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Reactive metabolite formation is a major mechanism of hepatotoxicity. Although reactive electrophiles can be soft or hard in nature, screening strategies have generally focused on the use of glutathione trapping assays to screen for soft electrophiles, with many data sets available to support their use. The use of a similar assay for hard electrophiles using cyanide as the trapping agent is far less common, and there is a lack of studies with sufficient supporting data. Using a set of 260 compounds with a defined hepatotoxicity status by the FDA, a comprehensive literature search yielded cyanide trapping data on an unbalanced set of 20 compounds that were all clinically hepatotoxic. Thus, a further set of 19 compounds was selected to generate cyanide trapping data, resulting in a more balanced data set of 39 compounds. Analysis of the data demonstrated that the cyanide trapping assay had high specificity (92%) and a positive predictive value (83%) such that hepatotoxic compounds would be confidently flagged. Structural analysis of the adducts formed revealed artifactual methylated cyanide adducts to also occur, highlighting the importance of full structural identification to confirm the nature of the adduct formed. The assay was demonstrated to add the most value for compounds containing typical structural alerts for hard electrophile formation: half of the severe hepatotoxins with these structural alerts formed cyanide adducts, while none of the severe hepatotoxins with no relevant structural alerts formed adducts. The assay conditions used included cytosolic enzymes (e.g., aldehyde oxidase) and an optimized cyanide concentration to minimize the inhibition of cytochrome P450 enzymes by cyanide. Based on the demonstrated added value of this assay, it is to be initiated for use at GSK as part of the integrated hepatotoxicity strategy, with its performance being reviewed periodically as more data is generated.

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. In biomedical image analysis, chosen performance metrics often do not reflect the domain interest, and thus fail to adequately measure scientific progress and hinder translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. Developed by a large international consortium in a multistage Delphi process, it is based on the novel concept of a problem fingerprint—a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), dataset and algorithm output. On the basis of the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as classification tasks at image, object or pixel level, namely image-level classification, object detection, semantic segmentation and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases.

Supplemental Digital Content is Available in the Text.Bullock, GS, Shanley, E, Thigpen, CA, Arden, NK, Noonan, TK, Kissenberth, MJ, Wyland, DJ, and Collins, GS. Improving clinical utility of real-world prediction models: updating through recalibration. J Strength Cond Res37(5): 1057–1063, 2023—Prediction models can aid clinicians in identifying at-risk athletes. However, sport and clinical practice patterns continue to change, causing predictive drift and potential suboptimal prediction model performance. Thus, there is a need to temporally recalibrate previously developed baseball arm injury models. The purpose of this study was to perform temporal recalibration on a previously developed injury prediction model and assess model performance in professional baseball pitchers. An arm injury prediction model was developed on data from a prospective cohort from 2009 to 2019 on minor league pitchers. Data for the 2015–2019 seasons were used for temporal recalibration and model performance assessment. Temporal recalibration constituted intercept-only and full model redevelopment. Model performance was investigated by assessing Nagelkerke’s R-square, calibration in the large, calibration, and discrimination. Decision curves compared the original model, temporal recalibrated model, and current best evidence-based practice. One hundred seventy-eight pitchers participated in the 2015–2019 seasons with 1.63 arm injuries per 1,000 athlete exposures. The temporal recalibrated intercept model demonstrated the best discrimination (0.81 [95% confidence interval [CI]: 0.73, 0.88]) and R-square (0.32) compared with original model (0.74 [95% CI: 0.69, 0.80]; R-square: 0.32) and the redeveloped model (0.80 [95% CI: 0.73, 0.87]; R-square: 0.30). The temporal recalibrated intercept model demonstrated an improved net benefit of 0.34 compared with current best evidence-based practice. The temporal recalibrated intercept model demonstrated the best model performance and clinical utility. Updating prediction models can account for changes in sport training over time and improve professional baseball arm injury outcomes.

