Evidence map›Paper›PMID 35421418›Full record

ArticleMechanisms of ageing and development2022

Routine laboratory parameters, including complete blood count, predict COVID-19 in-hospital mortality in geriatric patients.

Fabiola Olivieri, Jacopo Sabbatinelli, Anna Rita Bonfigli, Riccardo Sarzani, Piero Giordano, Antonio Cherubini, Roberto Antonicelli, Yuri Rosati, Simona Del Prete, Mirko Di Rosa and 4 more

Abstract read
In one paragraph

Article in Mechanisms of ageing and development, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

22 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Trial
  4. Effects of recombinantFrontiers in cellular and infection microbiology · 2026
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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

14 authors.

Fabiola OlivieriDepartment of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy; Center of Clinical Pathology and Innovative Therapy, IRCCS INRCA, Ancona, Italy.
Jacopo SabbatinelliDepartment of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy; Laboratory Medicine Unit, Azienda Ospedaliero Universitaria Ospedali Riuniti, Ancona, Italy.
Anna Rita BonfigliScientific Direction, IRCCS INRCA, Ancona, Italy. Electronic address: a.bonfigli@inrca.it.
Riccardo SarzaniDepartment of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy; Internal Medicine and Geriatrics, Italian National Research Centre on Aging, Hospital "U. Sestilli", IRCCS INRCA, Ancona, Italy.
Piero GiordanoInternal Medicine and Geriatrics, Italian National Research Centre on Aging, Hospital "U. Sestilli", IRCCS INRCA, Ancona, Italy.
Antonio CherubiniGeriatria, Accettazione geriatrica e Centro di Ricerca Per l'invecchiamento, IRCCS INRCA, Ancona, Italy.
Roberto AntonicelliCardiology Unit, IRCCS INRCA, Ancona, Italy.
Yuri RosatiPneumologia, IRCCS INRCA, Osimo, Italy.
Simona Del PreteMedicina Interna, IRCCS INRCA, Osimo, Italy.
Mirko Di RosaUnit of Geriatric Pharmacoepidemiology and Biostatistics, IRCCS INRCA, Cosenza, Italy.
Andrea CorsonelloUnit of Geriatric Pharmacoepidemiology and Biostatistics, IRCCS INRCA, Cosenza, Italy; Geriatric Medicine, IRCCS INRCA, 87100 Cosenza, Italy.
Roberta GaleazziClinical Laboratory and Molecular Diagnostic, IRCCS INRCA, Ancona, Italy.
Antonio Domenico ProcopioDepartment of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy; Clinical Laboratory and Molecular Diagnostic, IRCCS INRCA, Ancona, Italy.
Fabrizia LattanzioScientific Direction, IRCCS INRCA, Ancona, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To reduce the mortality of COVID-19 older patients, clear criteria to predict in-hospital mortality are urgently needed. Here, we aimed to evaluate the performance of selected routine laboratory biomarkers in improving the prediction of in-hospital mortality in 641 consecutive COVID-19 geriatric patients (mean age 86.6 ± 6.8) who were hospitalized at the INRCA hospital (Ancona, Italy). Thirty-four percent of the enrolled patients were deceased during the in-hospital stay. The percentage of severely frail patients, assessed with the Clinical Frailty Scale, was significantly increased in deceased patients compared to the survived ones. The age-adjusted Charlson comorbidity index (CCI) score was not significantly associated with an increased risk of death. Among the routine parameters, neutrophilia, eosinopenia, lymphopenia, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein, procalcitonin, IL-6, and NT-proBNP showed the highest predictive values. The fully adjusted Cox regressions models confirmed that high neutrophil %, NLR, derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), and low lymphocyte count, eosinophil %, and lymphocyte-to-monocyte ratio (LMR) were the best predictors of in-hospital mortality, independently from age, gender, and other potential confounders. Overall, our results strongly support the use of routine parameters, including complete blood count, in geriatric patients to predict COVID-19 in-hospital mortality, independent from baseline comorbidities and frailty.

Indexed as

COVID-19FrailtyAgedAged, 80 and overBlood Cell CountHospital MortalityHumansPrognosisRetrospective StudiesComplete blood countCOVID-19FrailtyIn-hospital mortalityNeutrophil-to-lymphocyte ratio

Identifiers

PMID35421418
PMCPMC8996472

What OpenQuestion holds

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Registered trials

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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.