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Journal For Immunotherapy of Cancer May 2024Artificial intelligence (AI) chatbots have become a major source of general and medical information, though their accuracy and completeness are still being assessed....
BACKGROUND
Artificial intelligence (AI) chatbots have become a major source of general and medical information, though their accuracy and completeness are still being assessed. Their utility to answer questions surrounding immune-related adverse events (irAEs), common and potentially dangerous toxicities from cancer immunotherapy, are not well defined.
METHODS
We developed 50 distinct questions with answers in available guidelines surrounding 10 irAE categories and queried two AI chatbots (ChatGPT and Bard), along with an additional 20 patient-specific scenarios. Experts in irAE management scored answers for accuracy and completion using a Likert scale ranging from 1 (least accurate/complete) to 4 (most accurate/complete). Answers across categories and across engines were compared.
RESULTS
Overall, both engines scored highly for accuracy (mean scores for ChatGPT and Bard were 3.87 vs 3.5, p<0.01) and completeness (3.83 vs 3.46, p<0.01). Scores of 1-2 (completely or mostly inaccurate or incomplete) were particularly rare for ChatGPT (6/800 answer-ratings, 0.75%). Of the 50 questions, all eight physician raters gave ChatGPT a rating of 4 (fully accurate or complete) for 22 questions (for accuracy) and 16 questions (for completeness). In the 20 patient scenarios, the average accuracy score was 3.725 (median 4) and the average completeness was 3.61 (median 4).
CONCLUSIONS
AI chatbots provided largely accurate and complete information regarding irAEs, and wildly inaccurate information ("hallucinations") was uncommon. However, until accuracy and completeness increases further, appropriate guidelines remain the gold standard to follow.
Topics: Humans; Artificial Intelligence; Immunotherapy; Neoplasms; Drug-Related Side Effects and Adverse Reactions
PubMed: 38816231
DOI: 10.1136/jitc-2023-008599 -
BMJ Open May 2024This study aimed to describe the clinical characteristics of adults with suspected acute community-acquired pneumonia (CAP) on hospitalisation, evaluate their prediction...
Community-acquired pneumonia: use of clinical characteristics of acutely admitted patients for the development of a diagnostic model - a cross-sectional multicentre study.
OBJECTIVES
This study aimed to describe the clinical characteristics of adults with suspected acute community-acquired pneumonia (CAP) on hospitalisation, evaluate their prediction performance for CAP and compare the performance of the model to the initial assessment of the physician.
DESIGN
Cross-sectional, multicentre study.
SETTING
The data originated from the INfectious DisEases in Emergency Departments study and were collected prospectively from patient interviews and medical records. The study included four Danish medical emergency departments (EDs) and was conducted between 1 March 2021 and 28 February 2022.
PARTICIPANTS
A total of 954 patients admitted with suspected infection were included in the study.
PRIMARY AND SECONDARY OUTCOME
The primary outcome was CAP diagnosis assessed by an expert panel.
RESULTS
According to expert evaluation, CAP had a 28% prevalence. 13 diagnostic predictors were identified using least absolute shrinkage and selection operator regression to build the prediction model: dyspnoea, expectoration, cough, common cold, malaise, chest pain, respiratory rate (>20 breaths/min), oxygen saturation (<96%), abnormal chest auscultation, leucocytes (<3.5×10/L or >8.8×10/L) and neutrophils (>7.5×10/L). C reactive protein (<20 mg/L) and having no previous event of CAP contributed negatively to the final model. The predictors yielded good prediction performance for CAP with an area under the receiver-operator characteristic curve (AUC) of 0.85 (CI 0.77 to 0.92). However, the initial diagnosis made by the ED physician performed better, with an AUC of 0.86 (CI 84% to 89%).
CONCLUSION
Typical respiratory symptoms combined with abnormal vital signs and elevated infection biomarkers were predictors for CAP on admission to an ED. The clinical value of the prediction model is questionable in our setting as it does not outperform the clinician's assessment. Further studies that add novel diagnostic tools and use imaging or serological markers are needed to improve a model that would help diagnose CAP in an ED setting more accurately.
TRIAL REGISTRATION NUMBER
NCT04681963.
Topics: Humans; Community-Acquired Infections; Cross-Sectional Studies; Male; Female; Middle Aged; Aged; Pneumonia; Emergency Service, Hospital; Hospitalization; Denmark; Adult; ROC Curve; Prospective Studies; C-Reactive Protein
PubMed: 38816044
DOI: 10.1136/bmjopen-2023-079123 -
BMJ Open Quality May 2024This service evaluation describes the rapid implementation of self-monitoring of blood pressure (SMBP) into maternity care at a tertiary referral centre during the...
