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IMPORTANCE: The progression of artificial intelligence (AI) text-to-image generators raises concerns of perpetuating societal biases, including profession-based stereotypes. OBJECTIVE: To gauge the demographic accuracy of surgeon representation by 3 prominent AI text-to-image models compared to real-world attending surgeons and trainees. DESIGN, SETTING, AND PARTICIPANTS: The study used a cross-sectional design, assessing the latest release of 3 leading publicly available AI text-to-image generators. Seven independent reviewers categorized AI-produced images. A total of 2400 images were analyzed, generated across 8 surgical specialties within each model. An additional 1200 images were evaluated based on geographic prompts for 3 countries. The study was conducted in May 2023. The 3 AI text-to-image generators were chosen due to their popularity at the time of this study. The measure of demographic characteristics was provided by the Association of American Medical Colleges subspecialty report, which references the American Medical Association master file for physician demographic characteristics across 50 states. Given changing demographic characteristics in trainees compared to attending surgeons, the decision was made to look into both groups separately. Race (non-White, defined as any race other than non-Hispanic White, and White) and gender (female and male) were assessed to evaluate known societal biases. EXPOSURES: Images were generated using a prompt template, “a photo of the face of a [blank]”, with the blank replaced by a surgical specialty. Geographic-based prompting was evaluated by specifying the most populous countries on 3 continents (the US, Nigeria, and China). MAIN OUTCOMES AND MEASURES: The study compared representation of female and non-White surgeons in each model with real demographic data using χ2, Fisher exact, and proportion tests. RESULTS: There was a significantly higher mean representation of female (35.8% vs 14.7%; P < .001) and non-White (37.4% vs 22.8%; P < .001) surgeons among trainees than attending surgeons. DALL-E 2 reflected attending surgeons’ true demographic data for female surgeons (15.9% vs 14.7%; P = .39) and non-White surgeons (22.6% vs 22.8%; P = .92) but underestimated trainees’ representation for both female (15.9% vs 35.8%; P < .001) and non-White (22.6% vs 37.4%; P < .001) surgeons. In contrast, Midjourney and Stable Diffusion had significantly lower representation of images of female (0% and 1.8%, respectively; P < .001) and non-White (0.5% and 0.6%, respectively; P < .001) surgeons than DALL-E 2 or true demographic data. Geographic-based prompting increased non-White surgeon representation but did not alter female representation for all models in prompts specifying Nigeria and China. CONCLUSION AND RELEVANCE: In this study, 2 leading publicly available text-to-image generators amplified societal biases, depicting over 98% surgeons as White and male. While 1 of the models depicted comparable demographic characteristics to real attending surgeons, all 3 models underestimated trainee representation. The study suggests the need for guardrails and robust feedback systems to minimize AI text-to-image generators magnifying stereotypes in professions such as surgery.

A noninvasive prediction tool for preoperative MRI helped identify patients likely to develop new symptoms at adjacent levels after anterior cervical diskectomy.

Study Design: Systematic review and meta-analysis.Objective: To perform a systematic review of clinical outcomes between stand-alone anchored spacers and traditional cages with plate fixation for dysphagia and pseudoarthrosis using data from clinical trials.Methods: Our search protocol was added to PROSPERO register and systematic review using PRISMA method was performed. Then, we systematically searched for studies addressing stand-alone anchored spacers in patients who underwent ACDF. Mean Neck Disability Index (NDI), dysphagia incidence % (Dinc%), and Swallowing–Quality of Life (SQOL) scores during preoperative, immediate postoperative and last follow-up visits were extracted. Chi-square and analysis of variance (ANOVA) tests were used for statistical comparisons (P≤ .05).Results: The initial search generated 506 articles in CENTRAL and 40 articles in MEDLINE. Finally, 14 articles were included. Total number of patients was 1173 (583 anchored stand-alone and 590 plate). Dinc% scores were statistically significantly lower in the stand-alone anchored spacer compared to the plate-screw construct (P≤ .05). ANOVA showed no statistically significant difference in the comparisons of SQOL. On the other hand, NDI scores were statistically significantly lower in baseline of stand-alone anchored spacer and the plate-screw construct compared with both immediate postoperative and last follow-up visits (P≤ .05).Conclusions: Our study results revealed that the stand-alone anchored spacers were associated with less dysphagia in the immediate and last follow-up.

Study Design: Systematic review.Objectives: Superiority claims for medical devices are commonly derived from noninferiority trials, but interpretation of such claims can be challenging. This study aimed to (a) establish the prevalence of noninferiority and superiority designs among spinal device trials, (b) assess the frequency of post hoc superiority claims from noninferiority studies, and (c) critically evaluate the risk of bias in claims that could translate to misleading conclusions.Methods: Study bias was assessed using the Cochrane Risk of Bias Tool. The risk of bias for the superiority claim was established based on post hoc hypothesis specification, analysis of the intention-to-treat population, post hoc modification of a priori primary outcomes, and sensitivity analyses.Results: Forty-one studies were identified from 1895 records. Nineteen (46%) were noninferiority trials. Fifteen more (37%) were noninferiority trials with a secondary superiority hypothesis specified a priori. Seven (17%) were superiority trials. Of the 34 noninferiority trials, 14 (41%) made superiority claims. A medium or high risk of bias was related to the superiority claim in 9 of those trials (64%), which was due to the analyzed population, lacking sensitivity analyses, claims not being robust during sensitivity analyses, post hoc hypotheses, or modified endpoints. Only 4 of the 14 (29%) noninferiority studies provided low bias in the superiority claim, compared with 3 of the 5 (60%) superiority trials.Conclusions: Health care decision makers should carefully evaluate the risk of bias in each superiority claim and weigh their conclusions appropriately.

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Study Design: Review and technical report.Objective: Intraoperative ultrasound has been used by spine surgeons since the early 1980s. Since that time, more advanced modes of intraoperative imaging and navigation have become widely available. Although the use of ultrasound during spine surgery has fallen out of favor, it remains the only true real-time imaging modality that allows surgeons to visualize soft tissue anatomy instantly and continuously while operating. It is our objective to demonstrate that for this reason, ultrasound is a useful adjunctive technique for spine surgeons, especially when approaching intradural lesions or when addressing pathology in the ventral spinal canal via a posterior approach.Methods: Using PubMed, the existing literature regarding the use of intraoperative ultrasound during spinal surgery was evaluated. Also, surgical case logs were reviewed to identify spinal operations during which intraoperative ultrasound was used. Illustrative cases were selected and reviewed in detail.Results: This article provides a brief review of the history of intraoperative ultrasound in spine surgery and describes certain surgical scenarios during which this technique might be useful. Several illustrative cases are provided from our own experience.Conclusions: Surgeons should consider the use of intraoperative ultrasound when approaching intradural lesions or when addressing pathology ventral to the thecal sac via a posterior approach.

A biomechanical study using human cadaveric lumbar spines.