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Namavarian A, Gabinet-Equihua A, Deng Y, Khalid S, Ziai H, Deutsch K, Huang J, Gilbert RW, Goldstein DP, Yao CMKL, Irish JC, Enepekides DJ, Higgins KM, Rudzicz F, Eskander A, Xu W, de Almeida JR. Length of Stay Prediction Models for Oral Cancer Surgery: Machine Learning, Statistical and ACS-NSQIP. Laryngoscope 2024; 134:3664-3672. [PMID: 38651539 DOI: 10.1002/lary.31443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 03/17/2024] [Accepted: 03/27/2024] [Indexed: 04/25/2024]
Abstract
OBJECTIVE Accurate prediction of hospital length of stay (LOS) following surgical management of oral cavity cancer (OCC) may be associated with improved patient counseling, hospital resource utilization and cost. The objective of this study was to compare the performance of statistical models, a machine learning (ML) model, and The American College of Surgeons National Surgical Quality Improvement Program's (ACS-NSQIP) calculator in predicting LOS following surgery for OCC. MATERIALS AND METHODS A retrospective multicenter database study was performed at two major academic head and neck cancer centers. Patients with OCC who underwent major free flap reconstructive surgery between January 2008 and June 2019 surgery were selected. Data were pooled and split into training and validation datasets. Statistical and ML models were developed, and performance was evaluated by comparing predicted and actual LOS using correlation coefficient values and percent accuracy. RESULTS Totally 837 patients were selected with mean patient age being 62.5 ± 11.7 [SD] years and 67% being male. The ML model demonstrated the best accuracy (validation correlation 0.48, 4-day accuracy 70%), compared with the statistical models: multivariate analysis (0.45, 67%) and least absolute shrinkage and selection operator (0.42, 70%). All were superior to the ACS-NSQIP calculator's performance (0.23, 59%). CONCLUSION We developed statistical and ML models that predicted LOS following major free flap reconstructive surgery for OCC. Our models demonstrated superior predictive performance to the ACS-NSQIP calculator. The ML model identified several novel predictors of LOS. These models must be validated in other institutions before being used in clinical practice. LEVEL OF EVIDENCE 3 Laryngoscope, 134:3664-3672, 2024.
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Affiliation(s)
- Amirpouyan Namavarian
- Department of Otolaryngology-Head & Neck Surgery, University of Toronto, Toronto, Ontario, Canada
| | | | - Yangqing Deng
- Department of Biostatistics, Princess Margaret Cancer Center-University Health Network, Toronto, Ontario, Canada
| | - Shuja Khalid
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
| | - Hedyeh Ziai
- Department of Otolaryngology-Head & Neck Surgery, University of Toronto, Toronto, Ontario, Canada
| | - Konrado Deutsch
- Department of Otolaryngology-Head & Neck Surgery, University of Toronto, Toronto, Ontario, Canada
| | - Jingyue Huang
- Department of Biostatistics, Princess Margaret Cancer Center-University Health Network, Toronto, Ontario, Canada
| | - Ralph W Gilbert
- Department of Otolaryngology-Head & Neck Surgery, University of Toronto, Toronto, Ontario, Canada
- Department of Otolaryngology-Head & Neck Surgery, Princess Margaret Cancer Center-University Health Network, Toronto, Ontario, Canada
| | - David P Goldstein
- Department of Otolaryngology-Head & Neck Surgery, University of Toronto, Toronto, Ontario, Canada
- Department of Otolaryngology-Head & Neck Surgery, Princess Margaret Cancer Center-University Health Network, Toronto, Ontario, Canada
| | - Christopher M K L Yao
- Department of Otolaryngology-Head & Neck Surgery, University of Toronto, Toronto, Ontario, Canada
- Department of Otolaryngology-Head & Neck Surgery, Princess Margaret Cancer Center-University Health Network, Toronto, Ontario, Canada
| | - Jonathan C Irish
- Department of Otolaryngology-Head & Neck Surgery, University of Toronto, Toronto, Ontario, Canada
- Department of Otolaryngology-Head & Neck Surgery, Princess Margaret Cancer Center-University Health Network, Toronto, Ontario, Canada
| | - Danny J Enepekides
- Department of Otolaryngology-Head & Neck Surgery, University of Toronto, Toronto, Ontario, Canada
- Department of Otolaryngology-Head & Neck Surgery, Sunnybrook Health Sciences Center, Toronto, Ontario, Canada
| | - Kevin M Higgins
- Department of Otolaryngology-Head & Neck Surgery, University of Toronto, Toronto, Ontario, Canada
- Department of Otolaryngology-Head & Neck Surgery, Sunnybrook Health Sciences Center, Toronto, Ontario, Canada
| | - Frank Rudzicz
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
- International Centre for Surgical Safety, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada
- Vector Institute for Artificial Intelligence, Toronto, Ontario, Canada
| | - Antoine Eskander
- Department of Otolaryngology-Head & Neck Surgery, University of Toronto, Toronto, Ontario, Canada
- Department of Otolaryngology-Head & Neck Surgery, Sunnybrook Health Sciences Center, Toronto, Ontario, Canada
| | - Wei Xu
- Department of Biostatistics, Princess Margaret Cancer Center-University Health Network, Toronto, Ontario, Canada
- Department of Otolaryngology-Head & Neck Surgery, Princess Margaret Cancer Center-University Health Network, Toronto, Ontario, Canada
- Department of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - John R de Almeida
- Department of Otolaryngology-Head & Neck Surgery, University of Toronto, Toronto, Ontario, Canada
- Department of Otolaryngology-Head & Neck Surgery, Princess Margaret Cancer Center-University Health Network, Toronto, Ontario, Canada
- Department of Otolaryngology-Head & Neck Surgery, Sinai Health System, Toronto, Ontario, Canada
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada
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Gaba F, Mohammadi SM, Krivonosov MI, Blyuss O. Predicting Risk of Post-Operative Morbidity and Mortality following Gynaecological Oncology Surgery (PROMEGO): A Global Gynaecological Oncology Surgical Outcomes Collaborative Led Study. Cancers (Basel) 2024; 16:2021. [PMID: 38893143 PMCID: PMC11170986 DOI: 10.3390/cancers16112021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2024] [Revised: 05/23/2024] [Accepted: 05/24/2024] [Indexed: 06/21/2024] Open
Abstract
The medical complexity of surgical patients is increasing, and surgical risk calculators are crucial in providing high-value, patient-centered surgical care. However, pre-existing models are not validated to accurately predict risk for major gynecological oncology surgeries, and many are not generalizable to low- and middle-income country settings (LMICs). The international GO SOAR database dataset was used to develop a novel predictive surgical risk calculator for post-operative morbidity and mortality following gynecological surgery. Fifteen candidate features readily available pre-operatively across both high-income countries (HICs) and LMICs were selected. Predictive modeling analyses using machine learning methods and linear regression were performed. The area-under-the-receiver-operating characteristic curve (AUROC) was calculated to assess overall discriminatory performance. Neural networks (AUROC 0.94) significantly outperformed other models (p < 0.001) for evaluating the accuracy of prediction across three groups, i.e., minor morbidity (Clavien-Dindo I-II), major morbidity (Clavien-Dindo III-V), and no morbidity. Logistic-regression modeling outperformed the clinically established SORT model in predicting mortality (AUROC 0.66 versus 0.61, p < 0.001). The GO SOAR surgical risk prediction model is the first that is validated for use in patients undergoing gynecological surgery. Accurate surgical risk predictions are vital within the context of major cytoreduction surgery, where surgery and its associated complications can diminish quality-of-life and affect long-term cancer survival. A model that requires readily available pre-operative data, irrespective of resource setting, is crucial to reducing global surgical disparities.
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Affiliation(s)
- Faiza Gaba
- Department of Gynaecological Oncology, The Royal Marsden Hospital, London SW3 6JJ, UK
- Institute of Applied Health Sciences, University of Aberdeen, Aberdeen AB24 3FX, UK
| | - Sara Mahvash Mohammadi
- Centre for Cancer Screening, Prevention and Early Detection, Wolfson Institute of Population Health, Queen Mary University of London, London EC1M 6BQ, UK
| | - Mikhail I. Krivonosov
- Research Center for Trusted Artificial Intelligence, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow 109004, Russia
- Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603105, Russia
| | - Oleg Blyuss
- Centre for Cancer Screening, Prevention and Early Detection, Wolfson Institute of Population Health, Queen Mary University of London, London EC1M 6BQ, UK
- Department of Pediatrics and Pediatric Infectious Diseases, Institute of Child’s Health, Sechenov University, Moscow 119991, Russia
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Vashistha N, Singhal S, Budhiraja S, Singhal D. Evaluation of ACS-NSQIP and CR-POSSUM risk calculators for the prediction of mortality after colorectal surgery: A retrospective cohort study. J Minim Access Surg 2024; 20:142-147. [PMID: 36124474 PMCID: PMC11095800 DOI: 10.4103/jmas.jmas_187_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 07/27/2022] [Accepted: 08/03/2022] [Indexed: 11/04/2022] Open
Abstract
BACKGROUND Several risk calculating tools have been introduced into clinical practice to provide patients and clinicians with objective, individualised estimates of procedure-related unfavourable outcomes. The currently available risk calculators (RCs) have been developed by well-endowed health systems in Europe and the USA. Applicability of these RCs in low-middle income country (LMIC) settings with wide disparities in patient population, surgical practice and healthcare infrastructure has not been adequately examined. PATIENTS AND METHODS Through this single tertiary care, LMIC-centre, retrospective cohort study, we investigated the accuracy of the two most widely validated RCs - American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) RC and ColoRectal Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (CR-POSSUM) - for the prediction of mortality in patients undergoing elective and emergency colorectal surgery (CRS) from March 2013 to March 2020. Online RCs were used to predict mortality and other outcomes. Accuracy was assessed by Brier score and C statistic. RESULTS Of 105 patients, 69 (65.71%) underwent elective and 36 (34.28%) underwent emergency CRS. The 30-day overall mortality was 12 - elective 1 (1.4%) and emergency 11 (30.5%). ACS-NSQIP RC performed better for the prediction of overall ( C statistic 0.939, Brier score 0.065) and emergency ( C statistic 0.840, Brier score 0.152) mortality. However, for elective CRS mortality, Brier scores were similar for both models (0.014), whereas C statistic (0.934 vs. 0.890) value was better for ACS-NSQIP. CONCLUSIONS Both ACS-NSQIP and CR-POSSUM were accurate for the prediction of CRS mortality. However, compared to CR-POSSUM, ACS-NSQIP performed better. The overall performance of both models is indicative of their wider applicability in LMIC centres also.
