Evidence map›Paper›PMID 34027496›Full record

ArticleSTAR protocols2021

Protocol for assessing and predicting acute respiratory decline in hospitalized patients.

Conor P Crowley, Louis T Merriam, Alisa A Mueller, Tomoyoshi Tamura, Jeremy R DeGrado, Hibah Haider, Justin D Salciccioli, Edy Y Kim

Abstract read
In one paragraph

Article in STAR protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

8 authors.

Conor P CrowleyDivision of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA.
Louis T MerriamDivision of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA.
Alisa A MuellerDivision of Rheumatology, Brigham and Women's Hospital, Boston, MA 02115 USA.
Tomoyoshi TamuraDivision of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA.
Jeremy R DeGradoDepartment of Pharmacy, Brigham and Women's Hospital, Boston, MA 02115 USA.
Hibah HaiderDivision of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA.
Justin D SalciccioliDivision of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA.
Edy Y KimDivision of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA.

Funding

MECHANISMS OF ARTHRITIC &DERMATOLOGY DISORDERST32AR007530 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI Michael B. Brenner, Ellen M Gravallese · 1986 to 2026
$10.4M
NIAMS NIH HHS T32 AR007530
6 · The paper itself

Abstract

This protocol aids both new and experienced researchers in designing retrospective clinical and translational studies of acute respiratory decline in hospitalized patients. This protocol addresses (1) the basics of respiratory failure and electronic health record research, (2) defining patient cohorts as "mild, progressive, or severe" instead of "ICU versus non-ICU", (3) adapting physiological indices, and (4) using biomarker trends. We apply these approaches to inflammatory biomarkers in COVID-19, but this protocol can be applied to any progressive respiratory failure study. For complete details on the use and execution of this protocol, please refer to Mueller et al. (2020).

Indexed as

COVID-19Diagnostic Tests, RoutineHospitalizationHumansIntensive Care UnitsRespiratory InsufficiencyRetrospective StudiesSARS-CoV-2Clinical ProtocolHealth SciencesImmunology

Identifiers

PMID34027496
PMCPMC8131117

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.