Evidence map›Paper›PMID 35663125›Full record

ArticleAnnals of medicine and surgery (2012)2022

Clinical characteristics and Co-morbidities among patients admitted with COVID-19.

Omair Al Hussain

Open access · diamondAbstract read
In one paragraph

Article in Annals of medicine and surgery (2012), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.6field-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

0 citing papers in PubMed, 6 citations in OpenAlex.

No citing paper in PubMed yet.

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

1 author at 1 institution in 1 country.

Omair Al HussainHead of Otolaryngology and Head & Neck Surgery Department, College of Medicine, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia.
Imam Mohammad ibn Saud Islamic University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: During the Coronavirus Disease-2019 (COVID-19) pandemic, several characteristics of COVID-19 patients, based on demographics, clinical symptoms, and the presence of comorbidities, were found to be associated with the complications developed. COVID-19 symptoms vary greatly and are more prominent with comorbid diseases. Therefore, the aim of this study to find the clinical characteristics and its association with different comorbidities. Methods: This is a retrospective study that was performed on the data obtained from medical records of 3999 patients in Riyadh. Demographic data, clinical symptoms and comorbidities were noted on the day of hospital admission. Complications developed during the COVID -19 infection were observed. Results: The average age of patients were 49.55 years old. Fever was the most common symptom among the patients (85.85%), followed by cough (85.85%), and shortness of breath (83.25%). The most common comorbidities were diabetes mellitus (39.51%), hypertension (33.91%), and asthma (9.45%), with chronic rhinosinusitis being the least common (0.5%). Pneumonia affected 61.90% of the patients admitted to the hospital. Furthermore, 8.73% got acute respiratory distress syndrome (ARDS), and 7.25% acquired pneumonia and Acute ARDS simultaneously. Co-morbidities were significantly correlated with complications developed during COVID-19. Conclusion: Hypertension and diabetes mellitus were two of the most common symptoms observed. Clinical symptoms, comorbidities, and complications are higher in female patients compared to male patients and most of the patients' developed complications.

Indexed as

Acute respiratory disorder syndromeComorbiditiesCOVID-19Pneumonia

Identifiers

PMID35663125
PMCPMC9153183
OpenAlexW4281715758

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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.