Patient Related Outcome Measures (Dec 2023)
The Pattern of Admission, Clinical Characteristics, and Outcomes Among Patients Admitted to the Intensive Care Unit of a Tertiary Hospital in Tanzania: A 5-Year Retrospective Review
Abstract
Nadeem Kassam,1 Philip B Adebayo,1 Iris Martin Matei,1 Eric Aghan,2 Samina Somji,1 Samwel Paul Kadelya,1 Yasson Abha,1 Frank Elton Swai,2 Mangaro Mabusi,1 Kamran Hameed,1 Hanifa Mbithe,1 Alyyah Thawer,1 Mandela Charles Makakala,1 Fatma Amirali Bakshi,1 Harrison Chuwa,1 Masolwa Ng’wanasayi,1 Casmir M Wambura,1 Robert Sostenes Mvungi,1 James Orwa,3 Munish Sharma,4 George Udeani,5 Salim Surani5 1Department of Internal Medicine, Aga Khan Health Service, Dar-es-Salaam, Tanzania; 2Department of Family Medicine, Aga Khan University Medical College, Nairobi, Kenya; 3Department of Population Health, Aga Khan University Medical College, Nairobi, Kenya; 4Department of Medicine, Division of Pulmonology and Critical Care, Baylor Scott and White Medical Center, Temple, Texas, USA; 5Department of Pharmacy, A&M University, College Station, Texas, USACorrespondence: Nadeem Kassam, Department of Internal Medicine, Aga Khan Health Service, Dar-es-Salaam, Tanzania, Email [email protected]: Despite the implementation of complex interventions, ICU mortality remains high and more so in developing countries. The demand for critical care in Sub-Saharan Africa is more than ever before as the region experiences a double burden of rising rates of non-communicable diseases (NCD) in the background battle of combating infectious diseases. Limited studies in Tanzania have reported varying factors associated with markedly high rates of ICU mortality. Investigating the burden of ICU care remains crucial in providing insights into the effectiveness and challenges of critical care delivery.Material and Methods: A single-center retrospective study that reviewed records of all medically admitted patients admitted to the ICU of the Aga Khan Hospital, Dar-es-Salaam, from 1st October 2018 to 30th April 2023. To define the population in the study, we used descriptive statistics. Patients’ outcomes were categorized based on ICU survival. Binary logistic regression was run (at 95% CI and p-value