Safdar, Aleeza

OBJECTIVE Artificial intelligence (AI) is increasingly capable of academic writing, with large language models such as ChatGPT showing potential to assist or even generate scientific manuscripts. However, concerns remain regarding the quality, reliability, and interpretive capabilities of AI-generated content. The authors’ study aimed to compare the quality of a human-written versus an AI-generated scientific manuscript to evaluate the strengths and limitations of AI in the context of academic publishing. METHODS Two manuscripts were developed using identical titles, abstracts, and tables of a simulated analysis: one authored by a physician with multiple publications, and the other generated by ChatGPT-4o. Three independent and blinded reviewers—two human and one AI—assessed each manuscript across five domains: clarity and readability, coherence and flow, technical accuracy, depth, and conciseness and precision. Each category was scored on a 10-point scale, and qualitative feedback was collected to highlight specific strengths and weaknesses. Additionally, all reviewers were asked to deduce authorship of the manuscripts. RESULTS The AI-generated manuscript scored higher in clarity and readability (mean 9.0 vs 7.2), but lower in technical accuracy (mean 6.3 vs 9.3) and depth (mean 5.5 vs 7.5). However, reviewers noted that the AI version lacked depth, critical analysis, and contextual interpretation. All reviewers accurately identified the authorship of each manuscript and tended to rate the version more favorably when it aligned with their own origin (human or AI); i.e., human reviewers assigned higher scores to the human-written manuscript, while the AI reviewer scored the AI-generated manuscript higher. CONCLUSIONS Although AI models can improve some aspects of scientific writing, particularly clarity and readability, they fall short in critical reasoning and contextual understanding. This reinforces the importance of human authorship and oversight in maintaining the critical analysis and scientific accuracy essential for academic publishing. AI may be used as a complementary tool to support, rather than replace, human-led scientific writing.

Study design: Cohort study. Objective: This study aimed to evaluate influence of facet cysts on outcomes in patients undergoing lumbar decompression, and the influence of spinal fusion in patients undergoing decompression for facet cysts. Summary of Background Data: The impact of facet cysts on outcomes following lumbar spine surgery for degenerative spine disease remains unclear. Methods: Our multicenter institutional Neurosurgery Enterprise Registry was queried for patients who underwent lumbar decompression for degenerative spine conditions. Patients were divided into 2 cohorts: those with lumbar spine facet cysts and those without. Retrospective propensity-score matching was performed using 13 baseline variables to adjust for potential confounding factors, including age, sex, race, body mass index, and comorbidities. Secondary analysis comparing outcomes in patients with facet cysts cases undergoing decompression only versus those undergoing decompression and fusion was conducted. Results: A total of 6768 patients were reviewed, of which 188 (2.8%) had facet cysts, which underwent lumbar decompression during 2019–2023. After 3:1 matching, patients with facet cysts were compared with 564 patients without it. We found no significant differences in LOS, nonroutine discharge, postoperative complications, readmissions, and reoperations. In addition, in cases with facet cysts, decompression reported no increased risk for discharge opioids, readmissions, and reoperations, whereas fusion (in a separate cohort of 127 patients with facet cysts) was associated with an increased risk for nonroutine discharge (3.7% vs. 10.2%, P=0.021), complications (2.1% vs. 7.1%, P=0.042), and longer LOS (0.89±1.69 vs. 3.74±2.03 d, P<0.001) and operative time (138.78±62.99 vs. 273.07±111.51 min, P <0.001). Conclusions: The presence of facet cysts does not significantly affect outcomes of lumbar decompression for degenerative spine disease. Decompression alone for facet cysts can have better outcomes than decompression and fusion. The need for fusion should be weighted with its higher risks of complications, longer hospital stays, and nonroutine discharges.

Study Design. Retrospective observational study. Objective. To evaluate whether the combined American Spine Registry and Medicare (ASR/CMS) data yield substantially different findings versus ASR data alone with regard to key parameters such as risk stratification, complication rates, and readmission rates in lumbar surgery investigated through an analysis of 8755 spondylolisthesis cases. Summary of Background Data. Medicare data correlation has been effective for determining revision rates for other procedures, such as total hip replacement. Our aim is to determine whether these findings are translatable in the realm of lumbar spinal surgery investigated through an analysis of 8755 spondylolisthesis cases. Materials and Methods. The American Spine Registry (ASR) was queried for Medicare-eligible patients who underwent lumbar spinal fusion for lumbar spondylolisthesis. This cohort was analyzed based on ASR data alone in comparison to the same patients in the combined ASR/Medicare (ASR/CMS) data set. The primary outcome of interest was readmission at 30 and 90 days postoperatively. Results. There were 8755 Medicare-eligible cases with a diagnosis of spondylolisthesis within the ASR. The mean age was 72.7 years and 60.8% were female. Medical comorbidities were more frequently detected in the combined ASR/CMS data set, reflected by a higher mean Charlson Comorbidity Index score (3.49 vs. 3.27, P<0.001). Hospital readmission rates were significantly higher in the combined ASR/CMS data set at both 30 days (4.89% vs. 1.83%, P<0.001) and 90 days (7.68% vs. 2.66%, P<0.001), with notable increases in readmissions for infections and medical complications. Discharge disposition remained comparable across data sets, with most patients discharged to home or home health care. Conclusion. This study demonstrates that integrating patient-identified Medicare data with the ASR provides a more comprehensive assessment of outcomes for lumbar spinal fusion surgery as demonstrated through an analysis of 8755 spondylolisthesis cases. These findings, establish the importance of multisource data linkage to overcome the limitations of single-source registries, thereby enhancing data quality for clinical decision-making and quality improvement in spinal surgery.