Evidence map›Paper›PMID 34468994›Full record

Observational studyJournal of medical virology2022

COVID-19 disease in hospitalized young adults in India and China: Evaluation of risk factors predicting progression across two major ethnic groups.

Smriti Panda, Sankanika Roy, Rohit K Garg, Gan Hui, Jack Gorard, Mayank Bhutada, Yuanli Sun, Sushma Bhatnagar, Anant Mohan, Lalit Dar and 1 more

Open access · bronzeAbstract readObservational Study
In one paragraph

Observational study in Journal of medical virology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 32% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

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

11 authors at 5 institutions in 3 countries.

Smriti PandaDepartment of Otorhinolaryngology, All India Institute of Medical Sciences, New Delhi, Delhi, India.
Sankanika RoyDepartment of Neurology, Nottingham University Hospitals, Nottingham, UK.
Rohit K GargDepartment of Medicine, All India Institute of Medical Sciences, New Delhi, Delhi, India.ORCID 0000-0001-8203-0323
Gan HuiDepartment of Allergy, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, Hubei, China.ORCID 0000-0002-4960-1507
Jack GorardDepartment of Internal Medicine, Lincoln County Hospital, Lincoln, UK.
Mayank BhutadaDepartment of Otorhinolaryngology, All India Institute of Medical Sciences, New Delhi, Delhi, India.
Yuanli SunDepartment of Allergy, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, Hubei, China.
Sushma BhatnagarDepartment of Onco-Anaesthesia, All India Institute of Medical Sciences, New Delhi, Delhi, India.
Anant MohanDepartment of Pulmonary Medicine, All India Institute of Medical Sciences, New Delhi, Delhi, India.
Lalit DarDepartment of Microbiology, All India Institute of Medical Sciences, New Delhi, Delhi, India.
Mao LiuDepartment of Neurology, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China.ORCID 0000-0002-1948-0337
All India Institute of Medical Sciences · INWuhan University · CNLincoln County Hospital · GBNottingham University Hospitals NHS Trust · GBTongji Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Data pertaining to risk factor analysis in coronavirus disease 2019 (COVID-19) is confounded by the lack of data from an ethnically diverse population. In addition, there is a lack of data for young adults. This study was conducted to assess risk factors predicting COVID-19 severity and mortality in hospitalized young adults. A retrospective observational study was conducted at two centers from China and India on COVID-19 patients aged 20-50 years. Regression analysis to predict adverse outcomes was performed using parameters including age, sex, country of origin, hospitalization duration, comorbidities, lymphocyte count, and National Early Warning Score 2 (NEWS2) score at admission. A total of 420 patients (172 East Asians and 248 South Asians) were included. The predictive model for intensive care unit (ICU) admission with variables NEWS2 Category II and higher, diabetes mellitus, liver dysfunction, and low lymphocyte counts had an area under the curve (AUC) value of 0.930 with a sensitivity of 0.931 and a specificity of 0.784. The predictive model for mortality with NEWS2 Category III, cancer, and decreasing lymphocyte count had an AUC value of 0.883 with a sensitivity of 0.903 and a specificity of 0.701. A combined predictive model with bronchial asthma and low lymphocyte count, in contrast, had an AUC value of 0.768 with a sensitivity of 0.828 and a specificity of 0.719 for NEWS2 score (5 or above) at presentation. NEWS2 supplemented with comorbidity profile and lymphocyte count could help identify hospitalized young adults at risk of adverse COVID-19 outcomes.

Indexed as

AdultAsian PeopleChinaComorbidityCOVID-19Disease ProgressionEarly Warning ScoreFemaleHospitalizationHumansIndiaIntensive Care UnitsLymphocyte CountMaleMiddle AgedPrognosisCOVID-19lymphocytelymphopeniaNEWSNEWS2prognostic factorsSARS-CoV-2

Identifiers

PMID34468994
PMCPMC8662198
OpenAlexW3196367305

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.