JAMA surgeryPub Date : 2024-10-09DOI: 10.1001/jamasurg.2024.4285
Armaan K Malhotra, Rachael H Jaffe, Husain Shakil, Francois Mathieu, Avery B Nathens, Abhaya V Kulkarni, Calvin Diep, Eva Y Yuan, Karim S Ladha, Peter C Coyte, Jefferson R Wilson, Walter P Wodchis, Christopher D Witiw
{"title":"Unemployment and Personal Income Loss After Traumatic Brain Injury.","authors":"Armaan K Malhotra, Rachael H Jaffe, Husain Shakil, Francois Mathieu, Avery B Nathens, Abhaya V Kulkarni, Calvin Diep, Eva Y Yuan, Karim S Ladha, Peter C Coyte, Jefferson R Wilson, Walter P Wodchis, Christopher D Witiw","doi":"10.1001/jamasurg.2024.4285","DOIUrl":"https://doi.org/10.1001/jamasurg.2024.4285","url":null,"abstract":"<p><strong>Importance: </strong>Employment and personal income loss after traumatic brain injury is a major source of postinjury stress and a barrier to societal reintegration. The magnitude of labor market ramifications following traumatic brain injury remains largely unknown.</p><p><strong>Objectives: </strong>To quantify the 3-year postinjury labor market consequences following traumatic brain injury in Canada. To also estimate the incurred national labor market cost over the study period.</p><p><strong>Design, setting, and participants: </strong>This retrospective quasi-experimental, pan-Canadian observational cohort study used linked administrative health and federal taxation data obtained between 2007 and 2017. Mixed-effects difference-in-difference regressions were constructed to estimate the annualized magnitude of the personal income and employment loss during each of the 3 years following injury, respectively, relative to preinjury baseline. Participants included tax-filing adult (19 to 61 years old) traumatic brain injury survivors.</p><p><strong>Exposure: </strong>Traumatic brain injury.</p><p><strong>Main outcome measures: </strong>Coprimary outcomes were personal income loss and the proportion of newly unemployed individuals per annum. Secondary objectives were to quantify income and employment loss within mild, moderate, and severe traumatic brain injury subgroups.</p><p><strong>Results: </strong>A total of 18 050 patients with traumatic brain injury between 2007 and 2017 were identified (mean age, 38.0 [SD, 12.4] years; 13 360 male [74.0%]), each of whom was followed up with for 3 consecutive fiscal years. Mean income was CAD $42 600 (US $31 083) in the fiscal year prior to injury and 82% were employed at time of injury. The adjusted mean loss of personal income was CAD $7635 (US $5650) in the first year after injury (Y+1) and CAD $5000 (US $3700) in the third year after injury (Y+3) relative to uninjured controls. In each of the 3 postinjury years, 7.8% individuals were newly unemployed compared with the preinjury baseline. The adjusted average personal income loss for mild, moderate, and severe traumatic brain injury subgroups were CAD $3354 (US $2482), CAD $6750 (US $4995), and CAD $17 375 (US $12 859), respectively, at Y+3; the proportion of unemployed individuals increased by 5.8%, 9.2%, and 20% across the same groups at Y+3 after injury relative to preinjury baseline. The estimated total reduction in personal income aggregated over the 3 postinjury years for the affected participants was CAD $588 million (US $435 million).</p><p><strong>Conclusions and relevance: </strong>This work represents national cohort data quantifying the labor market implications of traumatic brain injury. These results may be used to inform economic evaluations and social service resource allocation.</p>","PeriodicalId":14690,"journal":{"name":"JAMA surgery","volume":null,"pages":null},"PeriodicalIF":15.7,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142390614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JAMA surgeryPub Date : 2024-10-09DOI: 10.1001/jamasurg.2024.4297
Thomas H Shin, Stanley W Ashley, Thomas C Tsai
{"title":"Defining the Role of Machine Learning in Optimizing Surgical Outcomes.","authors":"Thomas H Shin, Stanley W Ashley, Thomas C Tsai","doi":"10.1001/jamasurg.2024.4297","DOIUrl":"https://doi.org/10.1001/jamasurg.2024.4297","url":null,"abstract":"","PeriodicalId":14690,"journal":{"name":"JAMA surgery","volume":null,"pages":null},"PeriodicalIF":15.7,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142390609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JAMA surgeryPub Date : 2024-10-09DOI: 10.1001/jamasurg.2024.4296
Nathan N O'Hara
