Implementation of targeted deprescribing of potentially inappropriate medications in patients on hemodialysis.

PURPOSE: Patients on hemodialysis have a high risk of medication-related problems. Studies using deprescribing algorithms to reduce the number of inappropriate medications in this population have been published, but none have used a patient-partnership approach. Our study evaluated the impact of a similar intervention with a patient-partnership approach. METHODS: The objective was to describe the implementation of a pharmacist-led intervention with a patient-partnership approach using deprescribing algorithms and its impact on the reduction of inappropriate medications in patients on hemodialysis. Eight algorithms were developed by pharmacists and nephrologists to assess the appropriateness of medications. Pharmacists identified patients taking targeted medications. Following patient enrollment, pharmacists assessed medications with patients and applied the algorithms. With patient consent, deprescription was suggested to nephrologists if applicable. Specific data on each targeted medication were collected at 4 and 16 weeks. Descriptive statistics were used to examine the effects of the deprescribing intervention. RESULTS: Of 270 patients, 256 were taking at least one targeted medication. Of the 122 patients taking at least one targeted medication who were approached to participate, 66 were included in the study. At enrollment, these patients were taking 252 targeted medications, of which 59 (23.4%) were determined to be inappropriate. Deprescription was initiated for 35 of these 59 medications (59.3%). At 4 weeks, 33 of the 59 medications (55.9%) were still deprescribed, while, at 16 weeks, 27 of the 59 medications (45.8%) were still deprescribed. Proton pump inhibitors and benzodiazepines or Z-drugs were the most common inappropriate medications, and allopurinol was the most deprescribed medication. CONCLUSION: A pharmacist-led intervention with a patient-partnership approach and using deprescribing algorithms reduced the number of inappropriate medications in patients on hemodialysis.

Machine Learning Support for Decision-Making in Kidney Transplantation: Step-by-step Development of a Technological Solution.

BACKGROUND: Kidney transplantation is the preferred treatment option for patients with end-stage renal disease. To maximize patient and graft survival, the allocation of donor organs to potential recipients requires careful consideration. OBJECTIVE: This study aimed to develop an innovative technological solution to enable better prediction of kidney transplant survival for each potential donor-recipient pair. METHODS: We used deidentified data on past organ donors, recipients, and transplant outcomes in the United States from the Scientific Registry of Transplant Recipients. To predict transplant outcomes for potential donor-recipient pairs, we used several survival analysis models, including regression analysis (Cox proportional hazards), random survival forests, and several artificial neural networks (DeepSurv, DeepHit, and recurrent neural network [RNN]). We evaluated the performance of each model in terms of its ability to predict the probability of graft survival after kidney transplantation from deceased donors. Three metrics were used: the C-index, integrated Brier score, and integrated calibration index, along with calibration plots. RESULTS: On the basis of the C-index metrics, the neural network-based models (DeepSurv, DeepHit, and RNN) had better discriminative ability than the Cox model and random survival forest model (0.650, 0.661, and 0.659 vs 0.646 and 0.644, respectively). The proposed RNN model offered a compromise between the good discriminative ability and calibration and was implemented in a technological solution of technology readiness level 4. CONCLUSIONS: Our technological solution based on the RNN model can effectively predict kidney transplant survival and provide support for medical professionals and candidate recipients in determining the most optimal donor-recipient pair.

Conductive filament evolution dynamics revealed by cryogenic (1.5 K) multilevel switching of CMOS-compatible Al2O3/TiO2 resistive memories.

Non-volatile resistive switching devices are considered as prime candidates for next-generation memory applications operating at room temperature and above, such as resistive random-access memories or brain-inspired in-memory computing. However, their operability in cryogenic conditions remains to be mastered to adopt these devices as building blocks enabling large-scale quantum technologies via quantum-classical electronics co-integration. This study demonstrates multilevel switching at 1.5 K of Al2O3/TiO2-x resistive memory devices fabricated with complementary metal-oxide-semiconducto-compatible processes and materials. The I-V characteristics exhibit a negative differential resistance (NDR) effect due to a Joule-heating-induced metal-insulator transition of the Ti4O7 conductive filament. Carrier transport analysis of all multilevel switching I-V curves show that while the insulating regime follows the space charge limited current (SCLC) model for all resistance states, the conduction in the metallic regime is dominated by SCLC and trap-assisted tunneling for low- and high-resistance states respectively. A non-monotonic conductance evolution is observed in the insulating regime, as opposed to the continuous and gradual conductance increase and decrease obtained in the metallic regime during the multilevel SET and RESET operations. Cryogenic transport analysis coupled to an analytical model accounting for the metal-insulator-transition-induced NDR effects and the resistance states of the device provide new insights on the conductive filament evolution dynamics and resistive switching mechanisms. Our findings suggest that the non-monotonic conductance evolution in the insulating regime is due to the combined effects of longitudinal and radial variations of the Ti4O7 conductive filament during the switching. This behavior results from the interplay between temperature- and field-dependent geometrical and physical characteristics of the filament.

Pharmacodynamics of 250 mg and 500 mg oral furosemide in peritoneal dialysis
.

