Evidence map›Paper›PMID 33225305›Full record

ArticleCritical care explorations2020

Timing of Tracheostomy for Prolonged Respiratory Wean in Critically Ill Coronavirus Disease 2019 Patients: A Machine Learning Approach.

Arunjit Takhar, Pavol Surda, Imran Ahmad, Nikul Amin, Asit Arora, Luigi Camporota, Poppy Denniston, Kariem El-Boghdadly, Miroslav Kvassay, Denisa Macekova and 8 more

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 3 pooled it
2.0field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 3 syntheses or guidelines pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Systematic review and meta-analysis of tracheostomy outcomes in COVID-19 patients.The British journal of oral & maxillofacial surgery · 2021
    Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors at 4 institutions in 2 countries.

Arunjit TakharDepartment of Otolaryngology and Head and Neck Surgery, Guy's & St Thomas' NHS Foundation Trust, London, United Kingdom.
Pavol SurdaDepartment of Otolaryngology and Head and Neck Surgery, Guy's & St Thomas' NHS Foundation Trust, London, United Kingdom.
Imran AhmadDepartment of Anaesthesia, Guy's & St Thomas' NHS Foundation Trust, London, United Kingdom.
Nikul AminDepartment of Otolaryngology and Head and Neck Surgery, Guy's & St Thomas' NHS Foundation Trust, London, United Kingdom.
Asit AroraDepartment of Otolaryngology and Head and Neck Surgery, Guy's & St Thomas' NHS Foundation Trust, London, United Kingdom.
Luigi CamporotaDepartment of Critical Care, Guy's & St Thomas' NHS Foundation Trust, London, United Kingdom.
Poppy DennistonDepartment of Respiratory Medicine, Guy's & St Thomas' NHS Foundation Trust, London, United Kingdom.
Kariem El-BoghdadlyDepartment of Anaesthesia, Guy's & St Thomas' NHS Foundation Trust, London, United Kingdom.
Miroslav KvassayDepartment of Informatics, Faculty of Management Science and Informatics, University of Zilina, Zilina, Slovakia.
Denisa MacekovaDepartment of Informatics, Faculty of Management Science and Informatics, University of Zilina, Zilina, Slovakia.
Michal MunkDepartment of Informatics, Constantine the Philosopher University, Nitra, Slovakia.
David RanfordDepartment of Critical Care, Guy's & St Thomas' NHS Foundation Trust, London, United Kingdom.
Jan RabcanDepartment of Informatics, Faculty of Management Science and Informatics, University of Zilina, Zilina, Slovakia.
Chysostomos TornariDepartment of Otolaryngology and Head and Neck Surgery, Guy's & St Thomas' NHS Foundation Trust, London, United Kingdom.
Duncan WyncollDepartment of Critical Care, Guy's & St Thomas' NHS Foundation Trust, London, United Kingdom.
Elena ZaitsevaDepartment of Informatics, Constantine the Philosopher University, Nitra, Slovakia.
Nicholas HartLane Fox Respiratory Unit, Guy's & St Thomas' NHS Foundation Trust, London, United Kingdom.
Stephen TricklebankDepartment of Critical Care, Guy's & St Thomas' NHS Foundation Trust, London, United Kingdom.
Guy's and St Thomas' NHS Foundation Trust · GBUniversity of Žilina · SKConstantine the Philosopher University in Nitra · SKKing's College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

coronavirus disease 2019mechanically ventilated patientssevere acute respiratory syndrome coronavirus-2tracheostomy

Identifiers

PMID33225305
PMCPMC7673767
OpenAlexW3106136033

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.