{"title":"The Untapped Potential of Tax Data in Health Research.","authors":"Nathan N O'Hara","doi":"10.1001/jamasurg.2024.4296","DOIUrl":"https://doi.org/10.1001/jamasurg.2024.4296","url":null,"abstract":"","PeriodicalId":14690,"journal":{"name":"JAMA surgery","volume":null,"pages":null},"PeriodicalIF":15.7,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142390613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JAMA surgeryPub Date : 2024-10-09DOI: 10.1001/jamasurg.2024.4299
Jeremy A Balch, Matthew M Ruppert, Ziyuan Guan, Timothy R Buchanan, Kenneth L Abbott, Benjamin Shickel, Azra Bihorac, Muxuan Liang, Gilbert R Upchurch, Christopher J Tignanelli, Tyler J Loftus
{"title":"Risk-Specific Training Cohorts to Address Class Imbalance in Surgical Risk Prediction.","authors":"Jeremy A Balch, Matthew M Ruppert, Ziyuan Guan, Timothy R Buchanan, Kenneth L Abbott, Benjamin Shickel, Azra Bihorac, Muxuan Liang, Gilbert R Upchurch, Christopher J Tignanelli, Tyler J Loftus","doi":"10.1001/jamasurg.2024.4299","DOIUrl":"10.1001/jamasurg.2024.4299","url":null,"abstract":"<p><strong>Importance: </strong>Machine learning tools are increasingly deployed for risk prediction and clinical decision support in surgery. Class imbalance adversely impacts predictive performance, especially for low-incidence complications.</p><p><strong>Objective: </strong>To evaluate risk-prediction model performance when trained on risk-specific cohorts.</p><p><strong>Design, setting, and participants: </strong>This cross-sectional study performed from February 2024 to July 2024 deployed a deep learning model, which generated risk scores for common postoperative complications. A total of 109 445 inpatient operations performed at 2 University of Florida Health hospitals from June 1, 2014, to May 5, 2021 were examined.</p><p><strong>Exposures: </strong>The model was trained de novo on separate cohorts for high-risk, medium-risk, and low-risk Common Procedure Terminology codes defined empirically by incidence of 5 postoperative complications: (1) in-hospital mortality; (2) prolonged intensive care unit (ICU) stay (≥48 hours); (3) prolonged mechanical ventilation (≥48 hours); (4) sepsis; and (5) acute kidney injury (AKI). Low-risk and high-risk cutoffs for complications were defined by the lower-third and upper-third prevalence in the dataset, except for mortality, cutoffs for which were set at 1% or less and greater than 3%, respectively.</p><p><strong>Main outcomes and measures: </strong>Model performance metrics were assessed for each risk-specific cohort alongside the baseline model. Metrics included area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), F1 scores, and accuracy for each model.</p><p><strong>Results: </strong>A total of 109 445 inpatient operations were examined among patients treated at 2 University of Florida Health hospitals in Gainesville (77 921 procedures [71.2%]) and Jacksonville (31 524 procedures [28.8%]). Median (IQR) patient age was 58 (43-68) years, and median (IQR) Charlson Comorbidity Index score was 2 (0-4). Among 109 445 operations, 55 646 patients were male (50.8%), and 66 495 patients (60.8%) underwent a nonemergent, inpatient operation. Training on the high-risk cohort had variable impact on AUROC, but significantly improved AUPRC (as assessed by nonoverlapping 95% confidence intervals) for predicting mortality (0.53; 95% CI, 0.43-0.64), AKI (0.61; 95% CI, 0.58-0.65), and prolonged ICU stay (0.91; 95% CI, 0.89-0.92). It also significantly improved F1 score for mortality (0.42; 95% CI, 0.36-0.49), prolonged mechanical ventilation (0.55; 95% CI, 0.52-0.58), sepsis (0.46; 95% CI, 0.43-0.49), and AKI (0.57; 95% CI, 0.54-0.59). After controlling for baseline model performance on high-risk cohorts, AUPRC increased significantly for in-hospital mortality only (0.53; 95% CI, 0.42-0.65 vs 0.29; 95% CI, 0.21-0.40).</p><p><strong>Conclusion and relevance: </strong>In this cross-sectional study, by training separate models using a priori knowledge for procedure-","PeriodicalId":14690,"journal":{"name":"JAMA surgery","volume":null,"pages":null},"PeriodicalIF":15.7,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11465118/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142390612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JAMA surgeryPub Date : 2024-10-09DOI: 10.1001/jamasurg.2024.4282
Ju-Hee Lee, Jiyeong Kim, Ji Yoon Choi
{"title":"Extended Follow-Up in Patients With Gastric Cancer-Applicable to Western Patients?-Reply.","authors":"Ju-Hee Lee, Jiyeong Kim, Ji Yoon Choi","doi":"10.1001/jamasurg.2024.4282","DOIUrl":"https://doi.org/10.1001/jamasurg.2024.4282","url":null,"abstract":"","PeriodicalId":14690,"journal":{"name":"JAMA surgery","volume":null,"pages":null},"PeriodicalIF":15.7,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142390611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JAMA surgeryPub Date : 2024-10-02DOI: 10.1001/jamasurg.2024.2749
