Evidence map›Paper›PMID 31312950›Full record

Observational studyWorld journal of surgery2019

ICU Risk Stratification Models Feasible for Use in Sub-Saharan Africa Show Poor Discrimination in Malawi: A Prospective Cohort Study.

Meghan Prin, Stephanie Pan, Clement Kadyaudzu, Guohua Li, Anthony Charles

Abstract readObservational Study
PubMed Publisher
In one paragraph

Observational study in World journal of surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 24% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 5 institutions in 2 countries.

Meghan PrinDepartment of Anesthesiology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX, 77030, USA. prin@bcm.edu.
Stephanie PanIcahn School of Medicine At Mt. Sinai, New York, NY, USA.
Clement KadyaudzuDepartment of Anesthesiology, Kamuzu Central Hospital, Lilongwe, Malawi.
Guohua LiDepartment of Anesthesiology, Columbia University College of Physicians & Surgeons, New York, NY, USA.
Anthony CharlesDepartment of Surgery, University of North Carolina At Chapel Hill, Chapel Hill, NC, USA.
Baylor School · USColumbia University · USIcahn School of Medicine at Mount Sinai · USKamuzu Central Hospital · MWUniversity of North Carolina at Chapel Hill · US

Funding

Fogarty Global Health Fellows Coordinating CenterR25TW009340 · FIC · UNIV OF NORTH CAROLINA CHAPEL HILL · PI CHI, BENJAMIN H. · 2012 to 2016
$6.9M
FIC NIH HHS R25 TW009340
6 · The paper itself

Abstract

backgroundCritical illness disproportionately affects people in low-income countries (LICs). Efforts to improve critical care in LICs must account for differences in demographics and infrastructure compared to high-income settings. Part of this effort includes the development and validation of intensive care unit (ICU) risk stratification models feasible for use in LICs. The purpose of this study was to validate and compare the performance of ICU mortality models developed for use in sub-Saharan Africa. MATERIALS AND

methodsThis was a prospective, observational cohort study of ICU patients in a referral hospital in Malawi. Models were selected for comparison based on a Medline search for studies which developed ICU mortality models based on cohorts in sub-Saharan Africa. Model discrimination was evaluated using the area under the curve with 95% confidence intervals (CI).

resultsDuring the study, 499 patients were admitted to the study ICU, and after exclusions, there were 319 patients. The cohort was 62% female, with the mean age 31 years (IQR: 23-41), and 74% had surgery preceding ICU admission. Discrimination for hospital mortality ranged from 0.54 (95% CI 0.48, 0.60) for the Universal Vital Assessment (UVA) to 0.72 (95% CI 0.66, 0.78) for the Malawi Intensive care Mortality Evaluation (MIME). After tenfold cross-validation, these results were unchanged.

conclusionsThe MIME outperformed other models in this prospective study. Most ICU models developed for LICs had poor to modest discrimination for hospital mortality. Future research may contribute to a better risk stratification model for LICs by refining and enhancing the MIME.

Indexed as

Hospital MortalityIntensive Care UnitsAdultCritical IllnessFemaleHumansMalePovertyProspective StudiesRisk Assessment

Identifiers

PMID31312950
OpenAlexW2961789985

What OpenQuestion holds

Textmetadata
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.