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Affiliation(s)
- Nitin Vashistha
- Department of Surgical Gastroenterology, Max Super Specialty Hospital, New Delhi, India
| | - Siddharth Singhal
- Department of Surgical Gastroenterology, Max Super Specialty Hospital, New Delhi, India
| | - Sandeep Budhiraja
- Clinical Directorate, Max Super Specialty Hospital, New Delhi, India
| | - Dinesh Singhal
- Department of Surgical Gastroenterology, Max Super Specialty Hospital, New Delhi, India
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Shroder M, Ford MM, Ye F, Zhao Z, Khan A, McChesney S, Hopkins MB, Hawkins AT. Development of a Predictive Nomogram for Circumferential Resection Margin in Rectal Cancer Surgery. J Surg Res 2024; 296:532-540. [PMID: 38335901 PMCID: PMC10947808 DOI: 10.1016/j.jss.2023.12.047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 11/18/2023] [Accepted: 12/31/2023] [Indexed: 02/12/2024]
Abstract
INTRODUCTION Circumferential resection margin (CRM) is a key quality metric and predictor of oncologic outcomes and overall survival following surgery for rectal cancer. We aimed to develop a nomogram to identify patients at risk for a positive CRM in the preoperative setting. METHODS We performed a retrospective evaluation of the National Cancer Database from 2010 to 2014 for patients with clinical stage I-III rectal cancer who underwent total mesorectal excision. Patients were excluded for emergency operation, resection for cancer recurrence, palliative resection, transanal resection, and missing CRM status. The primary outcome was positive CRM. Secondary outcomes included overall survival. RESULTS There were 28,790 patients included. 2245 (7.8%) had a positive CRM. Higher tumor grade, lack of neoadjuvant chemotherapy, mucinous/signet tumor histology, open approach, abdominoperineal resection, higher T stage, lymphovascular invasion, and perineural invasion were all significantly associated with positive CRM (P < 0.05) and were included in the nomogram. The C-statistic was 0.703, suggesting a good predictive model. CONCLUSIONS Positive CRM is associated with specific patient demographics and tumor characteristics. These factors can be used along with preoperative MRI to predict CRM positivity in the preoperative period and plan accordingly.
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Affiliation(s)
- Megan Shroder
- Division of General Surgery, Section of Colon & Rectal Surgery, Vanderbilt University, Nashville, Tennessee
| | - Molly M Ford
- Division of General Surgery, Section of Colon & Rectal Surgery, Vanderbilt University, Nashville, Tennessee
| | - Fei Ye
- Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Zhiguo Zhao
- Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Aimal Khan
- Division of General Surgery, Section of Colon & Rectal Surgery, Vanderbilt University, Nashville, Tennessee
| | - Shannon McChesney
- Division of General Surgery, Section of Colon & Rectal Surgery, Vanderbilt University, Nashville, Tennessee
| | - M Benjamin Hopkins
- Division of General Surgery, Section of Colon & Rectal Surgery, Vanderbilt University, Nashville, Tennessee
| | - Alexander T Hawkins
- Division of General Surgery, Section of Colon & Rectal Surgery, Vanderbilt University, Nashville, Tennessee.
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Campagnaro T, Poletto E, Tarchi P, Rattizzato S, Verlato G, Conci S, Pedrazzani C, De Manzini N, Guglielmi A, Ruzzenente A. Evaluation of the ACS-NSQIP Surgical Risk Calculator in Patients with Hepatic Metastases from Colorectal Cancer Undergoing Liver Resection. J Gastrointest Surg 2023; 27:2114-2125. [PMID: 37580490 PMCID: PMC10579123 DOI: 10.1007/s11605-023-05784-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 07/08/2023] [Indexed: 08/16/2023]
Abstract
BACKGROUND The American College of Surgeons National Surgical Quality Improvement Program surgical risk calculator (ACS-NSQIP SRC) has been designed to predict morbidity and mortality and help stratify surgical patients. This study evaluates the performance of the SRC for patients undergoing surgery for colorectal liver metastases (CRLM). METHODS SRC was retrospectively computed for patients undergoing liver or simultaneous colon and liver surgery for colorectal cancer (CRC) in two high tertiary referral centres from 2011 to 2020. C-statistics and Brier score were calculated as a mean of discrimination and calibration respectively, for both group and for every level of surgeon adjustment score (SAS) for liver resections in case of simultaneous liver-colon surgery. An AUC ≥ 0.7 shows acceptable discrimination; a Brier score next to 0 means the prediction tool has good calibration. RESULTS Four hundred ten patients were included, 153 underwent simultaneous resection, and 257 underwent liver-only resections. For simultaneous surgery, the ACS-NSQIP SRC showed good calibration and discrimination only for cardiac complication (AUC = 0.720, 0.740, and 0.702 for liver resection unadjusted, SAS-2, and SAS-3 respectively; 0.714 for colon resection; and Brier score = 0.04 in every case). For liver-only surgery, it only showed good calibration for cardiac complications (Brier score = 0.03). The SRC underestimated the incidence of overall complications, pneumonia, cardiac complications, and the length of hospital stay. CONCLUSIONS ACS-NSQIP SRC showed good predicting capabilities only for 1 out of 5 evaluated outcomes; therefore, it is not a reliable tool for patients undergoing liver surgery for CRLM, both in the simultaneous and staged resections.
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Affiliation(s)
- Tommaso Campagnaro
- Department of Surgery, Dentistry, Gynaecology and Paediatrics, Division of General and Hepato-Biliary Surgery, University of Verona, P. le L.A. Scuro, 37134, Verona, Italy
| | - Edoardo Poletto
- Department of Surgery, Dentistry, Gynaecology and Paediatrics, Division of General and Hepato-Biliary Surgery, University of Verona, P. le L.A. Scuro, 37134, Verona, Italy
| | - Paola Tarchi
- Surgical Clinic, University Hospital of Trieste (Azienda Sanitaria Giuliano-Isontina), 34149, Trieste, Italy
| | - Simone Rattizzato
- Department of Surgery, Dentistry, Gynaecology and Paediatrics, Division of General and Hepato-Biliary Surgery, University of Verona, P. le L.A. Scuro, 37134, Verona, Italy
| | - Giuseppe Verlato
- Diagnostics and Public Health-Unit of Epidemiology and Medical Statistics, University of Verona, Verona, Italy
| | - Simone Conci
- Department of Surgery, Dentistry, Gynaecology and Paediatrics, Division of General and Hepato-Biliary Surgery, University of Verona, P. le L.A. Scuro, 37134, Verona, Italy
| | - Corrado Pedrazzani
- Department of Surgery, Dentistry, Gynaecology and Paediatrics, Division of General and Hepato-Biliary Surgery, University of Verona, P. le L.A. Scuro, 37134, Verona, Italy
| | - Nicolò De Manzini
- Surgical Clinic, University Hospital of Trieste (Azienda Sanitaria Giuliano-Isontina), 34149, Trieste, Italy
| | - Alfredo Guglielmi
- Department of Surgery, Dentistry, Gynaecology and Paediatrics, Division of General and Hepato-Biliary Surgery, University of Verona, P. le L.A. Scuro, 37134, Verona, Italy
| | - Andrea Ruzzenente
- Department of Surgery, Dentistry, Gynaecology and Paediatrics, Division of General and Hepato-Biliary Surgery, University of Verona, P. le L.A. Scuro, 37134, Verona, Italy.
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Vernooij JEM, Koning NJ, Geurts JW, Holewijn S, Preckel B, Kalkman CJ, Vernooij LM. Performance and usability of pre-operative prediction models for 30-day peri-operative mortality risk: a systematic review. Anaesthesia 2023; 78:607-619. [PMID: 36823388 DOI: 10.1111/anae.15988] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/06/2023] [Indexed: 02/25/2023]
Abstract
Estimating pre-operative mortality risk may inform clinical decision-making for peri-operative care. However, pre-operative mortality risk prediction models are rarely implemented in routine clinical practice. High predictive accuracy and clinical usability are essential for acceptance and clinical implementation. In this systematic review, we identified and appraised prediction models for 30-day postoperative mortality in non-cardiac surgical cohorts. PubMed and Embase were searched up to December 2022 for studies investigating pre-operative prediction models for 30-day mortality. We assessed predictive performance in terms of discrimination and calibration. Risk of bias was evaluated using a tool to assess the risk of bias and applicability of prediction model studies. To further inform potential adoption, we also assessed clinical usability for selected models. In all, 15 studies evaluating 10 prediction models were included. Discrimination ranged from a c-statistic of 0.82 (MySurgeryRisk) to 0.96 (extreme gradient boosting machine learning model). Calibration was reported in only six studies. Model performance was highest for the surgical outcome risk tool (SORT) and its external validations. Clinical usability was highest for the surgical risk pre-operative assessment system. The SORT and risk quantification index also scored high on clinical usability. We found unclear or high risk of bias in the development of all models. The SORT showed the best combination of predictive performance and clinical usability and has been externally validated in several heterogeneous cohorts. To improve clinical uptake, full integration of reliable models with sufficient face validity within the electronic health record is imperative.
