Evidence map›Paper›PMID 39176144›Full record

ArticleTanaffos2023

Relationship between Underlying Diseases with Morbidity and Mortality in Patients with COVID-19.

Navid Shafigh, Morteza Hasheminik, Batoul Khoundabi, Hamidreza Jamaati, Payam Tabarsi, Majid Marjani, Elnaz Shafigh, Majid Malekmohammad, Navid Nooraei, Seyed Mohammad Reza Hashemian

Abstract read
In one paragraph

Article in Tanaffos, 2023. 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
–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

0 citing papers in PubMed.

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

10 authors.

Navid ShafighClinical Research and Development Unit at Shahid Modarres Hospital, Department of Anesthesiology, Shahid Beheshti University of Medical Sciences, and Tehran, Iran.
Morteza HasheminikDepartment of Nursing, Sabzevar Branch, Islamic Azad University, Sabzevar, Iran.
Batoul KhoundabiIran Helal Institute of Applied-Science and Technology, Red Crescent Society of Iran, Tehran, Iran.
Hamidreza JamaatiChronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Payam TabarsiClinical Tuberculosis and Epidemiology Research Center, NRITLD, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Majid MarjaniClinical Tuberculosis and Epidemiology Research Center, NRITLD, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Elnaz ShafighDepartment of Operative Dentistry Aja University Tehran Iran.
Majid MalekmohammadTracheal Diseases Research Center (TDRC), NRITLD, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Navid NooraeiClinical Research and Development Unit at Shahid Modarres Hospital, Department of Anesthesiology, Shahid Beheshti University of Medical Sciences, and Tehran, Iran.
Seyed Mohammad Reza HashemianChronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aims to investigate the clinical and demographic features of underlying medical conditions and the potential relationship between underlying diseases and the increased rate of morbidity and mortality due to COVID-19. Materials and Methods: This study was conducted on 350 COVID-19 patients hospitalized at the Masih Daneshvari Hospital from February-July 2021. All participants had confirmed COVID-19 diagnosis based on symptoms and/or positive PCR test or chest X-ray results. Data was collected from medical records on demographics, disease severity, symptoms, underlying conditions like diabetes, hypertension, coronary heart disease, obesity, renal disease/transplantation, and outcomes like hospital stay, ICU admission, and mortality. Relationships between age, underlying diseases, and mortality were analyzed using chi-square and Fisher's exact tests." Results: A total of 350 patients diagnosed with COVID-19 were included in the study, with an average estimated age of (60.8±15.4). The age group of 56 and above had the highest morbidity rate, which accounted for 50% of the total participants. Among the COVID-19 patients, diabetes was the most common underlying medical condition, accounting for 31.4% of the cases. High blood pressure was present in 27.1% of the patients, and 17.1% of the total participants had coronary heart disease (CHD). Additionally, 10.9% of the participants were overweight, and 30 of them had previously experienced kidney failure or transplantation. Moreover, the study found that 40% of patients with diabetes died, while the mortality rate was 38.3% in patients with CHD and 47.4% in overweight participants. High blood pressure patients had a mortality rate of 43.2%, and patients with renal failure or kidney transplantation had a significantly increased risk of mortality at 83.3%. The research also revealed a significant and direct relationship between mortality rate, age group, and underlying disease among the patients (P<0.05). Conclusion: The findings of the present study hold significant implications for preventive interventions and policy adoption, particularly in relation to the use of calendar age as the key criterion for risk evaluation. These results underscore the need for a more precise and focused approach to prioritizing patients with identified risk factors.

Indexed as

Chronic renal failureCOVID-19DiabetesHypertension

Identifiers

PMID39176144
PMCPMC11338504

What OpenQuestion holds

Textmetadata
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.