Evaluation of the impact of artificial intelligence-assisted image interpretation on the diagnostic performance of clinicians in identifying pneumothoraces on plain chest X-ray: a multi-case multi-reader study.

BACKGROUND: Artificial intelligence (AI)-assisted image interpretation is a fast-developing area of clinical innovation. Most research to date has focused on the performance of AI-assisted algorithms in comparison with that of radiologists rather than evaluating the algorithms' impact on the clinicians who often undertake initial image interpretation in routine clinical practice. This study assessed the impact of AI-assisted image interpretation on the diagnostic performance of frontline acute care clinicians for the detection of pneumothoraces (PTX). METHODS: A multicentre blinded multi-case multi-reader study was conducted between October 2021 and January 2022. The online study recruited 18 clinician readers from six different clinical specialties, with differing levels of seniority, across four English hospitals. The study included 395 plain CXR images, 189 positive for PTX and 206 negative. The reference standard was the consensus opinion of two thoracic radiologists with a third acting as arbitrator. General Electric Healthcare Critical Care Suite (GEHC CCS) PTX algorithm was applied to the final dataset. Readers individually interpreted the dataset without AI assistance, recording the presence or absence of a PTX and a confidence rating. Following a 'washout' period, this process was repeated including the AI output. RESULTS: Analysis of the performance of the algorithm for detecting or ruling out a PTX revealed an overall AUROC of 0.939. Overall reader sensitivity increased by 11.4% (95% CI 4.8, 18.0, p=0.002) from 66.8% (95% CI 57.3, 76.2) unaided to 78.1% aided (95% CI 72.2, 84.0, p=0.002), specificity 93.9% (95% CI 90.9, 97.0) without AI to 95.8% (95% CI 93.7, 97.9, p=0.247). The junior reader subgroup showed the largest improvement at 21.7% (95% CI 10.9, 32.6), increasing from 56.0% (95% CI 37.7, 74.3) to 77.7% (95% CI 65.8, 89.7, p<0.01). CONCLUSION: The study indicates that AI-assisted image interpretation significantly enhances the diagnostic accuracy of clinicians in detecting PTX, particularly benefiting less experienced practitioners. While overall interpretation time remained unchanged, the use of AI improved diagnostic confidence and sensitivity, especially among junior clinicians. These findings underscore the potential of AI to support less skilled clinicians in acute care settings.

Modelling the effect of seasonal influenza vaccination on the risk of pandemic influenza infection.

BACKGROUND: Recent studies have suggested that vaccination with seasonal influenza vaccine resulted in an apparent higher risk of infection with pandemic influenza H1N1 2009. A simple mathematical model incorporating strain competition and a hypothesised temporary strain-transcending immunity is constructed to investigate this observation. The model assumes that seasonal vaccine has no effect on the risk of infection with pandemic influenza. RESULTS: Results of the model over a range of reproduction numbers and effective vaccination coverage confirm this apparent increased risk in the Northern, but not the Southern, hemisphere. This is due to unvaccinated individuals being more likely to be infected with seasonal influenza (if it is circulating) and developing hypothesised temporary immunity to the pandemic strain. Because vaccinated individuals are less likely to have been infected with seasonal influenza, they are less likely to have developed the hypothesised temporary immunity and are therefore more likely to be infected with pandemic influenza. If the reproduction number for pandemic influenza is increased, as it is for children, an increase in the apparent risk of seasonal vaccination is observed. The maximum apparent risk effect is found when seasonal vaccination coverage is in the range 20-40%. CONCLUSIONS: Only when pandemic influenza is recently preceded by seasonal influenza circulation is there a modelled increased risk of pandemic influenza infection associated with prior receipt of seasonal vaccine.

Body image and attitudes toward male roles in anabolic-androgenic steroid users.