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Affiliation(s)
- J E M Vernooij
- Department of Anaesthesia, Rijnstate Hospital, the Netherlands
| | - N J Koning
- Department of Anaesthesia, Rijnstate Hospital, the Netherlands
| | - J W Geurts
- Department of Anaesthesia, Rijnstate Hospital, the Netherlands
| | - S Holewijn
- Department of Vascular Surgery, Rijnstate Hospital, the Netherlands
| | - B Preckel
- Department of Anaesthesia, Amsterdam UMC, Amsterdam, the Netherlands
| | - C J Kalkman
- University Medical Centre, Utrecht, the Netherlands
| | - L M Vernooij
- Department of Anaesthesia, University Medical Centre Utrecht, the Netherlands
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Red Blood Cell Transfusions and Risk of Postoperative Venous Thromboembolism. J Am Acad Orthop Surg 2022; 30:e919-e928. [PMID: 35439203 DOI: 10.5435/jaaos-d-22-00043] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 02/27/2022] [Indexed: 02/01/2023] Open
Abstract
INTRODUCTION Postoperative venous thromboembolism (VTE) is a major risk for orthopaedic surgery and associated with notable morbidity and mortality. Knowing a patient's risk for VTE may help guide the choice of perioperative VTE prophylaxis. Recently, red blood cells (RBCs) have been implicated for their role in pathologic thrombosis. Therefore, we examine the association between perioperative RBC transfusion and postoperative VTE after orthopaedic surgery. METHODS A retrospective cohort study was done by conducting a secondary analysis of data obtained from the 2016 American College of Surgeons National Surgical Quality Improvement Program database. Our population consisted of 234,608 adults who underwent orthopaedic surgery. The exposure was whether patients received a perioperative RBC transfusion. The primary outcome was postoperative VTE within 30 days of surgery that warranted therapeutic intervention, which was subsequently split into symptomatic deep vein thrombosis (DVT) and pulmonary embolism (PE). Odds ratios (ORs) were estimated using a multivariate logistic regression model. RESULTS At baseline, 1,952 patients (0.83%) had postoperative VTE (DVT in 1,299 [0.55%], PE in 801 [0.34%], and both DVT and PE in 148 [0.06%]). Seven hundred ninety-five patients (0.3%) received preoperative RBC transfusions only, 11,587 patients (4.9%) received postoperative RBC transfusions only, and 848 patients (0.4%) received both preoperative and postoperative RBC transfusions. Postoperative RBC transfusion was associated with higher odds of VTE (adjusted OR [aOR], 1.47; 95% confidence interval [CI], 1.19-1.81), DVT (aOR, 1.40; 95% CI, 1.09-1.79), PE (aOR, 1.59; 95% CI, 1.14-2.22), and 30-day mortality (aOR, 1.21; 95% CI, 1.01-1.45) independent of various presumed risk factors. When creating subgroups within orthopaedics by Current Procedural Terminology codes, postoperative transfusions in spine (aOR, 2.03; 95% CI, 1.13-3.67) and trauma (aOR, 1.40; 95% CI, 1.06-1.86) were associated with higher odds of postoperative VTE. CONCLUSION Our results suggest that postoperative RBC transfusion may be associated with an increased risk of postoperative VTE, both symptomatic DVT and life-threatening PE, independent of confounders. Additional prospective validation in cohort studies is necessary to confirm these findings. In addition, careful perioperative planning for patients deemed to be at high risk of requiring blood transfusion may reduce these postoperative complications in orthopaedic patients. LEVEL OF EVIDENCE III.
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Yung AE, Wong G, Pillinger N, Wykes J, Haddad R, McInnes S, Palme CE, Hubert Low TH, Clark JR, Sanders R, Ch'ng S. Validation of a risk prediction calculator in Australian patients undergoing head and neck microsurgery reconstruction. J Plast Reconstr Aesthet Surg 2022; 75:3323-3329. [PMID: 35768291 DOI: 10.1016/j.bjps.2022.04.073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Revised: 04/16/2022] [Accepted: 04/26/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND The American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) surgical risk calculator (SRC) is an open access calculator predicting patients' risk of postoperative complications. This study aims to assess the validity of the SRC in patients undergoing microsurgical free flap reconstruction at an Australian tertiary referral centre. METHODS This is a retrospective cohort study of 200 consecutive patients treated up to November 2020. SRC-predicted rates of postoperative complications and hospital length of stay (LOS) were compared to those observed for the ablative and reconstructive components of the procedure. The performance of the SRC was assessed using Brier scores, area under the receiver operating characteristic (ROC) curve (AUC), and the Hosmer-Lemeshow test. RESULTS For both ablative and reconstructive components, the SRC discriminates well for pneumonia and urinary tract infection, and it is calibrated well for readmission and sepsis, but it does not discriminate and calibrate well for any single outcome. SRC-predicted hospital LOS and actual LOS did not correlate well for the reconstructive component, but they correlated strongly for the ablative component. CONCLUSIONS The SRC is a poor predictor of postoperative complication rates and hospital LOS in patients undergoing head and neck microsurgical reconstruction.
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Affiliation(s)
- Amanda E Yung
- The University of Sydney Sydney Medical School, Sydney, Australia; The Royal Prince Alfred Institute of Academic Surgery, Sydney Local Health Distrinct, Sydney, Australia
| | - Gerald Wong
- Faculty of Medicine and Health, The University of Sydney, Sydney, Australia; Department of Anaesthetics, Royal Prince Alfred Hospital, Sydney, Australia
| | - Neil Pillinger
- Faculty of Medicine and Health, The University of Sydney, Sydney, Australia; Department of Anaesthetics, Royal Prince Alfred Hospital, Sydney, Australia
| | - James Wykes
- Department of Head and Neck Surgery, Chris O'Brien Lifehouse Cancer Centre, Sydney, Australia
| | - Roger Haddad
- Department of Plastics and Reconstructive Surgery, Royal Prince Alfred Hospital, Sydney, Australia
| | - Stephanie McInnes
- Department of Anaesthetics, Chris O'Brien Lifehouse Cancer Centre, Sydney, Australia
| | - Carsten E Palme
- Faculty of Medicine and Health, The University of Sydney, Sydney, Australia; Department of Head and Neck Surgery, Chris O'Brien Lifehouse Cancer Centre, Sydney, Australia
| | - Tsu-Hui Hubert Low
- Faculty of Medicine and Health, The University of Sydney, Sydney, Australia; Department of Head and Neck Surgery, Chris O'Brien Lifehouse Cancer Centre, Sydney, Australia
| | - Jonathan R Clark
- The Royal Prince Alfred Institute of Academic Surgery, Sydney Local Health Distrinct, Sydney, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, Australia; Department of Head and Neck Surgery, Chris O'Brien Lifehouse Cancer Centre, Sydney, Australia
| | - Robert Sanders
- The Royal Prince Alfred Institute of Academic Surgery, Sydney Local Health Distrinct, Sydney, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, Australia; Department of Anaesthetics, Royal Prince Alfred Hospital, Sydney, Australia
| | - Sydney Ch'ng
- The Royal Prince Alfred Institute of Academic Surgery, Sydney Local Health Distrinct, Sydney, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, Australia; Department of Plastics and Reconstructive Surgery, Royal Prince Alfred Hospital, Sydney, Australia; Melanoma Institute of Australia, Sydney, Australia.
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Tan XJ, Gu XX, Ge FM, Li ZY, Zhang LQ. Nomogram to predict postoperative complications in elderly with total hip replacement. World J Clin Cases 2022; 10:3720-3728. [PMID: 35647152 PMCID: PMC9100714 DOI: 10.12998/wjcc.v10.i12.3720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 02/22/2022] [Accepted: 03/26/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND By analyzing the risk factors of postoperative complications in elderly patients with hip replacement, We aimed to develop a nomogram model based on preoperative and intraoperative variables and verified the sensitivity and specificity for risk stratification of postoperative complications in elderly with total hip replacement patients.
AIM To develop a nomogram model for risk stratification of postoperative complications in elderly with total hip replacement patients.
METHODS A total of 414 elderly patients who underwent surgical treatment for total hip replacement hospitalized at the Affiliated Hospital of Guangdong Medical University from March 1, 2017 to August 31, 2019 were included into this study. Univariate and multivariate logistic regression were conducted to identify independent risk factors of postoperative complication in the 414 patients. A nomogram was developed by R software and validated to predict the risk of postoperative complications.
RESULTS Multivariate logistic regression analysis revealed that age (OR = 1.05, 95%CI: 1.00-1.09), renal failure (OR = 0.90, 95%CI: 0.83-0.97), Type 2 diabetes (OR = 1.05, 95%CI: 1.00-1.09), albumin (ALB) (OR = 0.91, 95%CI: 0.83-0.99) were independent risk factors of postoperative complication in elderly patients with hip replacement (P < 0.05). For validation of the nomogram, receive operating characteristic curve revealed that the model predicting postoperative complication in elderly patients with hip replacement was the area under the curve of 0.8254 (95%CI: 0.78-0.87), the slope of the calibration plot was close to 1 and the model passed Hosmer-Lemeshow goodness of fit test (χ2 = 10.16, P = 0.4264), calibration in R Emax = 0.176, Eavg = 0.027, which all demonstrated that the model was of good accuracy.
CONCLUSION The nomogram predicting postoperative complications in patients with total hip replacement constructed based on age, type 2 diabetes, renal failure and ALB is of good discrimination and accuracy, which was of clinical significance.
