Using an artificial intelligence tool incorporating natural language processing to identify patients with a diagnosis of ANCA-associated vasculitis in electronic health records

Background: Because anti-neutrophil cytoplasmatic antibody (ANCA)-associated vasculitis (AAV) is a rare, lifethreatening, auto-immune disease, conducting research is difficult but essential. A long-lasting challenge is to identify rare AAV patients within the electronic-health-record (EHR)-system to facilitate real-world research. Artificial intelligence (AI)-search tools using natural language processing (NLP) for text-mining are increasingly postulated as a solution.Methods: We employed an AI-tool that combined text-mining with NLP-based exclusion, to accurately identify rare AAV patients within large EHR-systems (>2.000.000 records). We developed an identification method in an academic center with an established AAV-training set (n = 203) and validated the method in a non-academic center with an AAV-validation set (n = 84). To assess accuracy anonymized patient records were manually reviewed.Results: Based on an iterative process, a text-mining search was developed on disease description, laboratory measurements, medication and specialisms. In the training center, 608 patients were identified with a sensitivity of 97.0 % (95%CI [93.7, 98.9]) and positive predictive value (PPV) of 56.9 % (95%CI [52.9, 60.1]). NLP-based exclusion resulted in 444 patients increasing PPV to 77.9 % (95%CI [73.7, 81.7]) while sensitivity remained 96.3 % (95%CI [93.8, 98.0]). In the validation center, text-mining identified 333 patients (sensitivity 97.6 % (95%CI [91.6, 99.7]), PPV 58.2 % (95%CI [52.8, 63.6])) and NLP-based exclusion resulted in 223 patients, increasing PPV to 86.1 % (95%CI [80.9, 90.4]) with 98.0 % (95%CI [94.9, 99.4]) sensitivity. Our identification method outperformed ICD-10-coding predominantly in identifying MPO+ and organ-limited AAV patients.Conclusions: Our study highlights the advantages of implementing AI, notably NLP, to accurately identify rare AAV patients within large EHR-systems and demonstrates the applicability and transportability. Therefore, this method can reduce efforts to identify AAV patients and accelerate real-world research, while avoiding bias by ICD-10-coding.Nephrolog

The effect of online hemodiafiltration on infections: Results from the CONvective TRAnsport STudy

Background: Hemodialysis (HD) patients have a high risk of infections. The uremic milieu has a negative impact on several immune responses. Online hemodiafiltration (HDF) may reduce the risk of infections by ameliorating the uremic milieu through enhanced clearance of middle molecules. Since there are few data on infectious outcomes in HDF, we compared the effects of HDF with low-flux HD on the incidence and type of infections. Patients and Methods: We used data of the 714 HD patients (age 64 ±14, 62% men, 25% Diabetes Mellitus, 7% catheters) participating in the CONvective TRAnsport STudy (CONTRAST), a randomized controlled trial evaluating the effect of HDF as compared to low-flux HD. The events were adjudicated by an independent event committee. The risk of infectious events was compared with Cox regression for repeated events and Cox proportional hazard models. The distributions of types of infection were compared between the groups. Results: Thirty one percent of the patients suffered from one or more infections leading to hospitalization during the study (median follow-up 1.96 years). The risk for infections during the entire follow-up did not differ significantly between treatment arms (HDF 198 and HD 169 infections in 800 and 798 person-years respectively, hazard ratio HDF vs. HD 1.09 (0.88-1.34), P = 0.42. No difference was found in the occurrence of the first infectious event (either fatal, nonfatal or type specific). Of all infections, respiratory infections (25% in HDF, 28% in HD) were most common, followed by skin/musculoskeletal infections (21% in HDF, 13% in HD). Conclusions: HDF as compared to HD did not result in a reduced risk of infections, larger studies are needed to confirm our findings. Trial Registration: ClinicalTrials.gov NCT00205556

Online Hemodiafiltration: treatment optimization and effects on biochemical parameters

Online hemodiafiltration is a promising dialysis technique with superior removal of uremic toxins as compared to conventional hemodialysis. Whether hemodiafiltration leads to improved clinical outcome is currently under investigation in the Dutch CONvective TRAnsport STudy (CONTRAST). In the first part of this thesis, the design and rationale of the CONTRAST study is described extensively. All data presented in this thesis originates from the CONTRAST study. State of the art treatment with online hemodiafiltration requires high convective volumes and sustained high microbiological quality of dialysis solutions. In the second part of this thesis, factors determining convective volumes in clinical practice were identified, to be able to establish highest possible volumes. In addition, the microbiological quality of dialysis solutions was evaluated in a sample of ten dialysis centers. In the third part of this thesis, the effects of hemodiafiltration on biochemical parameters (phosphate and beta-2-microglobulin) were evaluated. Residual kidney function appeared an important influencing factor of these parameters and was evaluated in more detail. In the last part of this thesis, practical recommendations to optimize convective volumes in clinical practice are provided. Furthermore, benefits and potential drawbacks of hemodiafiltration are summarized. Results from randomized controlled trials such as CONTRAST are warranted to provide conclusive evidence on the role of online hemodiafiltration to improve the prognosis of chronic hemodialysis patients

Left Ventricular Mass in Dialysis Patients, Determinants and Relation with Outcome. Results from the COnvective TRansport STudy (CONTRAST)

