Derivation and validation of a clinical system for predicting pneumonia in acute stroke

Neale R. Chumbler, Linda Williams, Carolyn K. Wells, Albert C. Lo, Steven Nadeau, Aldo J. Peixoto, Mark Gorman, John L. Boice, John Concato, Dawn Bravata

Research output: Contribution to journalArticle

45 Citations (Scopus)

Abstract

Aims: We derived and validated a clinical prediction rule that can be used to predict post-stroke pneumonia. Methods: We conducted a retrospective cohort study of patients admitted to hospital with a stroke. The cohort was subdivided into a derivation group and a validation group. Within the derivation group, a point scoring system was developed to predict pneumonia based on a logistic regression model. The point scoring system was then tested within the validation group. Results: Of the 1,363 patients with stroke, 10.5% of patients experienced new pneumonia. The most points were assigned for abnormal swallowing result and history of pneumonia (4 points), followed by greater NIHSS score (3 points), patient being 'found down' at symptom onset (3 points), and age >70 years (2 points). A 3-level classification system was created denoting low, medium and high risks of pneumonia, which accurately predicted pneumonia in the validation group. The discriminatory accuracy of the 3-level clinical prediction rule exceeded the acceptable range in both the derivation group (c statistic: 0.78) and validation group (c statistic: 0.76). Conclusion: A simple scoring system was derived and validated. This clinical scoring system may better identify stroke patients who are at high risk of developing new pneumonia.

Original languageEnglish
Pages (from-to)193-199
Number of pages7
JournalNeuroepidemiology
Volume34
Issue number4
DOIs
StatePublished - May 2010

Fingerprint

Pneumonia
Stroke
Decision Support Techniques
Logistic Models
Deglutition
Cohort Studies
Retrospective Studies

Keywords

  • Clinical prediction
  • Pneumonia
  • Stroke

ASJC Scopus subject areas

  • Epidemiology
  • Clinical Neurology

Cite this

Derivation and validation of a clinical system for predicting pneumonia in acute stroke. / Chumbler, Neale R.; Williams, Linda; Wells, Carolyn K.; Lo, Albert C.; Nadeau, Steven; Peixoto, Aldo J.; Gorman, Mark; Boice, John L.; Concato, John; Bravata, Dawn.

In: Neuroepidemiology, Vol. 34, No. 4, 05.2010, p. 193-199.

Research output: Contribution to journalArticle

Chumbler, NR, Williams, L, Wells, CK, Lo, AC, Nadeau, S, Peixoto, AJ, Gorman, M, Boice, JL, Concato, J & Bravata, D 2010, 'Derivation and validation of a clinical system for predicting pneumonia in acute stroke', Neuroepidemiology, vol. 34, no. 4, pp. 193-199. https://doi.org/10.1159/000289350
Chumbler, Neale R. ; Williams, Linda ; Wells, Carolyn K. ; Lo, Albert C. ; Nadeau, Steven ; Peixoto, Aldo J. ; Gorman, Mark ; Boice, John L. ; Concato, John ; Bravata, Dawn. / Derivation and validation of a clinical system for predicting pneumonia in acute stroke. In: Neuroepidemiology. 2010 ; Vol. 34, No. 4. pp. 193-199.
@article{4e62d462a3a64ae1981fc2f0a9e42bce,
title = "Derivation and validation of a clinical system for predicting pneumonia in acute stroke",
abstract = "Aims: We derived and validated a clinical prediction rule that can be used to predict post-stroke pneumonia. Methods: We conducted a retrospective cohort study of patients admitted to hospital with a stroke. The cohort was subdivided into a derivation group and a validation group. Within the derivation group, a point scoring system was developed to predict pneumonia based on a logistic regression model. The point scoring system was then tested within the validation group. Results: Of the 1,363 patients with stroke, 10.5{\%} of patients experienced new pneumonia. The most points were assigned for abnormal swallowing result and history of pneumonia (4 points), followed by greater NIHSS score (3 points), patient being 'found down' at symptom onset (3 points), and age >70 years (2 points). A 3-level classification system was created denoting low, medium and high risks of pneumonia, which accurately predicted pneumonia in the validation group. The discriminatory accuracy of the 3-level clinical prediction rule exceeded the acceptable range in both the derivation group (c statistic: 0.78) and validation group (c statistic: 0.76). Conclusion: A simple scoring system was derived and validated. This clinical scoring system may better identify stroke patients who are at high risk of developing new pneumonia.",
keywords = "Clinical prediction, Pneumonia, Stroke",
author = "Chumbler, {Neale R.} and Linda Williams and Wells, {Carolyn K.} and Lo, {Albert C.} and Steven Nadeau and Peixoto, {Aldo J.} and Mark Gorman and Boice, {John L.} and John Concato and Dawn Bravata",
year = "2010",
month = "5",
doi = "10.1159/000289350",
language = "English",
volume = "34",
pages = "193--199",
journal = "Neuroepidemiology",
issn = "0251-5350",
publisher = "S. Karger AG",
number = "4",