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Affiliation(s)
- Xiu-Juan Tan
- Department of Anesthesiology, The First Affiliated Hospital, Jinan University, Guangzhou 510630, Guangdong Province, China
| | - Xiao-Xia Gu
- Department of Anesthesiology, The Affiliated Hospital of Guangdong Medical University, Zhanjiang 524001, Guangdong Province, China
| | - Feng-Min Ge
- Department of Anesthesiology, The Affiliated Hospital of Guangdong Medical University, Zhanjiang 524001, Guangdong Province, China
| | - Zhi-Yi Li
- Department of Anesthesiology, The Affiliated Hospital of Guangdong Medical University, Zhanjiang 524001, Guangdong Province, China
| | - Liang-Qing Zhang
- Department of Anesthesiology, The Affiliated Hospital of Guangdong Medical University, Zhanjiang 524001, Guangdong Province, China
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10
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Gomes D, Le L, Perschbacher S, Haas NA, Netz H, Hasbargen U, Delius M, Lange K, Nennstiel U, Roscher AA, Mansmann U, Ensenauer R. Predicting the earliest deviation in weight gain in the course towards manifest overweight in offspring exposed to obesity in pregnancy: a longitudinal cohort study. BMC Med 2022; 20:156. [PMID: 35418073 PMCID: PMC9008920 DOI: 10.1186/s12916-022-02318-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 02/28/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Obesity in pregnancy and related early-life factors place the offspring at the highest risk of being overweight. Despite convincing evidence on these associations, there is an unmet public health need to identify "high-risk" offspring by predicting very early deviations in weight gain patterns as a subclinical stage towards overweight. However, data and methods for individual risk prediction are lacking. We aimed to identify those infants exposed to obesity in pregnancy at ages 3 months, 1 year, and 2 years who likely will follow a higher-than-normal body mass index (BMI) growth trajectory towards manifest overweight by developing an early-risk quantification system. METHODS This study uses data from the prospective mother-child cohort study Programming of Enhanced Adiposity Risk in CHildhood-Early Screening (PEACHES) comprising 1671 mothers with pre-conception obesity and without (controls) and their offspring. Exposures were pre- and postnatal risks documented in patient-held maternal and child health records. The main outcome was a "higher-than-normal BMI growth pattern" preceding overweight, defined as BMI z-score >1 SD (i.e., World Health Organization [WHO] cut-off "at risk of overweight") at least twice during consecutive offspring growth periods between age 6 months and 5 years. The independent cohort PErinatal Prevention of Obesity (PEPO) comprising 11,730 mother-child pairs recruited close to school entry (around age 6 years) was available for data validation. Cluster analysis and sequential prediction modelling were performed. RESULTS Data of 1557 PEACHES mother-child pairs and the validation cohort were analyzed comprising more than 50,000 offspring BMI measurements. More than 1-in-5 offspring exposed to obesity in pregnancy belonged to an upper BMI z-score cluster as a distinct pattern of BMI development (above the cut-off of 1 SD) from the first months of life onwards resulting in preschool overweight/obesity (age 5 years: odds ratio [OR] 16.13; 95% confidence interval [CI] 9.98-26.05). Contributing early-life factors including excessive weight gain (OR 2.08; 95% CI 1.25-3.45) and smoking (OR 1.94; 95% CI 1.27-2.95) in pregnancy were instrumental in predicting a "higher-than-normal BMI growth pattern" at age 3 months and re-evaluating the risk at ages 1 year and 2 years (area under the receiver operating characteristic [AUROC] 0.69-0.79, sensitivity 70.7-76.0%, specificity 64.7-78.1%). External validation of prediction models demonstrated adequate predictive performances. CONCLUSIONS We devised a novel sequential strategy of individual prediction and re-evaluation of a higher-than-normal weight gain in "high-risk" infants well before developing overweight to guide decision-making. The strategy holds promise to elaborate interventions in an early preventive manner for integration in systems of well-child care.
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Affiliation(s)
- Delphina Gomes
- Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Lien Le
- Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Sarah Perschbacher
- Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Nikolaus A Haas
- Division of Pediatric Cardiology and Intensive Care, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Heinrich Netz
- Division of Pediatric Cardiology and Intensive Care, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Uwe Hasbargen
- Department of Obstetrics and Gynecology, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Maria Delius
- Department of Obstetrics and Gynecology, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Kristin Lange
- Department of General Pediatrics, Neonatology, and Pediatric Cardiology, University Children's Hospital, Faculty of Medicine, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Uta Nennstiel
- Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Adelbert A Roscher
- Department of Pediatrics, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Ulrich Mansmann
- Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Regina Ensenauer
- Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany. .,Institute of Child Nutrition, Max Rubner-Institut, Federal Research Institute of Nutrition and Food, Karlsruhe, Germany.
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11
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Ludbrook GL. The Hidden Pandemic: the Cost of Postoperative Complications. CURRENT ANESTHESIOLOGY REPORTS 2021; 12:1-9. [PMID: 34744518 PMCID: PMC8558000 DOI: 10.1007/s40140-021-00493-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/14/2021] [Indexed: 12/17/2022]
Abstract
Purpose of Review Population-based increases in ageing and medical co-morbidities are expected to substantially increase the incidence of expensive postoperative complications. This threatens the sustainability of essential surgical care, with negative impacts on patients' health and wellbeing. Recent Findings Identification of key high-risk areas, and implementation of proven cost-effective strategies to manage both outcome and cost across the end-to-end journey of the surgical episode of care, is clearly feasible. However, good programme design and formal cost-effectiveness analysis is critical to identify, and implement, true high value change. Summary Both outcome and cost need to be a high priority for both fundholders and clinicians in perioperative care, with the focus for both groups on delivering high-quality care, which in itself, is the key to good cost management.
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Affiliation(s)
- Guy L. Ludbrook
- The University of Adelaide, and Royal Adelaide Hospital, C/O Royal Adelaide Hospital, 3G395, 1 Port Road, Adelaide, South Australia 5000 Australia
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12
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Liu R, Lai X, Wang J, Zhang X, Zhu X, Lai PBS, Guo CR. A non-linear ensemble model-based surgical risk calculator for mixed data from multiple surgical fields. BMC Med Inform Decis Mak 2021; 21:88. [PMID: 34330254 PMCID: PMC8323237 DOI: 10.1186/s12911-021-01450-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 02/18/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The misestimation of surgical risk is a serious threat to the lives of patients when implementing surgical risk calculator. Improving the accuracy of postoperative risk prediction has received much attention and many methods have been proposed to cope with this problem in the past decades. However, those linear approaches are inable to capture the non-linear interactions between risk factors, which have been proved to play an important role in the complex physiology of the human body, and thus may attenuate the performance of surgical risk calculators. METHODS In this paper, we presented a new surgical risk calculator based on a non-linear ensemble algorithm named Gradient Boosting Decision Tree (GBDT) model, and explored the corresponding pipeline to support it. In order to improve the practicability of our approach, we designed three different modes to deal with different data situations. Meanwhile, considering that one of the obstacles to clinical acceptance of surgical risk calculators was that the model was too complex to be used in practice, we reduced the number of input risk factors according to the importance of them in GBDT. In addition, we also built some baseline models and similar models to compare with our approach. RESULTS The data we used was three-year clinical data from Surgical Outcome Monitoring and Improvement Program (SOMIP) launched by the Hospital Authority of Hong Kong. In all experiments our approach shows excellent performance, among which the best result of area under curve (AUC), Hosmer-Lemeshow test ([Formula: see text]) and brier score (BS) can reach 0.902, 7.398 and 0.047 respectively. After feature reduction, the best result of AUC, [Formula: see text] and BS of our approach can still be maintained at 0.894, 7.638 and 0.060, respectively. In addition, we also performed multiple groups of comparative experiments. The results show that our approach has a stable advantage in each evaluation indicator. CONCLUSIONS The experimental results demonstrate that NL-SRC can not only improve the accuracy of predicting the surgical risk of patients, but also effectively capture important risk factors and their interactions. Meanwhile, it also has excellent performance on the mixed data from multiple surgical fields.
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Affiliation(s)
- Ruoyu Liu
- School of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Xin Lai
- School of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China. .,Department of Tumor Gynecology, Fujian Medical University Cancer Hospital and Fujian Cancer Hospital, Fuzhou, 350014, China.
| | - Jiayin Wang
- School of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Xuanping Zhang
- School of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Xiaoyan Zhu
- School of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Paul B S Lai
- Department of Surgery, The Chinese University of Hong Kong, Hong Kong, China
| | - Ci-Ren Guo
- Department of Tumor Gynecology, Fujian Medical University Cancer Hospital and Fujian Cancer Hospital, Fuzhou, 350014, China.
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13
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Dribin TE, Michelson KA, Vyles D, Neuman MI, Brousseau DC, Mistry RD, Dayan PS, Zhang N, Viswanathan S, Witry J, Boyd S, Schnadower D. PEMCRC anaphylaxis study protocol: a multicentre cohort study to derive and validate clinical decision models for the emergency department management of children with anaphylaxis. BMJ Open 2021; 11:e037341. [PMID: 33402402 PMCID: PMC7786808 DOI: 10.1136/bmjopen-2020-037341] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
INTRODUCTION There remain significant knowledge gaps about the management and outcomes of children with anaphylaxis. These gaps have led to practice variation regarding decisions to hospitalise children and length of observation periods following treatment with epinephrine. The objectives of this multicentre study are to (1) determine the prevalence of and risk factors for severe, persistent, refractory and biphasic anaphylaxis, as well as persistent and biphasic non-anaphylactic reactions; (2) derive and validate prediction models for emergency department (ED) discharge; and (3) determine data-driven lengths of ED and inpatient observation prior to discharge to home based on initial reaction severity. METHODS AND ANALYSIS The study is being conducted through the Pediatric Emergency Medicine Collaborative Research Committee (PEMCRC). Children 6 months to less than 18 years of age presenting to 30 participating EDs for anaphylaxis from October 2015 to December 2019 will be eligible. The primary outcomes for each objective are (1) severe, persistent, refractory or biphasic anaphylaxis, as well as persistent or biphasic non-anaphylactic reactions; (2) safe ED discharge, defined as no receipt of acute anaphylaxis medications or hypotension beyond 4 hours from first administered dose of epinephrine; and (3) time from first to last administered dose of epinephrine and vasopressor cessation. Analyses for each objective include (1) descriptive statistics to estimate prevalence and generalised estimating equations that will be used to investigate risk factors for anaphylaxis outcomes, (2) least absolute shrinkage and selection operator regression and binary recursive partitioning to derive and validate prediction models of children who may be candidates for safe ED discharge, and (3) Kaplan-Meier analyses to assess timing from first to last epinephrine doses and vasopressor cessation based on initial reaction severity. ETHICS AND DISSEMINATION All sites will obtain institutional review board approval; results will be published in peer-reviewed journals and disseminated via traditional and social media, blogs and online education platforms.
