P0687DO ALL PATIENTS BENEFIT FROM MULTIDISCIPLINARY CHRONIC KIDNEY DISEASE CLINICS?

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Bhanu Prasad ◽  
Maryam Jafari ◽  
Lexis Gordon ◽  
Navdeep Tangri ◽  
Joanne Kappel

Abstract Background and Aims: Multidisciplinary clinics (MDC’s) were established in Canada to offer a variety of support systems (diabetes care, social support, easy access to pharmacists, dietitians, specialty trained nurses), to monitor and delay progression through timed lab investigations and visits in conjunction with the Nephrologist. The reasons for better outcomes have been identified as better education, focus on self-care, dietary interventions, timely transplant referrals, modality education, lower hospitalizations and mortality. Treating all patients with chronic kidney disease (CKD) as part of a multidisciplinary care team runs the risk of adding unwarranted labs, interventions, polypharmacy and costs. Kidney Failure Risk Equation (KFRE) uses routine laboratory and clinical data, to stratify patients into three risk categories (low, medium, and high risk) of progression. KFRE has been shown to accurately estimate progression to kidney failure in adults with CKD. The objectives of the study were to i) validate the KFRE in our CKD patients, ii) evaluate health care utilization of patients based on the risk of progression in our province, Saskatchewan. iii) identify the subgroup of patients that benefit most from follow up in MDC. Methods: We conducted a retrospective study on 1007 patients with CKD stages G3 and G4 in two CKD multidisciplinary clinics in the province of Saskatchewan, Canada (January 2004-December 2012). The predicted risk of kidney failure (low, medium high) for each patient was calculated using the 8-variable KFRE. Patients were followed for five years to validate the KFRE; data on initiation of dialysis or death was collected. Cost of delivery of care per patient per year in the CKD clinic was determined. Health care utilization was evaluated by measuring the number/cost of hospital admissions, cardiovascular and thoracic (CVT) surgery, non-nephrology specialist appointments, and medications. Results: There were more patients in G 3 (n= 533) than in G 4 (n=474). 313 (59%), 150 (28%), and 70 (13%) were in low, medium and high-risk categories for G 3 CKD. 275 (58%), 86 (18%), and 113 (24%) were in similar categories for G 4. The mean age (SD) was 71 (12.8) years. The number of patients > 65 years of age was 75%. 57% were men, mean GFR (mls/min/1.73m2) for G3 was 40 (7.8) and 23 (4) for G4. Of the G3 patients, 4% of low risk, 11% of the medium risk and 26% of the high risk progressed to dialysis by 5 years. In G 4 patients, 7% of low risk, 17% of medium risk and 48% of high risk progressed to dialysis over 2 years. These results validate the KFRE in our population. The cost of care per patient in MDC was $ 3800 (CAD) per year. There was a difference in the cost of medications, number and cost of (inpatient hospitalizations, cardiovascular surgeries, non-Nephrology specialist visits, and day surgeries) between low risk patients vs high risk patients in G4 patients. Conclusion: We performed a cost-effectiveness analysis of our MDC’s and show that very few patients at low-risk of progression advance to ESRD. They are also unlikely to benefit from intensive care management and better managed in primary care with advice from tertiary centres. Individual programs have significant opportunity to improve health care delivery by identifying the sub- groups that benefit the most from MDC based on the risk of progression to allow optimal utilization of resources. At $ 3800 (CAD) per patient, we suggest that MDC’s are best utilized by patients with medium and high risk of progression. Further, we show that patients that the low-risk patients were older, had fewer inpatient visits, had lesser drug costs, underwent fewer cardiovascular surgeries, had fewer day surgery visits, and fewer non-nephrology specialist visits. This is the first study to our knowledge that focuses on health care utilization based on the risk of disease progression rather than the stage of CKD.

Author(s):  
Bhanu Prasad ◽  
Meric Osman ◽  
Maryam Jafari ◽  
Lexis Gordon ◽  
Navdeep Tangri ◽  
...  

