Validation of a Classification Algorithm for Chronic Kidney Disease Based on Health Information Systems

Ferraro, Pietro Manuel; Agabiti, Nera; Angelici, Laura; Cascini, Silvia; Bargagli, Anna Maria; Davoli, Marina; Gambaro, Giovanni; Marino, Claudia

doi:10.3390/jcm11102711

Cited by 3 publications

(1 citation statement)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The crude prevalence rate of CKD in the Lazio region was estimated at 1.76% (95%CI 1.75, 1.78). When applied to patients at Gemelli Hospital, an academic medical centre in Rome, the prevalence was estimated at 8.8% (95%CI 8.5–9.1) [ 38 ]. A recent French study used machine learning to identify patients with CKD based on a 1/97th representative sample of the general French population [ 39 ].…”

Section: Discussionmentioning

confidence: 99%

Prevalence of chronic kidney disease in France: methodological considerations and pitfalls with the use of Health claims databases

Couchoud,

Raffray,

Lassalle

et al. 2024

Clinical Kidney Journal

View full text Add to dashboard Cite

Background Health policy-making require careful assessment of CKD epidemiology to develop efficient and cost-effective care strategies. The aim of the present study was to use the RENALGO-EXPERT algorithm to estimate the global prevalence of CKD in France. Methods An expert group developed the RENALGO-EXPERT algorithm based on healthcare consumption. This algorithm has been applied to the French National Health claims database (SNDS), where no biological test findings are available in order to estimate a national CKD prevalence for the years 2018–2021. The CONSTANCES cohort (+ 219 000 adults aged 18–69 with one CKD-EPI eGFR) was used to discuss the limit of using health claims data. Results Between 2018 and 2021, the estimated prevalence in the SNDS increased from 8.1% to 10.5%. The RENALGO-EXPERT algorithm identified 4.5% of the volunteers in the CONSTANCES as CKD. The RENALGO-EXPERT algorithm had a PPV of 6.2% and NPV of 99.1% to detect an eGFR<60 ml/min/1.73m². Half of 252 false positive cases (ALGO +, eGFR > 90) had been diagnosed with kidney disease during hospitalization, and the other half based on healthcare consumption suggestive of a ‘high-risk’ profile. 95% of the 1661 false negatives (ALGO -, eGFR < 60) had an eGFR between 45 and 60 ml/min, ½ had medication and 2/3 a biological exams possibly linked to CKD. Half of them had a hospital stay during the period but none had a diagnosis of kidney disease. Conclusions Our result is in accordance with other estimations of CKD prevalence in the general population. Analysis of diverging cases (FP and FN) suggests using health claims data has inherent limitations. Such algorithm is able to identify patients whose care pathway is close to the usual and specific CKD pathways. It does not identify patients who have not been diagnosed or whose care is inappropriate or at early stage with stable GFR.

show abstract

Section: Discussionmentioning

confidence: 99%

Prevalence of chronic kidney disease in France: methodological considerations and pitfalls with the use of Health claims databases

Couchoud,

Raffray,

Lassalle

et al. 2024

Clinical Kidney Journal

View full text Add to dashboard Cite

show abstract

New Landmarks to Slow the Progression of Chronic Kidney Disease

Simonini

Vezzoli

2022

JCM

View full text Add to dashboard Cite

show abstract

Socioeconomic Inequalities Worsen the Risk of Death in CKD: A Population-Based Cohort Study in Italy

Giaccari,

Marino,

Ferraro

et al. 2024

Kidney360

View full text Add to dashboard Cite

Background: Few studies have explored the impact of socioeconomic position on chronic kidney disease (CKD). This study aims to fill this gap using a large Italian cohort of CKD patients. Methods: We analyzed a cohort of incident CKD cases from the Lazio regional Health Information System from 1 January 2012 to 31 December 2021. We used the deprivation index (DI), a 5-category census-block indicator that integrates several dimensions of disadvantage. The outcomes were mortality and end-stage kidney disease (ESKD). We characterized the health status of patients in the two years before CKD identification and followed each subject from the index date to the end of follow-up, i.e., the date of the outcome, of emigration, or 31 December 2022, whichever came first. We used Cox proportional hazard models to investigate the association between DI and outcomes (HR, 95% CI). Results: From 2012 to 2021, 127,457 new cases (55.9% men) were diagnosed. The average age was 72.2 (± 13.7) for men and 74.4 (± 14.8) for women. During an average follow-up of 4.3 years (± 3.2), 57,158 patients (45%) died, and 5,994 developed ESKD (5%). The age-adjusted association between DI and mortality was higher in men than in women (p-value interaction = 0.02), HRs for the extreme categories of DI (very high vs. very low) were 1.16, 95% CI 1.12-1.21 for men, and 1.08, 95% CI 1.04-1.13, for women). There was no evidence of association between DI and ESKD. Conclusions: In this population, socioeconomic disadvantage is associated with a higher risk of death but not of ESKD in CKD patients.

show abstract

Validation of a Classification Algorithm for Chronic Kidney Disease Based on Health Information Systems

Cited by 3 publications

References 18 publications

Prevalence of chronic kidney disease in France: methodological considerations and pitfalls with the use of Health claims databases

Prevalence of chronic kidney disease in France: methodological considerations and pitfalls with the use of Health claims databases

New Landmarks to Slow the Progression of Chronic Kidney Disease

Socioeconomic Inequalities Worsen the Risk of Death in CKD: A Population-Based Cohort Study in Italy

Contact Info

Product

Resources

About