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Affiliation(s)
- Timothy E Dribin
- Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Kenneth A Michelson
- Division of Emergency Medicine, Boston Children's Hospital, Boston, Massachusetts, USA
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
| | - David Vyles
- Section of Pediatric Emergency Medicine, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Mark I Neuman
- Division of Emergency Medicine, Boston Children's Hospital, Boston, Massachusetts, USA
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
| | - David C Brousseau
- Section of Pediatric Emergency Medicine, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Rakesh D Mistry
- Section of Emergency Medicine, Department of Pediatrics, Children's Hospital Colorado, Aurora, Colorado, USA
| | - Peter S Dayan
- Department of Pediatrics, Columbia University College of Physicians and Surgeons, New York City, New York, USA
| | - Nanhua Zhang
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Shiv Viswanathan
- Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - John Witry
- Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Stephanie Boyd
- Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - David Schnadower
- Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
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14
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Podrat JL, Del Val FR, Pei KY. Evolution of Risk Calculators and the Dawn of Artificial Intelligence in Predicting Patient Complications. Surg Clin North Am 2020; 101:97-107. [PMID: 33212083 DOI: 10.1016/j.suc.2020.08.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Risk calculators are an underused tool for surgeons and trainees when determining and communicating surgical risk. We summarize some of the more common risk calculators and discuss their evolution and limitations. We also describe artificial intelligence models, which have the potential to help clinicians better understand and use risk assessment.
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Affiliation(s)
- Jerica L Podrat
- Department of Surgery, Houston Methodist Hospital, 6550 Fannin Street, Suite SM1661, Houston, TX 77030, USA
| | - Fernando Ramirez Del Val
- Department of Surgery, Houston Methodist Hospital, 6550 Fannin Street, Suite SM1661, Houston, TX 77030, USA
| | - Kevin Y Pei
- Parkview Health GME, 2200 Randallia Drive, Administration, Fort Wayne, IN 46805, USA.
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15
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Schlick CJR, Yuce TK, Yang AD, McGee MF, Bentrem DJ, Bilimoria KY, Merkow RP. A postdischarge venous thromboembolism risk calculator for inflammatory bowel disease surgery. Surgery 2020; 169:240-247. [PMID: 33077197 DOI: 10.1016/j.surg.2020.09.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 08/26/2020] [Accepted: 09/04/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND Guidelines recommend extended chemoprophylaxis for venous thromboembolism in high-risk patients having operations for inflammatory bowel disease. Quantifying patients' risk of venous thromboembolism, however, remains challenging. We sought (1) to identify factors associated with postdischarge venous thromboembolism in patients undergoing colorectal resection for inflammatory bowel disease and (2) to develop a postdischarge venous thromboembolism risk calculator to guide prescribing of extended chemoprophylaxis. METHODS Patients who underwent an operation for inflammatory bowel disease from 2012 to 2018 were identified from the American College of Surgeons National Surgical Quality Improvement Program for colectomy and proctectomy procedure targeted modules. Postdischarge venous thromboembolism included pulmonary embolism or deep vein thrombosis diagnosed after discharge from the index hospitalization. Multivariable logistic regression estimated the association of patient/operative factors with postdischarge venous thromboembolism. A postdischarge venous thromboembolism risk calculator was subsequently constructed. RESULTS Of 18,990 patients, 199 (1.1%) developed a postdischarge venous thromboembolism within the first 30 postoperative days. Preoperative factors associated with postdischarge venous thromboembolism included body mass index (1.9% with body mass index ≥35 vs 0.8% with body mass index 18.5-24.9; odds ratio 2.34 [95% confidence interval 1.49-3.67]), steroid use (1.3% vs 0.7%; odds ratio 1.91 [95% confidence interval 1.37-2.66]), and ulcerative colitis (1.5% vs 0.8% with Crohn's disease; odds ratio 1.76 [95% confidence interval 1.32-2.34]). Minimally invasive surgery was associated with postdischarge venous thromboembolism (1.2% vs 0.9% with open; odds ratio 1.42 [95% confidence interval 1.05-1.92]), as was anastomotic leak (2.8% vs 1.0%; odds ratio 2.24 [95% confidence interval 1.31-3.83]) and ileus (2.1% vs 0.9%; odds ratio 2.60 [95% confidence interval 1.91-3.54]). The predicted probability of postdischarge venous thromboembolism ranged from 0.2% to 14.3% based on individual risk factors. CONCLUSION Preoperative, intraoperative, and postoperative factors are associated with postdischarge venous thromboembolism after an operation for inflammatory bowel disease. A postdischarge venous thromboembolism risk calculator was developed which can be used to tailor extended venous thromboembolism chemoprophylaxis by individual risk.
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Affiliation(s)
- Cary Jo R Schlick
- Surgical Outcomes and Quality Improvement Center, Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Tarik K Yuce
- Surgical Outcomes and Quality Improvement Center, Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Anthony D Yang
- Surgical Outcomes and Quality Improvement Center, Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Michael F McGee
- Surgical Outcomes and Quality Improvement Center, Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - David J Bentrem
- Surgical Outcomes and Quality Improvement Center, Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL; Surgery Service, Jesse Brown VA Medical Center, Chicago, IL
| | - Karl Y Bilimoria
- Surgical Outcomes and Quality Improvement Center, Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL; Division of Research and Optimal Patient Care, American College of Surgeons, Chicago, IL
| | - Ryan P Merkow
- Surgical Outcomes and Quality Improvement Center, Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL; Division of Research and Optimal Patient Care, American College of Surgeons, Chicago, IL.
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16
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Schlick CJR, Merkow RP, Yang AD, Bentrem DJ. Post-discharge venous thromboembolism after pancreatectomy for malignancy: Predicting risk based on preoperative, intraoperative, and postoperative factors. J Surg Oncol 2020; 122:675-683. [PMID: 32531819 PMCID: PMC7755307 DOI: 10.1002/jso.26046] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 05/17/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND AND OBJECTIVES Extended chemoprophylaxis is recommended for high-risk patients following pancreatectomy for malignancy. However, quantifying risk remains difficult. We sought to (a) identify factors associated with post-discharge venous thromboembolism (VTE) following pancreatectomy for malignancy and (b) develop a post-discharge VTE risk calculator to identify high-risk patients. METHODS Patients who underwent pancreatectomy for malignant histology from 2014 to 2018 were identified from the ACS NSQIP pancreatectomy procedure targeted dataset. Preoperative, intraoperative, and postoperative factors known at hospital discharge were evaluated for association with post-discharge VTE via multivariable logistic regression. A post-discharge VTE risk calculator was developed and validated. RESULTS Of 19 340 analyzed patients, 280 (1.5%) developed post-discharge VTE. Post-discharge VTE was associated with increasing body mass index (BMI; eg, morbidly obese BMI odds ratio [OR]: 1.99 [95% confidence interval {CI}: 1.30-3.02] vs normal BMI), procedure type (distal pancreatectomy OR: 1.47 [95% CI: 1.02-2.12] vs pancreaticoduodenectomy), pancreatic fistula (OR: 1.59 [95% CI: 1.19-2.13]) and delayed gastric emptying (OR: 1.81 [95% CI: 1.29-2.52]). Patients' predicted probability of post-discharge VTE ranged from 0.7% to 9.0%. Twenty iterations of 10-fold cross-validation demonstrated internal validity. CONCLUSIONS Preoperative, intraoperative, and postoperative factors were associated with post-discharge VTE following pancreatectomy for malignancy. This post-discharge VTE risk calculator allows for quantification of individual post-discharge VTE risk, which ranged from 0.7% to 9.0%.
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Affiliation(s)
- Cary Jo R. Schlick
- Surgical Outcomes and Quality Improvement Center, Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Ryan P. Merkow
- Surgical Outcomes and Quality Improvement Center, Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL
- Division of Research and Optimal Patient Care, American College of Surgeons, Chicago, IL
| | - Anthony D. Yang
- Surgical Outcomes and Quality Improvement Center, Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - David J. Bentrem
- Surgical Outcomes and Quality Improvement Center, Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL
- Surgery Service, Jesse Brown VA Medical Center, Chicago, IL
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17
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Analysis and Review of Automated Risk Calculators Used to Predict Postoperative Complications After Orthopedic Surgery. Curr Rev Musculoskelet Med 2020; 13:298-308. [PMID: 32418072 DOI: 10.1007/s12178-020-09632-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
PURPOSE OF REVIEW To discuss the automated risk calculators that have been developed and evaluated in orthopedic surgery. RECENT FINDINGS Identifying predictors of adverse outcomes following orthopedic surgery is vital in the decision-making process for surgeons and patients. Recently, automated risk calculators have been developed to quantify patient-specific preoperative risk associated with certain orthopedic procedures. Automated risk calculators may provide the orthopedic surgeon with a valuable tool for clinical decision-making, informed consent, and the shared decision-making process with the patient. Understanding how an automated risk calculator was developed is arguably as important as the performance of the calculator. Additionally, conveying and interpreting the results of these risk calculators with the patient and its influence on surgical decision-making are paramount. The most abundant research on automated risk calculators has been conducted in the spine, total hip and knee arthroplasty, and trauma literature. Currently, many risk calculators show promise, but much research is still needed to improve them. We recommend they be used only as adjuncts to clinical decision-making. Understanding how a calculator was developed, and accurate communication of results to the patient, is paramount.
