ALgorithm validation for Peripheral artery disease diagnosis in frEnch
hospital discharge database (The ALPES study)
Abstract
Objective: Peripheral artery disease (PAD) of the lower
extremities is a global health concern linked to substantial morbidity
and mortality. Nevertheless, research on PAD within health
administrative databases remains limited. This study aimed to develop
and validate algorithms for the identification of patients with PAD
using French health administrative data. Methods: The study was
conducted at Bordeaux University Hospital from January 2018 to December
2019. Four algorithms combining International Classification of
Diseases, Tenth Revision (ICD-10) codes and procedural codes were
created (1: i70.2 code alone, 2: one diagnosis procedural code, 3: two
diagnosis procedural codes, 4: one procedural code for
revascularization/non-traumatic amputation. PAD status was confirmed
through expert review of electronic medical records using consensus
criteria. Sensitivity, specificity, and predictive values were assessed
for each algorithm. Results: Among 700 randomly selected
patients, 12% were diagnosed with PAD. The first algorithm, using the
ICD-10 code i70.2, had the highest accuracy (sensitivity: 93%, 95%CI
(confidence interval)85-97), specificity: 97%, 95%CI(95-98)). Other
algorithms did not significantly improve these metrics.
Discussion: This study allows considering that in-hospital
coding is reliable for the identification of patients with symptomatic
lower limb PAD in health administrative databases. The i70.2 code alone
displayed the best performance for the identification of inpatient PAD.
International validation studies for PAD algorithms would be needed to
ensure that the proposed identification strategy presents with
acceptable performances in other settings.