate predictive performance for discovering known subtypes. Our model achieves a high (89.1%) ROCAUC. We integrated pre-trained deep learning language models and showed their benefits. Furthermore, we identify 515 disease candidates predicted to possess previously unannotated subtypes. Conclusions Our models can partition diseases into distinct subtypes. This methodology enables a robust, scalable approach for improving knowledge-based annotations and a comprehensive assessment of disease ontology tiers. Our candidates are attractive targets for further study and personalized medicine, potentially aiding in the unveiling of new therapeutic indications for sought-after targets.

Computer-aided systems can help the ophthalmologists in early detection of most of ocular abnormalities using retinal OCT images. The need for more accurate diagnosis increases the need for modifications and innovations to current algorithms. In this paper, we investigate the effect of different X-lets on the classification of OCT B-scans of a dataset with one normal class and two abnormal classes. Different transforms of each B-scan have been fed to the designed 2D-Convolutional-Neural-Network (2D-CNN) to extract the best-suited features. We compare the performance of them with MSVM and MLP classifiers. Comparison with the accuracy of normal and abnormal classes reveals substantially better results for normal cases using 2D-Discrete-Wavelet-Transform (2D-DWT), since the structure of most normal B-scans follows a pattern with zero-degree lines, while for abnormalities with circles appearing in the retinal structure (due to the accumulation of fluid), the circlet transform performs much better. Therefore, we combine these two X-lets and propose a new transform named CircWave which uses all sub-bands of both transformations in the form of a multi-channel-matrix, with the aim to increase the classification accuracy of normal and abnormal cases, simultaneously. We show that the classification results obtained based on CircWave transform outperform those based on the original images and each individual transform. Furthermore, the Grad-CAM class activation visualization for B-scans reconstructed from half of the CircWave sub-bands indicates a greater focus on appearing circles in abnormal cases and straight lines in normal cases at the same time, while for original B-scans the focus of the heat-map is on some irrelevant regions. To investigate the generalizability of our proposed method we have applied it also to another dataset. Using the CircWave transform, we have obtained an accuracy of 94.5% and 90% for the first and second dataset, respectively, while these values were 88% and 83% using the original images. The proposed CNN based on CircWave provides not only superior evaluation parameter values but also better interpretable results with more focus on features that are important for ophthalmologists.

Importance: The impact of antibiotics (ATBs) on the risk of colorectal cancer (CRC) recurrence after curative resection remains unknown. Objective: We aimed to evaluate the effect of the type and the class of ATBs on recurrence in patients with resected non-metastatic CRC. Design: Our cohort study included patients between 01/2012 and 12/2014. Each CRC patient was followed up to 3 years after surgical resection. Setting: This study was conducted using extracted data from the French cancer cohort set up based on the National Health Data System by the French National Cancer Institute. Participants: All newly diagnosed non-metastatic CRC patients resected were included. We excluded patients not affiliated to the major health insurance scheme in France (n=16 857) and with immunosuppression (n=32,359). Exposures: The perioperative ATB intake (from 6 months before surgery until 1 year after) was classified according to the class, the period of use (pre- vs post-resection), the disease stage (localized and locally advanced), and the primary tumor location (colon and rectum/junction). Main Outcome and Measure: The primary endpoint was the 3-year disease-free survival (DFS). The impact of ATB was assessed using time-dependent multivariate Cox models. Results: A total of 35,496 CRC patients were included. Seventy-nine percent of patients had at least one ATB intake. Outpatient ATB intake after surgery was associated with unfavorable 3-year DFS mostly in patients with locally advanced stage and during chemotherapy (HR ranging from 1.22 to 1.41, P<0.0001), while no excess of mortality was observed in patients receiving ATBs as outpatient. The ATBs associated with decreased 3-year DFS were cephalosporins, streptogramins, quinolones, penicillin A with beta-lactamase inhibitors, and antifungals with differential effects according to the primary tumor location and disease stage. Conclusion and Relevance: These findings suggest that ATBs modulate the risk of recurrence after early CRC resection with a differential impact of the ATB classes depending on disease stage and tumor site. This study also gives important clues on how ATBs may modulate the efficacy of cancer treatments. Ultimately, EVADER-1 will pave the way for therapeutic interventions targeting the microbiome aiming to improve cancer outcome.

