title: Novel risk score to predict pneumonia after acute ischemic stroke.
abstract: OBJECTIVE
  To develop and validate a risk score (acute ischemic stroke-associated pneumonia score [AIS-APS]) for predicting in-hospital stroke-associated pneumonia (SAP) after AIS.
  
  
  METHODS
  The AIS-APS was developed based on the China National Stroke Registry, in which eligible patients were randomly classified into derivation (60%) and internal validation cohort (40%). External validation was performed using the prospective Chinese Intracranial Atherosclerosis Study. Independent predictors of in-hospital SAP after AIS were obtained using multivariable logistic regression, and β-coefficients were used to generate point scoring system of the AIS-APS. The area under the receiver operating characteristic curve and the Hosmer-Lemeshow goodness-of-fit test were used to assess model discrimination and calibration, respectively.
  
  
  RESULTS
  The overall in-hospital SAP after AIS was 11.4%, 11.3%, and 7.3% in the derivation (n=8820), internal (n=5882) and external (n=3037) validation cohort, respectively. A 34-point AIS-APS was developed from the set of independent predictors including age, history of atrial fibrillation, congestive heart failure, chronic obstructive pulmonary disease and current smoking, prestroke dependence, dysphagia, admission National Institutes of Health Stroke Scale score, Glasgow Coma Scale score, stroke subtype (Oxfordshire), and blood glucose. The AIS-APS showed good discrimination (area under the receiver operating characteristic curve) in the internal (0.785; 95% confidence interval, 0.766-0.803) and external (0.792; 95% confidence interval, 0.761-0.823) validation cohort. The AIS-APS was well calibrated (Hosmer-Lemeshow test) in the internal (P=0.22) and external (P=0.30) validation cohort. When compared with 3 prior scores, the AIS-APS showed significantly better discrimination with regard to in-hospital SAP after AIS (all P<0.0001).
  
  
  CONCLUSIONS
  The AIS-APS is a valid risk score for predicting in-hospital SAP after AIS.
authors.affiliation: Tiantan Comprehensive Stroke Center, Beijing Tiantan Hospital, Capital Medical University, No. 6 Tiantanxili, Dongcheng District, Beijing 100050, China.
authors.forename: Ruijun
authors.initials: R
authors.lastname: Ji
authors.forename: Haipeng
authors.initials: H
authors.lastname: Shen
authors.forename: Yuesong
authors.initials: Y
authors.lastname: Pan
authors.forename: Panglian
authors.initials: P
authors.lastname: Wang
authors.forename: Gaifen
authors.initials: G
authors.lastname: Liu
authors.forename: Yilong
authors.initials: Y
authors.lastname: Wang
authors.forename: Hao
authors.initials: H
authors.lastname: Li
authors.forename: Yongjun
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002545:Brain Ischemia / Q000150:complications*; D002681:China; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011014:Pneumonia / Q000209:etiology*; D011237:Predictive Value of Tests; D011379:Prognosis; D011446:Prospective Studies; D012042:Registries; D012306:Risk; D018570:Risk Assessment; D012720:Severity of Illness Index; D020521:Stroke / Q000150:complications*