IntroductionMusculoskeletal injury (MSK-I) mitigation and prevention programmes (MSK-IMPPs) have been developed and implemented across militaries worldwide. Although programme efficacy is often reported, development and implementation details are often overlooked, limiting their scalability, sustainability and effectiveness. This scoping review aimed to identify the following in military populations: (1) barriers and facilitators to implementing and scaling MSK-IMPPs; (2) gaps in MSK-IMPP research and (3) future research priorities.MethodsA scoping review assessed literature from inception to April 2022 that included studies on MSK-IMPP implementation and/or effectiveness in military populations. Barriers and facilitators to implementing these programmes were identified.ResultsFrom 132 articles, most were primary research studies (90; 68.2%); the remainder were review papers (42; 31.8%). Among primary studies, 3 (3.3%) investigated only women, 62 (69%) only men and 25 (27.8%) both. Barriers included limited resources, lack of stakeholder engagement, competing military priorities and equipment-related factors. Facilitators included strong stakeholder engagement, targeted programme design, involvement/proximity of MSK-I experts, providing MSK-I mitigation education, low burden on resources and emphasising end-user acceptability. Research gaps included variability in reported MSK-I outcomes and no consensus on relevant surveillance metrics and definitions.ConclusionDespite a robust body of literature, there is a dearth of information about programme implementation; specifically, barriers or facilitators to success. Additionally, variability in outcomes and lack of consensus on MSK-I definitions may affect the development, implementation evaluation and comparison of MSK-IMPPs. There is a need for international consensus on definitions and optimal data reporting elements when conducting injury risk mitigation research in the military.

ObjectiveThis study reported the burden of gout and its attributable risk factors in the Middle East and North Africa (MENA) region between 1990 and 2019 by age, sex, and sociodemographic index (SDI).MethodsData on the prevalence, incidence, and years lived with disability (YLD) due to gout were obtained from the Global Burden of Disease 2019 study for the 21 countries in the MENA region, from 1990 to 2019.ResultsIn 2019, the regional age-standardized point prevalence and annual incidence rates of gout were 509.1 and 97.7 per 100,000 population, which represent a 12% and 11.1% increase since 1990, respectively. Moreover, in 2019 the regional age-standardized YLD rate was 15.8 per 100,000 population, an 11.7% increase since 1990. In 2019, Qatar and Afghanistan had the highest and lowest age-standardized YLD rates, respectively. Regionally, the age-standardized point prevalence of gout increased with age up to the oldest age group, and it was more prevalent among males in all age groups. In addition, there was an overall positive association between SDI and the burden of gout between 1990 and 2019. In 2019, high BMI (46.1%) was the largest contributor to the burden of gout in the MENA region.ConclusionThere were large intercountry variations in the burden of gout, but in general, it has increased in MENA over the last 3 decades. This increase is in line with the global trends of gout. However, the age-standardized YLD rate change was higher in MENA than at the global level.

Nuclear relaxation caused by diffusion of 111In/Cd probe atoms was measured in four phases having the tetragonal FeGa3 structure (tP16) using perturbed angular correlation spectroscopy (PAC) and used to gain insight into diffusion processes in phases having more than one diffusion sublattice. The three indide phases studied in this work have two inequivalent and interpenetrating In-sublattices, labeled In1 and In2, and nuclear quadrupole interactions were resolved for probes on each sublattice. The phases are line-compounds with narrow field-widths. Diffusional relaxations, fitted using an exponential damping ansatz, were measured at the two opposing boundary compositions as a function of temperature. “High” and “low” relaxation regimes were observed that are attributed to In-poorer and In-richer compositions, under the reasonable assumption that the atomic motion occurs via an indium-vacancy diffusion mechanism. Relaxation was observed to be greater for tracer atoms starting on In2 sites in the indides immediately following decay of 111In into 111Cd, which is attributed to a preference of daughter Cd-tracer atoms and/or indium vacancies to occupy In1 sites. Activation enthalpies for relaxation are compared with enthalpies for self-diffusion in indium metal.

Results from clinical trials can be deemed trustworthy only if they are properly conducted and their methods are fully reported. The SPIRIT and CONSORT checklists, which have improved clinical trial design, conduct and reporting, are being updated to reflect recent advances and improve the assessment of healthcare interventions.

Artificial intelligence is noninferior to clinicians in terms of diagnostic performance in fracture detection, showing promise as a useful diagnostic tool.

Over 70% of studies measuring ACL-RSI scores were judged to have high risk of bias (i.e., low internal validity), leading to a certainty of evidence rating of weak for all analyses.ACL-RSI scores do not appear to increase during typical rehabilitation periods after anterior cruciate ligament reconstruction.Age, sex, and time from injury to surgery (i.e., treatment approach) appear prognostic for early ACL-RSI scores, but their prognostic ability diminishes for later ACL-RSI scores.

