Evidence map›Paper›PMID 32574468›Full record

ArticleCritical care medicine2020

Predicting and Surviving Prolonged Critical Illness After Congenital Heart Surgery.

Aaron G DeWitt, Joseph W Rossano, David K Bailly, Priya N Bhat, Nikhil K Chanani, Brandon W Kirkland, Michael-Alice Moga, Gabe E Owens, Lauren B Retzloff, Wenying Zhang and 4 more

Open access · greenAbstract read
In one paragraph

Article in Critical care medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 12% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
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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

14 authors at 2 institutions in 1 country.

Aaron G DeWittDivision of Cardiac Critical Care Medicine, Departments of Pediatrics and Anesthesia & Critical Care Medicine, Children's Hospital of Philadelphia, Perelman School of Medicine, Philadelphia, PA.
Joseph W RossanoDivision of Cardiology, Department of Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine, Philadelphia, PA.
David K BaillyDivision of Critical Care, Department of Pediatrics, Primary Children's Hospital, University of Utah School of Medicine, Salt Lake City, UT.
Priya N BhatDivision of Pediatric Critical Care, Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, Houston, TX.
Nikhil K ChananiDivision of Cardiology, Sibley Heart Center, Children's Healthcare of Atlanta, Emory University, Atlanta, GA.
Brandon W KirklandDivision of Critical Care, Department of Pediatrics, Primary Children's Hospital, University of Utah School of Medicine, Salt Lake City, UT.
Michael-Alice MogaDepartment of Critical Care Medicine and Department of Paediatrics, The Hospital for Sick Children, University of Toronto School of Medicine, Toronto, ON, Canada.
Gabe E OwensDivision of Cardiology, Department of Pediatrics and Communicable Diseases, C.S. Mott Children's Hospital, University of Michigan Medical School, Ann Arbor, MI.
Lauren B RetzloffDivision of Cardiology, Department of Pediatrics and Communicable Diseases, C.S. Mott Children's Hospital, University of Michigan Medical School, Ann Arbor, MI.
Wenying ZhangCenter for Healthcare Outcomes & Policy, University of Michigan, Ann Arbor, MI.
Mousumi BanerjeeCenter for Healthcare Outcomes & Policy, University of Michigan, Ann Arbor, MI.
Andrew T CostarinoDivision of Cardiac Critical Care Medicine, Departments of Pediatrics and Anesthesia & Critical Care Medicine, Children's Hospital of Philadelphia, Perelman School of Medicine, Philadelphia, PA.
Geoffrey L BirdDivision of Cardiac Critical Care Medicine, Departments of Pediatrics and Anesthesia & Critical Care Medicine, Children's Hospital of Philadelphia, Perelman School of Medicine, Philadelphia, PA.
Michael GaiesDivision of Cardiology, Department of Pediatrics and Communicable Diseases, C.S. Mott Children's Hospital, University of Michigan Medical School, Ann Arbor, MI.
University of Michigan–Ann Arbor · USTexas Children's Hospital · US

Funding

Michigan Institute for Clinical and Health Research (MICHR)UL1TR002240 · NCATS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LUMENG, JULIE C, MASHOUR, GEORGE ALEXANDER · 2017 to 2022
$54.9M
Explaining Variation in Mortality after Pediatric Cardiac SurgeryK08HL116639 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GAIES, MICHAEL · 2014 to 2018
$767k
NCATS NIH HHS UL1 TR002240NHLBI NIH HHS K08 HL116639
6 · The paper itself

Abstract

objectivesProlonged critical illness after congenital heart surgery disproportionately harms patients and the healthcare system, yet much remains unknown. We aimed to define prolonged critical illness, delineate between nonmodifiable and potentially preventable predictors of prolonged critical illness and prolonged critical illness mortality, and understand the interhospital variation in prolonged critical illness.

designObservational analysis.

settingPediatric Cardiac Critical Care Consortium clinical registry. PATIENTS: All patients, stratified into neonates (≤28 d) and nonneonates (29 d to 18 yr), admitted to the pediatric cardiac ICU after congenital heart surgery at Pediatric Cardiac Critical Care Consortium hospitals.

interventionsNone. MEASUREMENTS AND MAIN

resultsThere were 2,419 neonates and 10,687 nonneonates from 22 hospitals. The prolonged critical illness cutoff (90th percentile length of stay) was greater than or equal to 35 and greater than or equal to 10 days for neonates and nonneonates, respectively. Cardiac ICU prolonged critical illness mortality was 24% in neonates and 8% in nonneonates (vs 5% and 0.4%, respectively, in nonprolonged critical illness patients). Multivariable logistic regression identified 10 neonatal and 19 nonneonatal prolonged critical illness predictors within strata and eight predictors of mortality. Only mechanical ventilation days and acute renal failure requiring renal replacement therapy predicted prolonged critical illness and prolonged critical illness mortality in both strata. Approximately 40% of the prolonged critical illness predictors were nonmodifiable (preoperative/patient and operative factors), whereas only one of eight prolonged critical illness mortality predictors was nonmodifiable. The remainders were potentially preventable (postoperative critical care delivery variables and complications). Case-mix-adjusted prolonged critical illness rates were compared across hospitals; six hospitals each had lower- and higher-than-expected prolonged critical illness frequency.

conclusionsAlthough many prolonged critical illness predictors are nonmodifiable, we identified several predictors to target for improvement. Furthermore, we observed that complications and prolonged critical care therapy drive prolonged critical illness mortality. Wide variation of prolonged critical illness frequency suggests that identifying practices at hospitals with lower-than-expected prolonged critical illness could lead to broader quality improvement initiatives.

Indexed as

Cardiac Surgical ProceduresChildChild, PreschoolCritical IllnessFemaleHeart DiseasesHumansInfantInfant, NewbornIntensive Care Units, PediatricLength of StayMaleRegistriesRisk Factors

Identifiers

PMID32574468
PMCPMC7316132
OpenAlexW3019361153

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.