Evidence map›Paper›PMID 37457796›Full record

ArticleInfection and drug resistance2023

Predictors of COVID-19 Severity in Elderly Patients Infected by Omicron in China, 18 December 2022-5 February 2023.

Yanqing Xing, Yupeng Li, Liting Feng, Rujie Huo, Xinkai Ma, Yanting Dong, Dai Liu, Yuheng Niu, Xinrui Tian, Erjing Chen

Open access · goldAbstract read
In one paragraph

Article in Infection and drug resistance, 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
1.2field-weighted citation impact, top 23% 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, 6 citations in OpenAlex.

  1. Pooled it
  2. Observational
  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

10 authors at 1 institution in 1 country.

Yanqing XingThe Second Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.ORCID 0000-0002-4000-5784
Yupeng LiThe Second Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.
Liting FengThe Second Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.ORCID 0009-0009-8390-8092
Rujie HuoThe Second Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.
Xinkai MaThe Second Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.
Yanting DongThe Second Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.
Dai LiuThe Second Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.
Yuheng NiuThe First Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.ORCID 0009-0004-8690-8702
Xinrui Tian *The Second Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.ORCID 0000-0002-2798-798X
Erjing Chen *The Second Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.
Shanxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To analyze the clinical characteristics and prognosis of patients hospitalized with non-severe, severe pneumonia and death in Omicron COVID-19. Patients and Methods: We collected clinical data from 118 patients with COVID-19 in China from 18 December, 2022 and 5 February, 2023. According to the outcome, the patients were divided into non-severe group, severe group and death group. Subsequently, we statistically analyzed the general condition, clinical manifestations, laboratory parameters, NLR, MLR, PLR and HALP of these groups. We also retrospectively analyzed the possible factors affecting the prognostic regression of patients with COVID-19. Results: A total of 118 COVID-19 patients were enrolled in this study, including 64 non-severe patients, 38 severe patients and 16 death patients. Compared with the non-severe group, T lymphocytes, B lymphocytes, Th1, Th2, Th17, Treg cells, IgA, IgG, IgM in the severe and death groups decreased more significantly ( Conclusion: The analysis of COVID-19 patients in China showed that severe patients were older, more likely to have related complications, lower lymphocyte count, liver and kidney function disorder, glucose and lipid metabolism disorders, myocardial injury, and abnormal coagulation function, suggesting the need for early anticoagulant therapy. In addition, NLR, MLR, PLR and HALP can be used as biomarkers to evaluate the severity and prognosis of COVID-19 patients.

Indexed as

clinical characteristicsCOVID-19lymphocyte subpopulationomicronShanxi

Identifiers

PMID37457796
PMCPMC10349581
OpenAlexW4383912816

What OpenQuestion holds

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LicenceCC BY-NC
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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.