Background and objectivesPatients with CKD exhibit heterogeneity in their rates of progression to kidney failure. The kidney failure risk equation (KFRE) has been shown to accurately estimate progression to kidney failure in adults with CKD. Our objective was to determine health care utilization patterns of patients on the basis of their risk of progression.Design, setting, participants, & measurementsWe conducted a retrospective cohort study of adults with CKD and eGFR of 15–59 ml/min per 1.73 m2 enrolled in multidisciplinary CKD clinics in the province of Saskatchewan, Canada. Data were collected from January 1, 2004 to December 31, 2012 and followed for 5 years (December 31, 2017). We stratified patients by eGFR and risk of progression and compared the number and cost of hospital admissions, physician visits, and prescription drugs.ResultsIn total, 1003 adults were included in the study. Within the eGFR of 15–29 ml/min per 1.73 m2 group, the costs of hospital admissions, physician visits, and drug dispensations over the 5-year study period comparing high-risk patients with low-risk patients were (Canadian dollars) $89,265 versus $48,374 (P=0.008), $23,423 versus $11,231 (P<0.001), and $21,853 versus $16,757 (P=0.01), respectively. Within the eGFR of 30–59 ml/min per 1.73 m2 group, the costs of hospital admissions, physician visits, and prescription drugs were $55,944 versus $36,740 (P=0.10), $13,414 versus $10,370 (P=0.08), and $20,394 versus $14,902 (P=0.02) in high-risk patients in comparison with low-risk patients, respectively, for progression to kidney failure.ConclusionsIn patients with CKD and eGFR of 15–59 ml/min per 1.73 m2 followed in multidisciplinary clinics, the costs of hospital admissions, physician visits, and drugs were higher for patients at higher risk of progression to kidney failure by the KFRE compared with patients in the low-risk category. The high-risk group of patients with CKD and eGFR of 15–29 ml/min per 1.73 m2 had stronger association with hospitalizations costs, physician visits, and drug utilizations.


2021 ◽  
Vol 22 (3) ◽  
pp. 1075
Author(s):  
Luca Bedon ◽  
Michele Dal Bo ◽  
Monica Mossenta ◽  
Davide Busato ◽  
Giuseppe Toffoli ◽  
...  

Although extensive advancements have been made in treatment against hepatocellular carcinoma (HCC), the prognosis of HCC patients remains unsatisfied. It is now clearly established that extensive epigenetic changes act as a driver in human tumors. This study exploits HCC epigenetic deregulation to define a novel prognostic model for monitoring the progression of HCC. We analyzed the genome-wide DNA methylation profile of 374 primary tumor specimens using the Illumina 450 K array data from The Cancer Genome Atlas. We initially used a novel combination of Machine Learning algorithms (Recursive Features Selection, Boruta) to capture early tumor progression features. The subsets of probes obtained were used to train and validate Random Forest models to predict a Progression Free Survival greater or less than 6 months. The model based on 34 epigenetic probes showed the best performance, scoring 0.80 accuracy and 0.51 Matthews Correlation Coefficient on testset. Then, we generated and validated a progression signature based on 4 methylation probes capable of stratifying HCC patients at high and low risk of progression. Survival analysis showed that high risk patients are characterized by a poorer progression free survival compared to low risk patients. Moreover, decision curve analysis confirmed the strength of this predictive tool over conventional clinical parameters. Functional enrichment analysis highlighted that high risk patients differentiated themselves by the upregulation of proliferative pathways. Ultimately, we propose the oncogenic MCM2 gene as a methylation-driven gene of which the representative epigenetic markers could serve both as predictive and prognostic markers. Briefly, our work provides several potential HCC progression epigenetic biomarkers as well as a new signature that may enhance patients surveillance and advances in personalized treatment.


2018 ◽  
Vol 85 (1) ◽  
pp. 148-154 ◽  
Author(s):  
Anamaria J. Robles ◽  
Lucy Z. Kornblith ◽  
Carolyn M. Hendrickson ◽  
Benjamin M. Howard ◽  
Amanda S. Conroy ◽  
...  

2021 ◽  
Author(s):  
Rossella Murtas ◽  
Nuccia Morici ◽  
Chiara Cogliati ◽  
Massimo Puoti ◽  
Barbara Omazzi ◽  
...  

