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1.
Sci Rep ; 14(1): 12139, 2024 05 27.
Article in English | MEDLINE | ID: mdl-38802549

ABSTRACT

High-density lipoprotein cholesterol (HDL-c) removes cholesterol, an essential component in lipid rafts, and this cholesterol removal can regulate protein attachment to lipid rafts, modulating their functionality in the immune cell response. Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can alter the lipid profile, there is little information on the role of HDL-c and other lipids in prognostic of the coronavirus disease 2019 (COVID-19) in Mexican population. This study aims to evaluate the predictive value of HDL-c and lipid profile on severity and survival of 102 patients infected with SARS-CoV-2 during the COVID-19 first wave. Our findings, derived from univariate and multivariate Cox proportional hazards regression models, highlighted age and hypertension as significant predictors of survival (HR = 1.04, p = 0.012; HR = 2.78, p = 0.027), while gender, diabetes, and obesity showed no significant impact. Triglycerides and HDL-c levels notably influenced mortality, with elevated triglycerides and lower HDL-c associated with higher mortality risk (p = 0.032). This study underscores the importance of lipid profiles alongside traditional risk factors in assessing COVID-19 risk and outcomes. It contributes to the understanding of COVID-19 patient management and emphasizes the need for further investigation into the role of dyslipidemia in influencing COVID-19 prognosis, potentially aiding in refined risk stratification and therapeutic strategies.


Subject(s)
COVID-19 , Cholesterol, HDL , SARS-CoV-2 , Humans , COVID-19/mortality , COVID-19/blood , Male , Female , Middle Aged , Cholesterol, HDL/blood , Adult , Aged , SARS-CoV-2/isolation & purification , Risk Factors , Triglycerides/blood , Prognosis , Lipids/blood , Mexico/epidemiology , Dyslipidemias/blood , Proportional Hazards Models , Hypertension/blood
2.
Microorganisms ; 11(9)2023 Sep 11.
Article in English | MEDLINE | ID: mdl-37764131

ABSTRACT

Monkeypox (Mpox) is an emerging zoonotic disease with the potential for severe complications. Early identification and diagnosis are essential to prompt treatment, control its spread, and reduce the risk of human-to-human transmission. This study aimed to develop a clinical diagnostic tool and describe the clinical and sociodemographic features of 19 PCR-confirmed Mpox cases during an outbreak in a nonendemic region of northwestern Mexico. The median age of patients was 35 years, and most were male. Mpox-positive patients commonly reported symptoms such as fever, lumbago, and asthenia, in addition to experiencing painful ulcers and a high frequency of HIV infection among people living with HIV (PLWH). Two diagnostic models using logistic regression were devised, with the best model exhibiting a prediction accuracy of 0.92 (95% CI: 0.8-1), a sensitivity of 0.86, and a specificity of 0.93. The high predictive values and accuracy of the top-performing model highlight its potential to significantly improve early Mpox diagnosis and treatment in clinical settings, aiding in the control of future outbreaks.

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