Hussain S Lalani1, Wangari Waweru-Siika2,3, Thomas Mwogi2,4, Protus Kituyi4,5, Joseph R Egger6, Lawrence P Park7,6, Peter S Kussin1,2. 1. 1 Division of Pulmonary, Allergy, and Critical Care Medicine, and. 2. 2 Academic Model Providing Access to Healthcare, Eldoret, Kenya. 3. 3 Department of Anesthesia, Aga Khan University Hospital, Nairobi, Kenya. 4. 4 Department of Anesthesia, Moi Teaching and Referral Hospital, and. 5. 5 Moi University School of Medicine, Eldoret, Kenya; and. 6. 6 Duke Global Health Institute, Durham, North Carolina. 7. 7 Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina.
Abstract
RATIONALE: The burden of critical care is greatest in resource-limited settings. Intensive care unit (ICU) outcomes at public hospitals in Kenya are unknown. The present study is timely, given the Kenyan Ministry of Health initiative to expand ICU capacity. OBJECTIVES: To identify factors associated with mortality at Moi Teaching and Referral Hospital and validate the Mortality Probability Admission Model II (MPM0-II). METHODS: A retrospective cohort of 450 patients from January 1, 2013, to April 5, 2015, was evaluated using demographics, presenting diagnoses, interventions, mortality, and cost data. RESULTS: ICU mortality was 53.6%, and 30-day mortality was 57.3%. Most patients were male (61%) and at least 18 years old (70%); the median age was 29 years. Factors associated with high adjusted odds of mortality were as follows: age younger than 10 years (adjusted odds ratio [aOR], 3.59; P ≤ 0.001), ages 35-49 years (aOR, 3.13; P = 0.002), and age above 50 years (aOR, 2.86; P = 0.004), with reference age range 10-24 years; sepsis (aOR, 3.39; P = 0.01); acute stroke (aOR, 8.14; P = 0.011); acute respiratory failure or mechanical ventilation (aOR, 6.37; P < 0.001); and vasopressor support (aOR, 7.98; P < 0.001). Drug/alcohol poisoning (aOR, 0.33; P = 0.005) was associated with lower adjusted odds of mortality. MPM0-II discrimination showed an area under the receiver operating characteristic curve of 0.78 (95% confidence interval, 0.72-0.82). The result of the Hosmer-Lemeshow test for calibration was significant (P < 0.001). CONCLUSIONS: In a Kenyan public ICU, high mortality was noted despite the use of advanced therapies. MPM0-II has acceptable discrimination but poor calibration. Modification of MPM0-II or development of a new model using a prospective multicenter global collaboration is needed. Standardized triage and treatment protocols for high-risk diagnoses are needed to improve ICU outcomes.
RATIONALE: The burden of critical care is greatest in resource-limited settings. Intensive care unit (ICU) outcomes at public hospitals in Kenya are unknown. The present study is timely, given the Kenyan Ministry of Health initiative to expand ICU capacity. OBJECTIVES: To identify factors associated with mortality at Moi Teaching and Referral Hospital and validate the Mortality Probability Admission Model II (MPM0-II). METHODS: A retrospective cohort of 450 patients from January 1, 2013, to April 5, 2015, was evaluated using demographics, presenting diagnoses, interventions, mortality, and cost data. RESULTS: ICU mortality was 53.6%, and 30-day mortality was 57.3%. Most patients were male (61%) and at least 18 years old (70%); the median age was 29 years. Factors associated with high adjusted odds of mortality were as follows: age younger than 10 years (adjusted odds ratio [aOR], 3.59; P ≤ 0.001), ages 35-49 years (aOR, 3.13; P = 0.002), and age above 50 years (aOR, 2.86; P = 0.004), with reference age range 10-24 years; sepsis (aOR, 3.39; P = 0.01); acute stroke (aOR, 8.14; P = 0.011); acute respiratory failure or mechanical ventilation (aOR, 6.37; P < 0.001); and vasopressor support (aOR, 7.98; P < 0.001). Drug/alcohol poisoning (aOR, 0.33; P = 0.005) was associated with lower adjusted odds of mortality. MPM0-II discrimination showed an area under the receiver operating characteristic curve of 0.78 (95% confidence interval, 0.72-0.82). The result of the Hosmer-Lemeshow test for calibration was significant (P < 0.001). CONCLUSIONS: In a Kenyan public ICU, high mortality was noted despite the use of advanced therapies. MPM0-II has acceptable discrimination but poor calibration. Modification of MPM0-II or development of a new model using a prospective multicenter global collaboration is needed. Standardized triage and treatment protocols for high-risk diagnoses are needed to improve ICU outcomes.
Entities:
Keywords:
Kenya; critical care; critical care outcomes; forecasting
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