BACKGROUND The coronavirus disease 2019 (COVID-19) pandemic has generated a huge strain on the health care system worldwide. The metropolitan area of Milan, Italy was one of the most hit area in the world. OBJECTIVE Robust risk prediction models are needed to stratify individual patient risk for public health purposes METHODS Two predictive algorithms were implemented in order to foresee the probability of being a COVID-19 patient and the risk of being hospitalized. The predictive model for COVID-19 positivity was developed in 61.956 symptomatic patients, whereas the model for COVID-19 hospitalization was developed in 36.834 COVID-19 positive patients. Exposures considered were age, gender, comorbidities and symptoms associated with COVID-19 (vomiting, cough, fever, diarrhoea, myalgia, asthenia, headache, anosmia, ageusia, and dyspnoea). RESULTS The predictive models showed a good fit for predicting COVID-19 disease [AUC 72.6% (95% CI 71.6%-73.5%)] and hospitalization [AUC 79.8% (95% CI 78.6%-81%)]. Using these results, 118,804 patients with COVID-19 from October 25 to December 11, 2020 were stratified into low, medium and high risk for COVID-19 severity. Among the overall population, 67.030 (56%) were classified as low-risk, 43.886 (37%) medium-risk, and 7.888 (7%) high-risk, with 89% of the overall population being assisted at home, 9% hospitalized, and 2% dead. Among those assisted at home, most people (60%) were classified as low risk, whereas only 4% were classified at high risk. According to ordinal logistic regression, the OR of being hospitalised or dead was 5.0 (95% CI 4.6-5.4) in high-risk patients and 2.7 (95% CI 2.6-2.9) in medium-risk patients, as compared to low-risk patients. CONCLUSIONS A simple monitoring system, based on primary care datasets with linkage to COVID-19 testing results, hospital admissions data and death records may assist in proper planning and allocation of patients and resources during the ongoing COVID-19 pandemic.


1999 ◽  
Vol 45 (4, Part 2 of 2) ◽  
pp. 123A-123A
Author(s):  
Ayman El-Mohandes ◽  
Michal Young ◽  
Lawrence Grylack ◽  
M Nabil El-Khorazaty ◽  
Kathy Katz ◽  
...  

2009 ◽  
Vol 29 (2_suppl) ◽  
pp. 153-157 ◽  
Author(s):  
Narayan Prasad ◽  
Amit Gupta ◽  
Archana Sinha ◽  
Anurag Singh ◽  
Raj Kumar Sharma ◽  
...  

Background Case-mix comorbidities and malnutrition influence outcome in continuous ambulatory peritoneal dialysis (CAPD) patients. In the present study, we analyzed the influence of stratified comorbidities on nutrition indices and survival in CAPD patients. Patients and Methods We categorized 373 CAPD patients (197 with and 176 without diabetes) into three risk groups: low—age under 70 years and no comorbid illness; medium—age 70 – 80 years, or any age with 1 comorbid illness, or age under 70 years with diabetes; high—age over 80 years, or any age with 2 comorbid illnesses. We then compared nutrition indices and malnutrition by subjective global assessment (SGA) between the three groups. Survival was compared using Kaplan–Meier survival analysis. Results Mean daily calorie and protein intakes in the low-risk group (21 ± 6.7 Kcal/kg, 0.85 ± 0.28 g/kg) were significantly higher than in the medium- (17.6 ± 5.2 Kcal/kg, 0.79 ± 0.25 g/kg) and high-risk (17.5 ± 6.1 Kcal/kg, 0.78 ± 0.26 g/kg) groups ( p = 0.001 and p = 0.04 respectively). Relative risk (RR) of malnutrition was less in the low-risk group (103/147, 70.06%) than in the medium-risk group [135/162, 83.3%; RR: 2.0; 95% confidence interval (CI): 2.1 to 3.4; p = 0.01] or the high-risk group (54/64, 84.4%; RR: 2.3; 95% CI: 2.1 to 4.9; p = 0.03). Mean survivals of patients in the low-, medium-, and high-risk groups were 51 patient–months (95% CI: 45.6 to 56.4 patient–months), 43.3 patient–months (95% CI: 37.8 to 48.7 patient–months), and 29.7 patient–months (95% CI: 23 to 36.4 patient–months) respectively (log-rank: 35.9 patient–months; p = 0.001). The 1-, 2-, 3-, 4-, and 5-year patient survivals in the low-, medium-, and high-risk groups were 96%, 87%, 79%, 65%, and 56%; 89%, 67%, 54%, 43%, and 34%; and 76%, 48%, 31%, 30%, and 30% respectively. Conclusions Intake of calories and protein was significantly lower in the medium-risk and high-risk groups than in the low-risk group. Survival was significantly better in low-risk patients than in medium- and high-risk patients.


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