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico evaluation, but few have yet demonstrated real benefit to patient care. Early-stage clinical evaluation is important to assess an AI system’s actual clinical performance at small scale, ensure its safety, evaluate the human factors surrounding its use and pave the way to further large-scale trials. However, the reporting of these early studies remains inadequate. The present statement provides a multi-stakeholder, consensus-based reporting guideline for the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence (DECIDE-AI). We conducted a two-round, modified Delphi process to collect and analyze expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 pre-defined stakeholder categories. The final composition and wording of the guideline was determined at a virtual consensus meeting. The checklist and the Explanation & Elaboration (E&E) sections were refined based on feedback from a qualitative evaluation process. In total, 123 experts participated in the first round of Delphi, 138 in the second round, 16 in the consensus meeting and 16 in the qualitative evaluation. The DECIDE-AI reporting guideline comprises 17 AI-specific reporting items (made of 28 subitems) and ten generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we developed a guideline comprising key items that should be reported in early-stage clinical studies of AI-based decision support systems in healthcare. By providing an actionable checklist of minimal reporting items, the DECIDE-AI guideline will facilitate the appraisal of these studies and replicability of their findings.

Although the presence of osteoporosis, on average, predicts future fractures at the population level, accumulating evidence indicates that both the identification of fracture-prone individuals and the effectiveness of bone-targeted medications [...]

Understanding global trends in the point prevalence, deaths, and disability-adjusted life-years (DALYs) for asthma will facilitate evidence-based decision-making.

Marathon Oil Co. has been able to maintain its 24-hr. drilling operation in the Gulf of Mexico by adopting a new total-project strategy. The strategy allowed the company to cost-effectively harness the best drilling technologies available. It involved modifications to rig equipment, optimal drilling techniques and the use of olefin-based synthetic drilling mud. A discussion of the key considerations Marathon Oil had toconsider in implementing its total-project strategy is presented., Rig equipment modifications and optimized techniques, combined with olefin-based synthetic fluid, produced significant efficiency improvements and cost reductions. Total-project strategy allows best technologies to be used, even if they are [...]

The use of a downhole splitter allows oil well drillers to drill two cased wells from one well bore. The downhole splitter can be used for subsea completions, offshore platforms, offshore exploitation and delineation wells, as well as in environmentally sensitive onshore areas. The downhole splitter system was developed in Apr 1992 and tested in Wyoming. A detailed analysis of how the downhole splitter works and performed during field tests is provided., A downhole multiwell drilling template, called a downhole splitter, allows two wells to be drilled, cased, and completed from one well bore. After completion, each well can be produced, serviced, [...]

Flow drilling horizontal wells can help improve drilling performance and minimize formation damage, thereby enhancing the post-drilling condition of oil and gas reservoirs. The process allows usable wells to be drilled at least cost and with minimal threats to safety and the environment. Considering its many benefits and risks, however, it is important that engineers carefully prepare plans pertaining to well parameters, surface equipment and the execution process itself., Underbalanced operations reduce formation damage, especially in horizontal wells where zones are exposed to mud for longer time periods. Benefits, risks, well control concerns, equipment and issues associated with these [...]

* Objective: To evaluate the relation between weight variability and death in high-risk, middle-aged men participating in the Multiple Risk Factor intervention Trial (MRFIT). * Design: Cohort study with 3.8 years of follow-up. * Setting: Multicenter, collaborative, primary prevention trial conducted at 22 clinical centers in the United States. * Participants: Men (n = 10 529) who were 35 to 57 years old at baseline and who were in the upper 10% to 15% of risk for coronary heart disease because of smoking, high blood pressure, and elevated cholesterol level. Participants were seen at least annually for 6 to 7 years for medical evaluations in study clinical centers. * Measurements: Death from cardiovascular disease (228 deaths) and from all causes (380 deaths). * Results: The primary measure of weight variability was the intrapersonal standard deviation of weight (ISD), which was calculated from measured weights obtained at clinic visits during a 6- to 7-year period. All-cause death rates per 1000 person-years of follow-up across ISD quartiles were 8.28, 8.25, 10.57, and 11.07 from the first to fourth quartiles, respectively. After adjusting for baseline risk factors associated with weight change, the relative risk for all-cause mortality in the fourth compared with the first quartile was 1.64 (95% Cl, 1.21 to 2.23). Cardiovascular death and ISD showed a similar pattern. The association between weight change and death was not observed in the heaviest men. * Conclusion: Greater weight variability was associated with a greater risk for cardiovascular disease and all-cause mortality in some types of high-risk men., Large fluctuations in body weight may increase the risk of cardiovascular disease and death in middle-aged men with a high-risk of coronary heart disease (CHD). Among 10,529 men between 35 and 57 years old in the upper 10% to 15% risk of CHD, 228 deaths from cardiovascular disease occurred and 380 deaths occurred from all causes. An significant association was found between changes in body weight and an increased risk of dying from cardiovascular disease and all other causes during the follow-up period. This association was not found among the men with the heaviest body weight. No distinction was made between voluntary and involuntary weight loss. Involuntary weight loss is a symptom of many diseases.

