Evidence map›Paper›PMID 34486808›Full record

ArticleInternational journal of clinical practice2021

Can prognostic nutritional index predict mortality in intensive care patients with COVID-19?

Behiye Deniz Kosovali, Berkay Kucuk, Ozlem Balkiz Soyal, Nevzat Mehmet Mutlu

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In one paragraph

Article in International journal of clinical practice, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 28% 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

6 citing papers in PubMed, 11 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

4 authors at 2 institutions in 1 country.

Behiye Deniz KosovaliDepartment of Critical Care, Ankara City Hospital, Ankara, Turkey.
Berkay KucukDepartment of Critical Care, Ankara City Hospital, Ankara, Turkey.
Ozlem Balkiz SoyalDeparment of Anesthesiology and Reanimation, Ankara City Hospital, Turkey.
Nevzat Mehmet MutluDepartment of Critical Care, Ankara City Hospital, Ankara, Turkey.
Memorial Ankara Hospital · TRTürk Anesteziyoloji ve Reanimasyon Derneği · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesPNI is a calculated parameter using the albumin and the lymphocyte count from the CBC, which demonstrates the immunological and nutritional status of the patient. The aim of this study is to show the relationship between PNI and mortality in COVID-19 patients and to reveal a PNI cut-off value for mortality. MATERIALS AND

methodsData of 690 PCR positive COVID-19 ICU patients were recorded. COVID-19 ICU patients were divided into two groups; the first group consisted of survivors, while the second group consisted of patients who died in the ICU. Patients were also evaluated in two groups according to the PNI cut-off value that predicted mortality (PNI ≤ 42.00, PNI ≥ 43) and were compared in terms of demographics, laboratory parameters, clinical findings and mortality rates.

resultsWhen 690 COVID-19 patients were divided into two groups as survivors (50.6%) and deceased (49.4%) in intensive care, PNI value was significantly lower in the deceased group compared to the surviving group (P < .001). The PNI cut-off value predicting mortality was determined as ≤42. Patients were classified into two groups according to the PNI cut-off value. PNI ≤42 was determined as an independent risk factor for mortality (OR:2.9 P < .001). AUC values for PNI, albumin, and lymphocyte were 0.628, 0.612, and 0.590, respectively; P < .001 for all.

conclusionPNI is an inexpensive method that can be easily calculated on the basis of routine laboratory parameters. We believe that the PNI value of COVID-19 patients on admission to the ICU may be an independent factor to predict mortality.

Indexed as

COVID-19Nutrition AssessmentCritical CareHumansNutritional StatusPrognosisRetrospective StudiesSARS-CoV-2COVID-19intensive care unitmarkermortalityprognostic nutritional index

Identifiers

PMID34486808
PMCPMC8646619
OpenAlexW3196395797

What OpenQuestion holds

Textmetadata
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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.