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Record W3120451288 · doi:10.1101/2021.01.09.21249490

Nutritional Status in Patients with Acute heart failure: A systematic review and meta-analysis with trial sequential analysis

2021· review· en· W3120451288 on OpenAlexaboutno aff
Jihane Belayachi, Imane Katir, Rhita Nechba Bennis, Naoufel Madani, Rédouane Abouqal

Bibliographic record

VenuemedRxiv · 2021
Typereview
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyMedicineMeta-analysisHeart failureHazard ratioConfidence intervalSubgroup analysisStudy heterogeneityMalnutritionCohort studyPublication biasInternal medicine

Abstract

fetched live from OpenAlex

Abstract A critical review of the prognosis impact of malnutrition in patients admitted with acute heart failure (AHF) has never been performed. We systematically reviewed the observational epidemiology literature to determine the all-cause mortality (ACM) in undernourished patients with acute heart failure or at risk of malnutrition through a meta-analysis of observational studies. A systemic search using PubMed, Scopus, and Web of Science was done for articles reporting an association between malnutrition and mortality in patient with acute heart failure published before December 2019. Original data from observational cohort studies in patients with acute heart failure at baseline, and with nutritional state evaluation at admission using screening, or assessment tools. The outcome of interest was mortality independent of the timeframe for follow up. The characteristics of the included study were collected. Data quality assessment using the Newcastle Ottawa Quality Assessment Scale. The hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were extracted. For the meta-analysis, a random-effects model was considered. Heterogeneity between studies was assessed using Cochran Q statistics and I2 statistics. Subgroup analyses were used to identify the source of heterogeneity. A sensitive analysis was performed to reflect the influence of the individual data set on the pooled HR. Publication bias was detected using the Doi plot and Luis Furuya-Kanamori asymmetry index (LFK index). The influence of potential publication bias on results was explored by using the trim-and-fill procedure. To assess the risks of random errors, trial sequential analysis (TSA) was performed. Seven studies were eligible for review and meta-analysis. There were 9053 participants and over 1536 events occurred. The prevalence of malnutrition varied from 33% to 78.8%. Mean follow-up varied between 189 and 951 days. ACM rates varied between 7% and 42.6%. Nutritional status is significantly associated with mortality in patients with AHF (Pooled HR=1.15;95%CI[1.08-1.23]). Considerable between-study heterogeneity was observed (I2=83%, P=0.001). Heterogeneity was partially explained by the different tools used to screen malnutrition risk, and follow-up durations used by the included studies. There was evidence of major publication bias regarding the risk of malnutrition-related to ACM. The obtained LFK index was 6.12 and suggests major asymmetry. The recalculated pooled HR that incorporates the hypothetical missing studies is 1.15; 95%CI (1.08-1.22). However, the accumulating number of participants and the required information size has not yet been achieved. Then, the trial sequential monitoring boundary is inconclusive. This first meta-analysis of the association between nutritional status in patients with acute heart failure and all-cause mortality indicated that malnutrition risk in a patient with acute heart failure was associated with increased all-cause mortality. The prognosis impact of malnutrition is real despite heterogeneity in tools and cut off for defining malnutrition and mean follow up duration. This review underlines the peremptory need for multicenter studies, for uniform guidelines for assessing nutritional status, and for reporting guidelines for prognostic studies in an acute cardiovascular setting. Better nutritional practice to improve patient care is emphasized in international and national health care guidelines.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.029
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.029
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.054
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0260.042
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.090
GPT teacher head0.385
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2021
Admission routes1
Has abstractyes

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