Diagnostic validity and solute-corrected prevalence for hyponatremia and hypernatremia among 1 813 356 admissions

Clin Kidney J. 2024 Oct 24;17(12):sfae319. doi: 10.1093/ckj/sfae319. eCollection 2024 Dec.

Abstract

Background and hypothesis: We aimed to evaluate the diagnostic validity of the International Classification of Diseases, 10th Revision (ICD-10) codes for hyponatremia and hypernatremia, using a database containing laboratory data. We also aimed to clarify whether corrections for blood glucose, triglyceride, and total protein may affect the prevalence and the diagnostic validity.

Methods: We retrospectively identified admissions with laboratory values using a Japanese hospital-based database. We calculated the sensitivity, specificity, and positive/negative predictive values of recorded ICD-10-based diagnoses of hyponatremia (E87.1) and hypernatremia (E87.2), using serum sodium measurements during hospitalization (<135 and >145 mmol/l, respectively) as the reference standard. We also performed analyses with corrections of sodium concentrations for blood glucose, triglyceride, and total protein.

Results: We identified 1 813 356 hospitalizations, including 419 470 hyponatremic and 132 563 hypernatremic cases based on laboratory measurements, and 18 378 hyponatremic and 2950 hypernatremic cases based on ICD-10 codes. The sensitivity, specificity, positive predictive value, and negative predictive value of the ICD-10 codes were 4.1%, 99.9%, 92.5%, and 77.6%, respectively, for hyponatremia and 2.2%, >99.9%, 96.5%, and 92.8%, respectively, for hypernatremia. Corrections for blood glucose, triglyceride, and total protein did not largely alter diagnostic values, although prevalence changed especially after corrections for blood glucose and total protein.

Conclusions: The ICD-10 diagnostic codes showed low sensitivity, high specificity, and high positive predictive value for identifying hyponatremia and hypernatremia. Corrections for glucose or total protein did not affect diagnostic values but would be necessary for accurate prevalence calculation.

Keywords: clinical epidemiology; database study; electrolytes; solute correction; validation study.