ArticleCritical care explorations2020
Timing of Tracheostomy for Prolonged Respiratory Wean in Critically Ill Coronavirus Disease 2019 Patients: A Machine Learning Approach.
Article in Critical care explorations, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled it.
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Who cites it
8 citing papers in PubMed, 3 syntheses or guidelines pooled it, 18 citations in OpenAlex.
- Tracheostomy outcomes in critically ill patients with COVID-19: a systematic review, meta-analysis, and meta-regression.British journal of anaesthesia · 2022Pooled it
- Systematic review and meta-analysis of tracheostomy outcomes in COVID-19 patients.The British journal of oral & maxillofacial surgery · 2021Pooled it
- Association of Tracheostomy With Outcomes in Patients With COVID-19 and SARS-CoV-2 Transmission Among Health Care Professionals: A Systematic Review and Meta-analysis.JAMA otolaryngology-- head & neck surgery · 2021Pooled it
- Deployable machine learning-based decision support system for tracheostomy in acute burn patients.Burns & trauma · 2025Article
- A New Fuzzy-Based Classification Method for Use in Smart/Precision Medicine.Bioengineering (Basel, Switzerland) · 2023Article
- Extracorporeal membrane oxygenation and inhaled sedation in coronavirus disease 2019-related acute respiratory distress syndrome.World journal of critical care medicine · 2021Review
- Outcomes of tracheostomy in COVID-19 patients in National Guard Health Affairs, Riyadh, Saudi Arabia.Saudi medical journal · 2021Article
- COUNTERPOINT: Tracheostomy in Patients With COVID-19: Should We Do It Before 14 Days? No.Chest · 2021Article
Corrections and comments
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Authors and funding
18 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo 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.
designProspective cohort study.
settingGuy'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.
interventionsBaseline 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
resultsOne-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];
conclusionsWe 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.
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