Evidence map›Paper›PMID 34336225›Full record

ArticleNew microbes and new infections2021

Evaluation of invasive ventilation rate and comorbidities, clinical signs and lab findings among COVID-19 patients.

N Farzan, S Vahabi, B Farzan, S S H Madani

Abstract read
In one paragraph

Article in New microbes and new infections, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
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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

4 authors.

N FarzanDepartment of Emergency Medicine, Clinical Research Development Centre, Qom University of Medical Sciences, Qom, Iran.
S VahabiDepartment of Anesthesiology, Faculty of Medicine, Lorestan University of Medical Sciences, Khorramabad, Iran.
B FarzanDepartment of Anesthesiology, Faculty of Medicine, Lorestan University of Medical Sciences, Khorramabad, Iran.
S S H MadaniEmergency Medicine Department, Student Research Development Centre, Qom University of Medical Sciences, Qom, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The severity of COVID-19 has been to be associated with comorbidities. It is defined as the presentation of severe respiratory dysfunction or failure, leading to the need for ventilation and mortality. The aim of this study is the evaluate the factors predicting the rate of invasive ventilation among these patients. This retrospective study involved 317 COVID-19 patients referred to (XXX) Hospital in Qom, Iran. The following data were obtained for all the patients: demographic parameters, comorbidities, need for mechanical ventilation, signs and symptoms and lab findings. The results from the demographic data of the study indicated that the need for mechanical ventilation is significantly associated with advanced age, p = 0.001. Additionally, hypertension, leukopenia and blood urea nitrogen to creatinine ratio p = 0.008. p = 0.042 and p < 0.001, respectively, are significantly associated with an increased need for mechanical ventilation. Malignancy, diabetes, asthma, chronic obstructive pulmonary disease, headache, fever, platelet count, prothrombin time, c-reactive protein, erythrocyte sedimentation rate and creatinine phosphatase were not significantly different in the two groups, p > 0.05. Prediction of the extent of severity among COVID-19 patients using clinical parameters and comorbidities prepare medical practitioners and health care centres to take immediate measurements and reduce the burden of the scarcity of health supplies and care.

Indexed as

ComorbiditiesCOVID-19invasive ventilation

Identifiers

PMID34336225
PMCPMC8302482

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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.