BACKGROUND
This service evaluation describes the rapid implementation of self-monitoring of blood pressure (SMBP) into maternity care at a tertiary referral centre during the COVID-19 pandemic. It summarises findings, identifies knowledge gaps and provides recommendations for further research and practice.
INTERVENTION
Pregnant and postpartum women monitored their blood pressure (BP) at home, with instructions on actions to take if their BP exceeded pre-determined thresholds. Some also conducted proteinuria self-testing.
DATA COLLECTION AND ANALYSIS
Maternity records, app data and staff feedback were used in interim evaluations to assess process effectiveness and guide adjustments, employing a Plan-Do-Study-Act and root cause analysis approach.
RESULTS
Between March 2020 and August 2021, a total of 605 women agreed to self-monitor their BP, including 10 women with limited English. 491 registered for telemonitoring (81.2%). 21 (3.5%) took part in urine self-testing. Engagement was high and increased over time with no safety issues. Biggest concerns related to monitor supply and postnatal monitoring. In December 2020, SMBP was integrated into the standard maternity care pathway.
CONCLUSIONS
This project demonstrated successful integration of SMBP into maternity care. Early stakeholder engagement and clear guidance were crucial and community midwifery support essential. Supplying BP monitors throughout pregnancy and post partum could improve the service and fully digitised maternity records would aid data collection. More research is needed on SMBP in the postnatal period and among non-English speakers. These findings support efforts to implement app-supported self-monitoring and guide future research.
Topics: Humans; Female; Pregnancy; COVID-19; Quality Improvement; Adult; United Kingdom; SARS-CoV-2; State Medicine; Blood Pressure Monitoring, Ambulatory; Pandemics; Self Care; Telemedicine
PubMed: 38816006
DOI: 10.1136/bmjoq-2023-002383 -
PloS One 2024After its emergence in China, the coronavirus SARS-CoV-2 has swept the world, leading to global health crises with millions of deaths. COVID-19 clinical manifestations...
BACKGROUND
After its emergence in China, the coronavirus SARS-CoV-2 has swept the world, leading to global health crises with millions of deaths. COVID-19 clinical manifestations differ in severity, ranging from mild symptoms to severe disease. Although perturbation of metabolism has been reported as a part of the host response to COVID-19 infection, scarce data exist that describe stage-specific changes in host metabolites during the infection and how this could stratify patients based on severity.
METHODS
Given this knowledge gap, we performed targeted metabolomics profiling and then used machine learning models and biostatistics to characterize the alteration patterns of 50 metabolites and 17 blood parameters measured in a cohort of 295 human subjects. They were categorized into healthy controls, non-severe, severe and critical groups with their outcomes. Subject's demographic and clinical data were also used in the analyses to provide more robust predictive models.
RESULTS
The non-severe and severe COVID-19 patients experienced the strongest changes in metabolite repertoire, whereas less intense changes occur during the critical phase. Panels of 15, 14, 2 and 2 key metabolites were identified as predictors for non-severe, severe, critical and dead patients, respectively. Specifically, arginine and malonyl methylmalonyl succinylcarnitine were significant biomarkers for the onset of COVID-19 infection and tauroursodeoxycholic acid were potential biomarkers for disease progression. Measuring blood parameters enhanced the predictive power of metabolic signatures during critical illness.
CONCLUSIONS
Metabolomic signatures are distinctive for each stage of COVID-19 infection. This has great translation potential as it opens new therapeutic and diagnostic prospective based on key metabolites.
Topics: Humans; COVID-19; Machine Learning; Male; Female; Biomarkers; Middle Aged; Metabolomics; Adult; Severity of Illness Index; SARS-CoV-2; Aged; Metabolome
PubMed: 38814977
DOI: 10.1371/journal.pone.0302977 -
PloS One 2024This research investigates the glass cliff effect and the positions held by women in leadership roles, focusing on their impact on operational liquidity. The study...
This research investigates the glass cliff effect and the positions held by women in leadership roles, focusing on their impact on operational liquidity. The study delves into the relationship between corporate governance attributes and operational liquidity in 60 non-financial companies listed on the Pakistan Stock Exchange during Covid-19. Utilizing Quine-McCluskey technique and fuzzy set Qualitative Comparative Analysis (fsQCA), it examines the combined effect of Women on the Board, Board Size, Ownership by Blockholders, Board Qualifications and Busy Directors on Operational Liquidity. The necessary condition analysis (NCA) emphasises that firms can operate without reliance on any particular variable taken in the study. The sufficiency analysis provided an expanded understanding of the three conditions leading to the same outcome both before and during the pandemic. This research highlights the significance of the glass cliff effect and emphasizes the pivotal role of women in effectively managing liquidity during times of crisis. Additionally, it provides valuable insights for policymakers regarding the impact of Covid-19 on the interplay between corporate governance characteristics and operational liquidity.
