Evidence map›Paper›PMID 34408476›Full record

ArticleInternational journal of general medicine2021

Independent Risk Factors for the Dynamic Development of COVID-19: A Retrospective Study.

Miaomiao Liu, Hua Jiang, Yujuan Li, Chunmei Li, Zhijun Tan, Faguang Jin, Tao Zhang, Yandong Nan

Open access · goldAbstract read
In one paragraph

Article in International journal of general medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 34% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
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

8 authors at 1 institution in 1 country.

Miaomiao Liu *Department of Respiratory and Critical Care Medicine, Tangdu Hospital, Air Force Military Medical University, Xi'an, 710038, People's Republic of China.
Hua Jiang *Department of Respiratory and Critical Care Medicine, Tangdu Hospital, Air Force Military Medical University, Xi'an, 710038, People's Republic of China.
Yujuan LiDepartment of Respiratory and Critical Care Medicine, Tangdu Hospital, Air Force Military Medical University, Xi'an, 710038, People's Republic of China.
Chunmei LiDepartment of Respiratory and Critical Care Medicine, Tangdu Hospital, Air Force Military Medical University, Xi'an, 710038, People's Republic of China.
Zhijun TanDepartment of Health Statistics, Air Force Military Medical University, Xi'an, 710032, People's Republic of China.
Faguang JinDepartment of Respiratory and Critical Care Medicine, Tangdu Hospital, Air Force Military Medical University, Xi'an, 710038, People's Republic of China.
Tao ZhangDepartment of Respiratory and Critical Care Medicine, Tangdu Hospital, Air Force Military Medical University, Xi'an, 710038, People's Republic of China.ORCID 0000-0001-8767-4793
Yandong NanDepartment of Respiratory and Critical Care Medicine, Tangdu Hospital, Air Force Military Medical University, Xi'an, 710038, People's Republic of China.
Air Force Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo identify the risk factors for predicting the dynamic progression of COVID-19.

methodsA total of 2321 eligible patients were included in this study from February 4 to April 15, 2020. Two illness conditions, including mild/moderate (M/M) subtype to severe/critical (S/C) and S/C to fatality, were classified. Clinical message was collected and compared, respectively. Kaplan-Meier method, Cox regression model and risk score system were used to predict disease progression in S/C COVID-19.

resultsA total of 112 of 1761 patients with M/M subtype were progressors (P) and 1649 non-progressors (NP). Increasing disease progression associated with higher levels of neutrophils count (HR=1.958, 95% CI=1.253-3.059,

conclusionElevated LDH level and lymphopenia were independent predictors for COVID-19 sustainable management in classifying non-severe patients who progressed to severe condition and identifying S/C patients who deteriorated to fatal outcomes as well. Total lesion volume ratio ≥10% may provide early predictive evidence with COVID-19 patients at high risk of developing into S/C to improve prognosis.

Indexed as

COVID-19fatalitymild/moderateprogressionrisk factorssevere/critical

Identifiers

PMID34408476
PMCPMC8364400
OpenAlexW3193962473

What OpenQuestion holds

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LicenceCC BY-NC
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.