Evidence map›Paper›PMID 31215498›Full record

Observational studyCritical care (London, England)2019

The association between nutritional adequacy and 28-day mortality in the critically ill is not modified by their baseline nutritional status and disease severity.

Charles Chin Han Lew, Gabriel Jun Yung Wong, Ka Po Cheung, Robert J L Fraser, Ai Ping Chua, Mary Foong Fong Chong, Michelle Miller

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Critical care (London, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 18% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

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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

7 authors at 3 institutions in 3 countries.

Charles Chin Han LewNutrition and Dietetics, College of Nursing and Health Sciences, Flinders University, GPO Box 2100, Adelaide, 5001, South Australia. Charles_lew@nuhs.edu.sg.ORCID http://orcid.org/0000-0001-6410-3859
Gabriel Jun Yung WongDietetics and Nutrition Department, Ng Teng Fong General Hospital, 1 Jurong East Street 21, Singapore, 609606, Singapore.
Ka Po CheungDietetics and Nutrition Department, Ng Teng Fong General Hospital, 1 Jurong East Street 21, Singapore, 609606, Singapore.
Robert J L FraserDepartment of Gastroenterology and Hepatology, College of Medicine and Public Health, Flinders University, GPO Box 2100, Adelaide, 5001, South Australia.
Ai Ping ChuaDepartment of Respiratory Medicine, Ng Teng Fong General Hospital, 1 Jurong East Street 21, Singapore, 609606, Singapore.
Mary Foong Fong ChongSaw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive 2, #10-01, Singapore, 117549, Singapore.
Michelle MillerNutrition and Dietetics, College of Nursing and Health Sciences, Flinders University, GPO Box 2100, Adelaide, 5001, South Australia.
Flinders University · AUNg Teng Fong General Hospital · SGNational University of Singapore · SG

Funding

JurongHealth Internal Research & Development (R&D) Grant. -
6 · The paper itself

Abstract

backgroundDuring the initial phase of critical illness, the association between the dose of nutrition support and mortality risk may vary among patients in the intensive care unit (ICU) because the prevalence of malnutrition varies widely (28 to 78%), and not all ICU patients are severely ill. Therefore, we hypothesized that a prognostic model that integrates nutritional status and disease severity could accurately predict mortality risk and classify critically ill patients into low- and high-risk groups. Additionally, in critically ill patients placed on exclusive nutritional support (ENS), we hypothesized that their risk categories could modify the association between dose of nutrition support and mortality risk.

methodsA prognostic model that predicts 28-day mortality was built from a prospective cohort study of 440 patients. The association between dose of nutrition support and mortality risk was evaluated in a subgroup of 252 mechanically ventilated patients via logistic regressions, stratified by low- and high-risk groups, and days of exclusive nutritional support (ENS) [short-term (≤ 6 days) vs. longer-term (≥ 7 days)]. Only the first 6 days of ENS was evaluated for a fair comparison.

resultsThe prognostic model demonstrated good discrimination [AUC 0.78 (95% CI 0.73-0.82), and a bias-corrected calibration curve suggested fair accuracy. In high-risk patients with short-term ENS (≤ 6 days), each 10% increase in goal energy and protein intake was associated with an increased adjusted odds (95% CI) of 28-day mortality [1.60 (1.19-2.15) and 1.47 (1.12-1.86), respectively]. In contrast, each 10% increase in goal protein intake during the first 6 days of ENS in high-risk patients with longer-term ENS (≥ 7 days) was associated with a lower adjusted odds of 28-day mortality [0.75 (0.57-0.99)]. Despite the opposing associations, the mean predicted mortality risks and prevalence of malnutrition between short- and longer-term ENS patients were similar.

conclusionsCombining baseline nutritional status and disease severity in a prognostic model could accurately predict 28-day mortality. However, the association between the dose of nutrition support during the first 6 days of ENS and 28-day mortality was independent of baseline disease severity and nutritional status.

Indexed as

Nutritional StatusAgedArea Under CurveCohort StudiesCritical IllnessEnergy IntakeFemaleHumansLogistic ModelsMaleMiddle AgedMortalityNutritional SupportPrognosisProspective StudiesROC CurveCritical illnessMalnutritionMortalityNUTRICNutritional support

Identifiers

PMID31215498
PMCPMC6580600
OpenAlexW2952205897

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.