Individualized Prediction Of Stroke-Associated Pneumonia For Patients With Acute Ischemic Stroke

Abstract

Background: Stroke-associated pneumonia (SAP) is a serious and common complication in stroke patients.

Purpose: We aimed to develop and validate an easy-to-use model for predicting the risk of SAP in acute ischemic stroke (AIS) patients.

Patients and methods: The nomogram was established by univariate and multivariate binary logistic analyses in a training cohort of 643 AIS patients. The prediction performance was determined based on the receiver operating characteristic curve (ROC) and calibration plots in a validation cohort (N=340). Individualized clinical decision-making was conducted by weighing the net benefit in each AIS patient by decision curve analysis (DCA).

Results: Seven predictors, including age, NIHSS score on admission, atrial fibrillation, nasogastric tube intervention, mechanical ventilation, fibrinogen, and leukocyte count were incorporated to construct the nomogram model. The nomogram showed good predictive performance in ROC analysis [AUROC of 0.845 (95% CI: 0.814-0.872) in training cohort, and 0.897 (95% CI: 0.860-0.927) in validation cohort], and was superior to the A²DS², ISAN, and PANTHERIS scores. Furthermore, the calibration plots showed good agreement between actual and nomogram-predicted SAP probabilities, in both training and validation cohorts. The DCA confirmed that the SAP nomogram was clinically useful.

Conclusion: Our nomogram may provide clinicians with a simple and reliable tool for predicting SAP based on routinely available data. It may also assist clinicians with respect to individualized treatment decision-making for patients differing in risk level.

Keywords: acute ischemic stroke; nomogram; prediction; stroke-associated pneumonia.

Figure 1

Study flow diagram. Abbreviations: AIS, acute ischemic stroke; TIA, transient ischemic attack.

Figure 2

Nomogram model for predicting individual risk of stroke-associated pneumonia (SAP) in AIS patients. For all patients, adding up the points identified on the points scale for all seven indicators. Then, the sum is located on the “Total Points” axis. Finally, the risk of SAP according to the nomogram is the probability of “Stroke-associated pneumonia” corresponding to “Total Points”.

Figure 3

Comparison of area under the receiver operating characteristic curve (AUROC) values among different scoring systems for prediction of SAP, in the training cohort (A) and validation cohort (B). a vs b, p=0.025; a vs c, p=0.003; a vs d, p=0.020. Abbreviation: CI, confidence interval.

Figure 4

Calibration curve of the nomogram for the training cohort (A) and the validation cohort (B). (A) mean absolute error=0.020 (training cohort); (B) mean absolute error=0.019 (validation cohort).

Figure 5

Decision curves of the different scoring systems for predicting SAP. The net benefit was calculated by adding the true-positives and subtracting the false-positives. For a threshold probability >4%, application of the SAP nomogram would add net benefit compared to either the treat-all strategy or the treat-none strategy. In addition, the SAP nomogram always showed a greater net benefit than the A²DS², ISAN, and PANTHERIS scores for predicting SAP with a threshold probability >4%.