Clinical and laboratory predictors of Lassa fever outcome in a dedicated treatment facility in Nigeria: a retrospective, observational cohort study

Abstract

Background: Lassa fever is a viral haemorrhagic disease endemic to west Africa. No large-scale studies exist from Nigeria, where the Lassa virus (LASV) is most diverse. LASV diversity, coupled with host genetic and environmental factors, might cause differences in disease pathophysiology. Small-scale studies in Nigeria suggest that acute kidney injury is an important clinical feature and might be a determinant of survival. We aimed to establish the demographic, clinical, and laboratory factors associated with mortality in Nigerian patients with Lassa fever, and hypothesised that LASV was the direct cause of intrinsic renal damage for a subset of the patients with Lassa fever.

Methods: We did a retrospective, observational cohort study of consecutive patients in Nigeria with Lassa fever, who tested positive for LASV with RT-PCR, and were treated in Irrua Specialist Teaching Hospital. We did univariate and multivariate statistical analyses, including logistic regression, of all demographic, clinical, and laboratory variables available at presentation to identify the factors associated with patient mortality.

Findings: Of 291 patients treated in Irrua Specialist Teaching Hospital between Jan 3, 2011, and Dec 11, 2015, 284 (98%) had known outcomes (died or survived) and seven (2%) were discharged against medical advice. Overall case-fatality rate was 24% (68 of 284 patients), with a 1·4 times increase in mortality risk for each 10 years of age (p=0·00017), reaching 39% (22 of 57) for patients older than 50 years. Of 284 patients, 81 (28%) had acute kidney injury and 104 (37%) had CNS manifestations and thus both were considered important complications of acute Lassa fever in Nigeria. Acute kidney injury was strongly associated with poor outcome (case-fatality rate of 60% [49 of 81 patients]; odds ratio [OR] 15, p<0·00001). Compared with patients without acute kidney injury, those with acute kidney injury had higher incidence of proteinuria (32 [82%] of 39 patients) and haematuria (29 [76%] of 38) and higher mean serum potassium (4·63 [SD 1·04] mmol/L) and lower blood urea nitrogen to creatinine ratio (8·6 for patients without clinical history of fluid loss), suggesting intrinsic renal damage. Normalisation of creatinine concentration was associated with recovery. Elevated serum creatinine (OR 1·3; p=0·046), aspartate aminotransferase (OR 1·5; p=0·075), and potassium (OR 3·6; p=0·0024) were independent predictors of death.

Interpretation: Our study presents detailed clinical and laboratory data for Nigerian patients with Lassa fever and provides strong evidence for intrinsic renal dysfunction in acute Lassa fever. Early recognition and treatment of acute kidney injury might significantly reduce mortality.

Funding: German Research Foundation, German Center for Infection Research, Howard Hughes Medical Institute, US National Institutes of Health, and World Bank.

Figure 1. Geographic distribution of LF cases and mortality as function of age

(A) map of Nigeria showing the LF cases treated at ISTH between 2011 and 2015, clustered by mutual proximity. The area of the clusters is proportional to the number of cases, and the color coding represents the observed mortality. (B) bar plot representing mortality as a function of patient age. Age was binned in 10-years intervals, with the exception of the 70-90 years bin, since there was only one patient older than 80 years of age. The height of the histogram bars represents the CFR within each age group. The total patient count in each group is represented by the continuous black line. The inset shows the box plot of the age distribution of surviving and fatal cases.

Figure 2. Performance of the multivariate logistic regression model of LF outcome

This model includes age, severe central nervous system (CNS) symptoms, bleeding, jaundice, aspartate aminotransferase (AST), creatinine (Cr), and potassium (K) as predictors. (A) Receiver Operator Characteristic (ROC) curve, with Area Under the Curve (AUC) in the lower right corner. (B) calibration curve, with calibration score in the lower right corner. (C) sensitivity/specificity plot showing the patient counts within each risk bin, as predicted by the model, separated between fatal (red) and surviving (blue) cases. The thresholds defining low, medium, and high risks are shown in this plot as well. (D) bar plot depicting the percentage of fatal and surviving cases in each risk group, as defined by the thresholds shown in the bottom (same as those in the sensitivity/specificity plot). (E) mortality as a function of the days of fever before presentation (DOFBP), for DOFBP < 3, up to 6 days, up to 13 days, and more than 2 weeks, for each risk group as defined in the previous plots.

Figure 3. Incidence of complications, including acute kidney injury, and laboratory biomarkers indicative of intrinsic renal involvement in LF

(A) bar plot ranking complications in decreasing order of P-value of association with outcome. Incidence of each complication is shown separately for all, surviving, and fatal cases. (B) distributions of BUN:Cr for all patients who developed AKI with and without history of fluid loss (as measured by presence of diarrhea, bleeding, or vomiting at some point during treatment.) Each light-colored curve was obtained from a single imputed dataset from a total of 50 multiple imputations, while the solid curves represent the distributions over all imputations aggregated together. The aggregate densities are significantly different at P<0.001. (C) Fractions of surviving and fatal cases, plotted as a function of Cr, and AST levels (normal/high) at admission and at discharge or death. Normal levels are defined as <2 mg/dl for Cr and <120 IU/L for AST.