Benazir Hodzic-Santor BA , Michael Colacci MD , Afsaneh Raissi BHSc , Prachi Ray HBSc , Amol A. Verma MD, MPhil , Fahad Razak MD, MSc , Derek R. MacFadden MD, ScD , Tor Biering-Sørensen MD, MPH, MSc, PhD , Kristoffer Grundtvig Skaarup MD , Shohinee Sarma MD, MPH , Michael Fralick MD, PhD
{"title":"验证糖尿病酮症酸中毒国际疾病分类-10代码的诊断准确性水平:一项多中心横断面研究","authors":"Benazir Hodzic-Santor BA , Michael Colacci MD , Afsaneh Raissi BHSc , Prachi Ray HBSc , Amol A. Verma MD, MPhil , Fahad Razak MD, MSc , Derek R. MacFadden MD, ScD , Tor Biering-Sørensen MD, MPH, MSc, PhD , Kristoffer Grundtvig Skaarup MD , Shohinee Sarma MD, MPH , Michael Fralick MD, PhD","doi":"10.1016/j.jcjd.2024.01.006","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><p>International Classification of Diseases (ICD) codes are commonly used to identify cases of diabetic ketoacidosis (DKA) in health services research, but they have not been validated. Our aim in this study was to assess the accuracy of ICD, 10th revision (ICD-10) diagnosis codes for DKA.</p></div><div><h3>Methods</h3><p>We conducted a multicentre, cross-sectional study using data from 5 hospitals in Ontario, Canada. Each hospitalization event has a single most responsible diagnosis code. We identified all hospitalizations assigned diagnosis codes for DKA. A true case of DKA was defined using laboratory values (serum bicarbonate ≤18 mmol/L, arterial pH ≤7.3, anion gap ≥14 mEq/L, and presence of ketones in urine or blood). Chart review was conducted to validate DKA if laboratory values were missing or the diagnosis of DKA was unclear. Outcome measures included positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity of ICD-10 codes in patients with laboratory-defined DKA.</p></div><div><h3>Results</h3><p>We identified 316,517 hospitalizations. Among these, 312,948 did not have an ICD-10 diagnosis code for DKA and 3,569 had an ICD-10 diagnosis code for DKA. Using a combination of laboratory and chart review, we identified that the overall PPV was 67.0%, the NPV was 99.7%, specificity was 99.6%, and sensitivity was 74.9%. When we restricted our analysis to hospitalizations in which DKA was the most responsible discharge diagnosis (n=3,374 [94.5%]), the test characteristics were PPV 69.8%, NPV 99.7%, specificity 99.7%, and sensitivity 71.9%.</p></div><div><h3>Conclusion</h3><p>ICD-10 codes can identify patients with DKA among those admitted to general internal medicine.</p></div>","PeriodicalId":9565,"journal":{"name":"Canadian Journal of Diabetes","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Validation of the Diagnostic Accuracy Levels of International Classification of Diseases, 10th Revision Codes for Diabetic Ketoacidosis: A Multicentre, Cross-sectional Study of Adults\",\"authors\":\"Benazir Hodzic-Santor BA , Michael Colacci MD , Afsaneh Raissi BHSc , Prachi Ray HBSc , Amol A. Verma MD, MPhil , Fahad Razak MD, MSc , Derek R. MacFadden MD, ScD , Tor Biering-Sørensen MD, MPH, MSc, PhD , Kristoffer Grundtvig Skaarup MD , Shohinee Sarma MD, MPH , Michael Fralick MD, PhD\",\"doi\":\"10.1016/j.jcjd.2024.01.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objectives</h3><p>International Classification of Diseases (ICD) codes are commonly used to identify cases of diabetic ketoacidosis (DKA) in health services research, but they have not been validated. Our aim in this study was to assess the accuracy of ICD, 10th revision (ICD-10) diagnosis codes for DKA.</p></div><div><h3>Methods</h3><p>We conducted a multicentre, cross-sectional study using data from 5 hospitals in Ontario, Canada. Each hospitalization event has a single most responsible diagnosis code. We identified all hospitalizations assigned diagnosis codes for DKA. A true case of DKA was defined using laboratory values (serum bicarbonate ≤18 mmol/L, arterial pH ≤7.3, anion gap ≥14 mEq/L, and presence of ketones in urine or blood). Chart review was conducted to validate DKA if laboratory values were missing or the diagnosis of DKA was unclear. Outcome measures included positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity of ICD-10 codes in patients with laboratory-defined DKA.</p></div><div><h3>Results</h3><p>We identified 316,517 hospitalizations. Among these, 312,948 did not have an ICD-10 diagnosis code for DKA and 3,569 had an ICD-10 diagnosis code for DKA. Using a combination of laboratory and chart review, we identified that the overall PPV was 67.0%, the NPV was 99.7%, specificity was 99.6%, and sensitivity was 74.9%. When we restricted our analysis to hospitalizations in which DKA was the most responsible discharge diagnosis (n=3,374 [94.5%]), the test characteristics were PPV 69.8%, NPV 99.7%, specificity 99.7%, and sensitivity 71.9%.</p></div><div><h3>Conclusion</h3><p>ICD-10 codes can identify patients with DKA among those admitted to general internal medicine.</p></div>\",\"PeriodicalId\":9565,\"journal\":{\"name\":\"Canadian Journal of Diabetes\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Canadian Journal of Diabetes\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1499267124000224\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Canadian Journal of Diabetes","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1499267124000224","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Validation of the Diagnostic Accuracy Levels of International Classification of Diseases, 10th Revision Codes for Diabetic Ketoacidosis: A Multicentre, Cross-sectional Study of Adults
Objectives
International Classification of Diseases (ICD) codes are commonly used to identify cases of diabetic ketoacidosis (DKA) in health services research, but they have not been validated. Our aim in this study was to assess the accuracy of ICD, 10th revision (ICD-10) diagnosis codes for DKA.
Methods
We conducted a multicentre, cross-sectional study using data from 5 hospitals in Ontario, Canada. Each hospitalization event has a single most responsible diagnosis code. We identified all hospitalizations assigned diagnosis codes for DKA. A true case of DKA was defined using laboratory values (serum bicarbonate ≤18 mmol/L, arterial pH ≤7.3, anion gap ≥14 mEq/L, and presence of ketones in urine or blood). Chart review was conducted to validate DKA if laboratory values were missing or the diagnosis of DKA was unclear. Outcome measures included positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity of ICD-10 codes in patients with laboratory-defined DKA.
Results
We identified 316,517 hospitalizations. Among these, 312,948 did not have an ICD-10 diagnosis code for DKA and 3,569 had an ICD-10 diagnosis code for DKA. Using a combination of laboratory and chart review, we identified that the overall PPV was 67.0%, the NPV was 99.7%, specificity was 99.6%, and sensitivity was 74.9%. When we restricted our analysis to hospitalizations in which DKA was the most responsible discharge diagnosis (n=3,374 [94.5%]), the test characteristics were PPV 69.8%, NPV 99.7%, specificity 99.7%, and sensitivity 71.9%.
Conclusion
ICD-10 codes can identify patients with DKA among those admitted to general internal medicine.
期刊介绍:
The Canadian Journal of Diabetes is Canada''s only diabetes-oriented, peer-reviewed, interdisciplinary journal for diabetes health-care professionals.
Published bimonthly, the Canadian Journal of Diabetes contains original articles; reviews; case reports; shorter articles such as Perspectives in Practice, Practical Diabetes and Innovations in Diabetes Care; Diabetes Dilemmas and Letters to the Editor.