Real-time monitoring of progression towards renal failure in primary care patients

Biostatistics

Volumn 16, Issue 3, 2015, Pages 522-536

  Diggle, Peter J ^a,b   Sousa, Inês ^c   Asar, Özgür ^a,b  

^a LANCASTER UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF LIVERPOOL   (United Kingdom)

^c UNIVERSITY OF MINHO   (Portugal)

Author keywords

Dynamic modeling; Kidney failure; Longitudinal data analysis; Non stationarity; Real time prediction; Renal medicine; Stochastic processes.

Indexed keywords

ADOLESCENT; ADULT; AGED; BIOLOGICAL MODEL; BIOSTATISTICS; COMPUTER SIMULATION; COMPUTER SYSTEM; DISEASE COURSE; EARLY DIAGNOSIS; FEMALE; GLOMERULUS FILTRATION RATE; HUMAN; KIDNEY FAILURE, CHRONIC; LONGITUDINAL STUDY; MALE; MARKOV CHAIN; MIDDLE AGED; PATHOPHYSIOLOGY; PATIENT REFERRAL; PRIMARY HEALTH CARE; STATISTICAL MODEL; VERY ELDERLY; YOUNG ADULT;

ADOLESCENT; ADULT; AGED; AGED, 80 AND OVER; BIOSTATISTICS; COMPUTER SIMULATION; COMPUTER SYSTEMS; DISEASE PROGRESSION; EARLY DIAGNOSIS; FEMALE; GLOMERULAR FILTRATION RATE; HUMANS; KIDNEY FAILURE, CHRONIC; LONGITUDINAL STUDIES; MALE; MIDDLE AGED; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PRIMARY HEALTH CARE; REFERRAL AND CONSULTATION; STOCHASTIC PROCESSES; YOUNG ADULT;

EID: 84936765021     PISSN: 14654644     EISSN: 14684357     Source Type: Journal    
DOI: 10.1093/biostatistics/kxu053     Document Type: Article

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