Predictors of stroke-associated pneumonia and the predictive value of neutrophil percentage-to-albumin ratio

ABSTRACT

Background

Early recognition of stroke-associated pneumonia (SAP) is critical to reducing morbidity and mortality associated with SAP. This study investigated the predictors of SAP, and the predictive value of the neutrophil percentage-to-albumin ratio (NPAR) for SAP.

Methods

This retrospective cohort study was conducted among stroke patients admitted to Jordan University Hospital from January 2015 to May 2021. Multivariable logistic regression was used to identify independent predictors for SAP. The predictive performance was assessed using C-statistics, described as the area under the receiver-operating characteristic curve (AUC, ROC) with a 95% confidence interval.

Results

Four hundred and six patients were included in the analysis, and the prevalence of SAP was 19.7%. Multivariable logistic analysis showed that males (Adjusted Odds Ratio (AOR): 5.74; 95% Confidence Interval (95%CI): 2.04–1 6.1)], dysphagia (AOR: 5.29; 95% CI: 1.80–15.5), hemiparesis (AOR: 3.27; 95% CI: 1.13–9.47), lower GCS score (AOR: 0.73; 95% CI: 0.58–0.91), higher levels of neutrophil-lymphocyte ratio (NLR) (AOR: 1.15; 95% CI: 1.07–1.24), monocyte-lymphocyte ratio (MLR) (AOR: 1.49; 95% CI: 1.13–1.96), and neutrophil percentage to albumin ratio (NPAR) (AOR: 1.53; 95% CI: 1.33–1.76) were independent predictors of SAP. The NPAR demonstrated a significantly higher AUC than both the NLR (0.939 versus 0.865, Z = 3.169, p = 0.002) and MLR (0.939 versus 0.842, Z = 3.940, p < 0.001). The AUCs of the NLR and MLR were comparable (0.865 versus 0.842, Z = 1.274, p = 0.203).

Conclusion

Male gender, dysphagia and hemiparesis were the strongest predictors of SAP, and NPAR has an excellent performance in predicting SAP which was better than high NLR and MLR.

KEYWORDS:

• Stroke associated pneumonia
• stroke
• predictors
• neutrophil percentage-to-albumin ratio
• SAP prediction

Acknowledgments

The authors would like to thank to the Institute of Postgraduate Studies (IPS), University Sains Malaysia (USM) for fellowship support [Ref. no. P-FD0006/20 (R)].

Declaration of financial/other relationships

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Author contributions

Mohammed Zawiah: conceptualization, data curation, formal analysis, methodology, project administration, software, validation, writing – original draft; Amer Hayat Khan: conceptualization, investigation, methodology, project administration, supervision, writing – review & editing; Rana Abu Farha: conceptualization, data curation, investigation, project administration, supervision, writing – review & editing; Abubakar Usman: conceptualization, investigation, methodology, supervision, writing – review & editing; Khawla Abu Hammour: data curation, investigation, project administration, resources, writing – review & editing; Marwa Abdeen: data curation, investigation, resources, writing – review & editing; Rawand Albooz: data curation, investigation, writing – review & editing.

Additional information

Funding

This paper was not funded.