Late potentials detected by signal-averaged electrocardiography (SAECG) are an important noninvasive indicator identifying patients with previous myocardial infarction at risk for developing ventricular tachycardia. The role of myocardial ischemia in the development of late potentials is undefined. This study attempts to determine if late potentials on SAECG can be produced during scintigraphically proven ischemia. A signal-averaged electrocardiogram was obtained before and immediately after single-photon emission computed tomography thallium exercise testing in 51 patients. Reversible ischemia was documented in 25 cases with no significant changes in the parameters of SAECG; patients with previous myocardial infarction (n = 10) also had no significant changes from baseline. Multivariate analysis with respect to reversible ischemia and previous myocardial infarction was unrevealing. Patients with late potentials at baseline (n = 10) who developed reversible ischemia (n = 5) had a shorter QRS duration than those with late potentials at baseline and no reversible ischemia. The data indicate that exercise-induced scintigraphically proven ischemia does not alter SAECG even in the presence of previous myocardial infarction. Patients with late potentials at baseline may actually have a shortened QRS duration during reversible ischemia as opposed to the expected lengthening of the QRS. (Am J Cardiol 1992;70:432-435)

"War changed me forever." Almost every combat veteran says this in retrospect. Generations of combat-exposed veterans as well as their families have struggled with the psychological toll war takes in […]

Background: Osteoarthritis (OA) is a chronic joint disease, with increasing global burden of disability and healthcare utilisation. Recent meta-analyses have shown a range of effects of OA on mortality, reflecting different OA definitions and study methods. We seek to overcome limitations introduced when using aggregate results by gathering individual participant-level data (IPD) from international observational studies and standardising methods to determine the association of knee OA with mortality in the general population. Methods: Seven community-based cohorts were identified containing knee OA-related pain, radiographs, and time-to-mortality, six of which were available for analysis. A two-stage IPD meta-analysis framework was applied: (1) Cox proportional hazard models assessed time-to-mortality of participants with radiographic OA (ROA), OA-related pain (POA), and a combination of pain and ROA (PROA) against pain and ROA-free participants; (2) hazard ratios (HR) were then pooled using the Hartung–Knapp modification for random-effects meta-analysis. Findings: 10,723 participants in six cohorts from four countries were included in the analyses. Multivariable models (adjusting for age, sex, race, BMI, smoking, alcohol consumption, cardiovascular disease, and diabetes) showed a pooled HR, compared to pain and ROA-free participants, of 1.03 (0.83, 1.28) for ROA, 1.35 (1.12, 1.63) for POA, and 1.37 (1.22, 1.54) for PROA. Discussion: Participants with POA or PROA had a 35–37% increased association with reduced time-to-mortality, independent of confounders. ROA showed no association with mortality, suggesting that OA-related knee pain may be driving the association with time-to-mortality. Funding: Versus Arthritis Centre for Sport, Exercise and Osteoarthritis and Osteoarthritis Research Society International.

ObjectivePrognostic models aid clinical decision making and evaluation of hospital performance. Existing neonatal prognostic models typically use physiological measures that are often not available, such as pulse oximetry values, in routine practice in low-resource settings. We aimed to develop and validate two novel models to predict all cause in-hospital mortality following neonatal unit admission in a low-resource, high-mortality setting.Study design and settingWe used basic, routine clinical data recorded by duty clinicians at the time of admission to derive (n=5427) and validate (n=1627) two novel models to predict in-hospital mortality. The Neonatal Essential Treatment Score (NETS) included treatments prescribed at the time of admission while the Score for Essential Neonatal Symptoms and Signs (SENSS) used basic clinical signs. Logistic regression was used, and performance was evaluated using discrimination and calibration.ResultsAt derivation, c-statistic (discrimination) for NETS was 0.92 (95% CI 0.90 to 0.93) and that for SENSS was 0.91 (95% CI 0.89 to 0.93). At external (temporal) validation, NETS had a c-statistic of 0.89 (95% CI 0.86 to 0.92) and SENSS 0.89 (95% CI 0.84 to 0.93). The calibration intercept for NETS was −0.72 (95% CI −0.96 to −0.49) and that for SENSS was −0.33 (95% CI −0.56 to −0.11).ConclusionUsing routine neonatal data in a low-resource setting, we found that it is possible to predict in-hospital mortality using either treatments or signs and symptoms. Further validation of these models may support their use in treatment decisions and for case-mix adjustment to help understand performance variation across hospitals.