Introduction: A key Sustainable Development Goal target is to eliminate all forms of malnutrition. Existing evidence suggests children with disabilities are at greater risks of malnutrition, exclusion from nutrition programmes, and mortality from severe acute malnutrition than children without disabilities. However, there is limited evidence on the nutritional outcomes of children with disabilities in large-scale global health surveys. Methods: We analysed Multiple Indicator Cluster Survey (MICS) data from 30 low and middle-income countries (LMICs) to compare nutritional outcomes for children aged 2 to 4 years with and without disabilities. We estimated the adjusted prevalence ratios for stunting, wasting, and underweight comparing children with and without disabilities by country and sex, using quasi-Poisson models with robust standard errors. We accounted for the complex survey design, wealth quintile, location, and age in the analyses. We meta-analysed these results to create an overall estimate for each of these outcomes. Results: Our analyses included 229,621 children aged 2-4 across 30 countries, including 15,071 children with disabilities (6.6%). Overall, children with disabilities were more likely to be stunted (aRR: 1.16, 95% C.I.: 1.11, 1.20), wasted (aRR: 1.28, 95% C.I.: 1.18, 1.39), and underweight (aRR: 1.33, 95% C.I.: 1.17, 1.51) than children without disabilities. These patterns were observed in both girls and boys with disabilities, compared to those without. Conclusion: Children with disabilities are significantly more likely to experience all forms of malnutrition, making it critical to accelerate efforts to improve disability-inclusion within nutrition programmes. Ending all forms of malnutrition will not be achievable without a focus on disability.

Cognitive impairment (CI) is one of the most prominent non-motor symptoms in Parkinson's disease (PD). How brain network abnormalities contribute to CI in PD patients remain largely unclear. The goal of this study is to explore whether aberrations of brain network topology were causally associated with cognitive decline in PD patients. PD patients receiving magnetic resonance imaging from Parkinson's Progression Markers Initiative (PPMI) database were specifically selected. According to the scores of Montreal Cognitive Assessment (MoCA), PD patients were classified into CI+ group (MoCA score [≤] 25) and CI- group (MoCA score > 25) to investigate whether clinical features and brain networks were significantly different between two groups. Mediation analysis was utilized to evaluate whether brain network alterations contributed to CI in PD patients. We revealed CI + group exhibited more severe non-motor symptoms compared to CI- group. In addition, age, excessive daytime sleepiness, and depressive symptoms were found to be significantly associated with CI of PD patients. Moreover, CI+ group exhibited statistically different local topological properties in structural network compared to CI- group. Furthermore, differential local topological metrics in structural network meditated the effects of age, excessive daytime sleepiness, and depression on cognitive decline of PD patients. Taken together, out study suggested that PD patients with CI exhibited notable disturbances of structural network topology, which mediated negative associations between of age, excessive daytime sleepiness, depression and cognitive decline of PD patients.

Rare kidney diseases are not well characterised, despite making a significant contribution to the burden of kidney disease globally. The National Registry of Rare Kidney Diseases (RaDaR) collects longitudinal disease and treatment related data from people living with rare kidney diseases across the UK, and is the largest rare kidney disease registry in the world. We present the clinical demographics and renal function of 25,880 prevalent patients and evaluate for any potential recruitment bias to RaDaR. RaDaR recruits patients from 108 UK hospitals and is linked with the UK Renal Registry (UKRR, with which all UK patients receiving Kidney Replacement Therapy (KRT) are registered). To assess for recruitment bias to RaDaR we performed three comparisons of ethnicity and socioeconomic status: 1) All prevalent RaDaR patients receiving KRT were compared with patients with eligible rare disease diagnoses receiving KRT in the UKRR 2) Patients recruited to RaDaR and all eligible unrecruited patients at two renal centres were compared 3) The age-stratified ethnicity distribution RaDaR patients with Autosomal Dominant Polycystic Kidney Disease (ADPKD) was compared with the English Census. We observed over-representation of individuals reporting South Asian ethnicity in some rare diseases (most markedly Cystinosis and Primary Hyperoxaluria). We found no evidence of systematic bias in recruitment to RaDaR in terms of ethnicity or social deprivation. Predominant rare kidney diseases in adults ([≥]18 years) were ADPKD (29.2%), Vasculitis (15.8%) and IgA nephropathy (15.7%), compared to Idiopathic nephrotic syndrome (43.6%), Vasculitis (10.8%) and Alport Syndrome (5.9%) in children (<18 years). Compared with either adults recruited to RaDaR or the general UK population, children recruited to RaDaR were more likely to be of Asian ethnicity and live in more socially deprived areas.