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18
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White HJ, Bradley J, Hadgis N, Wittke E, Piland B, Tuttle B, Erickson M, Horn ME. Predicting Patient-Centered Outcomes from Spine Surgery Using Risk Assessment Tools: a Systematic Review. Curr Rev Musculoskelet Med 2020; 13:247-263. [PMID: 32388726 DOI: 10.1007/s12178-020-09630-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
PURPOSE OF REVIEW The purpose of this systematic review is to evaluate the current literature in patients undergoing spine surgery in the cervical, thoracic, and lumbar spine to determine the available risk assessment tools to predict the patient-centered outcomes of pain, disability, physical function, quality of life, psychological disposition, and return to work after surgery. RECENT FINDINGS Risk assessment tools can assist surgeons and other healthcare providers in identifying the benefit-risk ratio of surgical candidates. These tools gather demographic, medical history, and other pertinent patient-reported measures to calculate a probability utilizing regression or machine learning statistical foundations. Currently, much is still unknown about the use of these tools to predict quality of life, disability, and other factors following spine surgery. A systematic review was conducted using PRISMA guidelines that identified risk assessment tools that utilized patient-reported outcome measures as part of the calculation. From 8128 identified studies, 13 articles met inclusion criteria and were accepted into this review. The range of c-index values reported in the studies was between 0.63 and 0.84, indicating fair to excellent model performance. Post-surgical patient-reported outcomes were identified in the following categories (n = total number of predictive models): return to work (n = 3), pain (n = 9), physical functioning and disability (n = 5), quality of life (QOL) (n = 6), and psychosocial disposition (n = 2). Our review has synthesized the available evidence on risk assessment tools for predicting patient-centered outcomes in patients undergoing spine surgery and described their findings and clinical utility.
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Affiliation(s)
- Hannah J White
- Department of Orthopaedic Surgery, Duke University, Durham, NC, USA.
| | - Jensyn Bradley
- Department of Orthopaedic Surgery, Duke University, Durham, NC, USA
| | - Nicholas Hadgis
- Department of Orthopaedic Surgery, Duke University, Durham, NC, USA
| | - Emily Wittke
- Department of Orthopaedic Surgery, Duke University, Durham, NC, USA
| | - Brett Piland
- Department of Orthopaedic Surgery, Duke University, Durham, NC, USA
| | - Brandi Tuttle
- Medical Center Library & Archives, Duke University, Durham, NC, USA
| | - Melissa Erickson
- Department of Orthopaedic Surgery, Duke University, Durham, NC, USA
| | - Maggie E Horn
- Department of Orthopaedic Surgery, Duke University, Durham, NC, USA.,Department of Population Health Sciences, Duke University, Durham, NC, USA
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19
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Goel R, Josephson CD, Patel EU, Petersen MR, Makhani S, Frank SM, Ness PM, Bloch EM, Gehrie EA, Lokhandwala PM, Nellis MM, Karam O, Shaz BH, Patel RM, Tobian AAR. Perioperative Transfusions and Venous Thromboembolism. Pediatrics 2020; 145:e20192351. [PMID: 32198293 PMCID: PMC7111487 DOI: 10.1542/peds.2019-2351] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/03/2019] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Annual incidence of venous thromboembolism (VTE) including postoperative VTE in hospitalized children is rising significantly. A growing body of evidence supports the role of red blood cells (RBCs) in pathologic thrombosis. In this study, we examined the association of perioperative RBC transfusion with postoperative VTE in pediatric patients. METHODS The pediatric databases of the American College of Surgeons' National Surgical Quality Improvement Project from 2012 to 2017 were used. Multivariable logistic regression was used to examine the association between perioperative RBC transfusion status and the development of new or progressive VTE within 30 days of surgery. The analyses were age stratified, as follows: neonates (≤28 days), infants (>28 days and <1 year), and children (≥1 year). RESULTS In this study, we included 20 492 neonates, 79 744 infants, and 382 862 children. Postoperative development of VTE was reported in 99 (0.48%) neonates, 147 (0.2%) infants, and 374 (0.1%) children. In all age groups, development of VTE was significantly more common among patients with a perioperative RBC transfusion than patients without a perioperative RBC transfusion (neonates: adjusted odds ratio [aOR] = 4.1, 95% confidence interval [CI] = 2.5-6.7; infants: aOR = 2.4, 95% CI = 1.7-3.6; children: aOR = 2.2, 95% CI = 1.7-2.9). Among children who received an intra- or postoperative transfusion, the weight-based volume of RBCs (mL/kg) transfused was associated with postoperative VTE in a dose-dependent manner: second tertile (odds ratio = 2.3, 95% CI = 1.3-4.1) and third tertile (odds ratio = 4.1, 95% CI = 2.3-7.4) versus first tertile. CONCLUSIONS Perioperative RBC transfusions are independently associated with development of new or progressive postoperative VTE in children, infants, and neonates. These findings need further validation in prospective studies and emphasize the need for evidence-based perioperative pediatric blood transfusion decisions.
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Affiliation(s)
- Ruchika Goel
- Division of Transfusion Medicine, Department of Pathology, Johns Hopkins University, Baltimore, Maryland
- Departments of Internal Medicine and Pediatrics, School of Medicine, Southern Illinois University and Mississippi Valley Regional Blood Center, Springfield, Illinois
| | - Cassandra D Josephson
- Department of Pathology, School of Medicine, Emory University and
- Department of Pediatrics, Children's Healthcare of Atlanta and School of Medicine, Emory University, Atlanta, Georgia
| | - Eshan U Patel
- Division of Transfusion Medicine, Department of Pathology, Johns Hopkins University, Baltimore, Maryland
| | - Molly R Petersen
- Division of Transfusion Medicine, Department of Pathology, Johns Hopkins University, Baltimore, Maryland
| | - Sarah Makhani
- Herbert Wertheim College of Medicine, Florida International University, Miami, Florida
| | - Steven M Frank
- Department of Anesthesiology, Johns Hopkins Hospital, Baltimore, Maryland
| | - Paul M Ness
- Division of Transfusion Medicine, Department of Pathology, Johns Hopkins University, Baltimore, Maryland
| | - Evan M Bloch
- Division of Transfusion Medicine, Department of Pathology, Johns Hopkins University, Baltimore, Maryland
| | - Eric A Gehrie
- Division of Transfusion Medicine, Department of Pathology, Johns Hopkins University, Baltimore, Maryland
| | - Parvez M Lokhandwala
- Division of Transfusion Medicine, Department of Pathology, Johns Hopkins University, Baltimore, Maryland
| | - Marianne M Nellis
- Department of Pediatrics, Weill Cornell Medicine, New York, New York
| | - Oliver Karam
- Department of Pediatrics, Children's Hospital of Richmond at Virginia Commonwealth University, Richmond, Virginia; and
| | | | - Ravi M Patel
- Department of Pediatrics, Children's Healthcare of Atlanta and School of Medicine, Emory University, Atlanta, Georgia
| | - Aaron A R Tobian
- Division of Transfusion Medicine, Department of Pathology, Johns Hopkins University, Baltimore, Maryland
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Padilla Herrera CJ, Vega Peña NV, José Barrios AJ, Juan Pablo Ruiz JPR, Lora A. Análisis multicéntrico del reparo de la hernia ventral en instituciones de IV nivel, 2015-2019. REVISTA COLOMBIANA DE CIRUGÍA 2020. [DOI: 10.30944/20117582.587] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Introducción. La cirugía de hernia ventral implica una situación de complejidad, dadas las múltiples variables que se deben controlar para estimar los posibles factores determinantes del éxito quirúrgico y la aparición de complicaciones. Según la literatura científica mundial, la incidencia de hernia ventral se estima entre el 10 y el 15 %, y la tasa promedio de complicaciones de esta cirugía varía entre el 10 y el 37 %.
El objetivo del presente estudio fue describir la experiencia y los resultados de la cirugía de hernia ventral en dos instituciones de IV nivel, en el periodo de enero de 2015 a marzo de 2019.
Métodos. Se trata de un estudio observacional, descriptivo y de cohorte histórica, de pacientes mayores de edad sometidos a corrección de hernia ventral en la Clínica Colsanitas en los últimos cinco años. Los datos se tomaron del registro estadístico de las instituciones en mención.
Resultados. Se incluyeron 612 pacientes en un periodo de cinco años, la mayoría de los cuales era de sexo femenino, con sobrepeso, y predominantemente, con defectos combinados mediales; la tasa general de complicaciones fue del 20 % y, el porcentaje de infección del sitio operatorio, de 9 %; para el desarrollo de esta infección, la técnica de separación de componentes se encontró como un factor de riesgo (p=0,01; RR=2,9; IC 95% 1,32-6,5). En este estudio, no se analizó la recidiva como factor de los diferentes resultados.
Conclusiones. Existen pocos datos en la literatura nacional sobre los resultados de este tipo de procedimiento quirúrgico. Es por ello que se procuró brindar a la comunidad científica los resultados de morbimortalidad de esta muestra de pacientes intervenidos por hernia ventral en los últimos cinco años.
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Pre-Operative, Intra-Operative, and Post-Operative Factors Associated with Post-Discharge Venous Thromboembolism Following Colorectal Cancer Resection. J Gastrointest Surg 2020; 24:144-154. [PMID: 31420856 PMCID: PMC6992485 DOI: 10.1007/s11605-019-04354-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Accepted: 07/30/2019] [Indexed: 02/08/2023]
Abstract
BACKGROUND Venous thromboembolism (VTE) is the most common preventable cause of 30-day post-operative mortality, with many events occurring after hospital discharge. High-level evidence supports post-discharge VTE chemoprophylaxis following abdominal/pelvic cancer resection; however, some studies support a more tailored approach. Our objectives were to (1) identify risk factors associated with post-discharge VTE in a large cohort of patients undergoing colorectal cancer resection and (2) develop a post-discharge VTE risk calculator. METHODS Patients who underwent colorectal cancer resection from 2012 to 2016 were identified from ACS NSQIP colectomy and proctectomy procedure-targeted modules. Multivariable logistic regression was used to identify factors associated with post-discharge VTE. Incorporating pre-operative, intra-operative, and post-operative variables, a post-discharge VTE risk calculator was constructed and validated. RESULTS Of 51,139 patients, 387 (0.76%) developed post-discharge VTE. Pre-operative factors associated with post-discharge VTE included BMI (e.g., morbidly obese OR 2.27, 95% CI 1.65-3.12 vs. normal BMI), and thrombocytosis (OR 1.41, 95% CI 1.03-1.92). Intra-operative factors included operative time (4-6 h OR 1.56, 95% CI 1.12-2.17; > 6 h, OR 1.85, 95% CI 1.21-2.84, vs. < 2 h), and type of operation (e.g., open partial colectomy OR 1.67, 95% CI 1.30-2.16 vs. laparoscopic partial colectomy). Post-operative factors included anastomotic leak (OR 2.05, 95% CI 1.31-3.21) and post-operative ileus (OR 1.39, 95% CI 1.07-1.79). Using the risk calculator, the predicted probability of post-discharge VTE ranged from 0.04 to 10.29%. On a 10-fold cross validation, the calculator's mean C-Statistic was 0.65. CONCLUSIONS Patient-specific factors are associated with varying rates of post-discharge VTE. We present the first post-discharge VTE risk calculator designed for use at the time of discharge following colorectal cancer resection.