Topics: Leadership; Humans; Female; COVID-19; Pakistan; SARS-CoV-2; Pandemics
PubMed: 38814963
DOI: 10.1371/journal.pone.0302210 -
PloS One 2024The objective was to investigate the effectiveness of a person-centred active rehabilitation programme on symptoms associated with suspected Chronic Traumatic...
OBJECTIVE
The objective was to investigate the effectiveness of a person-centred active rehabilitation programme on symptoms associated with suspected Chronic Traumatic Encephalopathy (CTE). This was accomplished by (1) assessing the effect that a person-centred active rehabilitation programme had on participant symptoms, and (2) exploring how temporal contextual factors affected the participants' experience with, and perceived effectiveness of, the active rehabilitation programme.
METHODS
A twelve-month mixed-methods single case experimental research design was used with six cases (participants). Individual cases were involved in a 51-week study period including an initial interview and three-week baseline phase. Cases were then randomly allocated to one of two n-of-1 study designs (i.e., A-B, B-A, B-A, A-B or B-A, A-B, A-B, B-A) where A and B represent a non-intervention and intervention phase, respectively. Interviews were conducted regularly throughout the study whilst outcome measures were assessed at each follow-up. Analysis of the data included visual, statistical, and qualitative analysis.
RESULTS
Visual and statistical analysis of cognitive and executive function, and mindful attention, demonstrated trivial-to-large effects with the summary reflecting positive or unclear results. A mixed picture was observed for mood and behaviour with effects considered trivial-to-large, and the summary demonstrating positive, unclear and negative effects. Qualitative analysis indicated a perceived improvement in outcome measures such as memory, attention, anxiety, and emotional control despite mixed quantitative findings whilst a clear impact of contextual factors, such as COVID-19, the political atmosphere, exercise tolerance, programme progression, and motivation were evident during the intervention.
CONCLUSIONS
This study has provided primary-level evidence to suggest active rehabilitation as a potential intervention for the management of suspected CTE symptoms. This study has also demonstrated the benefit of a person-centred approach to both clinical research and practice, particularly by considering contextual factors for a better understanding of an intervention effect.
Topics: Humans; Male; Female; Adult; Middle Aged; Chronic Traumatic Encephalopathy; Patient-Centered Care; Cognition; Executive Function; COVID-19; Single-Case Studies as Topic
PubMed: 38814891
DOI: 10.1371/journal.pone.0302260 -
PloS One 2024Amid the ongoing global repercussions of SARS-CoV-2, it is crucial to comprehend its potential long-term psychiatric effects. Several recent studies have suggested a...
SARS-CoV-2 infection is associated with an increase in new diagnoses of schizophrenia spectrum and psychotic disorder: A study using the US national COVID cohort collaborative (N3C).
Amid the ongoing global repercussions of SARS-CoV-2, it is crucial to comprehend its potential long-term psychiatric effects. Several recent studies have suggested a link between COVID-19 and subsequent mental health disorders. Our investigation joins this exploration, concentrating on Schizophrenia Spectrum and Psychotic Disorders (SSPD). Different from other studies, we took acute respiratory distress syndrome (ARDS) and COVID-19 lab-negative cohorts as control groups to accurately gauge the impact of COVID-19 on SSPD. Data from 19,344,698 patients, sourced from the N3C Data Enclave platform, were methodically filtered to create propensity matched cohorts: ARDS (n = 222,337), COVID-19 positive (n = 219,264), and COVID-19 negative (n = 213,183). We systematically analyzed the hazard rate of new-onset SSPD across three distinct time intervals: 0-21 days, 22-90 days, and beyond 90 days post-infection. COVID-19 positive patients consistently exhibited a heightened hazard ratio (HR) across all intervals [0-21 days (HR: 4.6; CI: 3.7-5.7), 22-90 days (HR: 2.9; CI: 2.3 -3.8), beyond 90 days (HR: 1.7; CI: 1.5-1.)]. These are notably higher than both ARDS and COVID-19 lab-negative patients. Validations using various tests, including the Cochran Mantel Haenszel Test, Wald Test, and Log-rank Test confirmed these associations. Intriguingly, our data indicated that younger individuals face a heightened risk of SSPD after contracting COVID-19, a trend not observed in the ARDS and COVID-19 negative groups. These results, aligned with the known neurotropism of SARS-CoV-2 and earlier studies, accentuate the need for vigilant psychiatric assessment and support in the era of Long-COVID, especially among younger populations.
