Evidence map›Paper›PMID 34877710›Full record

ArticleJournal of clinical laboratory analysis2022

Malnutrition on admission increases the in-hospital mortality and length of stay in elder adults with acute ischemic stroke.

Ruixiao Hao, Xuemei Qi, Xiaoshuang Xia, Lin Wang, Xin Li

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Journal of clinical laboratory analysis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07628283 (A Prospective, Open-Label, Cluster Randomized Controlled Trial to Evaluate the Efficacy of a Rural Doctor-Led, Telemedicine-Supported Integrated Care Model for Reducing Cardiovascular and Cerebrovascular Events in Elderly Adults at High Risk of Stroke in China), which is not on this map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
3.5field-weighted citation impact, top 6% 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.

NCT07628283 narecruitingnot on this mapstarted 2026, after this paper: background citation

A Prospective, Open-Label, Cluster Randomized Controlled Trial to Evaluate the Efficacy of a Rural Doctor-Led, Telemedicine-Supported Integrated Care Model for Reducing Cardiovascular and Cerebrovascular Events in Elderly Adults at High Risk of Stroke in China

TypeinterventionalSponsorJiangsu Province (Suqian) HospitalRan2026 to 2030Enrolled2,510ConditionsStroke, Brain Ischemia, Cerebral Hemorrhage, Transient Ischemic AttackArmsEnhanced Usual Stroke Care, Digital Health Platform-Supported Integrated Stroke Management
3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 34 citations in OpenAlex.

  1. Review
  2. Article
  3. Observational
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  6. Observational
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  10. Review
  11. Machine Learning and Clinical Predictors of Mortality in Cardiac Arrest Patients: A Comprehensive Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2024
    Article
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  15. Article
  16. Review
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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

5 authors at 1 institution in 1 country.

Ruixiao HaoDepartment of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Xuemei QiDepartment of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Xiaoshuang XiaDepartment of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Lin WangDepartment of Geriatrics, The Second Hospital of Tianjin Medical University, Tianjin, China.
Xin LiDepartment of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, China.ORCID https://orcid.org/0000-0002-2977-5075
Second Hospital of Tianjin Medical University · CN

Funding

Clinical Medicine Research Project of the Second University of Tianjin Medical University 2020LC04Research and promotion project of appropriate technology for intervention of high risk population of stroke in China 2020R0005the Key Technology Research and Development Program of Science and Technology, Tianjin 18ZXDBSY00210
6 · The paper itself

Abstract

purposeMalnutrition, as determined by the Controlling Nutritional Status (CONUT), has an effect on the 3-month and long-term prognosis of stroke patients. The association between malnutrition and in-hospital mortality has not been well established. We aimed to investigate the relationship between the CONUT score on admission and in-hospital mortality and length of stay (LOS) in elderly patients with acute ischemic stroke (AIS).

methodsThis study analyzed controls and patients with AIS. Malnutrition was determined using the CONUT score. A CONUT score of 5-12 was defined as undernutrition status. Based on the CONUT scores, the patients were divided into the low CONUT (0-4) and high CONUT (5-12) groups.

resultsIn total, 1079 participants were recruited, comprising 288 controls and 791 AIS patients. Among the 791 patients, 64 (8.1%) had malnutrition and 63 (7.9%) had an in-hospital death. Compared to the controls, the AIS patients presented higher CONUT scores, higher proportion of in-hospital mortality (8.0%), and longer length of stay. Malnutrition was independently associated with in-hospital mortality in the AIS patients (adjusted odds ratio: 3.77, 95% confidence interval [CI]: 1.55-9.15; p = 0.003). The general linear models showed an association between the CONUT score and LOS (β = 0.574, 95% CI: 0.208-0.934; p = 0.002). Furthermore, the effect of the interaction between infection and nutrition status on in-hospital mortality showed borderline statistical significance (p = 0.06).

conclusionsMalnutrition estimated by the CONUT score on admission can be a predictor of in-hospital mortality and increased LOS in elderly AIS patients.

Indexed as

Brain IschemiaMalnutritionStrokeAgedAged, 80 and overAlbuminsCholesterolFemaleHumansLength of StayLeukocyte CountMaleNutritional StatusAlbuminsCholesterolcontrolling nutritional status scorelymphocytemalnutritionmortalitynutritionserum albuminstroketotal cholesterol

Identifiers

PMID34877710
PMCPMC8761426
OpenAlexW4200015831

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Registered trials

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.