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Raymond BL, Wanderer JP, Hawkins AT, Geiger TM, Ehrenfeld JM, Stokes JW, McEvoy MD. Use of the American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator During Preoperative Risk Discussion: The Patient Perspective. Anesth Analg 2019; 128:643-650. [PMID: 30169413 DOI: 10.1213/ane.0000000000003718] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
BACKGROUND The American College of Surgeons (ACS) National Surgical Quality Improvement Program Surgical Risk Calculator (ACS Calculator) provides empirically derived, patient-specific risks for common adverse perioperative outcomes. The ACS Calculator is promoted as a tool to improve shared decision-making and informed consent for patients undergoing elective operations. However, to our knowledge, no data exist regarding the use of this tool in actual preoperative risk discussions with patients. Accordingly, we performed a survey to assess (1) whether patients find the tool easy to interpret, (2) how accurately patients can predict their surgical risks, and (3) the impact of risk disclosure on levels of anxiety and future motivations to decrease personal risk. METHODS Patients (N = 150) recruited from a preoperative clinic completed an initial survey where they estimated their hospital length of stay and personal perioperative risks of the 12 clinical complications analyzed by the ACS Calculator. Next, risk calculation was performed by entering participants' demographics into the ACS Calculator. Participants reviewed their individualized risk reports in detail and then completed a follow-up survey to evaluate their perceptions. RESULTS Nearly 90% of participants desire to review their ACS Calculator report before future surgical consents. High-risk patients were 3 times more likely to underestimate their risk of any complication, serious complication, and length of stay compared to low-risk patients (P < .001). After reviewing their calculated risks, 70% stated that they would consider participating in prehabilitation to decrease perioperative risk, and nearly 40% would delay their surgery to do so. Knowledge of personal ACS risk calculations had no effect on anxiety in 20% and decreased anxiety in 71% of participants. CONCLUSIONS The ACS Calculator may be of particular benefit to high-risk surgical populations by providing realistic expectations of outcomes and recovery. Use of this tool may also provide motivation for patients to participate in risk reduction strategies.
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Affiliation(s)
| | | | | | - Timothy M Geiger
- General Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - John W Stokes
- General Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
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Goel R, Patel EU, Cushing MM, Frank SM, Ness PM, Takemoto CM, Vasovic LV, Sheth S, Nellis ME, Shaz B, Tobian AAR. Association of Perioperative Red Blood Cell Transfusions With Venous Thromboembolism in a North American Registry. JAMA Surg 2019; 153:826-833. [PMID: 29898202 DOI: 10.1001/jamasurg.2018.1565] [Citation(s) in RCA: 112] [Impact Index Per Article: 22.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Importance Increasing evidence supports the role of red blood cells (RBCs) in physiological hemostasis and pathologic thrombosis. Red blood cells are commonly transfused in the perioperative period; however, their association with postoperative thrombotic events remains unclear. Objective To examine the association between perioperative RBC transfusions and postoperative venous thromboembolism (VTE) within 30 days of surgery. Design, Setting, and Participants This analysis used prospectively collected registry data from the American College of Surgery National Surgical Quality Improvement Program (ACS-NSQIP) database, a validated registry of 525 teaching and nonteaching hospitals in North America. Participants included patients in the ACS-NSQIP registry who underwent a surgical procedure from January 1 through December 31, 2014. Data were analyzed from July 1, 2016, through March 15, 2018. Main Outcomes and Measures Risk-adjusted odds ratios (aORs) were estimated using multivariable logistic regression. The primary outcome was the development of postoperative VTE (deep venous thrombosis [DVT] and pulmonary embolism [PE]) within 30 days of surgery that warranted therapeutic intervention; DVT and PE were also examined separately as secondary outcomes. Subgroup analyses were performed by surgical subtypes. Propensity score matching was performed for sensitivity analyses. Results Of 750 937 patients (56.8% women; median age, 58 years; interquartile range, 44-69 years), 47 410 (6.3%) received at least 1 perioperative RBC transfusion. Postoperative VTE occurred in 6309 patients (0.8%) (DVT in 4336 [0.6%]; PE in 2514 [0.3%]; both DVT and PE in 541 [0.1%]). Perioperative RBC transfusion was associated with higher odds of VTE (aOR, 2.1; 95% CI, 2.0-2.3), DVT (aOR, 2.2; 95% CI, 2.1-2.4), and PE (aOR, 1.9; 95% CI, 1.7-2.1), independent of various putative risk factors. A significant dose-response effect was observed with increased odds of VTE as the number of intraoperative and/or postoperative RBC transfusion events increased (aOR, 2.1 [95% CI, 2.0-2.3] for 1 event; 3.1 [95% CI, 1.7-5.7] for 2 events; and 4.5 [95% CI, 1.0-19.4] for ≥3 events vs no intraoperative or postoperative RBC transfusion; P < .001 for trend). In subgroup analyses, the association between any perioperative RBC transfusion and postoperative VTE remained statistically significant across all surgical subspecialties analyzed. The association between any perioperative RBC transfusion and the development of postoperative VTE also remained robust after 1:1 propensity score matching (47 142 matched pairs; matched OR, 1.9; 95% CI, 1.8-2.1). Conclusions and Relevance The results of this study suggest that perioperative RBC transfusions may be significantly associated with the development of new or progressive postoperative VTE, independent of several putative confounders. These findings, if validated, should reinforce the importance of rigorous perioperative management of blood transfusion practices.
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Affiliation(s)
- Ruchika Goel
- Division of Transfusion Medicine, Department of Pathology, New York Presbyterian Hospital, Weill Cornell Medicine, New York.,Division of Pediatric Hematology/Oncology, Department of Pediatrics, New York Presbyterian Hospital, Weill Cornell Medicine, New York
| | - Eshan U Patel
- Division of Transfusion Medicine, Department of Pathology, Johns Hopkins University, Baltimore, Maryland
| | - Melissa M Cushing
- Division of Transfusion Medicine, Department of Pathology, New York Presbyterian Hospital, Weill Cornell Medicine, New York
| | - Steven M Frank
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Paul M Ness
- Division of Transfusion Medicine, Department of Pathology, Johns Hopkins University, Baltimore, Maryland
| | - Clifford M Takemoto
- Division of Pediatric Hematology, Johns Hopkins University, Baltimore, Maryland
| | - Ljiljana V Vasovic
- Division of Transfusion Medicine, Department of Pathology, New York Presbyterian Hospital, Weill Cornell Medicine, New York
| | - Sujit Sheth
- Division of Pediatric Hematology/Oncology, Department of Pediatrics, New York Presbyterian Hospital, Weill Cornell Medicine, New York
| | - Marianne E Nellis
- Division of Pediatric Critical Care Medicine, Department of Pediatrics, New York Presbyterian Hospital, Weill Cornell Medicine, New York
| | | | - Aaron A R Tobian
- Division of Transfusion Medicine, Department of Pathology, Johns Hopkins University, Baltimore, Maryland
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Hyde LZ, Valizadeh N, Al-Mazrou AM, Kiran RP. ACS-NSQIP risk calculator predicts cohort but not individual risk of complication following colorectal resection. Am J Surg 2018; 218:131-135. [PMID: 30522696 DOI: 10.1016/j.amjsurg.2018.11.017] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Revised: 10/27/2018] [Accepted: 11/14/2018] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Compare the ACS-NSQIP risk calculator with institutional risk for colorectal surgery. METHODS Actual and predicted outcomes were compared for both cohort and individuals. RESULTS For the cohort, the risk calculator was accurate for 7/8 outcomes; there were more serious complications than predicted (19.4 vs 14.7%, p < 0.05). Risk calculator Brier scores and null Brier scores were comparable. PATIENTS with better outcomes than predicted were current smokers (OR 4.3 95% CI 1.2-15.4), ASA ≥ 3 (OR 10.4, 95% CI 2.8-39.2), underwent total/subtotal colectomy (OR 3.5, 95% CI 1.1-12.2) or operated by Surgeon 2 (OR 2.9, 95% CI 1.4-11.6). Patients with serious complications who had low predicted risk had low ASA (OR 10.5, 95% CI 1.3-82.6), and underwent operation by Surgeon 2 (OR 11.8, 95% CI 2.5, 55.2). LIMITATIONS Single center study, sample size may bias subgroup analyses. CONCLUSIONS The ACS NSQIP calculator did not predict outcome better than sample risk.
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Affiliation(s)
- Laura Z Hyde
- Division of Colorectal Surgery, Columbia University Medical Center/New York Presbyterian Hospital, USA; Department of Surgery, University of California San Francisco East Bay, USA
| | - Neda Valizadeh
- Division of Colorectal Surgery, Columbia University Medical Center/New York Presbyterian Hospital, USA
| | - Ahmed M Al-Mazrou
- Division of Colorectal Surgery, Columbia University Medical Center/New York Presbyterian Hospital, USA
| | - Ravi P Kiran
- Division of Colorectal Surgery, Columbia University Medical Center/New York Presbyterian Hospital, USA.
