Acute febrile illness in Kenya: Clinical characteristics and pathogens detected among patients hospitalized with fever, 2017-2019.

Acute febrile illness (AFI) is a common reason for healthcare seeking and hospitalization in Sub-Saharan Africa and is often presumed to be malaria. However, a broad range of pathogens cause fever, and more comprehensive data on AFI etiology can improve clinical management, prevent unnecessary prescriptions, and guide public health interventions. We conducted surveillance for AFI (temperature ≥38.0°C <14 days duration) among hospitalized patients of all ages at four sites in Kenya (Nairobi, Mombasa, Kakamega, and Kakuma). For cases of undifferentiated fever (UF), defined as AFI without diarrhea (≥3 loose stools in 24 hours) or lower respiratory tract symptoms (cough/difficulty breathing plus oxygen saturation <90% or [in children <5 years] chest indrawing), we tested venous blood with real-time PCR-based TaqMan array cards (TAC) for 17 viral, 8 bacterial, and 3 protozoal fever-causing pathogens. From June 2017 to March 2019, we enrolled 3,232 AFI cases; 2,529 (78.2%) were aged <5 years. Among 3,021 with outcome data, 131 (4.3%) cases died while in hospital, including 106/2,369 (4.5%) among those <5 years. Among 1,735 (53.7%) UF cases, blood was collected from 1,340 (77.2%) of which 1,314 (98.1%) were tested by TAC; 715 (54.4%) had no pathogens detected, including 147/196 (75.0%) of those aged <12 months. The most common pathogen detected was Plasmodium, as a single pathogen in 471 (35.8%) cases and in combination with other pathogens in 38 (2.9%). HIV was detected in 51 (3.8%) UF cases tested by TAC and was most common in adults (25/236 [10.6%] ages 18-49, 4/40 [10.0%] ages ≥50 years). Chikungunya virus was found in 30 (2.3%) UF cases, detected only in the Mombasa site. Malaria prevention and control efforts are critical for reducing the burden of AFI, and improved diagnostic testing is needed to provide better insight into non-malarial causes of fever. The high case fatality of AFI underscores the need to optimize diagnosis and appropriate management of AFI to the local epidemiology.

Epidemiology of SARS-CoV-2 in Kakuma Refugee Camp Complex, Kenya, 2020-20211.

Understanding SARS-CoV-2 infection in populations at increased risk for poor health is critical to reducing disease. We describe the epidemiology of SARS-CoV-2 infection in Kakuma Refugee Camp Complex, Kenya. We performed descriptive analyses of SARS-CoV-2 infection in the camp and surrounding community during March 16, 2020‒December 31, 2021. We identified cases in accordance with national guidelines.We estimated fatality ratios and attack rates over time using locally weighted scatterplot smoothing for refugees, host community members, and national population. Of the 18,864 SARS-CoV-2 tests performed, 1,024 were positive, collected from 664 refugees and 360 host community members. Attack rates were 325.0/100,000 population (CFR 2.9%) for refugees,150.2/100,000 population (CFR 1.11%) for community, and 628.8/100,000 population (CFR 1.83%) nationwide. During 2020-2021, refugees experienced a lower attack rate but higher CFR than the national population, underscoring the need to prioritize SARS-CoV-2 mitigation measures, including vaccination.

Association of Modified Body Mass Index With In-Hospital Outcomes After Intermediate or High-Risk Pulmonary Embolism.

Background: Pulmonary embolism (PE) outcomes are determined by presentation severity and host-related factors. Limited data exist regarding the association of modified body mass index (mBMI), used as a frailty surrogate, with clinical outcomes after treatment for PE. Therefore, we sought to determine the association of mBMI with mortality and bleeding after treatment for intermediate or high-risk PE. Methods: Patients treated for intermediate-risk or high-risk PE at a large academic center between 2013 and 2019 were studied. PE was characterized as intermediate risk (right ventricular compromise) or high risk (hemodynamic compromise) per European Society of Cardiology guidelines. mBMI was defined as the product of serum albumin concentration and body mass index. Patients were stratified according to mBMI quartiles, with low mBMI defined as ≤79, and evaluated for primary end points of in-hospital mortality and bleeding after treatment. A multivariable logistic regression analysis was performed for primary end points. Results: A total of 843 patients were treated for PE. Low mBMI was associated with increased burden of comorbidities and lower rates of interventional or surgical treatment. mBMI was independently associated with mortality (Q1, 22.8%; Q2, 12.4%; Q3, 10.9%; Q4, 6.6%; P = .005) and bleeding (Q1, 20.1%; Q2, 10.1%; Q3, 13.3%; Q4, 11.0%; P = .006). Compared with the lowest mBMI quartile, the highest mBMI quartile was independently associated with lower rates of mortality (OR, 0.28; 95% CI, 0.13-0.58; P < .001) and bleeding (OR, 0.42; 95% CI, 0.23-0.76; P = .004). Conclusions: Low mBMI is prevalent in patients with intermediate-risk and high-risk PE and is independently associated with in-hospital mortality and bleeding after treatment.