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Timing of Tracheostomy for Prolonged Respiratory Wean in Critically Ill Coronavirus Disease 2019 Patients: A Machine Learning Approach
OBJECTIVES: To propose the optimal timing to consider tracheostomy insertion for weaning of mechanically ventilated patients recovering from coronavirus disease 2019 pneumonia. We investigated the relationship between duration of mechanical ventilation prior to tracheostomy insertion and in-hospital...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7673767/ https://www.ncbi.nlm.nih.gov/pubmed/33225305 http://dx.doi.org/10.1097/CCE.0000000000000279 |
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author | Takhar, Arunjit Surda, Pavol Ahmad, Imran Amin, Nikul Arora, Asit Camporota, Luigi Denniston, Poppy El-Boghdadly, Kariem Kvassay, Miroslav Macekova, Denisa Munk, Michal Ranford, David Rabcan, Jan Tornari, Chysostomos Wyncoll, Duncan Zaitseva, Elena Hart, Nicholas Tricklebank, Stephen |
author_facet | Takhar, Arunjit Surda, Pavol Ahmad, Imran Amin, Nikul Arora, Asit Camporota, Luigi Denniston, Poppy El-Boghdadly, Kariem Kvassay, Miroslav Macekova, Denisa Munk, Michal Ranford, David Rabcan, Jan Tornari, Chysostomos Wyncoll, Duncan Zaitseva, Elena Hart, Nicholas Tricklebank, Stephen |
author_sort | Takhar, Arunjit |
collection | PubMed |
description | OBJECTIVES: To propose the optimal timing to consider tracheostomy insertion for weaning of mechanically ventilated patients recovering from coronavirus disease 2019 pneumonia. We investigated the relationship between duration of mechanical ventilation prior to tracheostomy insertion and in-hospital mortality. In addition, we present a machine learning approach to facilitate decision-making. DESIGN: Prospective cohort study. SETTING: Guy’s & St Thomas’ Hospital, London, United Kingdom. PATIENTS: Consecutive patients admitted with acute respiratory failure secondary to coronavirus disease 2019 requiring mechanical ventilation between March 3, 2020, and May 5, 2020. INTERVENTIONS: Baseline characteristics and temporal trends in markers of disease severity were prospectively recorded. Tracheostomy was performed for anticipated prolonged ventilatory wean when levels of respiratory support were favorable. Decision tree was constructed using C4.5 algorithm, and its classification performance has been evaluated by a leave-one-out cross-validation technique. MEASUREMENTS AND MAIN RESULTS: One-hundred seventy-six patients required mechanical ventilation for acute respiratory failure, of which 87 patients (49.4%) underwent tracheostomy. We identified that optimal timing for tracheostomy insertion is between day 13 and day 17. Presence of fibrosis on CT scan (odds ratio, 13.26; 95% CI [3.61–48.91]; p ≤ 0.0001) and Pao(2):Fio(2) ratio (odds ratio, 0.98; 95% CI [0.95–0.99]; p = 0.008) were independently associated with tracheostomy insertion. Cox multiple regression analysis showed that chronic obstructive pulmonary disease (hazard ratio, 6.56; 95% CI [1.04–41.59]; p = 0.046), ischemic heart disease (hazard ratio, 4.62; 95% CI [1.19–17.87]; p = 0.027), positive end-expiratory pressure (hazard ratio, 1.26; 95% CI [1.02–1.57]; p = 0.034), Pao(2):Fio(2) ratio (hazard ratio, 0.98; 95% CI [0.97–0.99]; p = 0.003), and C-reactive protein (hazard ratio, 1.01; 95% CI [1–1.01]; p = 0.005) were independent late predictors of in-hospital mortality. CONCLUSIONS: We propose that the optimal window for consideration of tracheostomy for ventilatory weaning is between day 13 and 17. Late predictors of mortality may serve as adverse factors when considering tracheostomy, and our decision tree provides a degree of decision support for clinicians. |
format | Online Article Text |
