Literature DB >> 28495862

The Diagnosis-Wide Landscape of Hospital-Acquired AKI.

Anne-Sophie Jannot1,2,3,4, Anita Burgun1,2,3,4, Eric Thervet2,3,5, Nicolas Pallet6,3,5,7.   

Abstract

BACKGROUND AND OBJECTIVES: The exploration of electronic hospital records offers a unique opportunity to describe in-depth the prevalence of conditions associated with diagnoses at an unprecedented level of comprehensiveness. We used a diagnosis-wide approach, adapted from phenome-wide association studies (PheWAS), to perform an exhaustive analysis of all diagnoses associated with hospital-acquired AKI (HA-AKI) in a French urban tertiary academic hospital over a period of 10 years. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We retrospectively extracted all diagnoses from an i2b2 (Informatics for Integrating Biology and the Bedside) clinical data warehouse for patients who stayed in this hospital between 2006 and 2015 and had at least two plasma creatinine measurements performed during the first week of their stay. We then analyzed the association between HA-AKI and each International Classification of Diseases (ICD)-10 diagnostic category to draw a comprehensive picture of diagnoses associated with AKI. Hospital stays for 126,736 unique individuals were extracted.
RESULTS: Hemodynamic impairment and surgical procedures are the main factors associated with HA-AKI and five clusters of diagnoses were identified: sepsis, heart diseases, polytrauma, liver disease, and cardiovascular surgery. The ICD-10 code corresponding to AKI (N17) was recorded in 30% of the cases with HA-AKI identified, and in this situation, 20% of the diagnoses associated with HA-AKI corresponded to kidney diseases such as tubulointerstitial nephritis, necrotizing vasculitis, or myeloma cast nephropathy. Codes associated with HA-AKI that demonstrated the greatest increase in prevalence with time were related to influenza, polytrauma, and surgery of neoplasms of the genitourinary system.
CONCLUSIONS: Our approach, derived from PheWAS, is a valuable way to comprehensively identify and classify all of the diagnoses and clusters of diagnoses associated with HA-AKI. Our analysis delivers insights into how diagnoses associated with HA-AKI evolved over time. On the basis of ICD-10 codes, HA-AKI appears largely underestimated in this academic hospital.
Copyright © 2017 by the American Society of Nephrology.

Entities:  

Keywords:  Acute Kidney Injury; Heart Diseases; Hemodynamics; Hospital Records; Humans; Influenza, Human; International Classification of Diseases; Length of Stay; Liver Diseases; Multiple Trauma; Neoplasms; Nephritis, Interstitial; Prevalence; Retrospective Studies; Sepsis; Urogenital System; acute renal failure; clinical nephrology; creatinine; hospitalization; vasculitis

Mesh:

Substances:

Year:  2017        PMID: 28495862      PMCID: PMC5460713          DOI: 10.2215/CJN.10981016

Source DB:  PubMed          Journal:  Clin J Am Soc Nephrol        ISSN: 1555-9041            Impact factor:   8.237


  22 in total

1.  Data integration of structured and unstructured sources for assigning clinical codes to patient stays.

Authors:  Elyne Scheurwegs; Kim Luyckx; Léon Luyten; Walter Daelemans; Tim Van den Bulcke
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2.  External phenome analysis enables a rational federated query strategy to detect changing rates of treatment-related complications associated with multiple myeloma.

Authors:  Jeremy L Warner; Gil Alterovitz; Kelly Bodio; Robin M Joyce
Journal:  J Am Med Inform Assoc       Date:  2013-03-20       Impact factor: 4.497

3.  Acute kidney injury, mortality, length of stay, and costs in hospitalized patients.

Authors:  Glenn M Chertow; Elisabeth Burdick; Melissa Honour; Joseph V Bonventre; David W Bates
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5.  Identifying phenotypic signatures of neuropsychiatric disorders from electronic medical records.

Authors:  Svetlana Lyalina; Bethany Percha; Paea LePendu; Srinivasan V Iyer; Russ B Altman; Nigam H Shah
Journal:  J Am Med Inform Assoc       Date:  2013-08-16       Impact factor: 4.497

Review 6.  Mining electronic health records: towards better research applications and clinical care.