ABSTRACTIntroductionThe use of observational data to assess drug effectiveness and safety can provide relevant information, much of which may not be feasible to obtain through randomized clinical trials. Because observational studies provide critical drug safety and effectiveness information that influences drug policy and prescribing practices, transparent, consistent, and accurate reporting of these studies is critical.Areas CoveredWe provide recommendations to extend existing reporting guidelines, covering the main components of primary research studies (methods, results, discussion).Expert OpinionOur recommendations include extending drug safety and effectiveness guidelines to include explicit checklist items on: study registration, causal diagrams, rationale for measures of effect, comprehensive assessment of bias, comprehensive data cleaning steps, drug equivalents, subject-level drug data visualization, sex and gender-based analyses and results, patient-oriented outcomes, and patient involvement in research.

Misuse of statistics in medical and sports science research is common and may lead to detrimental consequences to healthcare. Many authors, editors and peer reviewers of medical papers will not have expert knowledge of statistics or may be unconvinced about the importance of applying correct statistics in medical research. Although there are guidelines on reporting statistics in medical papers, a checklist on the more general and commonly seen aspects of statistics to assess when peer-reviewing an article is needed. In this article, we propose a CHecklist for statistical Assessment of Medical Papers (CHAMP) comprising 30 items related to the design and conduct, data analysis, reporting and presentation, and interpretation of a research paper. While CHAMP is primarily aimed at editors and peer reviewers during the statistical assessment of a medical paper, we believe it will serve as a useful reference to improve authors’ and readers’ practice in their use of statistics in medical research. We strongly encourage editors and peer reviewers to consult CHAMP when assessing manuscripts for potential publication. Authors also may apply CHAMP to ensure the validity of their statistical approach and reporting of medical research, and readers may consider using CHAMP to enhance their statistical assessment of a paper.

Among patients with out-of-hospital cardiac arrest (OHCA) and ventricular fibrillation, more than half present with refractory ventricular fibrillation unresponsive to initial standard advanced cardiac life support (ACLS) treatment. We did the first randomised clinical trial in the USA of extracorporeal membrane oxygenation (ECMO)-facilitated resuscitation versus standard ACLS treatment in patients with OHCA and refractory ventricular fibrillation.

I opened your March 2 edition to read the article 'Still Wrestling with the Devil,' by Randall Balmer, with myself fully dressed in my sanctimonious Sunday's best! Halfway through the [...]

The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by providing evidence-based recommendations for the minimum set of items to be addressed. This guidance has been instrumental in promoting transparent evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes. The SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trial protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports: CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 26 candidate items, which were consulted upon by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The SPIRIT-AI extension includes 15 new items that were considered sufficiently important for clinical trial protocols of AI interventions. These new items should be routinely reported in addition to the core SPIRIT 2013 items. SPIRIT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention will be integrated, considerations for the handling of input and output data, the human–AI interaction and analysis of error cases. SPIRIT-AI will help promote transparency and completeness for clinical trial protocols for AI interventions. Its use will assist editors and peer reviewers, as well as the general readership, to understand, interpret, and critically appraise the design and risk of bias for a planned clinical trial.

The CONSORT 2010 statement provides minimum guidelines for reporting randomised trials. Its widespread use has been instrumental in ensuring transparency in the evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate impact on health outcomes. The CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trials evaluating interventions with an AI component. It was developed in parallel with its companion statement for clinical trial protocols: SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 29 candidate items, which were assessed by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a two-day consensus meeting (31 stakeholders), and refined through a checklist pilot (34 participants). The CONSORT-AI extension includes 14 new items that were considered sufficiently important for AI interventions that they should be routinely reported in addition to the core CONSORT 2010 items. CONSORT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention is integrated, the handling of inputs and outputs of the AI intervention, the human–AI interaction and provision of an analysis of error cases. CONSORT-AI will help promote transparency and completeness in reporting clinical trials for AI interventions. It will assist editors and peer reviewers, as well as the general readership, to understand, interpret, and critically appraise the quality of clinical trial design and risk of bias in the reported outcomes.

