Evidence map›Paper›PMID 33642143›Full record

ArticleClinical nutrition (Edinburgh, Scotland)2022

Phase angle and standardized phase angle from bioelectrical impedance measurements as a prognostic factor for mortality at 90 days in patients with COVID-19: A longitudinal cohort study.

Isabel Cornejo-Pareja, Isabel M Vegas-Aguilar, Jose Manuel García-Almeida, Diego Bellido-Guerrero, Antonio Talluri, Henry Lukaski, Francisco J Tinahones

Open access · bronzeAbstract read
In one paragraph

Article in Clinical nutrition (Edinburgh, Scotland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 4 pooled it
8.6field-weighted citation impact, top 1% 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

56 citing papers in PubMed, 4 syntheses or guidelines pooled it, 80 citations in OpenAlex.

  1. Pooled it
  2. Phase angle and COVID-19: A systematic review with meta-analysis.Reviews in endocrine & metabolic disorders · 2023
    Pooled it
  3. Pooled it
  4. Association between phase angle and adverse clinical outcomes in hospitalized patients with COVID-19: A systematic review.Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition · 2022
    Pooled it
  5. Article
  6. Article
  7. Article
  8. "Muscle quality": rethinking an imprecise term.European geriatric medicine · 2026
    Review
  9. Novel insights into phase angle in breast cancer - stage-specific associations between body composition and metabolic age.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2026
    Article
  10. Article
  11. Observational
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Observational
  20. 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

7 authors at 5 institutions in 2 countries.

Isabel Cornejo-ParejaDepartment of Endocrinology and Nutrition, Virgen de la Victoria Hospital (IBIMA), Malaga University, Malaga, Spain; Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Málaga, Spain. Electronic address: isabelmaria_cornejo@hotmail.com.
Isabel M Vegas-AguilarDepartment of Endocrinology and Nutrition, Virgen de la Victoria Hospital (IBIMA), Malaga University, Malaga, Spain; Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Málaga, Spain. Electronic address: isabel.mva@hotmail.com.
Jose Manuel García-AlmeidaDepartment of Endocrinology and Nutrition, Virgen de la Victoria Hospital (IBIMA), Malaga University, Malaga, Spain; Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Málaga, Spain. Electronic address: jgarciaalmeida@gmail.com.
Diego Bellido-GuerreroDepartment of Endocrinology and Nutrition, Complejo Hospitalario Universitario de Ferrol, Ferrol, La Coruña, Spain. Electronic address: diegobellido@gmail.com.
Antonio TalluriAntonio Talluri BME, Fatbyte, Inc., 50012 Bagno a Ripoli, Florence, Italy. Electronic address: tony@tonytalluri.com.
Henry LukaskiDepartment of Kinesiology and Public Health Education, University of North Dakota, Grand Forks, ND 58202-7166, USA. Electronic address: henry.lukaski@und.edu.
Francisco J TinahonesDepartment of Endocrinology and Nutrition, Virgen de la Victoria Hospital (IBIMA), Malaga University, Malaga, Spain; Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Málaga, Spain. Electronic address: fjtinahones@uma.es.
Hospital Clínico Universitario Virgen de la Victoria · ESCentro de Investigación Biomédica en Red · ESComplexo Hospitalario Universitario A Coruña · ESInstituto de Investigación Biomédica de Málaga · ESUniversity of North Dakota · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND &

aimsSevere acute COVID-19 has taken on pandemic proportions with growing interest in identification of prognostic factors for mortality. Standardized bioelectrical impedance (BI) phase angle (SPhA), which is PhA adjusted by age and sex, has been related to mortality in patients with several diseases but never investigated in COVID-19. Inflammation, a consequence of COVID-19 infection, affects fluid status (hydration) and can be identified with PhA. The aim of this study was to determine the predictive role of PhA on 90 days survival of adults with COVID-19.

methodsWe studied 127 consecutive patients diagnosed with COVID-19. BI measurements determined with a 50 kHz phase-sensitive BI device, body composition parameters and laboratory markers were evaluated as predictors of mortality.

resultsNon-surviving COVID-19 patients had significantly lower PhA and SPhA values (p < 0.001) and increased hydration (p < 0.001) compared to surviving patients. Patients in the lowest SPhA quartile had increased (p < 0.001) mortality and hospital stay, hyperhydration (p < 0.001), increased inflammation biomarkers [CRP (p < 0.001)], decreased nutritional parameters: body mass cell index [BCMI (p < 0.001) albumin (p < 0.001)], and reduced other biomarkers [D-dimer (p = 0.002)]. Multivariate analysis (Cox regression) revealed that PhA and hydration status, adjusted for age, sex, BMI, diabetes, hypertension, dyslipidaemia or heart disease, were associated (p < 0.001) with increased mortality. The hazard ratio was 2.48 (95% CI, 1.60-3.84, p < 0.001) for PhA and 1.12 (95% CI, 1.04-1.20, p = 0.003) for hydration percentage. PhA <3.95° was the cut-off for predicting mortality in acute COVID-19 with 93.8% sensitivity and 66.7% specificity. PhA offers greater sensitivity as a predictive prognostic test at admission, compared to the established analytical parameters of poor prognosis (CRP, lymphocytes, prealbumin).

conclusionsLow PhA (<3.95°), independent of age, sex, BMI, and comorbidities, is a significant predictor of mortality risk in COVID-19. These findings suggest that the evaluation of body composition with single-frequency phase-sensitive BI measurements should be included in the routine clinical assessment of COVID-19 patients at hospital admission to identify patients at increased mortality risk.

Indexed as

COVID-19Nutritional StatusAdultBiomarkersBody CompositionCohort StudiesElectric ImpedanceHumansInflammationLongitudinal StudiesPrognosisBiomarkersBioelectrical impedanceCOVID-19MortalityPhase angleSurvival analysis

Identifiers

PMID33642143
PMCPMC7886631
OpenAlexW3132411301

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.