Defining surgical risk in octogenarians undergoing paraesophageal hernia repair

Wilson, Hadley H.; Ayuso, Sullivan A.; Rose, Michael; Ku, Dau; Scarola, Gregory T.; Augenstein, Vedra A.; Colavita, Paul D.; Heniford, B. Todd

doi:10.1007/s00464-023-10270-z

Cited by 7 publications

(2 citation statements)

References 27 publications

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“…Wilson et. al have recently published data with a similar design, using the Nationwide Readmission Database to compare octogenarians against adult patients aged 18–79 undergoing paraesophageal hernia repair [ 10 ]. After controlling for multiple variables including Charlson Comorbidity Index scores, they did not find that octogenarian status was interpedently predictive of mortality, though undergoing an emergent operation was.…”

Section: Discussionmentioning

confidence: 99%

Morbidity and mortality following hiatal hernia repair in geriatric patients: a multicenter research network study

Kumar,

Rama,

Koeneman

et al. 2024

Surg Endosc

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Background Hiatal hernia is a common surgical pathology. Such hernias can be found incidentally and patients may opt for an initial nonoperative approach though many will pursue surgery after symptom progression. Data on the effects of age on the outcomes of hiatal hernia repair may help inform this decision-making process. Methods The TriNetX database was queried for all adult patients undergoing hiatal hernia repair from 2000 to 2023. Patients were divided into elective and emergent cohorts on the basis of diagnosis codes indicating obstruction or gangrene. Patients aged 80–89 were compared against those aged 65–79 in unadjusted analysis. Logistic regression models controlling for additional health history covariates were created to calculate odds ratios for primary outcomes. Results There were 2310 octogenarians and 15,295 seniors who underwent elective hiatal hernia repair, and 406 octogenarians and 1462 seniors who underwent emergent repair during the study period. The vast majority of patients in both groups underwent minimally invasive operations. In the elective cohort, octogenarians had higher rates of mortality, malnutrition, sepsis, respiratory failure, pneumonia, DVT, blood transfusion, and discharge to nursing facility. In the emergent cohort, octogenarians had higher rates of mortality, malnutrition, sepsis, and respiratory failure. The odds ratios for mortality in the elective and emergent cohorts were 3.9 (95% CI 3.1–5.0) and 3.5 (95% CI 2.1–5.6), respectively. Conclusion Octogenarians are at a meaningfully increased risk for mortality and morbidity after both elective and emergent hiatal hernia repair compared to senior-aged patients. Greater consideration should be given to surgical repair prior to the 8th decade of life.

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Section: Discussionmentioning

confidence: 99%

Morbidity and mortality following hiatal hernia repair in geriatric patients: a multicenter research network study

Kumar,

Rama,

Koeneman

et al. 2024

Surg Endosc

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“…Ten additional abstracts 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 were used to investigate the chatbots’ ability to generate scientific abstracts. These abstracts were written by 5 different trainees within the first 6 months of their research year at the same medical center between 2018 to 2023 to account for the novice period.…”

Section: Methodsmentioning

confidence: 99%

Comparison of Medical Research Abstracts Written by Surgical Trainees and Senior Surgeons or Generated by Large Language Models

Holland,

Lorenz,

Cavanagh

et al. 2024

JAMA Netw Open

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ImportanceArtificial intelligence (AI) has permeated academia, especially OpenAI Chat Generative Pretrained Transformer (ChatGPT), a large language model. However, little has been reported on its use in medical research.ObjectiveTo assess a chatbot’s capability to generate and grade medical research abstracts.Design, Setting, and ParticipantsIn this cross-sectional study, ChatGPT versions 3.5 and 4.0 (referred to as chatbot 1 and chatbot 2) were coached to generate 10 abstracts by providing background literature, prompts, analyzed data for each topic, and 10 previously presented, unassociated abstracts to serve as models. The study was conducted between August 2023 and February 2024 (including data analysis).ExposureAbstract versions utilizing the same topic and data were written by a surgical trainee or a senior physician or generated by chatbot 1 and chatbot 2 for comparison. The 10 training abstracts were written by 8 surgical residents or fellows, edited by the same senior surgeon, at a high-volume hospital in the Southeastern US with an emphasis on outcomes-based research. Abstract comparison was then based on 10 abstracts written by 5 surgical trainees within the first 6 months of their research year, edited by the same senior author.Main Outcomes and MeasuresThe primary outcome measurements were the abstract grades using 10- and 20-point scales and ranks (first to fourth). Abstract versions by chatbot 1, chatbot 2, junior residents, and the senior author were compared and judged by blinded surgeon-reviewers as well as both chatbot models. Five academic attending surgeons from Denmark, the UK, and the US, with extensive experience in surgical organizations, research, and abstract evaluation served as reviewers.ResultsSurgeon-reviewers were unable to differentiate between abstract versions. Each reviewer ranked an AI-generated version first at least once. Abstracts demonstrated no difference in their median (IQR) 10-point scores (resident, 7.0 [6.0-8.0]; senior author, 7.0 [6.0-8.0]; chatbot 1, 7.0 [6.0-8.0]; chatbot 2, 7.0 [6.0-8.0]; P = .61), 20-point scores (resident, 14.0 [12.0-7.0]; senior author, 15.0 [13.0-17.0]; chatbot 1, 14.0 [12.0-16.0]; chatbot 2, 14.0 [13.0-16.0]; P = .50), or rank (resident, 3.0 [1.0-4.0]; senior author, 2.0 [1.0-4.0]; chatbot 1, 3.0 [2.0-4.0]; chatbot 2, 2.0 [1.0-3.0]; P = .14). The abstract grades given by chatbot 1 were comparable to the surgeon-reviewers’ grades. However, chatbot 2 graded more favorably than the surgeon-reviewers and chatbot 1. Median (IQR) chatbot 2-reviewer grades were higher than surgeon-reviewer grades of all 4 abstract versions (resident, 14.0 [12.0-17.0] vs 16.9 [16.0-17.5]; P = .02; senior author, 15.0 [13.0-17.0] vs 17.0 [16.5-18.0]; P = .03; chatbot 1, 14.0 [12.0-16.0] vs 17.8 [17.5-18.5]; P = .002; chatbot 2, 14.0 [13.0-16.0] vs 16.8 [14.5-18.0]; P = .04). When comparing the grades of the 2 chatbots, chatbot 2 gave higher median (IQR) grades for abstracts than chatbot 1 (resident, 14.0 [13.0-15.0] vs 16.9 [16.0-17.5]; P = .003; senior author, 13.5 [13.0-15.5] vs 17.0 [16.5-18.0]; P = .004; chatbot 1, 14.5 [13.0-15.0] vs 17.8 [17.5-18.5]; P = .003; chatbot 2, 14.0 [13.0-15.0] vs 16.8 [14.5-18.0]; P = .01).Conclusions and RelevanceIn this cross-sectional study, trained chatbots generated convincing medical abstracts, undifferentiable from resident or senior author drafts. Chatbot 1 graded abstracts similarly to surgeon-reviewers, while chatbot 2 was less stringent. These findings may assist surgeon-scientists in successfully implementing AI in medical research.

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