Your browser doesn't support javascript.
loading
Predictors of disease severity in patients hospitalized with coronavirus disease 2019.
Edathodu, Jameela; Alsugair, Ali; Al-Bugami, Muneerah; Alomar, Ibrahim; Alrasheed, Abdulmajeed; Fadel, Roqayah; Albalawi, Waad; Alshammary, Amal; Alsuhaim, Abdullah; Alghayti, Saleh; Alkadi, AlJawharah; Peedikayil, Mushtafa; Aldakhil, Haifa; Albedah, Norah; Mohamed, Gamal.
Afiliação
  • Edathodu J; From the Department of Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
  • Alsugair A; From the Department of Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
  • Al-Bugami M; From the Department of Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
  • Alomar I; From the Department of Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
  • Alrasheed A; From the Department of Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
  • Fadel R; From the Department of Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
  • Albalawi W; From the Department of Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
  • Alshammary A; From the Department of Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
  • Alsuhaim A; From the Department of Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
  • Alghayti S; From the Department of Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
  • Alkadi A; From the Department of Biostatistics, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
  • Peedikayil M; From the Department of Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
  • Aldakhil H; From the Department of Biostatistics, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
  • Albedah N; From the Department of Biostatistics, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
  • Mohamed G; From the Department of Biostatistics, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
Ann Saudi Med ; 43(4): 254-261, 2023.
Article em En | MEDLINE | ID: mdl-37554023
ABSTRACT

BACKGROUND:

Coronavirus disease 2019 (COVID-19), caused by a novel coronavirus, manifests as a respiratory illness primarily and symptoms range from asymptomatic to severe respiratory syndrome and even death. During the pandemic, due to overcrowding of medical facilities, clinical assessment to triage patients for home care or in-hospital treatment was an essential element of management.

OBJECTIVES:

Study the demographic features, comorbidities and bio-markers that predict severe illness and mortality from COVID-19 infection.

DESIGN:

Retrospective observational

SETTING:

Single tertiary care center PATIENTS AND

METHODS:

The study included all patients admitted with a positive PCR test for COVID-19 during the period from March 2020 to September 2020 (7 months). Data on demographics, clinical data and laboratory parameters was collected from medical records every 3 days during hospital stay or up until transfer to ICU. MAIN OUTCOME

MEASURES:

Demographic, comorbidities and biochemical features that might predict severe COVID-19 disease. SAMPLE SIZE 372

RESULTS:

Of the 372 patients, 72 (19.4%) had severe disease requiring admission to intensive care unit (ICU); 6 (1.6%) died. Individuals over 62 years were more likely to be admitted to the ICU (P=.0001, while a BMI of 40 and higher increased the odds of severe disease (P=.032). Male gender (P=.042), hypertension (P=.006) and diabetes (P=.001) conferred a statistically significant increased risk of admission to ICU, while coexisting COPD, and ischemic heart disease did not. Laboratory features related to severe COVID-19 infection were leukocytosis (P=.015), thrombocytopenia (P=.001), high levels of C-reactive protein (P=.0001), lactic dehydrogenase (P=.0001), D-dimer (P=.0001) and ferritin (P=.001). With the multivariate analysis, diabetes, high lac-tate dehydrogenase, C-reactive protein and thrombocytopenia were associated with severity of illness.

CONCLUSIONS:

Particular demographic and clinical parameters may predict severe illness and need for ICU care.

LIMITATIONS:

Single referral center, several cases of severe COVID-19 could not be included due to lack of consent and or data. CONFLICT OF INTEREST None.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Trombocitopenia / Diabetes Mellitus / COVID-19 Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans / Male Idioma: En Revista: Ann Saudi Med Assunto da revista: MEDICINA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Arábia Saudita

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Trombocitopenia / Diabetes Mellitus / COVID-19 Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans / Male Idioma: En Revista: Ann Saudi Med Assunto da revista: MEDICINA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Arábia Saudita