}

TY - JOUR

T1 - Derivation and validation of a clinical system for predicting pneumonia in acute stroke

AU - Chumbler, Neale R.

AU - Williams, Linda

AU - Wells, Carolyn K.

AU - Lo, Albert C.

AU - Nadeau, Steven

AU - Peixoto, Aldo J.

AU - Gorman, Mark

AU - Boice, John L.

AU - Concato, John

AU - Bravata, Dawn

PY - 2010/5

Y1 - 2010/5

N2 - Aims: We derived and validated a clinical prediction rule that can be used to predict post-stroke pneumonia. Methods: We conducted a retrospective cohort study of patients admitted to hospital with a stroke. The cohort was subdivided into a derivation group and a validation group. Within the derivation group, a point scoring system was developed to predict pneumonia based on a logistic regression model. The point scoring system was then tested within the validation group. Results: Of the 1,363 patients with stroke, 10.5% of patients experienced new pneumonia. The most points were assigned for abnormal swallowing result and history of pneumonia (4 points), followed by greater NIHSS score (3 points), patient being 'found down' at symptom onset (3 points), and age >70 years (2 points). A 3-level classification system was created denoting low, medium and high risks of pneumonia, which accurately predicted pneumonia in the validation group. The discriminatory accuracy of the 3-level clinical prediction rule exceeded the acceptable range in both the derivation group (c statistic: 0.78) and validation group (c statistic: 0.76). Conclusion: A simple scoring system was derived and validated. This clinical scoring system may better identify stroke patients who are at high risk of developing new pneumonia.

AB - Aims: We derived and validated a clinical prediction rule that can be used to predict post-stroke pneumonia. Methods: We conducted a retrospective cohort study of patients admitted to hospital with a stroke. The cohort was subdivided into a derivation group and a validation group. Within the derivation group, a point scoring system was developed to predict pneumonia based on a logistic regression model. The point scoring system was then tested within the validation group. Results: Of the 1,363 patients with stroke, 10.5% of patients experienced new pneumonia. The most points were assigned for abnormal swallowing result and history of pneumonia (4 points), followed by greater NIHSS score (3 points), patient being 'found down' at symptom onset (3 points), and age >70 years (2 points). A 3-level classification system was created denoting low, medium and high risks of pneumonia, which accurately predicted pneumonia in the validation group. The discriminatory accuracy of the 3-level clinical prediction rule exceeded the acceptable range in both the derivation group (c statistic: 0.78) and validation group (c statistic: 0.76). Conclusion: A simple scoring system was derived and validated. This clinical scoring system may better identify stroke patients who are at high risk of developing new pneumonia.

KW - Clinical prediction

KW - Pneumonia

KW - Stroke

UR - http://www.scopus.com/inward/record.url?scp=77449123622&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77449123622&partnerID=8YFLogxK

U2 - 10.1159/000289350

DO - 10.1159/000289350

M3 - Article

C2 - 20197702

AN - SCOPUS:77449123622

VL - 34

SP - 193

EP - 199

JO - Neuroepidemiology

JF - Neuroepidemiology

SN - 0251-5350

IS - 4

ER -