Sex and gender-based analysis and diversity metric reporting in acute care trials published in high-impact journals: a systematic review.

OBJECTIVE: To characterise sex and gender-based analysis (SGBA) and diversity metric reporting, representation of female/women participants in acute care trials and temporal changes in reporting before and after publication of the 2016 Sex and Gender Equity in Research guideline. DESIGN: Systematic review. DATA SOURCES: We searched MEDLINE for trials published in five leading medical journals in 2014, 2018 and 2020. STUDY SELECTION: Trials that enrolled acutely ill adults, compared two or more interventions and reported at least one clinical outcome. DATA ABSTRACTION AND SYNTHESIS: 4 reviewers screened citations and 22 reviewers abstracted data, in duplicate. We compared reporting differences between intensive care unit (ICU) and cardiology trials. RESULTS: We included 88 trials (75 (85.2%) ICU and 13 (14.8%) cardiology) (n=111 428; 38 140 (34.2%) females/women). Of 23 (26.1%) trials that reported an SGBA, most used a forest plot (22 (95.7%)), were prespecified (21 (91.3%)) and reported a sex-by-intervention interaction with a significance test (19 (82.6%)). Discordant sex and gender terminology were found between headings and subheadings within baseline characteristics tables (17/32 (53.1%)) and between baseline characteristics tables and SGBA (4/23 (17.4%)). Only 25 acute care trials (28.4%) reported race or ethnicity. Participants were predominantly white (78.8%) and male/men (65.8%). No trial reported gendered-social factors. SGBA reporting and female/women representation did not improve temporally. Compared with ICU trials, cardiology trials reported significantly more SGBA (15/75 (20%) vs 8/13 (61.5%) p=0.005). CONCLUSIONS: Acute care trials in leading medical journals infrequently included SGBA, female/women and non-white trial participants, reported race or ethnicity and never reported gender-related factors. Substantial opportunity exists to improve SGBA and diversity metric reporting and recruitment of female/women participants in acute care trials. PROSPERO REGISTRATION NUMBER: CRD42022282565.

Predicting amputation using machine learning: A systematic review.

Amputation is an irreversible, last-line treatment indicated for a multitude of medical problems. Delaying amputation in favor of limb-sparing treatment may lead to increased risk of morbidity and mortality. This systematic review aims to synthesize the literature on how ML is being applied to predict amputation as an outcome. OVID Embase, OVID Medline, ACM Digital Library, Scopus, Web of Science, and IEEE Xplore were searched from inception to March 5, 2023. 1376 studies were screened; 15 articles were included. In the diabetic population, models ranged from sub-optimal to excellent performance (AUC: 0.6-0.94). In trauma patients, models had strong to excellent performance (AUC: 0.88-0.95). In patients who received amputation secondary to other etiologies (e.g.: burns and peripheral vascular disease), models had similar performance (AUC: 0.81-1.0). Many studies were found to have a high PROBAST risk of bias, most often due to small sample sizes. In conclusion, multiple machine learning models have been successfully developed that have the potential to be superior to traditional modeling techniques and prospective clinical judgment in predicting amputation. Further research is needed to overcome the limitations of current studies and to bring applicability to a clinical setting.

Developmental Foot Deformities in Patients with Connective Tissue Disorders.

¼: Foot deformities make up a large percentage of all orthopaedic complaints in patients with Down syndrome, Marfan syndrome, Ehlers-Danlos syndrome, Larsen syndrome, and osteogenesis imperfecta. ¼: Some common causes of foot deformities in these conditions include increased ligament laxity, hypotonia, and hypermobility of the joints. ¼: Treatment options for syndromic foot deformities include the use of foot orthoses, physical therapy, bracing, and various surgical procedures. ¼: There is limited evidence supporting the use of surgical intervention to correct foot deformities associated with Down syndrome, Marfan syndrome, Ehlers-Danlos syndrome, Larsen syndrome, and osteogenesis imperfecta. Therefore, further research is needed to determine the short-term and long-term outcomes of these procedures.