Jennifer E B Harman, David C Linehan, Anusha Naganathan
{"title":"Supporting Surgeon-Scientists to Prosper as Researchers.","authors":"Jennifer E B Harman, David C Linehan, Anusha Naganathan","doi":"10.1001/jamasurg.2024.2749","DOIUrl":"https://doi.org/10.1001/jamasurg.2024.2749","url":null,"abstract":"","PeriodicalId":14690,"journal":{"name":"JAMA surgery","volume":null,"pages":null},"PeriodicalIF":15.7,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142361523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JAMA surgeryPub Date : 2024-10-02DOI: 10.1001/jamasurg.2024.4183
Rodney H Breau, Luke T Lavallée, Ilias Cagiannos, Franco Momoli, Gregory L Bryson, Salmaan Kanji, Christopher Morash, Alexis F Turgeon, Ryan Zarychanski, Brett L Houston, Daniel I McIsaac, Ranjeeta Mallick, Greg A Knoll, Girish Kulkarni, Jonathan Izawa, Fred Saad, Wassim Kassouf, Vincent Fradet, Ricardo Rendon, Bobby Shayegan, Adrian Fairey, Darrel E Drachenberg, Dean Fergusson
{"title":"Tranexamic Acid During Radical Cystectomy: A Randomized Clinical Trial.","authors":"Rodney H Breau, Luke T Lavallée, Ilias Cagiannos, Franco Momoli, Gregory L Bryson, Salmaan Kanji, Christopher Morash, Alexis F Turgeon, Ryan Zarychanski, Brett L Houston, Daniel I McIsaac, Ranjeeta Mallick, Greg A Knoll, Girish Kulkarni, Jonathan Izawa, Fred Saad, Wassim Kassouf, Vincent Fradet, Ricardo Rendon, Bobby Shayegan, Adrian Fairey, Darrel E Drachenberg, Dean Fergusson","doi":"10.1001/jamasurg.2024.4183","DOIUrl":"10.1001/jamasurg.2024.4183","url":null,"abstract":"<p><strong>Importance: </strong>Among cancer surgeries, patients requiring open radical cystectomy have the highest risk of red blood cell (RBC) transfusion. Prophylactic tranexamic acid (TXA) reduces blood loss during cardiac and orthopedic surgery, and it is possible that similar effects of TXA would be observed during radical cystectomy.</p><p><strong>Objective: </strong>To determine whether TXA, administered before incision and for the duration of radical cystectomy, reduced the number of RBC transfusions received by patients up to 30 days after surgery.</p><p><strong>Design, setting, and participants: </strong>The Tranexamic Acid During Cystectomy Trial (TACT) was a double-blind, placebo-controlled, randomized clinical trial with enrollment between June 2013 and January 2021. This multicenter trial was conducted in 10 academic centers. A consecutive sample of patients was eligible if the patients had a planned open radical cystectomy for the treatment of bladder cancer.</p><p><strong>Intervention: </strong>Before incision, patients in the intervention arm received a loading dose of intravenous TXA, 10 mg/kg, followed by a maintenance infusion of 5 mg/kg per hour for the duration of the surgery. In the control arm, patients received indistinguishable matching placebo.</p><p><strong>Main outcomes and measures: </strong>The primary outcome was receipt of RBC transfusion up to 30 days after surgery.</p><p><strong>Results: </strong>A total of 386 patients were assessed for eligibility, and 33 did not meet eligibility. Of 353 randomized patients (median [IQR] age, 69 [62-75] years; 263 male [74.5%]), 344 were included in the intention-to-treat analysis. RBC transfusion up to 30 days occurred in 64 of 173 patients (37.0%) in the TXA group and 64 of 171 patients (37.4%) in the placebo group (relative risk, 0.99; 95% CI, 0.83-1.18). There were no differences in secondary outcomes among the TXA group vs placebo group including mean (SD) number of RBC units transfused (0.9 [1.5] U vs 1.1 [1.8] U; P = .43), estimated blood loss (927 [733] mL vs 963 [624] mL; P = .52), intraoperative transfusion (28.3% [49 of 173] vs 24.0% [41 of 171]; P = .08), or venous thromboembolic events (3.5% [6 of 173] vs 2.9% [5 of 171]; P = .57). Non-transfusion-related adverse events were similar between groups.</p><p><strong>Conclusions and relevance: </strong>Results of this randomized clinical trial reveal that TXA did not reduce blood transfusion in patients undergoing open radical cystectomy for bladder cancer. Based on this trial, routine use of TXA during open radical cystectomy is not recommended.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov Identifier: NCT01869413.</p>","PeriodicalId":14690,"journal":{"name":"JAMA surgery","volume":null,"pages":null},"PeriodicalIF":15.7,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11447623/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142361524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}