AKI is a rapid and usually reversible impairment of kidney function that is life-threatening in the short term well described by the "Kidney Disease: Improving Global Outcomes - KDIGO" classification of 2012. Whatever etiology of acute renal failure, drug iatrogeny still has its place. Hospital data from the information systems medicalization program (PMSI) can be used for epidemiological research. No study has yet been performed on these data to assess drug-related AKI. However, it should be remembered that these databases were not originally designed for research purposes but for reimbursement of care. Therefore, before conducting a large-scale study, it remains important to determine the validity and representativeness of the codes used for coding the studied events. The objective of this project is therefore to validate the use of hospital coding to identify AKI.
Acute kidney injury (AKI) is a rapid and usually reversible impairment of kidney function that is life-threatening in the short term; the grades of which are defined by the KDIGO classification of 2012. Whatever etiology of acute renal failure, drug iatrogeny still has its place. Data literature indicate that AKI affects more than one in five adults worldwide while hospitalized, with an associated mortality rate above 20%. It constitutes a non-negligible part of hospitalizations when it is acquired in the community, and also causes prolongations of hospitalizations, and therefore an increase in the cost for the hospital. Hospital data from the information systems medicalization program (PMSI) is a device that is part of the reform of the French health system with the aim of reducing inequalities in resources between health establishments. Since 2007, it has been possible to link all discharge summaries for one patient. The diagnoses identified during hospitalization are coded according to the 10th edition of the International Classification of Diseases (ICD-10). The data from PMSI coding can be used for epidemiological research. The majority of studies were related to patients with chronic kidney disease, especially dialysis patients. No study has yet been performed on these data to assess drug-related AKI. However, it should be remembered that these databases were not originally designed for research purposes but for reimbursement of care. Therefore, before conducting a large-scale study, it remains important to determine the validity and representativeness of the codes used for coding the events to be studied.
Study Type
OBSERVATIONAL
Enrollment
498
CHU Amiens
Amiens, France
identification of AKIs by codes in the PMSI database
Time frame: two years
identification of drug-induced AKIs by codes in the PMSI database
Time frame: two years
Variation of performance of the codes according to the characteristics of the AKI
Time frame: two years
Variation of performance of the codes according to KDIGO grade
Time frame: two years
Variation of performance of the codes according to hospitalization service
Time frame: two years
Identification of the type of drugs involved in drug-induced AKI
Time frame: two years
incidence of drug-induced AKI
incidence of drug-induced AKI (community-based and hospital-induced AKI (AKI-AH))
Time frame: two years
Identification of AKI Risk factors
Time frame: two years
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