Background: Limited data are available regarding factors associated with initiation of treatment and treatment outcomes after diagnosis of non-tuberculous mycobacteria (NTM) pulmonary infection and disease. Objective: To investigate trends of NTM pulmonary infections, patient characteristics and factors associated with initiation of treatment and treatment outcomes in patients with NTM pulmonary infection and disease. Methods: We evaluated 154 patients with NTM pulmonary infection, identified by having at least one record coded with ICD-10 A31.0 at Haukeland University Hospital in Bergen, Norway, from 2000 to 2021. A univariate and multivariate binary logistic regression was carried out to find the odds of factors associated with the initiation of treatment and treatment outcomes. Results: 70% of the patients were older than 65 years. 49 % of patients had pulmonary comorbidity and the three most common symptoms were cough, dyspnoea, and weight loss. The most frequently observed mycobacterial species was M. avium complex (MAC), followed by M. malmoense, and M. abscessus. There was a decreasing trend in NTM pulmonary infection and NTM pulmonary disease from the year 2000 to 2014, while an increase was observedfrom 2015 to 2019. A total of 72 (47%) patients received antibiotic treatment. Patients with high symptom scores, those below the age of 65, and those with MAC infection had more than three times the odds of receiving antibiotic treatment (P = 0.006, P = 0.006, and P = .005 respectively). Of 72 patients who received treatment, 53 (74%) had a favourable response and culture conversion. 17 (32%) of them had a relapse. Out of 82 patients who did not receive treatment, 45 (55%) had spontaneous culture conversion. 8 (18%) of them had a relapse. No factor was identified to be significantly associated with a favourable treatment response including the time taken to start treatment or presence of pulmonary cavities. Conclusion: Favourable response to treatment was seen in 74% patients whereas spontaneous culture conversion was seen in 55% of non-treated patients. Factors associated with favourable treatment response were not found.

Abstract Objective : This study investigates the effectiveness of booster doses on the Omicron wave in Morocco against COVID-19 severe and critical hospitalizations and deaths; Participants/methods: This study uses nationally representative data on COVID-19 from 15 December 2021 to 31 January 2022. To investigate the effectiveness of the inactivated COVID-19 vaccine BBIBP-CorV (Vero Cells) Sinopharm booster doses on the Omicron wave in morocco by using real-world data established from nationally representative statistics on COVID-19 cases, deaths and vaccinations. Statistical Analyses : The screening method was used to estimate vaccine effectiveness against COVID-19 severe or critical hospitalization and COVID-19-related deaths. The data were grouped by, age subgroup, sex, week, and geographical area and were analyzed by using binary logistic regression with an offset for vaccine coverage. Results: The overall sinopharm VE estimate is 89% (95% CI 85 to 92) effective in curbing COVID-19 death, and 81% (95% CI 78 to 84 in curbing COVID-19 severe critical hospitalization. Death-related VE estimate was 86% (95% CI 81 to 90) for patients aged [>=]65 years, 96% (95% CI 90 to 98) for those aged < 65 years, 95% (95% CI 88 to 98) in no risk factor patient was, 91% (95% CI 85 to 94) with 1 risk factor ; 90% (95% CI 83 to 95) with 2 risk factors; 72% (95% CI 52 to 84) in patient with 3 risk factors and more. Severe critical hospitalization VE, estimate was 78% (95% CI 74 to 82) for patients aged [>=]65 years, 87% (95% CI 82 to 90) for those aged < 65 years, 86% (95% CI 80 to 90) in no risk factor patient was, 80% (95% CI 73 to 84) with 1 risk factor ; 80% (95% CI 70 to 85) with 2 risk factors; 80% (95% CI 68 to 86) in patient with 3 risk factors and more. Conclusions : Sinopharm Boosters are effective in increasing protection against Omicron variant-related COVID-19 death and severe critical hospitalization. The protection is reduced with older age and higher risk factors. These findings emphasize the importance of targeted vaccination strategies for different demographic groups and underscore the protective benefits of the third booster Sinopharm vaccine.

