Evidence map›Paper›PMID 33344544›Full record

ArticleWorld journal of clinical cases2020

High serum lactate dehydrogenase and dyspnea: Positive predictors of adverse outcome in critical COVID-19 patients in Yichang.

Xiao-Ting Lv, Yong-Ping Zhu, Ai-Guo Cheng, Yong-Xu Jin, Hai-Bo Ding, Cai-Yun Wang, Shu-Yu Zhang, Gong-Ping Chen, Qing-Quan Chen, Qi-Cai Liu

Open access · diamondAbstract read
In one paragraph

Article in World journal of clinical cases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.5field-weighted citation impact, top 20% 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

10 citing papers in PubMed, 22 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

10 authors at 2 institutions in 1 country.

Xiao-Ting LvDepartment of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China.
Yong-Ping ZhuDepartment of Cardiovascular Surgery, Fujian Medical University Attached Union Hospital, Fuzhou 350001, Fujian Province, China.
Ai-Guo ChengDepartment of Critical Medicine, the Third People's Hospital of Yichang, Yichang 443000, Hubei Province, China.
Yong-Xu JinDepartment of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China.
Hai-Bo DingDepartment of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China.
Cai-Yun WangDepartment of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China.
Shu-Yu ZhangDepartment of Laboratory Medicine, Fujian Medical University, Fuzhou 350004, Fujian Province, China.
Gong-Ping ChenDepartment of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China.
Qing-Quan ChenDepartment of Laboratory Medicine, Fujian Medical University, Fuzhou 350004, Fujian Province, China.
Qi-Cai LiuDepartment of Reproductive Medicine Centre, First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China. lqc673673673@163.com.
Fujian Medical University · CNSecond Hospital of Yichang · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak in China, constitutes a Public Health Emergency of International Concern. It is well known that COVID-19 patients may have increased serum lactate dehydrogenase (LDH) levels in the early stage. The clinical changes in LDH may have predictive value in disease evolution and prognosis in critically ill COVID-19 patients.

aimTo examine serum LDH and clinical characteristics in patients with COVID-19 and their predictive value for prognosis.

methodsThis retrospective study analyzed the clinical data of forty-seven critical COVID-19 patients in the intensive care unit of the Third People's Hospital of Yichang City from January 27 to March 25, 2020 and divided them into survivors and non-survivors. The patients were diagnosed according to the World Health Organization interim guidance and critical cases met any one of the following criteria: Respiratory failure and required mechanical ventilation, the occurrence of shock, and the combined failure of other organs that required intensive care unit monitoring and treatments, according to the diagnostic criteria of critical COVID-19. Clinical data including symptoms, detection of SARS-CoV-2, chest computed tomography (CT) images, changes in serum LDH in different clinical phases, and prognosis were collected. Statistical analysis of the data was performed. Continuous variables were expressed as median (interquartile range) and compared with the Mann-Whitney U test. Categorical variables were compared with the Chi-square test. Survival data were analyzed using Kaplan-Meier survival curves and log-rank tests.

resultsAccording to chest CT images, we observed the alveolitis and fibrosis stages in all critical patients in this study. Most non-survivors died in the fibrosis stage. Non-survivors had fewer days of hospitalization, shorter disease duration, shorter duration of alveolitis and fibrosis, and had dyspnea symptoms at disease onset (

conclusionHigh LDH and dyspnea symptoms were positive predictors of an adverse outcome in critical COVID-19. The rapid progressive fibrosis stage was more perilous than the alveolitis stage, even if SARS-CoV-2 is undetectable.

Indexed as

COVID-19DyspneaLactate dehydrogenaseOverall survivalPulmonary fibrosisSARS-CoV-2

Identifiers

PMID33344544
PMCPMC7716337
OpenAlexW3109409101

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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.