Contains fulltext : 138535.pdf (publisher's version ) (Open Access)BACKGROUND AND OBJECTIVES: Left ventricular mass (LVM) is known to be related to overall and cardiovascular mortality in end stage kidney disease (ESKD) patients. The aims of the present study are 1) to determine whether LVM is associated with mortality and various cardiovascular events and 2) to identify determinants of LVM including biomarkers of inflammation and fibrosis. DESIGN SETTING PARTICIPANTS & MEASUREMENTS: Analysis was performed with data of 327 ESKD patients, a subset from the CONvective TRAnsport STudy (CONTRAST). Echocardiography was performed at baseline. Cox regression analysis was used to assess the relation of LVM tertiles with clinical events. Multivariable linear regression models were used to identify factors associated with LVM. RESULTS: Median age was 65 (IQR: 54-73) years, 203 (61%) were male and median LVM was 227 (IQR: 183-279) grams. The risk of all-cause mortality (hazard ratio (HR) = 1.73, 95% CI: 1.11-2.99), cardiovascular death (HR = 3.66, 95% CI: 1.35-10.05) and sudden death (HR = 13.06; 95% CI: 6.60-107) was increased in the highest tertile (>260grams) of LVM. In the multivariable analysis positive relations with LVM were found for male gender (B = 38.8+/-10.3), residual renal function (B = 17.9+/-8.0), phosphate binder therapy (B = 16.9+/-8.5), and an inverse relation for a previous kidney transplantation (B = -41.1+/-7.6) and albumin (B = -2.9+/-1.1). Interleukin-6 (Il-6), high-sensitivity C-reactive protein (hsCRP), hepcidin-25 and connective tissue growth factor (CTGF) were not related to LVM. CONCLUSION: We confirm the relation between a high LVM and outcome and expand the evidence for increased risk of sudden death. No relationship was found between LVM and markers of inflammation and fibrosis. TRIAL REGISTRATION: Controlled-Trials.com ISRCTN38365125

The Effect of Online Hemodiafiltration on Infections: Results from the CONvective TRAnsport STudy

Contains fulltext : 152801.PDF (publisher's version ) (Open Access)BACKGROUND: Hemodialysis (HD) patients have a high risk of infections. The uremic milieu has a negative impact on several immune responses. Online hemodiafiltration (HDF) may reduce the risk of infections by ameliorating the uremic milieu through enhanced clearance of middle molecules. Since there are few data on infectious outcomes in HDF, we compared the effects of HDF with low-flux HD on the incidence and type of infections. PATIENTS AND METHODS: We used data of the 714 HD patients (age 64 +/-14, 62% men, 25% Diabetes Mellitus, 7% catheters) participating in the CONvective TRAnsport STudy (CONTRAST), a randomized controlled trial evaluating the effect of HDF as compared to low-flux HD. The events were adjudicated by an independent event committee. The risk of infectious events was compared with Cox regression for repeated events and Cox proportional hazard models. The distributions of types of infection were compared between the groups. RESULTS: Thirty one percent of the patients suffered from one or more infections leading to hospitalization during the study (median follow-up 1.96 years). The risk for infections during the entire follow-up did not differ significantly between treatment arms (HDF 198 and HD 169 infections in 800 and 798 person-years respectively, hazard ratio HDF vs. HD 1.09 (0.88-1.34), P = 0.42. No difference was found in the occurrence of the first infectious event (either fatal, non-fatal or type specific). Of all infections, respiratory infections (25% in HDF, 28% in HD) were most common, followed by skin/musculoskeletal infections (21% in HDF, 13% in HD). CONCLUSIONS: HDF as compared to HD did not result in a reduced risk of infections, larger studies are needed to confirm our findings. TRIAL REGISTRATION: ClinicalTrials.gov NCT00205556

Protein-energy nutritional status and kidney disease-specific quality of life in hemodialysis patients

Objective: Health-related quality of life (HRQOL) is an important outcome in dialysis care. Previous research has related protein-energy nutritional status to generic HRQOL domains, but it is still not clear as to how it relates to HRQOL domains that are unique to hemodialysis patients. Therefore, our aim was to study the relation between protein-energy nutritional status and kidney disease-specific HRQOL domains in hemodialysis patients. Design: This was a cross-sectional study. Setting: This study was performed at multiple centers. Patients or Other Participants: We evaluated the first 590 hemodialysis patients who had enrolled in the Convective Transport Study. Determinants: We measured protein-energy nutritional status by using the Subjective Global Assessment, albumin, normalized nitrogen appearance, creatinine, body mass index, and cholesterol. Main Outcome Measure: HRQOL was assessed by using the Kidney Disease Quality Of Life-Short Form. Results: In all, 83% of the cohort was found to be well-nourished on the basis of the Subjective Global Assessment. Multiple nutritional parameters were positively related to the physical summary of generic HRQOL and to the following kidney disease-specific HRQOL scales: the effects of the kidney disease on daily life, the burden of the kidney disease, and overall health. Conclusions: This study showed that, even in predominantly well-nourished hemodialysis patients, protein-energy nutritional status was significantly related to kidney disease-specific HRQOL. (C) 2011 by the National Kidney Foundation, Inc. All rights reserved