Predictors of Mortality Among Hospitalized Patients With Lower Respiratory Tract Infections in a High HIV Burden Setting

Abstract

Introduction Lower respiratory tract infections (LRTIs) are a leading cause of mortality in sub-Saharan Africa. Triaging identifies patients at high-risk of death but laboratory tests proposed for use in severity-of-illness scores are not readily available, limiting their clinical use. Our objective was to determine whether baseline characteristics in hospitalized participants with LRTI predicted increased risk of death. Methods This was a secondary analysis from the MIND-IHOP cohort of adults hospitalized with LRTI who underwent standardized investigations and treatment. The primary outcome was all-cause mortality at two months. Predictors of mortality were determined using multiple logistic regression. Results Of 1887 hospitalized participants with LRTI, 372 (19.7%) died. The median participant age was 34.3 years (Interquartile Range, IQR, 28.0–43.3 years), 978 (51.8%) were men, and 1192 (63.2%) were HIV-positive with median CD4 counts of 81 cells/µL (IQR 21–226 cells/µL). Seven hundred eleven (37.7%) participants had a microbiologically confirmed diagnosis. Temperature <35.5ºC (aOR=1.77, 95% CI=1.20–2.60; p=0.004), heart rate >120/minute (aOR=1.82, 95% CI=1.37–2.43; p<0.0001), oxygen saturation <90% (aOR=2.74, 95% CI=1.97–3.81; p<0.0001), being bed-bound (aOR=1.88, 95% CI=1.47–2.41; p<0.0001) and being HIV-positive (aOR=1.49, 95%CI=1.14–1.94; p=0.003) were independently associated with mortality at two months. Conclusions Having temperature <35.5°C, heart rate >120/minute, hypoxia; being HIV positive and bed-bound independently predicts mortality in participants hospitalized with LRTI. These readily-available characteristics could be used to triage patients with LRTI in low-income settings. Providing adequate oxygen, adequate intravenous fluids; and early antiretroviral therapy (in people living with HIV/AIDS) may be life-saving in hospitalized patients with LRTI.

Oxygen delivery systems for adults in Sub-Saharan Africa: A scoping review

“…Five studies assessed hypoxemia among specific populations, ranging from those with cor pulmonale to sepsis to Ebola Virus Disease. The heterogeneity in patient populations makes it difficult to discern the overall need in various settings, but prevalence ranged from 11%-89% [ 35 , 37 , 40 , 45 , 46 ]. Several of these studies demonstrated high mortality among those with hypoxemia and an additional two studies focused specifically on hypoxemia as a risk factor for mortality [ 36 , 42 ].…”

“…Several of these studies demonstrated high mortality among those with hypoxemia and an additional two studies focused specifically on hypoxemia as a risk factor for mortality [ 36 , 42 ]. For example, among hospitalized patients who presented with lower respiratory tract infection and cough at Mulago Hospital in Uganda, 10.6% had an oxygen saturation of <90%, and hypoxemia was associated with both in-hospital and two-month mortality [ 46 ]. Among patients with Ebola Virus Disease in West Africa, 18 of 41 (44%) patients required and received supplemental oxygen via concentrators, and 16 of 18 (89%) died [ 37 ].…”

Risk scores for predicting early antiretroviral therapy mortality in sub-Saharan Africa to inform who needs intensification of care: a derivation and external validation cohort study

“…Because heart rate might be more easily available in LMIC settings than temperature, we also created an alternate clinical score where heart rate replaced temperature (see Additional file 6 , table showing alternate clinical score). In this alternate score, we used heart rate cut-offs of > 120 versus ≤ 120 beats/minute, which were informed by both prior published literature [ 22 , 27 ] and observed inflection points in the association between heart rate and risk of death (see Additional file 5 , figure of association between heart rate and risk of death).…”

HIV infection is associated with elevated biomarkers of immune activation in Ugandan adults with pneumonia

“…To do so, 5 variables known to be associated with pneumonia severity were selected for adjustment; these were age, heart rate, respiratory rate, oxygen saturation, and whether or not a participant was, by self-report, bedbound. [23,24] Initially, to determine whether differences in biomarker levels were independent of pneumonia severity, we fit a multiple linear regression model for each biomarker as a continuous outcome in which HIV status (infected or uninfected) was the predictor of interest, and co-variates were age, heart rate, respiratory rate, oxygen saturation, and bedbound status. However, regression diagnostics suggested that for several biomarkers, model residuals were not normally distributed and that variance differed substantially between the HIV-infected and HIV-uninfected subgroups.…”