Evidence map›Paper›PMID 31813832›Full record

ArticleJournal of cardiothoracic and vascular anesthesia2020

Making Sense of Big Data to Improve Perioperative Care: Learning Health Systems and the Multicenter Perioperative Outcomes Group.

Michael R Mathis, Timur Z Dubovoy, Matthew D Caldwell, Milo C Engoren

Abstract readEditorial
In one paragraph

Article in Journal of cardiothoracic and vascular anesthesia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Observational
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Observational
  14. Article
  15. Article
  16. Observational
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

4 authors.

Michael R MathisDepartment of Anesthesiology, Adult Cardiothoracic Division, University of Michigan Health System; Center for Computational Medicine and Bioinformatics, University of Michigan Health System; Michigan Integrated Center for Health Analytics and Medical Prediction, Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI. Electronic address: mathism@med.umich.edu.
Timur Z DubovoyDepartment of Anesthesiology, Adult Cardiothoracic Division, University of Michigan Health System.
Matthew D CaldwellDepartment of Anesthesiology, Adult Cardiothoracic Division, University of Michigan Health System.
Milo C EngorenDepartment of Anesthesiology, Adult Cardiothoracic Division, University of Michigan Health System.

Funding

Early Diagnosis of Heart Failure: A Perioperative Data-Driven ApproachK01HL141701 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MATHIS, MICHAEL ROBERT · 2018 to 2022
$862k
NHLBI NIH HHS K01 HL141701
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Big DataLearning Health SystemDelivery of Health CareHumansMulticenter Studies as TopicPerioperative Care

Identifiers

PMID31813832
PMCPMC8640957

What OpenQuestion holds

Textmetadata
LicenceTDM
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.