ObjectivesTo determine the extent and content of academic publishers’ and scientific journals’ guidance for authors on the use of generative artificial intelligence (GAI).DesignCross sectional, bibliometric study.SettingWebsites of academic publishers and scientific journals, screened on 19-20 May 2023, with the search updated on 8-9 October 2023.ParticipantsTop 100 largest academic publishers and top 100 highly ranked scientific journals, regardless of subject, language, or country of origin. Publishers were identified by the total number of journals in their portfolio, and journals were identified through the Scimago journal rank using the Hirsch index (H index) as an indicator of journal productivity and impact.Main outcome measuresThe primary outcomes were the content of GAI guidelines listed on the websites of the top 100 academic publishers and scientific journals, and the consistency of guidance between the publishers and their affiliated journals.ResultsAmong the top 100 largest publishers, 24% provided guidance on the use of GAI, of which 15 (63%) were among the top 25 publishers. Among the top 100 highly ranked journals, 87% provided guidance on GAI. Of the publishers and journals with guidelines, the inclusion of GAI as an author was prohibited in 96% and 98%, respectively. Only one journal (1%) explicitly prohibited the use of GAI in the generation of a manuscript, and two (8%) publishers and 19 (22%) journals indicated that their guidelines exclusively applied to the writing process. When disclosing the use of GAI, 75% of publishers and 43% of journals included specific disclosure criteria. Where to disclose the use of GAI varied, including in the methods or acknowledgments, in the cover letter, or in a new section. Variability was also found in how to access GAI guidelines shared between journals and publishers. GAI guidelines in 12 journals directly conflicted with those developed by the publishers. The guidelines developed by top medical journals were broadly similar to those of academic journals.ConclusionsGuidelines by some top publishers and journals on the use of GAI by authors are lacking. Among those that provided guidelines, the allowable uses of GAI and how it should be disclosed varied substantially, with this heterogeneity persisting in some instances among affiliated publishers and journals. Lack of standardization places a burden on authors and could limit the effectiveness of the regulations. As GAI continues to grow in popularity, standardized guidelines to protect the integrity of scientific output are needed.

ObjectivesTo answer a national research priority by comparing the risk-benefit and costs associated with reverse total shoulder replacement (RTSR) and anatomical total shoulder replacement (TSR) in patients having elective primary shoulder replacement for osteoarthritis.DesignPopulation based cohort study using data from the National Joint Registry and Hospital Episode Statistics for England.SettingPublic hospitals and publicly funded procedures at private hospitals in England, 2012-20.ParticipantsAdults aged 60 years or older who underwent RTSR or TSR for osteoarthritis with intact rotator cuff tendons. Patients were identified from the National Joint Registry and linked to NHS Hospital Episode Statistics and civil registration mortality data. Propensity score matching and inverse probability of treatment weighting were used to balance the study groups.Main outcome measuresThe main outcome measure was revision surgery. Secondary outcome measures included serious adverse events within 90 days, reoperations within 12 months, prolonged hospital stay (more than three nights), change in Oxford Shoulder Score (preoperative to six month postoperative), and lifetime costs to the healthcare service.ResultsThe propensity score matched population comprised 7124 RTSR or TSR procedures (126 were revised), and the inverse probability of treatment weighted population comprised 12 968 procedures (294 were revised) with a maximum follow-up of 8.75 years. RTSR had a reduced hazard ratio of revision in the first three years (hazard ratio local minimum 0.33, 95% confidence interval 0.18 to 0.59) with no clinically important difference in revision-free restricted mean survival time, and a reduced relative risk of reoperations at 12 months (odds ratio 0.45, 95% confidence interval 0.25 to 0.83) with an absolute risk difference of −0.51% (95% confidence interval −0.89 to −0.13). Serious adverse events and prolonged hospital stay risks, change in Oxford Shoulder Score, and modelled mean lifetime costs were similar. Outcomes remained consistent after weighting.ConclusionsThis study’s findings provide reassurance that RTSR is an acceptable alternative to TSR for patients aged 60 years or older with osteoarthritis and intact rotator cuff tendons. Despite a significant difference in the risk profiles of revision surgery over time, no statistically significant and clinically important differences between RTSR and TSR were found in terms of long term revision surgery, serious adverse events, reoperations, prolonged hospital stay, or lifetime healthcare costs.

Tony Koester's Trains of Thought in the February issue about cereal-box trains brought back some really good memories. I got my start in HO trains through the good people of [...]

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