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Suárez-de-la-Rica A, Ripollés-Melchor J, Aldecoa C, Abad-Motos A, Ferrando C, Abad-Gurumeta A, Díaz-Almirón M, Gil-Lapetra C, García-Miguel FJ, Pedregosa-Sanz A, Esteve-Pérez N, Rodríguez-Jiménez R, Gimeno Fernandez P, Maseda E. Postoperative Critical Care Admission Was Not Associated with Improved Postoperative Outcomes in Elective Colorectal Surgery: Secondary Analysis Of POWER Trial. J Gastrointest Surg 2023; 27:2187-2198. [PMID: 37550589 DOI: 10.1007/s11605-023-05780-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 06/30/2023] [Indexed: 08/09/2023]
Abstract
BACKGROUND The efficacy of routine admission of high-risk patients to a critical care unit after surgery is not clear. The aim of our study was to investigate the association between critical care admission after scheduled colorectal surgery and postoperative complications, 30-day mortality, and length of stay in hospital. METHODS A pre-defined secondary substudy of POWER study was performed. POWER study was a prospective multicenter observational study of patients undergoing elective primary colorectal surgery during a single period of two months of recruitment between September and December 2017. RESULTS A total of 2084 patients from 80 Spanish hospitals were included, of which 722 (34.6%) were admitted to critical care unit (CCU) after elective surgery. After adjusting for confounding factors in the multivariate analysis, postoperative CCU admission was independently associated with a higher incidence of moderate-to-severe postoperative complications (adjusted OR 1.951, 95% CI 1.570, 2.425; p < 0.001). Regarding secondary outcomes, postoperative critical care admission was independently associated with higher 30-day mortality (adjusted OR 6.736; 95% CI 2.507, 18.101; p < 0.001) and independently associated with an increased hospital length of stay (adjusted OR 1.143, 95% CI 1.112, 1.175; p < 0.001). CONCLUSIONS Direct admission to CCU after scheduled colorectal surgery was not associated with a reduction in moderate-to-severe postoperative complications.
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Affiliation(s)
- Alejandro Suárez-de-la-Rica
- Department of Anesthesiology and Surgical Critical Care, Hospital Universitario de La Princesa, Madrid, Spain.
- Spanish Perioperative Audit and Research Network (REDGERM-SPARN), Saragossa, Spain.
| | - Javier Ripollés-Melchor
- Spanish Perioperative Audit and Research Network (REDGERM-SPARN), Saragossa, Spain
- Department of Anesthesiology and Surgical Critical Care, Hospital Universitario Infanta Leonor, Madrid, Spain
| | - César Aldecoa
- Spanish Perioperative Audit and Research Network (REDGERM-SPARN), Saragossa, Spain
- Department of Anesthesiology and Surgical Critical Care, Hospital Universitario Río Hortega, Valladolid, Spain
| | - Ane Abad-Motos
- Spanish Perioperative Audit and Research Network (REDGERM-SPARN), Saragossa, Spain
- Department of Anesthesiology and Surgical Critical Care, Hospital Universitario Infanta Leonor, Madrid, Spain
| | - Carlos Ferrando
- Spanish Perioperative Audit and Research Network (REDGERM-SPARN), Saragossa, Spain
- Department of Anesthesiology and Surgical Critical Care, Hospital Clínic, Barcelona, Spain
| | - Alfredo Abad-Gurumeta
- Spanish Perioperative Audit and Research Network (REDGERM-SPARN), Saragossa, Spain
- Department of Anesthesiology and Surgical Critical Care, Hospital Universitario Infanta Leonor, Madrid, Spain
| | | | - Cristina Gil-Lapetra
- Department of Anesthesiology, Hospital Universitario de Fuenlabrada, Fuenlabrada, Spain
| | | | | | - Neus Esteve-Pérez
- Department of Anesthesiology and Surgical Critical Care, Hospital Universitario de Son Espases, Palma, Spain
| | - Rita Rodríguez-Jiménez
- Department of Anesthesiology and Surgical Critical Care, Hospital Clínico Valladolid, Valladolid, Spain
| | - Pablo Gimeno Fernandez
- Department of Anesthesiology, Hospital Nuestra Señora del Prado, Talavera de La Reina, Spain
| | - Emilio Maseda
- Department of Anesthesiology, Hospital Quirónsalud Valle del Henares, Torrejón de Ardoz, Spain.
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Romero-Brufau S, Whitford D, Johnson MG, Hickman J, Morlan BW, Therneau T, Naessens J, Huddleston JM. Using machine learning to improve the accuracy of patient deterioration predictions: Mayo Clinic Early Warning Score (MC-EWS). J Am Med Inform Assoc 2021; 28:1207-1215. [PMID: 33638343 DOI: 10.1093/jamia/ocaa347] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 12/01/2020] [Accepted: 01/27/2021] [Indexed: 11/12/2022] Open
Abstract
OBJECTIVE We aimed to develop a model for accurate prediction of general care inpatient deterioration. MATERIALS AND METHODS Training and internal validation datasets were built using 2-year data from a quaternary hospital in the Midwest. Model training used gradient boosting and feature engineering (clinically relevant interactions, time-series information) to predict general care inpatient deterioration (resuscitation call, intensive care unit transfer, or rapid response team call) in 24 hours. Data from a tertiary care hospital in the Southwest were used for external validation. C-statistic, sensitivity, positive predictive value, and alert rate were calculated for different cutoffs and compared with the National Early Warning Score. Sensitivity analysis evaluated prediction of intensive care unit transfer or resuscitation call. RESULTS Training, internal validation, and external validation datasets included 24 500, 25 784 and 53 956 hospitalizations, respectively. The Mayo Clinic Early Warning Score (MC-EWS) demonstrated excellent discrimination in both the internal and external validation datasets (C-statistic = 0.913, 0.937, respectively), and results were consistent in the sensitivity analysis (C-statistic = 0.932 in external validation). At a sensitivity of 73%, MC-EWS would generate 0.7 alerts per day per 10 patients, 45% less than the National Early Warning Score. DISCUSSION Low alert rates are important for implementation of an alert system. Other early warning scores developed for the general care ward have achieved lower discrimination overall compared with MC-EWS, likely because MC-EWS includes both nursing assessments and extensive feature engineering. CONCLUSIONS MC-EWS achieved superior prediction of general care inpatient deterioration using sophisticated feature engineering and a machine learning approach, reducing alert rate.
