A multivariable prediction model for invasive pulmonary aspergillosis in immunocompromised patients with acute respiratory failure (IPA-GRRR-OH score).

Purpose: Invasive pulmonary aspergillosis (IPA) is a life-threatening opportunistic infection in immunocompromised patients. The diagnosis is often made late, with mortality reaching 90% when mechanical ventilation is needed. We sought to develop and validate a risk prediction model for the diagnosis of IPA.

Methods: We used two independent datasets of immunocompromised patients with acute respiratory failure admitted to 12 intensive care units (ICUs). The derivation dataset include 3262 patients. Factors associated with probable or proven IPA were identified, and a risk prediction model was developed. This model was then validated in a prospective dataset (776 patients).

Results: IPA prevalence was 4.5% (146/3262) and 3.3% (26/776), in the derivation and the validation cohorts, respectively. The final model included eight variables constitutive of the IPA-GRRR-OH score: type of immunosuppression, high-dose or long-term corticosteroids, neutropenia, the presence of structural lung disease, time from symptoms onset to ICU admission > 7 days, hemoptysis, focal alveolar pattern on the chest imaging, and viral co-infection. The median score [IQR] was 2 [1-3] in the derivation and 1 [0-3] in the validation cohort. The best cutoff score for IPA diagnosis was 4 (sensitivity 23.1%; specificity 90.5%; negative predictive value 91.4%). Discrimination and calibration were good in both the derivation (AUC 0.72 [0.68-0.76]) and the validation cohort (AUC 0.85 [0.76-0.93]).

Conclusion: The IPA-GRRR-OH is a clinical score, easily available at ICU admission, which reliably predicts IPA in immunocompromised patients with acute respiratory failure. Studies to demonstrate benefits from the bedside implementation of this score are warranted.