OBJECTIVE: The authors sought to expand on previous observations suggesting that body-image pathology is associated with illicit use of anabolic-androgenic steroids (AAS). In particular, the authors compared current versus past AAS users and short-term versus long-term users in this respect. METHOD: The authors assessed 89 heterosexual men who lifted weights regularly-48 AAS users and 41 nonusers-on measures of self-esteem, attitudes toward male roles, body image, eating-related attitudes and behaviors, and muscle dysmorphia ("reverse anorexia nervosa"). RESULTS: AAS users as a whole showed few differences from nonusers on most measures but showed greater symptoms of muscle dysmorphia (e.g., not allowing their bodies to be seen in public, giving up pleasurable activities because of body-appearance concerns). The current and past AAS users each differed only modestly from nonusers on most measures. Short-term AAS "experimenters" were also largely indistinguishable from nonusers, but the long-term AAS users showed striking and significant differences from nonusers on many measures, including marked symptoms of muscle dysmorphia and stronger endorsement of conventional male roles. CONCLUSIONS: Both body-image pathology and narrow stereotypic views of masculinity appear to be prominent among men with long-term AAS use. Although our cross-sectional observations cannot confirm that these factors help to cause or perpetuate AAS use, a causal hypothesis is certainly plausible and deserving of further testing in longitudinal studies. If these factors are indeed causal, then AAS users might respond to cognitive behavior approaches that simultaneously take aim at both types of maladaptive beliefs.

Tracking scientific interest in the dissociative disorders: a study of scientific publication output 1984-2003.

OBJECTIVE: We attempted to track scientific interest in dissociative amnesia and dissociative identity disorder by estimating the annual output of publications regarding these entities over the last 20 years. METHODS: Using a standard medical index, PsycINFO, we counted the number of indexed publications involving dissociative amnesia and dissociative identity disorder listed for each year. We then compared these rates with those of well-established diagnoses such as anorexia nervosa, alcohol abuse, and schizophrenia. We also systematically reviewed all publications involving dissociative amnesia that appeared in 2003. RESULTS: Annual publications involving dissociative amnesia and dissociative identity disorder rose from low levels in the 1980's to a sharp peak in the mid 1990's, followed by an equally sharp decline to only about one quarter of their peak levels by 2002 and 2003. In contrast, all of the 25 comparison diagnoses in our survey showed constant or steadily rising publication rates; none showed the 'bubble' pattern of the dissociative disorders. Of the 34 papers involving dissociative amnesia identified by PsycINFO for 2003, 10 (32%) appeared skeptical of the validity of dissociative amnesia and/or recovered-memory therapy. Despite a detailed search using multiple medical indices and search terms, we could find only 13 explicit cases of individuals with dissociative amnesia worldwide in the 2003 literature. CONCLUSIONS: Dissociative amnesia and dissociative identity disorder have not generated consistent scientific interest over the years, but instead apparently enjoyed a brief period of fashion that now has waned. Overall, our observations suggest that these diagnostic entities presently do not command widespread scientific acceptance.

Residual neuropsychological effects of illicit 3,4-methylenedioxymethamphetamine (MDMA) in individuals with minimal exposure to other drugs.

BACKGROUND: A substantial literature suggests that users of illicit 3,4-methylenedioxymethamphetamine (MDMA or "ecstasy") display residual cognitive deficits. Most MDMA users, however, use other illicit drugs as well, so it is difficult to be certain that these deficits are due to MDMA, as opposed to other drug use or additional confounding factors. METHODS: We administered a battery of neuropsychological tests to 23 young MDMA users who reported minimal exposure to any other drugs, including alcohol, and to 16 comparison individuals equally involved with the rave subculture, but reporting no MDMA use. We compared the groups by regression analyses adjusting for numerous potentially confounding variables. To test for a possible dose-response effect, we also performed a median split of 12 moderate MDMA users (22-50 lifetime uses) and 11 heavy users (60-450 uses), and compared these subgroups with non-users. RESULTS: MDMA users as a whole performed worse than non-users on most test measures, but these comparisons rarely reached statistical significance. This picture changed markedly in the subgroup analysis: although moderate users displayed virtually no differences from non-users on any measures, the heavy users displayed significant deficits on many measures, particularly those associated with mental processing speed and impulsivity. These differences did not appear explainable by differences in family-of-origin variables, verbal IQ, levels of depression, or time since last MDMA use. CONCLUSIONS: The presence of residual cognitive deficits, even among unusually "pure" frequent users of illicit MDMA, analyzed with adjustment for confounding variables, augments the evidence that MDMA itself, rather than some associated factor, is responsible for the deficits observed.