Accepted medical journal manuscripts serve as the primary currency of the scientific community. Over the past few decades, there has been a gradual increase in the number of women entering the medical field. However, women remain underrepresented as first and last authors in medical journals. This lack of representation makes it harder for them to reach leadership roles and advance in their academic careers. Therefore, this study aims to investigate the gender distribution among authors and explore disparities in authorship in relation to the type of publication (original research, case reports, and review articles) as well as the authors' geographic locations. Our analysis included 6,088 articles from 54 research journals sourced from Colombia's Ministry of Health official website. These articles were predominantly original research articles, although case reports and reviews were also present. The analysis specifically focused on published research articles, as they are extensively studied in existing literature. Until now, there has been no assessment of gender disparities in authorship within medical and surgical specialty journals in Colombia. We could evidence persistent gender disparity in primary authorship in Colombia, regardless of the timeframe, location, or field of study. This emphasizes the urgent need for enhanced support for female researchers and equitable resource allocation to rectify regional imbalances. Furthermore, our findings highlight the imperative need to address gender disparities in authorship in medical and surgical research articles in Colombia and other Latin American countries.

Background: Control of several neglected tropical diseases (NTDs), including schistosomiasis, relies on the regular distribution of preventive chemotherapy (PC) over many years. For the sake of sustainable NTD control, a decision must be made at some stage to scale down or stop PC. These stopping decisions are based on population surveys that assess whether infection levels are sufficiently low (typically less than 1%). For schistosomiasis control, concerns have been raised regarding the limited sensitivity of the currently-used diagnostic (Kato-Katz or KK) to detect low intensity infections. The use of new, more sensitive, molecular diagnostics has been proposed. Methods: Through statistical analysis of Schistosoma mansoni egg counts collected from Burundi and a simulation study using an established transmission model for schistosomiasis, we investigated the extent to which more sensitive diagnostics can improve decision making regarding stopping or continuing PC for the control of S. mansoni. Results: We found that KK-based strategies perform reasonably well for determining when to stop PC at a local scale. Use of more sensitive diagnostics only leads to a marginally improved health impact (person-years lived with heavy infection) and comes at a cost of continuing PC for longer, unless the decision threshold for stopping PC is adapted upwards. However, if this threshold is set too high, PC may be stopped prematurely, resulting in a rebound of infection levels. Conclusions: We conclude that the potential value of more sensitive diagnostics lies more in the reduction of survey-related costs than in the direct health impact of improved parasite control.

