Attributable mortality from extensively drug-resistant gram-negative infections using propensity-matched tracer antibiotic algorithms.

Journal: American Journal Of Infection Control
Published:
Abstract

Background: Tracer antibiotic algorithms using administrative data were investigated to estimate mortality attributable to extensively drug-resistant gram-negative infections (GNIs).

Methods: Among adult inpatients coded for GNIs, colistin cases and 2 comparator cohorts (non-carbapenem β-lactams or carbapenems) treated for ≥4 consecutive days, or died while receiving the antibiotic, were separately propensity score-matched (1:2). Attributable mortality was the in-hospital mortality difference among propensity-matched groups. Infection characteristics and sepsis severity influences on attributable mortality were examined. Algorithm accuracy was assessed by chart review.

Results: Of 232,834 GNIs between 2010 and 2013 at 79 hospitals, 1,023 per 3,350 (30.5%) colistin and 9,188 per 105,641 (8.7%) β-lactam (non-carbapenem) comparator cases died. Propensity-matched colistin and β-lactam case mortality was 29.2% and 16.6%, respectively, for an attributable mortality of 12.6% (95% confidence interval 10.8-14.4%). Attributable mortality varied from 11.0% (7.5%-14.7%) for urinary to 15.5% (12.6%-18.4%) for respiratory (P < .0001), and 4.6% (2.1%-7.4%) for early (≤4 days) to 16.6% (14.3%-18.9%) for late-onset infections (P < .0001). Attributable mortality decreased to 7.5% (5.6%-9.4%) using a carbapenem comparator cohort but increased 9-fold in patients coded for severe sepsis or septic shock (P < .0001). Our colistin algorithm had a positive predictive value of 60.4% and sensitivity of 65.3%.

Conclusions: Mortality attributable to treatment-limiting resistance during GNIs varied considerably by site, onset, and severity of infection.

Authors
Sameer Kadri, Jeffrey Strich, Bruce Swihart, Samuel Hohmann, John Dekker, Tara Palmore, Stephanie Bonne, Bradley Freeman, Jillian Raybould, Nirav Shah, Devang Patel, Jennifer Husson, Mitchell Jacobs, Lan Duong, Dean Follmann, David Hooper, Joseph Timpone, Robert Danner
Relevant Conditions

Sepsis