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Affiliation(s)
- Santiago Romero-Brufau
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA.,Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Daniel Whitford
- Department of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Matthew G Johnson
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Joel Hickman
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Bruce W Morlan
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Terry Therneau
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - James Naessens
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Jeanne M Huddleston
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
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Continuous remote monitoring to detect critical early warning scores after abdominal surgery: A prospective cohort study. Eur J Anaesthesiol 2021; 38:673-675. [PMID: 33967262 DOI: 10.1097/eja.0000000000001472] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Zhu Y, Chiu YD, Villar SS, Brand JW, Patteril MV, Morrice DJ, Clayton J, Mackay JH. Dynamic individual vital sign trajectory early warning score (DyniEWS) versus snapshot national early warning score (NEWS) for predicting postoperative deterioration. Resuscitation 2020; 157:176-184. [PMID: 33181231 PMCID: PMC7762721 DOI: 10.1016/j.resuscitation.2020.10.037] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 10/15/2020] [Accepted: 10/28/2020] [Indexed: 12/12/2022]
Abstract
Aims International early warning scores (EWS) including the additive National Early Warning Score (NEWS) and logistic EWS currently utilise physiological snapshots to predict clinical deterioration. We hypothesised that a dynamic score including vital sign trajectory would improve discriminatory power. Methods Multicentre retrospective analysis of electronic health record data from postoperative patients admitted to cardiac surgical wards in four UK hospitals. Least absolute shrinkage and selection operator-type regression (LASSO) was used to develop a dynamic model (DyniEWS) to predict a composite adverse event of cardiac arrest, unplanned intensive care re-admission or in-hospital death within 24 h. Results A total of 13,319 postoperative adult cardiac patients contributed 442,461 observations of which 4234 (0.96%) adverse events in 24 h were recorded. The new dynamic model (AUC = 0.80 [95% CI 0.78−0.83], AUPRC = 0.12 [0.10−0.14]) outperforms both an updated snapshot logistic model (AUC = 0.76 [0.73−0.79], AUPRC = 0.08 [0.60−0.10]) and the additive National Early Warning Score (AUC = 0.73 [0.70−0.76], AUPRC = 0.05 [0.02−0.08]). Controlling for the false alarm rates to be at current levels using NEWS cut-offs of 5 and 7, DyniEWS delivers a 7% improvement in balanced accuracy and increased sensitivities from 41% to 54% at NEWS 5 and 18% to –30% at NEWS 7. Conclusions Using an advanced statistical approach, we created a model that can detect dynamic changes in risk of unplanned readmission to intensive care, cardiac arrest or in-hospital mortality and can be used in real time to risk-prioritise clinical workload.
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Affiliation(s)
- Yajing Zhu
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
| | - Yi-Da Chiu
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK; Research and Development, Royal Papworth Hospital, Cambridge, UK.
| | - Sofia S Villar
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK; Research and Development, Royal Papworth Hospital, Cambridge, UK.
| | - Jonathan W Brand
- Department of Anaesthesia and Critical Care, James Cook University Hospital, Middlesbrough, UK.
| | - Mathew V Patteril
- Department of Anaesthesia and Critical Care, University Hospitals Coventry and Warwickshire, Coventry, UK.
| | - David J Morrice
- Department of Anaesthesia and Critical Care, New Cross Hospital, Wolverhampton, UK.
| | - James Clayton
- Clinical Governance, Royal Papworth Hospital, Cambridge, UK.
| | - Jonathan H Mackay
- Department of Anaesthesia and Critical Care, Royal Papworth Hospital, Cambridge, UK.
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Abstract
Surgery represents one of the main therapeutic references in the world, affording greater survival and life expectancy for many patients. In general, the estimated postoperative mortality is low (around 1-4%). Thirteen percent of the surgical procedures have a high risk of complications, accounting for 80% of all postoperative deaths. Recently, there have been significant advances related to organizational aspects, new anesthetic and surgical techniques, prognostic scales, perioperative management and greater participation and involvement of the patient. This new series of Medicina Intensiva will address fundamental aspects of how Departments of Intensive Care Medicine can add value to the surgical process, in a coordinated manner with other services. Institutional policies are required to ensure the detection of patients at risk in hospitalization wards, with early admission to the ICU of those patients in whom admission is indicated, adapting the treatment in the ICU and optimizing the criteria for discharge. The detection and prevention of post-ICU syndrome in patients and relatives, and the follow-up of ICU discharge and hospitalization in a multidisciplinary manner can reduce the sequelae among critical surgical patients, improving the outcomes and quality of life, and restoring the patient to society. In future publications of this series directed to the surgical patient, updates will be provided on the perioperative management of some of the most complex surgeries.
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Loer SA. Anesthesiologists should bring in their expertise during the early postoperative period to improve surgical outcome. Curr Opin Anaesthesiol 2018; 31:713-715. [PMID: 30247164 DOI: 10.1097/aco.0000000000000663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Affiliation(s)
- Stephan A Loer
- Department of Anesthesiology, Amsterdam University Medical Centers, VU University Medical Center, Amsterdam, The Netherlands
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