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- W4366410150 abstract "Abstract Rationale and Background: Drug-related problems are an underdiagnosed and frequently forgotten diagnosis that accounts for a significant cut of medical expenses, morbidity, and mortality. Drug-induced kidney disease is a subsection of such problem and a major contributor to kidney disease which lacks major worldwide investigation. Objectives : Our main objective is to identify the predominant drugs associated with the main renal manifestations that clinicians deal with daily, allowing clinicians to identify and correctly approach drug-induced kidney disease. Methods: The authors will collect data from a major worldwide database that collects spontaneous drug-adverse reaction notifications. The statistical analysis will consider four different steps: 1) Univariable descriptive analysis, 2) Inferential analysis for two variables, 3) Classification analysis either with clustering techniques or with models in the format of decision trees, and 4) Interdependence analysis. To perform such statistical tests, IBM SPSS Statistics, version 28.0 and R language will be used. Discussion: Kidney-related manifestations or syndromes associated with drugs are extremely underdiagnosed but responsible for considerable iatrogenic consequences, either clinically or in costs. The majority of such manifestations are recoverable, and patients can recover with few or no consequences if the diagnosis is made in a timely manner, making the diagnosis of drug-induced kidney disease a highly impactable action. With this study, the authors aim to bring into light new data and information that will increase the recognition and improve the diagnosis of such conditions." @default.
- W4366410150 created "2023-04-21" @default.
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- W4366410150 date "2023-04-19" @default.
- W4366410150 modified "2023-09-25" @default.
- W4366410150 title "Kidney-related manifestations or syndromes associated with drugs: a protocol for a database study" @default.
- W4366410150 doi "https://doi.org/10.21203/rs.3.rs-2706427/v1" @default.
- W4366410150 hasPublicationYear "2023" @default.
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