Background. In 2020, people around the world were challenged by the outbreak of the COVID-19 pandemic. Countries responded with various restrictions, including lockdowns and stay-at-home orders, in an attempt to prevent the spread of the disease. Citizens were thus subjected to unprecedented uncertainty and stress. Prolonged exposure to such conditions may impact human health and well-being. One of the core aspects of proper physiological functioning is sleep. This prospective longitudinal study aims to investigate sleep quality and its relationship to chronotype over a year-long period from September 2020. Methods and findings. Our year-long longitudinal prospective study focused on an employee cohort (N=54) at the Research Centre for Toxic Compounds in the Environment (RECETOX) of Masaryk University in the Czech Republic. During the first half of this period, three lockdowns with a cumulative duration of 100 days were imposed. During the second half of this period, the imposed restrictions were relaxed. Individuals were measured quarterly, i.e. at five time points. Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI) while chronotype was established using the Reduced Morningness-Eveningness Questionnaire (rMEQ). We also used Perceived Stress Scale (PSS-14), Beck Depression Inventory (BDI-II), and General Anxiety Disorder-7 (GAD-7) to address potential confounders. The response rates of valid measurements across time points ranged from 87.04 % to 61.11 %. Our results show that sleep quality significantly worsened across the year for the evening chronotype but improved for the neutral and early chronotypes. Overall, over the year the incidence of poor sleep decreased by 16.13 % with 95% CI [-6.10%; 37.16%]. We did not find any significant sex differences in sleep quality. Perceived stress, symptoms of anxiety and depression were positively significantly associated with sleep problems in all measurements except in June. This study is limited by the small sample, decreasing number of individuals in chronotype categories and the lack of information on napping behavior. Conclusion. These findings shed new light on the long-term influence of pandemic-related restrictions on individuals and particularly on the potentially more vulnerable evening chronotypes.

Objectives: Inhibitory control deficits are considered a key pathogenic factor in anxiety disorders. To assess inhibitory control, the antisaccade task is a well-established measure, assessing antisaccade performance via latencies and error rates. The present study follows three aims: (1) to investigate inhibitory control via antisaccade latencies and errors in an antisaccade task, and their associations with multiple measures of fear in patients with spider phobia (SP) versus healthy controls (HC), (2) to investigate the modifiability of antisaccade performance via a fear-specific antisaccade training in patients with SP and HC, and (3) to explore associations between putative changes in antisaccade performance in SPs and diverse measures of fear following the training. Methods: Towards aim 1, we assess antisaccade latencies (primary outcome) and error rates (secondary outcome) in an emotional antisaccade task. Further, the baseline assessment includes assessments of psychophysiological, behavioral, and psychometric indices of fear in patients with SP and HCs. To address aim 2, we compare effects of a fear-specific antisaccade training with effects of a prosaccade training as a control condition. The primary and secondary outcomes are reassessed at a post-1-assessment in both SPs and HCs. Aim 3 employs a cross-over design and is piloted in patients with SP, only. Towards this aim, primary and secondary outcomes, as well as psychophysiological, behavioral, and psychometric measures of fear are reassessed at a post-2-assessment after the second training block. Conclusion: This study aims to better understand inhibitory control processes and their modifiability in spider phobia. If successful, antisaccade training may assist in the treatment of specific phobia by directly targeting the putative underlying inhibitory control deficits. This study has been preregistered with ISRCTN (ID: ISRCTN12918583) on 28th February 2022.

Objective: to describe coping strategies during medical education and their relationship with course periods, with gender, and depressive and anxiety range symptoms. Method: the Ways of Coping Questionnaire (WCQ), the Beck Depression Inventory (BDI), and the Spielberger Trait Anxiety Inventory (STAI-T) were administered to 599 medical students from basic, intermediate and internship periods. Results: The response rate was 80.3% (279 females and 190 males aged 21.9). Belong to internship or basic/intermediate levels make a significant difference in choosing coping factors. Female students reported greater use of factors indicating a need for social support and fantasy. In contrast, male students reported greater use of factors such as substance use and self-control. Twenty percent of students scored high on anxiety (STAI-T>49), whereas 7.6% scored on the depression range (>20) and 8.0% on the dysphoric range (16-20) of the BDI. Students at the normal range at the BDI and the STAI-T reported greater use of factors such as of social support and problem solving. The factor analysis of the WCQ showed that dysphoric, depressive, and high anxiety students reported greater use of factors indicating fantasy, search of relief and escape. Conclusion: Dysphoria, depressive, and highly anxious medical students choose similar strategies to deal with stress related to medical graduation. Women and men exhibit distinct coping strategies related to medical education and training. Support and counseling services for medical students should take into consideration these depressive and anxiety ranges, and gender differences in coping strategies, with potentially important preventive and therapeutic implications.