Authors:  Peter B Jensen; Lars J Jensen; Søren Brunak
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Authors:  Mary Regina Boland; George Hripcsak; David J Albers; Ying Wei; Adam B Wilcox; Jin Wei; Jianhua Li; Steven Lin; Michael Breene; Ronnie Myers; John Zimmerman; Panos N Papapanou; Chunhua Weng
Journal:  J Clin Periodontol       Date:  2013-03-15       Impact factor: 8.728

8.  PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations.

Authors:  Joshua C Denny; Marylyn D Ritchie; Melissa A Basford; Jill M Pulley; Lisa Bastarache; Kristin Brown-Gentry; Deede Wang; Dan R Masys; Dan M Roden; Dana C Crawford
Journal:  Bioinformatics       Date:  2010-03-24       Impact factor: 6.937

9.  Combining free text and structured electronic medical record entries to detect acute respiratory infections.

Authors:  Sylvain DeLisle; Brett South; Jill A Anthony; Ericka Kalp; Adi Gundlapallli; Frank C Curriero; Greg E Glass; Matthew Samore; Trish M Perl
Journal:  PLoS One       Date:  2010-10-14       Impact factor: 3.240

10.  False-Positive Rate of AKI Using Consensus Creatinine-Based Criteria.

Authors:  Jennie Lin; Hilda Fernandez; Michael G S Shashaty; Dan Negoianu; Jeffrey M Testani; Jeffrey S Berns; Chirag R Parikh; F Perry Wilson
Journal:  Clin J Am Soc Nephrol       Date:  2015-09-03       Impact factor: 8.237

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Journal:  Dtsch Arztebl Int       Date:  2019-03-01       Impact factor: 5.594

Review 2.  Phenotyping of Acute Kidney Injury: Beyond Serum Creatinine.

Authors:  Dennis G Moledina; Chirag R Parikh
Journal:  Semin Nephrol       Date:  2018-01       Impact factor: 5.299

3.  Use of a hospital administrative database to identify and characterize community-acquired, hospital-acquired and drug-induced acute kidney injury.

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4.  Construction of a Glycaemia-Based Signature for Predicting Acute Kidney Injury in Ischaemic Stroke Patients after Endovascular Treatment.

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5.  Clinical and Pharmacological Aspects of Hospital-Acquired Acute Kidney Injuries Outside the Intensive Care Unit: A Phenome-Wide Association Study.

Authors:  Camille Nevoret; Anne-Sophie Jannot; Nicolas Pallet
Journal:  Kidney Dis (Basel)       Date:  2019-08-06

Review 6.  The use of diagnostic tools for pediatric AKI: applying the current evidence to the bedside.

Authors:  Dana Fuhrman
Journal:  Pediatr Nephrol       Date:  2021-01-25       Impact factor: 3.714

7.  Female sex reduces the risk of hospital-associated acute kidney injury: a meta-analysis.

Authors:  Joel Neugarten; Ladan Golestaneh
Journal:  BMC Nephrol       Date:  2018-11-08       Impact factor: 2.388

8.  Statins for primary prevention of cardiovascular disease and the risk of acute kidney injury.

Authors:  Joël Coste; Alexandre Karras; Annie Rudnichi; Rosemary Dray-Spira; Jacques Pouchot; Philippe Giral; Mahmoud Zureik
Journal:  Pharmacoepidemiol Drug Saf       Date:  2019-09-13       Impact factor: 2.890

9.  Incidence and impact on outcomes of acute kidney injury after a stroke: a systematic review and meta-analysis.

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10.  Health Care Analytics With Time-Invariant and Time-Variant Feature Importance to Predict Hospital-Acquired Acute Kidney Injury: Observational Longitudinal Study.

Authors:  Horng-Ruey Chua; Kaiping Zheng; Anantharaman Vathsala; Kee-Yuan Ngiam; Hui-Kim Yap; Liangjian Lu; Ho-Yee Tiong; Amartya Mukhopadhyay; Graeme MacLaren; Shir-Lynn Lim; K Akalya; Beng-Chin Ooi
Journal:  J Med Internet Res       Date:  2021-12-24       Impact factor: 5.428

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