id | pubmed-7673767 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-76737672020-11-19 Timing of Tracheostomy for Prolonged Respiratory Wean in Critically Ill Coronavirus Disease 2019 Patients: A Machine Learning Approach Takhar, Arunjit Surda, Pavol Ahmad, Imran Amin, Nikul Arora, Asit Camporota, Luigi Denniston, Poppy El-Boghdadly, Kariem Kvassay, Miroslav Macekova, Denisa Munk, Michal Ranford, David Rabcan, Jan Tornari, Chysostomos Wyncoll, Duncan Zaitseva, Elena Hart, Nicholas Tricklebank, Stephen Crit Care Explor Original Clinical Report OBJECTIVES: To propose the optimal timing to consider tracheostomy insertion for weaning of mechanically ventilated patients recovering from coronavirus disease 2019 pneumonia. We investigated the relationship between duration of mechanical ventilation prior to tracheostomy insertion and in-hospital mortality. In addition, we present a machine learning approach to facilitate decision-making. DESIGN: Prospective cohort study. SETTING: Guy’s & St Thomas’ Hospital, London, United Kingdom. PATIENTS: Consecutive patients admitted with acute respiratory failure secondary to coronavirus disease 2019 requiring mechanical ventilation between March 3, 2020, and May 5, 2020. INTERVENTIONS: Baseline characteristics and temporal trends in markers of disease severity were prospectively recorded. Tracheostomy was performed for anticipated prolonged ventilatory wean when levels of respiratory support were favorable. Decision tree was constructed using C4.5 algorithm, and its classification performance has been evaluated by a leave-one-out cross-validation technique. MEASUREMENTS AND MAIN RESULTS: One-hundred seventy-six patients required mechanical ventilation for acute respiratory failure, of which 87 patients (49.4%) underwent tracheostomy. We identified that optimal timing for tracheostomy insertion is between day 13 and day 17. Presence of fibrosis on CT scan (odds ratio, 13.26; 95% CI [3.61–48.91]; p ≤ 0.0001) and Pao(2):Fio(2) ratio (odds ratio, 0.98; 95% CI [0.95–0.99]; p = 0.008) were independently associated with tracheostomy insertion. Cox multiple regression analysis showed that chronic obstructive pulmonary disease (hazard ratio, 6.56; 95% CI [1.04–41.59]; p = 0.046), ischemic heart disease (hazard ratio, 4.62; 95% CI [1.19–17.87]; p = 0.027), positive end-expiratory pressure (hazard ratio, 1.26; 95% CI [1.02–1.57]; p = 0.034), Pao(2):Fio(2) ratio (hazard ratio, 0.98; 95% CI [0.97–0.99]; p = 0.003), and C-reactive protein (hazard ratio, 1.01; 95% CI [1–1.01]; p = 0.005) were independent late predictors of in-hospital mortality. CONCLUSIONS: We propose that the optimal window for consideration of tracheostomy for ventilatory weaning is between day 13 and 17. Late predictors of mortality may serve as adverse factors when considering tracheostomy, and our decision tree provides a degree of decision support for clinicians. Lippincott Williams & Wilkins 2020-11-17 /pmc/articles/PMC7673767/ /pubmed/33225305 http://dx.doi.org/10.1097/CCE.0000000000000279 Text en Copyright © 2020 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. |
spellingShingle | Original Clinical Report Takhar, Arunjit Surda, Pavol Ahmad, Imran Amin, Nikul Arora, Asit Camporota, Luigi Denniston, Poppy El-Boghdadly, Kariem Kvassay, Miroslav Macekova, Denisa Munk, Michal Ranford, David Rabcan, Jan Tornari, Chysostomos Wyncoll, Duncan Zaitseva, Elena Hart, Nicholas Tricklebank, Stephen Timing of Tracheostomy for Prolonged Respiratory Wean in Critically Ill Coronavirus Disease 2019 Patients: A Machine Learning Approach |
title | Timing of Tracheostomy for Prolonged Respiratory Wean in Critically Ill Coronavirus Disease 2019 Patients: A Machine Learning Approach |
title_full | Timing of Tracheostomy for Prolonged Respiratory Wean in Critically Ill Coronavirus Disease 2019 Patients: A Machine Learning Approach |
title_fullStr | Timing of Tracheostomy for Prolonged Respiratory Wean in Critically Ill Coronavirus Disease 2019 Patients: A Machine Learning Approach |
title_full_unstemmed | Timing of Tracheostomy for Prolonged Respiratory Wean in Critically Ill Coronavirus Disease 2019 Patients: A Machine Learning Approach |
title_short | Timing of Tracheostomy for Prolonged Respiratory Wean in Critically Ill Coronavirus Disease 2019 Patients: A Machine Learning Approach |
title_sort | timing of tracheostomy for prolonged respiratory wean in critically ill coronavirus disease 2019 patients: a machine learning approach |
topic | Original Clinical Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7673767/ https://www.ncbi.nlm.nih.gov/pubmed/33225305 http://dx.doi.org/10.1097/CCE.0000000000000279 |
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