Demographic and clinical predictors of mortality from highly pathogenic avian influenza A (H5N1) virus infection: CART analysis of international cases

Abstract

Background: Human infections with highly pathogenic avian influenza (HPAI) A (H5N1) viruses have occurred in 15 countries, with high mortality to date. Determining risk factors for morbidity and mortality from HPAI H5N1 can inform preventive and therapeutic interventions.

Methods: We included all cases of human HPAI H5N1 reported in World Health Organization Global Alert and Response updates and those identified through a systematic search of multiple databases (PubMed, Scopus, and Google Scholar), including articles in all languages. We abstracted predefined clinical and demographic predictors and mortality and used bivariate logistic regression analyses to examine the relationship of each candidate predictor with mortality. We developed and pruned a decision tree using nonparametric Classification and Regression Tree methods to create risk strata for mortality.

Findings: We identified 617 human cases of HPAI H5N1 occurring between December 1997 and April 2013. The median age of subjects was 18 years (interquartile range 6-29 years) and 54% were female. HPAI H5N1 case-fatality proportion was 59%. The final decision tree for mortality included age, country, per capita government health expenditure, and delay from symptom onset to hospitalization, with an area under the receiver operator characteristic (ROC) curve of 0.81 (95% CI: 0.76-0.86).

Interpretation: A model defined by four clinical and demographic predictors successfully estimated the probability of mortality from HPAI H5N1 illness. These parameters highlight the importance of early diagnosis and treatment and may enable early, targeted pharmaceutical therapy and supportive care for symptomatic patients with HPAI H5N1 virus infection.

Figure 1. Literature search strategy.

*: Total number of excluded articles is less than the sum of articles excluded by each criterion because most articles failed multiple criteria.

Figure 2. Variable summary and patterns of missing data.

*: Variable was excluded from modeling. Each row represents one of 617 human cases; each column represents a variable abstracted from the literature. The color of each cell indicates whether the corresponding variable was missing (dark green) or observed (light green) for the given case.

Figure 3. Classification tree for mortality following highly pathogenic avian influenza H5N1 virus infection.

Model was trained on all n = 607 cases with observed mortality. The following variables were candidates for inclusion: age, PCGEH, country, delay to hospitalization, sex, season, contact with poultry.

Figure 4. ROC curve for pruned CART tree.

ROC curve represents performance of CART model on all cases without missing observations on any model variables (n = 301). Error bars represent bootstrapped 95% confidence intervals for sensitivity-specificity thresholds.