ArticleBMC public health2025
Unveiling the hidden effect of multi-morbidities on the severity of Covid-19: a latent class analysis approach.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEpidemiological studies showed that Covid-19 patients with underlying diseases had higher rates of severe Covid-19. Previous studies focused on the presence of a single chronic disease but this study investigated the prevalence and patterns of multi-morbidities in patients with Covid-19 and its relationship with the severity of Covid-19.
methodsThis retrospective study focused on patients age 30 years and older with positive polymerase chain reaction (PCR) results in 24 hospitals of Mashhad in northeastern Iran from 20-3-2020 to 21-1-2022. The number of studied confirmed patients was 318,502. The underlying diseases were identified according to the International Classification of Diseases, and the severity of Covid-19, including death, need for ventilation, and need for treatment in the intensive care unit (ICU). The pattern of multi-morbidities in these confirmed cases was investigated using latent class analysis (LCA), and the relationship between this pattern and the severity of Covid-19 was determined by multivariate logistic regression.
resultsThe most common coexisting diseases were hypertension in 30,100 patients (9.5%), metabolic disorders in 23,798 (7.5%) and hyperlipidemia in 22,454 (7%). Different comorbidities were grouped into three classes by the LCA model. Class 1 was patients without multi-morbidities, or 83% people., Class 2, which included 9% patients, was patients with hypertension, diabetes, respiratory diseases, and mental behavioral disorders (HRMD class). Class 3, which included patients with metabolic diseases, for whom the probability of developing hypertension, hyperlipidemia, diabetes, and metabolic disorders was high, included 7% patients. The results of multivariate logistic regression showed that having HRMD and metabolic diseases compared to no multi-morbidity adjusted for some risk factors increased the odds of developing severe Covid-19 by 81% and 55%, respectively.
conclusionsThe classes identified in this study provided a clear view of different groups of Covid-19 patients with certain multi-morbidities and underscore the importance of considering these patterns, rather than individual comorbidities, in risk assessment and management of COVID-19 patients. This approach will guide clinical decision-making and resource allocation in the ongoing management of the COVID-19 pandemic.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.