Residual renal function and diuresis preservation are associated with improved volume control and lower mortality in peritoneal dialysis (PD). Loop diuretics are used to maintain diuresis, although their optimal dosage remains unclear. This study aimed to compare the pharmacodynamics of a 250-mg and a 500-mg dose of oral furosemide in PD patients. 12 patients with a diuresis > 100 mL per day were randomized in a crossover pattern to successively receive an oral dose of 250 mg and 500 mg of furosemide. Twelve-hour natriuresis and diuresis were measured before and after each furosemide dose. Fractional excretion of sodium (FENa) and absolute sodium excretion increased after each dose, although these rises were not statistically significantly different (5.8% (250 mg) vs. 6.9% (500 mg), p = 0.57 for FENa and 42.6 mmol/12h (250 mg) vs. 70.8 mmol/12h (500 mg), p = 0.07 for absolute sodium excretion). Urinary volume was significantly increased after the 500-mg dose, whilst the difference did not reach statistical significance after the 250-mg dose. Furthermore, the higher dose was associated with a greater increase in diuresis than the lower dose (226 mL (250 mg) vs. 522 mL (500 mg), p = 0.04). Furosemide could be used at oral single doses reaching 500 mg in PD patients requiring greater volume control.

Diagnosis and outcomes of acute kidney injury using surrogate and imputation methods for missing preadmission creatinine values.

BACKGROUND: Missing preadmission serum creatinine (SCr) values are a common obstacle to assess acute kidney injury (AKI) diagnosis and outcomes. The Kidney Disease Improving Global Outcomes (KDIGO) guidelines suggest using a SCr computed from the Modification of Diet in Renal Disease (MDRD) with an estimated glomerular filtration rate of 75 ml/min/1.73 m2. We aimed to identify the best surrogate method for baseline SCr to assess AKI diagnosis and outcomes. METHODS: We compared the use of 1) first SCr at hospital admission 2) minimal SCr over 2 weeks after intensive care unit admission 3) MDRD computed SCr and 4) Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) computed SCr to assess AKI diagnosis and outcomes. We then performed multilinear regression models to predict preadmission SCr and imputation strategies to assess AKI diagnosis. RESULTS: Our one-year retrospective cohort study included 1001 critically ill adults; 498 of them had preadmission SCr values. In these patients, AKI incidence was 25.1% using preadmission SCr. First SCr had the best agreement for AKI diagnosis (22.5%; kappa = 0.90) and staging (kappa = 0.81). MDRD, CKD-EPI and minimal SCr overestimated AKI diagnosis (26.7%, 27.1% and 43.2%;kappa = 0.86, 0.86 and 0.60, respectively). However, MDRD and CKD-EPI computed SCr had a better sensitivity than first SCr for AKI (93% and 94% vs. 87%). Eighty-eight percent of patients experienced renal recovery at least 3 months after hospital discharge. All methods except the first SCr significantly underestimated the percentage of renal recovery. In a multivariate model, age, male gender, hypertension, heart failure, undergoing surgery and log first SCr best predicted preadmission SCr (adjusted R2 = 0.56). Imputation methods with first SCr increased AKI incidence to 23.9% (kappa = 0.92) but not with MDRD computed SCr (26.7%;kappa = 0.89). CONCLUSION: In our cohort, first SCr performed better for AKI diagnosis and staging, as well as for renal recovery after hospital discharge than MDRD, CKD-EPI or minimal SCr. However, MDRD SCr and CKD-EPI SCr improved AKI diagnosis sensitivity. Imputation methods minimally increased agreement for AKI diagnosis.

Continuous venovenous hemofiltration using customized replacement fluid for acute kidney injury with severe hypernatremia.

The initiation of continuous renal replacement therapy (CRRT) in acute kidney injury (AKI) with severe hypernatremia is challenging since sodium concentrations in commercial replacement fluid (RF) and dialysate solutions are usually fixed at 140 mEq/L. We present a case of AKI with severe hypernatremia successfully treated with CRRT using commercial RF solutions customized to prevent rapid correction of hypernatremia. None of the few case reports published on hypernatremia and AKI requiring CRRT have included formulas to help modulate the sodium content in the solutions. We present an equation to facilitate adjustment of the sodium concentration in this setting.

Acute Kidney Injury and Renal Recovery with the Use of Aminoglycosides: A Large Retrospective Study.

BACKGROUND: Recent acute kidney injury (AKI) guidelines, based on studies performed a decade ago, recommend avoiding aminoglycosides (AGs) in patients at risk of AKI. Whether present patient characteristics and management have changed this risk is uncertain. We determined the current incidence, risk factors and outcomes of AG-AKI. METHODS: We retrospectively identified adult patients who received gentamicin or tobramycin for ≥5 days in 2 large university-affiliated centers, excluding critically ill and dialysis patients. We assessed the incidence of Risk, Injury, Failure, Loss and End-stage kidney disease criteria of AKI risk and then matched each AKI to 2 controls of same age and gender to determine factors associated with AG-AKI and its recovery, defined by a creatinine within 150% of baseline by 21 days. RESULTS: Since 2001, the frequency of AG administration and dosing declined, but the incidence of AG-AKI remained constant. Of the 562 patients who received AG for ≥5 days, 65 (12%) developed AG-AKI after 11 (IQR 8-15) days, with 56, 29 and 15% having stages 1, 2 and 3 AKI, respectively. We matched these to 130 controls. In this nested case-control study, independent AKI risk factors were vancomycin coadministration, high AG trough levels and heart failure. AG-AKI compared to AG exposure without AKI was associated with greater mortality. Renal recovery occurred in 51% of the AKI patients and was less likely with heart failure and higher AKI severity. CONCLUSION: AG administration has recently decreased but the risk of AKI remained unchanged and half of the patients did not recover. Vancomycin coadministration, high AG trough levels and heart failure independently predicted AKI.