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Juo YY, Ziaeian B, Benharash P. Myocardial Infarction After Vascular Surgery-Reply. JAMA Surg 2018; 153:497. [PMID: 29417142 PMCID: PMC7676383 DOI: 10.1001/jamasurg.2017.6144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Affiliation(s)
- Yen-Yi Juo
- Center for Advanced Surgical and Interventional Technology, University of California, Los Angeles.,Department of Surgery, George Washington University, Washington, DC
| | - Boback Ziaeian
- Department of Cardiology, Veteran Affairs Greater Los Angeles Healthcare System, Los Angeles, California
| | - Peyman Benharash
- Center for Advanced Surgical and Interventional Technology, University of California, Los Angeles.,Department of Surgery, University of California, Los Angeles
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Madhavan S, Shelat VG, Soong SL, Woon WWL, Huey T, Chan YH, Junnarkar SP. Predicting morbidity of liver resection. Langenbecks Arch Surg 2018; 403:359-369. [PMID: 29417211 DOI: 10.1007/s00423-018-1656-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Accepted: 01/25/2018] [Indexed: 02/08/2023]
Abstract
PURPOSE Multiple models have attempted to predict morbidity of liver resection (LR). This study aims to determine the efficacy of American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) surgical risk calculator and the Physiological and Operative Severity Score in the enUmeration of Mortality and Morbidity (POSSUM) in predicting post-operative morbidity in patients who underwent LR. METHODS A retrospective analysis was conducted on patients who underwent elective LR. Morbidity risk was calculated with the ACS-NSQIP surgical risk calculator and POSSUM equation. Two models were then constructed for both ACS-NSQIP and POSSUM-(1) the original risk probabilities from each scoring system and (2) a model derived from logistic regression of variables. Discrimination, calibration, and overall performance for ACS-NSQIP and POSSUM were compared. Sub-group analysis was performed for both primary and secondary liver malignancies. RESULTS Two hundred forty-five patients underwent LR. Two hundred twenty-three (91%) had malignant liver pathologies. The post-operative morbidity, 90-day mortality, and 30-day mortality rate were 38.3%, 3.7%, and 2.4% respectively. ACS-NSQIP showed superior discriminative ability, calibration, and performance to POSSUM (p = 0.03). Hosmer-Lemeshow plot demonstrated better fit of the ACS-NSQIP model than POSSUM in predicting morbidity. CONCLUSION In patients undergoing LR, the ACS-NSQIP surgical risk calculator was superior to POSSUM in predicting morbidity risk.
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Affiliation(s)
- Sudharsan Madhavan
- Ministry of Health Holdings, 1 Maritime Square, #11-25 HarbourFront Centre, Singapore, 099253, Republic of Singapore
| | - Vishal G Shelat
- Hepato-Pancreatico-Biliary Surgery, Department of General Surgery, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore, 308433, Republic of Singapore
| | - Su-Lin Soong
- Hepato-Pancreatico-Biliary Surgery, Department of General Surgery, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore, 308433, Republic of Singapore
| | - Winston W L Woon
- Hepato-Pancreatico-Biliary Surgery, Department of General Surgery, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore, 308433, Republic of Singapore
| | - Terence Huey
- Hepato-Pancreatico-Biliary Surgery, Department of General Surgery, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore, 308433, Republic of Singapore
| | - Yiong H Chan
- Biostatistics Unit, National University Health System, 1E Kent Ridge Road, Singapore, 119228, Republic of Singapore
| | - Sameer P Junnarkar
- Hepato-Pancreatico-Biliary Surgery, Department of General Surgery, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore, 308433, Republic of Singapore.
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Costa G, Massa G. Frailty and emergency surgery in the elderly: protocol of a prospective, multicenter study in Italy for evaluating perioperative outcome (The FRAILESEL Study). Updates Surg 2018; 70:97-104. [PMID: 29383680 DOI: 10.1007/s13304-018-0511-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Accepted: 01/13/2018] [Indexed: 02/07/2023]
Abstract
Improvements in living conditions and progress in medical management have resulted in better quality of life and longer life expectancy. Therefore, the number of older people undergoing surgery is increasing. Frailty is often described as a syndrome in aged patients where there is augmented vulnerability due to progressive loss of functional reserves. Studies suggest that frailty predisposes elderly to worsening outcome after surgery. Since emergency surgery is associated with higher mortality rates, it is paramount to have an accurate stratification of surgical risk in such patients. The aim of our study is to characterize the clinicopathological findings, management, and short-term outcome of elderly patients undergoing emergency surgery. The secondary objectives are to evaluate the presence and influence of frailty and analyze the prognostic role of existing risk-scores. The final FRAILESEL protocol was approved by the Ethical Committee of "Sapienza" University of Rome, Italy. The FRAILESEL study is a nationwide, Italian, multicenter, observational study conducted through a resident-led model. Patients over 65 years of age who require emergency surgical procedures will be included in this study. The primary outcome measures are 30-day postoperative mortality and morbidity rates. The Clavien-Dindo classification system is used to categorize complications. The secondary outcome measures include length of hospital stay, length of stay in intensive care unit, and predictive value for morbidity and mortality of several frailty and surgical risk-scores. The results of the FRAILESEL study will be disseminated through national and international conference presentations and peer-reviewed journals. The study is also registered at ClinicalTrials.gov (ClinicalTrials.gov identifier: NCT02825082).
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Affiliation(s)
- Gianluca Costa
- Surgical and Medical Department of Translational Medicine, Sant'Andrea Teaching Hospital, "Sapienza" University, 00189, Rome, Italy
| | - Giulia Massa
- Surgical and Medical Department of Translational Medicine, Sant'Andrea Teaching Hospital, "Sapienza" University, 00189, Rome, Italy.
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The DGAV risk calculator: development and validation of statistical models for a web-based instrument predicting complications of colorectal cancer surgery. Int J Colorectal Dis 2017; 32:1385-1397. [PMID: 28799112 DOI: 10.1007/s00384-017-2869-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/25/2017] [Indexed: 02/04/2023]
Abstract
PURPOSE The purpose of this study is to provide a web-based calculator predicting complication probabilities of patients undergoing colorectal cancer (CRC) surgery in Germany. METHODS Analyses were based on records of first-time CRC surgery between 2010 and February 2017, documented in the database of the Study, Documentation, and Quality Center (StuDoQ) of the Deutsche Gesellschaft für Allgemein- und Viszeralchirurgie (DGAV), a registry of CRC surgery in hospitals throughout Germany, covering demography, medical history, tumor features, comorbidity, behavioral risk factors, surgical procedures, and outcomes. Using logistic ridge regression, separate models were developed in learning samples of 6729 colon and 4381 rectum cancer patients and evaluated in validation samples of sizes 2407 and 1287. Discrimination was assessed using c statistics. Calibration was examined graphically by plotting observed versus predicted complication probabilities and numerically using Brier scores. RESULTS We report validation results regarding 15 outcomes such as any major complication, surgical site infection, anastomotic leakage, bladder voiding disturbance after rectal surgery, abdominal wall dehiscence, various internistic complications, 30-day readmission, 30-day reoperation rate, and 30-day mortality. When applied to the validation samples, c statistics ranged between 0.60 for anastomosis leakage and 0.85 for mortality after rectum cancer surgery. Brier scores ranged from 0.003 to 0.127. CONCLUSIONS While most models showed satisfactory discrimination and calibration, this does not preclude overly optimistic or pessimistic individual predictions. To avoid misinterpretation, one has to understand the basic principles of risk calculation and risk communication. An e-learning tool outlining the appropriate use of the risk calculator is provided.
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Hamdan MH, Walsh KE, Brignole M, Key J. Outreach syncope clinic managed by a nurse practitioner: Outcome and cost effectiveness. J Telemed Telecare 2017; 24:566-571. [PMID: 28741420 DOI: 10.1177/1357633x17718087] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Introduction The purpose of this study was to assess the clinical and financial outcomes of a novel outreach syncope clinic. Methods We compared the clinical outcome of the Faint and Fall Clinic at the American Center (January-June 2016) with that of the University of Wisconsin Health and Clinics Faint and Fall Clinic (January 2013-December 2014). The American Center-Faint and Fall Clinic is run solely by a nurse practitioner, assisted by online faint-decision software and consultancy of a faint specialist through video-conferencing. Results Five hundred and twenty-eight consecutive patients were seen at the University of Wisconsin Hospital and Clinics-Faint and Fall Clinic and 68 patients at the American Center-Faint and Fall Clinic. The patients' clinical characteristics were similar except for a lower age in the American Center patients (45 ± 18 vs 51 ± 22, p = 0.03). Overall, a diagnosis was made within 45 days in 70% (95% confidence interval 66-74%) of the University of Wisconsin Hospital and Clinics patients and 69% (95% confidence interval 58-80%) of the American Center patients, ( p = 0.9). A mean of 3.0 ± 1.6 tests per patient was used in the University of Wisconsin Hospital and Clinics group compared to 1.5 ± 0.8 tests per patient in the American Center group, p = 0.001. Over the six-month study period, the total revenue at the American Center was US$152,597 (contribution margin of US$122,393 plus professional revenue of US$30,204). The total cost of the nurse practitioner including benefits was US$66,662 ((US$98,466 salary/year + 35.4% benefits)/2). Total revenue minus expenses resulted in a net profit of US$85,935. Discussion A nurse practitioner-run outreach syncope-clinic equipped with online faint-decision software and consultancy of a faint specialist through vedio-conferencing is feasible and financially self-sustainable. It allows the dissemination of standardized high-quality syncope care to patients who have no immediate access to a tertiary teaching hospital.
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Affiliation(s)
- Mohamed H Hamdan
- 1 Division of Cardiovascular Medicine, University of Wisconsin, Madison, Wisconsin, USA
| | - Kathleen E Walsh
- 1 Division of Cardiovascular Medicine, University of Wisconsin, Madison, Wisconsin, USA
| | | | - Jamie Key
- 1 Division of Cardiovascular Medicine, University of Wisconsin, Madison, Wisconsin, USA
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