Evidence map›Paper›PMID 35252224›Full record

ArticleFrontiers in medicine2021

Reintubation Summation Calculation: A Predictive Score for Extubation Failure in Critically Ill Patients.

Vikas Bansal, Nathan J Smischney, Rahul Kashyap, Zhuo Li, Alberto Marquez, Daniel A Diedrich, Jason L Siegel, Ayan Sen, Amanda D Tomlinson, Carla P Venegas-Borsellino and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
2.4field-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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Observational
  5. Review
  6. Article
  7. Review
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

11 authors at 5 institutions in 1 country.

Vikas BansalDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN, United States.
Nathan J SmischneyCritical Care Independent Multidisciplinary Program, Mayo Clinic, Rochester, MN, United States.
Rahul KashyapCritical Care Independent Multidisciplinary Program, Mayo Clinic, Rochester, MN, United States.
Zhuo LiBiostatistics Unit, Mayo Clinic, Jacksonville, FL, United States.
Alberto MarquezDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, United States.
Daniel A DiedrichCritical Care Independent Multidisciplinary Program, Mayo Clinic, Rochester, MN, United States.
Jason L SiegelDepartment of Critical Care Medicine, Mayo Clinic, Jacksonville, FL, United States.
Ayan SenDepartment of Critical Care Medicine, Mayo Clinic Hospital, Phoenix, AZ, United States.
Amanda D TomlinsonDepartment of Critical Care Medicine, Mayo Clinic, Jacksonville, FL, United States.
Carla P Venegas-BorsellinoDepartment of Critical Care Medicine, Mayo Clinic, Jacksonville, FL, United States.
William David FreemanDepartment of Critical Care Medicine, Mayo Clinic, Jacksonville, FL, United States.
Mayo Clinic in Arizona · USMayo Clinic in Florida · USMayo Clinic · USWinnMed · USMayo Clinic Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo derive and validate a multivariate risk score for the prediction of respiratory failure after extubation. PATIENTS AND

methodsWe performed a retrospective cohort study of adult patients admitted to the intensive care unit from January 1, 2006, to December 31, 2015, who received mechanical ventilation for ≥48 h. Extubation failure was defined as the need for reintubation within 72 h after extubation. Multivariate logistic regression model coefficient estimates generated the

resultsThe 6,161 included patients were randomly divided into 2 sets: derivation (

conclusionRISC predicts extubation failure in mechanically ventilated patients in the intensive care unit using several clinically relevant variables available in the electronic medical record but requires a larger validation cohort before widespread clinical implementation.

Indexed as

critical care medicineextubation failureintensive care unitmechanical ventilationprediction scalepredictive modelingreintubation

Identifiers

PMID35252224
PMCPMC8891541
OpenAlexW4213013879

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.