Introduction: While general-purpose large language models(LLMs) were able to pass USMLE-style examinations, their ability to perform in a specialized context, like gastroenterology, is unclear. In this study, we assessed the performance of three widely available LLMs: PaLM-2, GPT-3.5, and GPT-4 on the most recent ACG self-assessment(2022), utilizing both a basic and a prompt-engineered technique. Methods: We interacted with the chat interfaces of PaLM-2, GPT-3.5, and GPT-4. We first applied a basic prompt approach, providing each exam question and answer text with minimalist text descriptions of any images. For the engineered approach, we added additional context and instructions. We assessed each model-prompt combination in terms of overall and difficulty-stratified performance and compared this to average human performance. We also evaluated each models self-assessed uncertainty. The highest scoring model-prompt combination was further assessed on the 2021 exam. We also assessed the impact of image descriptions on our findings. Results: Using a basic prompt, PaLM-2, GPT-3.5, and GPT-4 achieved scores of 32.6%, 55.3%, and 68.9% respectively. With the engineered prompt, scores improved to 42.7%, 65.2%, and 76.3% respectively. Testing GPT-4 on the ACG-2021 exam yielded a similar score(75.3%). GPT-4 scores matched the average score for human test-takers reported by ACG(75.7%). GPT-4 showed a capability to self-assess its confidence accurately in the context of a multiple-choice exam with its confidence estimates falling within 5% of its actual performance. Excluding image-based questions didnt change the primary findings. Discussion: Our study highlights the capability of GPT-4 to answer subspecialty board-exam questions at a level commensurate with the average human test-taker. The results confirm that prompt-engineering can enhance LLMs performance on medical reasoning tasks. We also show GPT-4 can provide insightful measures of uncertainty in the setting of board-style multiple-choice questions, alerting users to low-quality answers. Future studies of LLMs in gastroenterology should incorporate prompt-engineering to maximize model capabilities.

Typhoid fever, caused by Salmonella enterica serovar Typhi, results in over 1.2 million cases and 29 thousand deaths annually from sub-Saharan Africa. Combating this disease requires various intervention approaches, such as typhoid conjugate vaccines and improving water, sanitation, and hygiene. Enhancing the effectiveness of these strategies necessitates a deeper understanding of the variation of the typhoid fever across the target region. Although the magnitude and variation of typhoid fever at the country level have been studied globally, sub-national variation remains underexplored. To address this gap, we collected data from 265 published reports on typhoid fever occurrences in sub-Saharan Africa between January 2000 and December 2020. The dataset includes information on the year and geographical location of observation, diagnostic tests used, and the type of studies in which typhoid fever was reported. By analyzing this dataset, we can gain insights into the sub-national heterogeneity of typhoid fever's burden in the region. This knowledge will be instrumental in designing more effective intervention strategies to combat the disease.

Introduction Randomised controlled trials (RCTs) inform healthcare decisions. It is now apparent that some published RCTs contain false data, and some appear to have been entirely fabricated. Systematic reviews are performed to identify and synthesise all RCTs that have been conducted on a given topic. While it is usual to assess methodological features of the RCTs in the process of undertaking a systematic review, it is not usual to consider whether the RCTs contain false data. Studies containing false data therefore go unnoticed, and contribute to systematic review conclusions. The INSPECT-SR project will develop a tool to assess the trustworthiness of RCTs in systematic reviews of healthcare related interventions. Methods and analysis The INSPECT-SR tool will be developed using expert consensus in combination with empirical evidence, over five stages: 1) a survey of experts to assemble a comprehensive list of checks for detecting problematic RCTs, 2) an evaluation of the feasibility and impact of applying the checks to systematic reviews, 3) a Delphi survey to determine which of the checks are supported by expert consensus, culminating in 4) a consensus meeting to select checks to be included in a draft tool and to determine its format, 5) prospective testing of the draft tool in the production of new health systematic reviews, to allow refinement based on user feedback. We anticipate that the INSPECT-SR tool will help researchers to identify problematic studies, and will help patients by protecting them from the influence of false data on their healthcare.