Evidence map›Paper›PMID 37448393›Full record

ArticleCureus2023

The Evaluation of Laboratory Parameters as Predictors of Disease Severity and Mortality in COVID-19 Patients: A Retrospective Study From a Tertiary Care Hospital in India.

Tanima Dwivedi, Apurva Raj, Nupur Das, Ritu Gupta, Nishkarsh Gupta, Pawan Tiwari, Biswajeet Sahoo, Hari Krishna Raju Sagiraju, Prashant Sirohiya, Brajesh Ratre and 3 more

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 30% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

13 authors at 1 institution in 1 country.

Tanima DwivediDepartment of Laboratory Oncology, All India Institute of Medical Sciences, New Delhi, IND.
Apurva RajDepartment of Laboratory Oncology, All India Institute of Medical Sciences, New Delhi, IND.
Nupur DasDepartment of Laboratory Oncology, All India Institute of Medical Sciences, New Delhi, IND.
Ritu GuptaDepartment of Laboratory Oncology, All India Institute of Medical Sciences, New Delhi, IND.
Nishkarsh GuptaDepartment of Onco-Anesthesiology and Palliative Medicine, All India Institute of Medical Sciences, New Delhi, IND.
Pawan TiwariDepartment of Pulmonary, Critical Care, and Sleep Medicine, All India Institute of Medical Sciences, New Delhi, IND.
Biswajeet SahooDepartment of Laboratory Oncology, All India Institute of Medical Sciences, New Delhi, IND.
Hari Krishna Raju SagirajuDepartment of Preventive Oncology, All India Institute of Medical Sciences, New Delhi, IND.
Prashant SirohiyaDepartment of Onco-Anesthesiology and Palliative Medicine, All India Institute of Medical Sciences, New Delhi, IND.
Brajesh RatreDepartment of Onco-Anesthesiology and Palliative Medicine, All India Institute of Medical Sciences, New Delhi, IND.
Arunmozhimaran ElavarasiDepartment of Neurology, All India Institute of Medical Sciences, New Delhi, IND.
Anant MohanDepartment of Pulmonary, Critical Care, and Sleep Medicine, All India Institute of Medical Sciences, New Delhi, IND.
Sushma BhatnagarDepartment of Onco-Anesthesiology and Palliative Medicine, All India Institute of Medical Sciences, New Delhi, IND.
All India Institute of Medical Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection affects and alters various laboratory parameters that are predictors of disease severity and mortality, and hence, their prompt identification can aid in patient triaging and resource allocation. Objectives A retrospective study was conducted on 7416 admitted coronavirus disease 2019 (COVID-19) patients from 20 March 2020 to 9 August 2021 to identify crucial laboratory biomarkers as predictors of disease severity and outcome; also, their optimal cutoffs were also calculated. A comparison of laboratory markers between both COVID-19 waves was also performed. Results The majority of patients had mild disease (4295/7416, 57.92%), whereas 1262/7416 (17.02%) had severe disease. The overall fatal outcome was reported in 461 (6.22%) patients. Predictors for mortality were age (>52 years), albumin/globulin (A/G) ratio (≤1.47), chloride (≤101 mmol/L), ferritin (>483.89 ng/mL), lactate dehydrogenase (LDH) (>393 U/L), procalcitonin (>0.10 ng/mL), interleukin-6 (IL-6) (>8.8 pg/mL), fibrinogen (>403 mg/dL), international normalized ratio (INR) (>1.18), and D-dimer (>268 ng/mL). Disease severity predictors were neutrophils (>81%), lymphocyte (≤25.4%), absolute lymphocyte count (ALC) (≤1.38×10

Indexed as

biomarkerscovid-19laboratory parametersmortalitysars-cov-2severity

Identifiers

PMID37448393
PMCPMC10336329
OpenAlexW4380263894

What OpenQuestion holds

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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.