External validation demonstrated the Ottawa SAH prediction models can identify pSAH using health administrative data

Shane W English; Victoria Saigle; Lauralyn McIntyre; Michaël Chassé; Dean Fergusson; Alexis F Turgeon; François Lauzier; Donald Griesdale; Allan Garland; Ryan Zarychanski; Almunder Algird; Evan J Wiens; Vivien Hu; Pallavi Dutta; Vincent Boun; Carl van Walraven

doi:10.1016/j.jclinepi.2020.06.024

External validation demonstrated the Ottawa SAH prediction models can identify pSAH using health administrative data

J Clin Epidemiol. 2020 Oct:126:122-130. doi: 10.1016/j.jclinepi.2020.06.024. Epub 2020 Jul 1.

Authors

Shane W English¹, Victoria Saigle², Lauralyn McIntyre³, Michaël Chassé⁴, Dean Fergusson⁵, Alexis F Turgeon⁶, François Lauzier⁷, Donald Griesdale⁸, Allan Garland⁹, Ryan Zarychanski¹⁰, Almunder Algird¹¹, Evan J Wiens¹², Vivien Hu⁸, Pallavi Dutta¹³, Vincent Boun¹⁴, Carl van Walraven¹⁵

Affiliations

¹ Department of Medicine (Critical Care), uOttawa, Civic Campus Room F202, 1053 Carling Avenue, Ottawa, Ontario K1Y 4E9, Canada; Clinical Epidemiology Program (CEP), Ottawa Hospital Research Institute (OHRI), Civic Campus Room F202, 1053 Carling Avenue, Ottawa, Ontario K1Y 4E9, Canada. Electronic address: senglish@ohri.ca.
² Clinical Epidemiology Program, Ottawa Hospital Research Institute, The Ottawa Hospital - General Campus, 501 Smyth Road, Ottawa, Ontario K1H 8L6, Canada.
³ Department of Medicine (Critical Care), uOttawa, Civic Campus Room F202, 1053 Carling Avenue, Ottawa, Ontario K1Y 4E9, Canada; Clinical Epidemiology Program, Ottawa Hospital Research Institute, The Ottawa Hospital - General Campus, 501 Smyth Road, Ottawa, Ontario K1H 8L6, Canada.
⁴ Division of Critical Care, Department of Medicine, Centre de Recherche du Centre Hospitalier de l'Université de Montréal, 900 St Denis Street, Montreal, Quebec H2X 0A9, Canada.
⁵ Clinical Epidemiology Program, Ottawa Hospital Research Institute, The Ottawa Hospital - General Campus, 501 Smyth Road, Ottawa, Ontario K1H 8L6, Canada; Department of Medicine (Clinical Epidemiology), uOttawa, 501 Smyth Road, Ottawa, Ontario K1H 8L6, Canada.
⁶ Centre de recherche du CHU de Québec - Université Laval, Population Health and Optimal Health Practices Research Unit (Trauma - Emergency - Critical Care Medicine), 1050 Chemin Sainte-Foy, Local K0-03, Québec, Québec G1S 4L8, Canada; Division of Critical Care Medicine, Department of Anesthesiology and Critical Care Medicine, Université Laval, 2325 Rue de l'Université, Québec, Québec G1V 0A6, Canada.
⁷ Centre de recherche du Centre Hospitalier de l'Université de Québec, Université Laval, Québec City, Québec, Canada; Department of Anesthesiology and Critical Care Medicine, Division of Critical Care Medicine, and Department of Medicine, Université Laval, 2325 Rue de l'Université, Québec, Québec G1V 0A6, Canada.
⁸ Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, 2176 Health Sciences Mall, Vancouver, British Columbia V6T 1Z3, Canada.
⁹ Sections of Critical Care and Respirology, Department of Internal Medicine, University of Manitoba, Health Sciences Centre, University of Manitoba, 820 Sherbrook Street, Winnipeg, Manitoba R3A 1R9, Canada.
¹⁰ Department of Internal Medicine, Sections of Critical Care and Hematology/Medical Oncology, University of Manitoba, Health Sciences Centre, University of Manitoba, 820 Sherbrook Street, Winnipeg Manitoba R3A 1R9, Canada.
¹¹ Department of Neurosurgery, McMaster University, Hamilton Health Sciences, 1200 Main St W, Hamilton, Ontario L8N 3Z5, Canada.
¹² Department of Internal Medicine, University of Manitoba, Health Sciences Centre, University of Manitoba, 820 Sherbrook Street, Winnipeg Manitoba R3A 1R9, Canada.
¹³ Faculty of Health Sciences, McMaster University, 1200 Main St W, Hamilton, Ontario L8N 3Z5, Canada.
¹⁴ Centre de recherche du CHU de Québec - Université Laval, Population Health and Optimal Health Practices Research Unit (Trauma - Emergency - Critical Care Medicine), 1050 Chemin Sainte-Foy, Local K0-03, Québec, Québec G1S 4L8, Canada.
¹⁵ Department of Medicine (Clinical Epidemiology), uOttawa, 501 Smyth Road, Ottawa, Ontario K1H 8L6, Canada; Clinical Epidemiology Program, Ottawa Hospital Research Institute, 1053 Carling Avenue Building, 1st Floor, Ottawa, Ontario K1Y 4E9, Canada; ICES-uOttawa, Administrative Services, 1053 Carling Avenue Building, 1st Floor, Ottawa, Ontario K1Y 4E9, Canada.

