Prediction of stroke-associated pneumonia by the A2DS2, AIS-APS, and ISAN scores: a systematic review and meta-analysis

Background: Different scoring systems (A2DS2, AISAPS, ISAN) have been designed to predict the risk of in-hospital stroke-associated pneumonia (SAP). Studies have assessed the accuracy of these scores for predicting SAP. We performed this meta-analysis to consolidate the evidence on the predictive accuracies for SAP of the A2DS2, AISAPS, and ISAN scores. Materials and methods: We conducted a systematic search for all studies reporting the SAP predictive accuracy of A2DS2, AISAPS, or ISAN scores in the databases of PubMed Central, SCOPUS, MEDLINE, Embase, and Cochrane from inception until December 2020. We used the STATA software for the meta-analysis. Results: We included 19 studies with 35 849 patients. The pooled score sensitivities were 78% (95% CI, 71%-83%) for A2DS2, 79% (95% CI, 77%-81%) for AISAPS, and 79% (95% CI, 77%-81%) for ISAN. The pooled score specificities were 73% (95% CI, 65%-80%) for A2DS2, 74% (95% CI, 69%-79%) for AISAPS, and 74% (95% CI, 69%-79%) for ISAN. We found significant heterogeneity for all the scoring systems based on the chi-square test results and an I-2 statistic > 75%. We performed meta-regression to explore the source of heterogeneity and found that patient selection (p< 0.05) and reference standards (p< 0.05) in the sensitivity model, index test standards (p< 0.05), flow and timing of tests (p< 0.01) in the specificity model, and mean age (p < 0.001) in the joint model were the source of heterogeneity. Conclusions: To summarize, we found that A2S2, AISAPS and ISAN have moderate predictive accuracy for SAP with A2S2 having a stable cutoff value.