Prevalence of and factors associated with multimorbidity among adults in Kuwait.

BACKGROUND: This cross-sectional study aimed to assess the prevalence of morbidity i.e., one morbidity and multimorbidity (≥ 2 morbid conditions) among adults in Kuwait and to examine the sociodemographic and lifestyle factors associated with morbidity as a multinomial outcome in the study population. METHODS: The data were collected from January 26, 2021, to February 3, 2021, using an electronic questionnaire, which was distributed on social media platforms. The consent form was attached with the questionnaire and the participants were requested to sign the consent form before completing the questionnaire. The prevalences (%) of each morbidity and multimorbidity were computed. Multivariable polychotomous logistic regression analysis was used to evaluate the association between the demographic and lifestyle factors with morbidity as a multinomial outcome. RESULTS: Of 3572 respondents included, 89% were Kuwaiti, 78.3% females and 66% were 21- 40 years old. The prevalence of multimorbidity and one morbidity respectively was 27.4% and 29.7%. The prevalence of multimorbidity with two, three, four or five ill-health conditions were 14.3%, 7.4%, 3.5%, and 1.2%, respectively. A higher prevalence of multimorbidity was among respondents over 60 years of age (71%) and Kuwaiti nationals (28.9%). The final multivariable polychotomous logistic regression model revealed that age, sex, nativity, sedentary lifestyle, smoking, and alcohol drinking were significantly (p < 0.05) associated with multimorbidity. However, age and alcohol drinking were significant (p < 0.05) predictors of one morbidity. CONCLUSION: This study provides evidence that multimorbidity is more prevalent among the elderly, females, and Kuwaiti nationals. Sedentary behaviour, smoking and alcohol consumption were significantly and independently associated with multimorbidity. These findings highlight the burden of multimorbidity and should be considered in the development of future prevention programs.

Prognostic Factors and Predictors of In-Hospital Mortality Among COVID-19 Patients Admitted to the Intensive Care Unit: An Aid for Triage, Counseling, and Resource Allocation.

BACKGROUND:  The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains today a global health pandemic. Those with severe infection are at risk of rapid clinical deterioration; as a result, intensive care unit (ICU) admission is not uncommon in such patients. A number of determinants have been identified as predictors of poor prognosis and in-hospital mortality, ranging from demographic characteristics, laboratory and/or radiological findings. AIM: To identify determinants of in-hospital mortality and examine the accuracy of seven early warning scores in predicting in-hospital mortality. METHODS: This is a retrospective study conducted in Kuwait from July 2020 to March 2021, and participants were adult patients with a positive test on the real-time polymerase chain reaction (RT-PCR) for SARS-CoV-2 and who met the criteria for ICU admission. Data collected included: demographics, clinical status on hospital arrival, laboratory test results, and ICU course. Furthermore, we calculated seven early warning scores for each of our patients. RESULTS: A total of 133 patients were admitted to our COVID-19 ICU with a median age of 59 years. Arrival to ICU on mechanical ventilation (MV), developing in-hospital complications, having chronic kidney disease (CKD), having a high white blood count (WBC), lactate dehydrogenase (LDH), lactate, or urea levels were found to be significant predictors of in-hospital mortality. Furthermore, the 4C mortality score for COVID-19, VACO index for COVID-19 mortality, and the PRIEST COVID-19 clinical severity score proved to be the most superior in predicting in-hospital mortality. CONCLUSION: Identifying high-risk patients and those with a poor prognosis allows for efficient triaging and the delivery of high-standard care while minimizing the strain on the healthcare system.