PMID: 32619751
DOI: 10.1016/j.jclinepi.2020.06.024

Abstract

Objectives: The objective of the study is to externally validate three primary subarachnoid hemorrhage (pSAH) identification models.

Study design and setting: We evaluated three models that identify pSAH using recursive partitioning (A), logistic regression (B), and a prevalence-adjusted logistic regression(C), respectively. Blinded chart review and/or linkage to existing registries determined pSAH status. We included all patients aged ≥18 in four participating center registries or whose discharge abstracts contained ≥1 administrative codes of interest between January 1, 2012 and December 31, 2013.

Results: A total of 3,262 of 193,190 admissions underwent chart review (n = 2,493) or registry linkage (n = 769). A total of 657 had pSAH confirmed (20·1% sample, 0·34% admissions). The sensitivity, specificity, and positive predictive value (PPV) were as follows: i) model A: 98·3% (97·0-99·2), 53·5% (51·5-55·4), and 34·8% (32·6-37·0); ii) model B (score ≥6): 98·0% (96·6-98·9), 47·4% (45·5-49·4), and 32·0% (30·0-34·1); and iii) model C (score ≥2): 95·7% (93·9-97·2), 85·5% (84·0-86·8), and 62·3 (59·3-65·3), respectively. Model C scores of 0, 1, 2, 3, or 4 had probabilities of 0·5% (0·2-1·5), 1·5% (1·0-2·2), 24·8% (21·0-29·0), 90·0% (86·8-92·0), and 97·8% (88·7-99·6), without significant difference between centers (P = 0·86). The PPV of the International Classification of Diseases code (I60) was 63·0% (95% confidence interval: 60·0-66·0).

Conclusions: All three models were highly sensitive for pSAH. Model C could be used to adjust for misclassification bias.

Keywords: Cerebral aneurysm; Epidemiology; Health administrative data; International classification of diseases; Subarachnoid hemorrhage; Validation studies.

Publication types

Comparative Study

MeSH terms

Adult
Algorithms
Bias
Canada / epidemiology
Databases, Factual
Hospitalization / statistics & numerical data
Humans
International Classification of Diseases / standards*
Logistic Models
Patient Discharge / statistics & numerical data*
Predictive Value of Tests
Prevalence
Probability
Registries / statistics & numerical data
Retrospective Studies
Sensitivity and Specificity
Subarachnoid Hemorrhage / classification*
Subarachnoid Hemorrhage / diagnosis
Subarachnoid Hemorrhage / epidemiology*
Validation Studies as Topic