Topics: Humans; COVID-19; Schizophrenia; Male; Psychotic Disorders; Female; Adult; Middle Aged; Cohort Studies; SARS-CoV-2; United States; Respiratory Distress Syndrome; Aged; Young Adult
PubMed: 38814888
DOI: 10.1371/journal.pone.0295891 -
Journal of Medical Internet Research May 2024Since the beginning of the COVID-19 pandemic, >1 million studies have been collected within the COVID-19 Open Research Dataset, a corpus of manuscripts created to...
BACKGROUND
Since the beginning of the COVID-19 pandemic, >1 million studies have been collected within the COVID-19 Open Research Dataset, a corpus of manuscripts created to accelerate research against the disease. Their related abstracts hold a wealth of information that remains largely unexplored and difficult to search due to its unstructured nature. Keyword-based search is the standard approach, which allows users to retrieve the documents of a corpus that contain (all or some of) the words in a target list. This type of search, however, does not provide visual support to the task and is not suited to expressing complex queries or compensating for missing specifications.
OBJECTIVE
This study aims to consider small graphs of concepts and exploit them for expressing graph searches over existing COVID-19-related literature, leveraging the increasing use of graphs to represent and query scientific knowledge and providing a user-friendly search and exploration experience.
METHODS
We considered the COVID-19 Open Research Dataset corpus and summarized its content by annotating the publications' abstracts using terms selected from the Unified Medical Language System and the Ontology of Coronavirus Infectious Disease. Then, we built a co-occurrence network that includes all relevant concepts mentioned in the corpus, establishing connections when their mutual information is relevant. A sophisticated graph query engine was built to allow the identification of the best matches of graph queries on the network. It also supports partial matches and suggests potential query completions using shortest paths.
RESULTS
We built a large co-occurrence network, consisting of 128,249 entities and 47,198,965 relationships; the GRAPH-SEARCH interface allows users to explore the network by formulating or adapting graph queries; it produces a bibliography of publications, which are globally ranked; and each publication is further associated with the specific parts of the query that it explains, thereby allowing the user to understand each aspect of the matching.
CONCLUSIONS
Our approach supports the process of query formulation and evidence search upon a large text corpus; it can be reapplied to any scientific domain where documents corpora and curated ontologies are made available.
Topics: COVID-19; Humans; Algorithms; SARS-CoV-2; Pandemics; Information Storage and Retrieval; Biomedical Research; Unified Medical Language System; Search Engine
PubMed: 38814687
DOI: 10.2196/52655 -
ELife May 2024Nonstructural protein 5 (Nsp5) is the main protease of SARS-CoV-2 that cleaves viral polyproteins into individual polypeptides necessary for viral replication. Here, we...
Nonstructural protein 5 (Nsp5) is the main protease of SARS-CoV-2 that cleaves viral polyproteins into individual polypeptides necessary for viral replication. Here, we show that Nsp5 binds and cleaves human tRNA methyltransferase 1 (TRMT1), a host enzyme required for a prevalent post-transcriptional modification in tRNAs. Human cells infected with SARS-CoV-2 exhibit a decrease in TRMT1 protein levels and TRMT1-catalyzed tRNA modifications, consistent with TRMT1 cleavage and inactivation by Nsp5. Nsp5 cleaves TRMT1 at a specific position that matches the consensus sequence of SARS-CoV-2 polyprotein cleavage sites, and a single mutation within the sequence inhibits Nsp5-dependent proteolysis of TRMT1. The TRMT1 cleavage fragments exhibit altered RNA binding activity and are unable to rescue tRNA modification in TRMT1-deficient human cells. Compared to wild-type human cells, TRMT1-deficient human cells infected with SARS-CoV-2 exhibit reduced levels of intracellular viral RNA. These findings provide evidence that Nsp5-dependent cleavage of TRMT1 and perturbation of tRNA modification patterns contribute to the cellular pathogenesis of SARS-CoV-2 infection.
Topics: Humans; SARS-CoV-2; tRNA Methyltransferases; Proteolysis; RNA, Transfer; COVID-19; Coronavirus 3C Proteases; HEK293 Cells; Virus Replication; Viral Nonstructural Proteins
PubMed: 38814682
DOI: 10.7554/eLife.90316 -
JAMA Network Open May 2024
Randomized Controlled Trial
Topics: Humans; Acute Coronary Syndrome; COVID-19; Female; Male; COVID-19 Vaccines; SARS-CoV-2; Aged; Middle Aged; Vaccination
PubMed: 38814645
DOI: 10.1001/jamanetworkopen.2024.13946