Citations

AbstractIntroductionEmerging medical technology has allowed for monitoring of heart rhythm abnormalities using smartphone compatible devices. The safety and utility of such devices have not been established in patients with cardiac implantable electronic devices (CIEDs). We sought to assess the safety and compatibility of the Food and Drug Administration‐approved AliveCor Kardia device in patients with CIEDs.Methods and ResultsWe prospectively recruited patients with CIED for a Kardia recording during their routine device interrogation. A recording was obtained in paced and nonpaced states. Adverse clinical events were noted at the time of recording. Electrograms (EGMs) from the cardiac device were obtained at the time of recording to assess for any electromagnetic interference (EMI) introduced by Kardia. Recordings were analyzed for quality and given a score of 3 (interpretable rhythm, no noise), 2 (interpretable rhythm, significant noise) or 1 (uninterpretable). A total of 251 patients were recruited (59% with a pacemaker and 41% with ICD). There were no adverse clinical events noted at the time of recording and no changes to CIED settings. Review of all EGMs revealed no EMI introduced by Kardia. Recordings were correctly interpreted in 90% of paced recordings (183 had a score of 3, 43 of 2, and 25 of 1) and 94.7% of nonpaced recordings (147 of 3, 15 of 2, and 9 of 1).ConclusionThe AliveCor Kardia device has an excellent safety profile when used in conjunction with most CIEDs. The quality of recordings was preserved in this population. The device, therefore, can be considered for heart rhythm monitoring in patients with CIEDs.

Background and objectives Withdrawal from maintenance hemodialysis before death has become more common because of high disease and treatment burden. The study objective was to identify patient factors and examine the terminal course associated with hemodialysis withdrawal, and assess patterns of palliative care involvement before death among patients on maintenance hemodialysis. Design, setting, participants, & measurements We designed an observational cohort study of adult patients on incident hemodialysis in a midwestern United States tertiary center, from January 2001 to November 2013, with death events through to November 2015. Logistic regression models evaluated associations between patient characteristics and withdrawal status and palliative care service utilization. Results Among 1226 patients, 536 died and 262 (49% of 536) withdrew. A random sample (10%; 52 out of 536) review of Death Notification Forms revealed 73% sensitivity for withdrawal. Risk factors for withdrawal before death included older age, white race, palliative care consultation within 6 months, hospitalization within 30 days, cerebrovascular disease, and no coronary artery disease. Most withdrawal decisions were made by patients (60%) or a family member (33%; surrogates). The majority withdrew either because of acute medical complications (51%) or failure to thrive/frailty (22%). After withdrawal, median time to death was 7 days (interquartile range, 4–11). In-hospital deaths were less common in the withdrawal group (34% versus 46% nonwithdrawal, P =0.003). A third (34%; 90 out of 262) of those that withdrew received palliative care services. Palliative care consultation in the withdrawal group was associated with longer hemodialysis duration (odds ratio, 1.19 per year; 95% confidence interval, 1.10 to 1.3; P <0.001), hospitalization within 30 days of death (odds ratio, 5.78; 95% confidence interval, 2.62 to 12.73; P <0.001), and death in hospital (odds ratio, 1.92; 95% confidence interval, 1.13 to 3.27; P =0.02). Conclusions In this single-center study, the rate of hemodialysis withdrawals were twice the frequency previously described. Acute medical complications and frailty appeared to be driving factors. However, palliative care services were used in only a minority of patients.

SummaryBackgroundHepatitis E virus (HEV) infection appears to be more common than previously thought. HEV seroprevalence in patients on maintenance haemodialysis (HD) is unclear with a range from 0% to 44%. In addition, risk factors of transmission of HEV in patients on haemodialysis are unknown.AimTo perform a systematic review and meta‐analysis of HEV seroprevalence in HD patients compared with controls.MethodsA systematic search of several databases identified all observational studies with comparative arms. Two reviewers extracted data and assessed the methodological quality. A random‐effects model was used for pooled odds ratio (OR) and 95% confidence interval (CI) of positive anti‐HEV IgG in both groups. Heterogeneity and publication bias were assessed with appropriate tests.ResultsWe identified 31 studies from 17 countries between 1994 and 2016. Sixteen studies were judged to have adequate quality and 15 to have moderate limitations. HEV infection was more prevalent in patients on haemodialysis compared with controls (OR 2.47, 95% CI 1.79‐3.40, I2 = 75.2%, P < .01). We conducted several subgroup analyses without difference in results. Egger regression test did not suggest publication bias (P = .83). Specific risk factors of HEV transmission in patients on haemodialysis were not clearly identified.ConclusionsHepatitis E virus infection is more prevalent in patients on haemodialysis compared with non‐haemodialysis control groups. Further studies are needed to determine risk factors of acquisition, impact on health, and risk for chronic HEV especially among those patients going to receive organ transplantation.

Renal function improves early after left ventricular assist device (LVAD) implantation but later decline has been observed. We sought to determine the occurrence and evaluate possible causes for this decline. In 62 consecutive patients with HeartMateII LVAD with available calculated glomerular filtration rate (GFR, ml/min/1.73 m2) 1 year after implant, GFR was assessed repeatedly and possible predictors for decline from 3 to 12 months were investigated. Post-mortem renal specimens for patients supported with an LVAD were evaluated. GFR 54.5 ± 19.5 at admission increased to 66.4 ± 22.3 preoperatively and to 79.2 ± 30.1 ~1 month after implantation. Subsequently at ~3 months GFR declined to 74.7 ± 25.4, at ~6 months to 68.8 ± 23.1, and ~1 year after implant to 63.9 ± 17.7. Glomerular filtration rate at 1 year was significantly lower (p < 0.0001, p < 0.0001, p = 0.005) than GFR 1, 3, and 6 months after implant. Early rise in GFR after surgery was not associated with late decline. Shorter bypass time (β = −0.09, p = 0.048) and higher albumin 3 months after LVAD (β = 14.4, p = 0.025) were significantly associated with less later decline in GFR. Arteriosclerosis was identified in autopsy renal specimens. In conclusion, early gains in renal function after LVAD implant are not sustained in many patients. Patient, device, and operative factors may influence long-term renal function in these patients.

Background Hyper‐ and hypokalemia are clinically silent, common in patients with renal or cardiac disease, and are life threatening. A noninvasive, unobtrusive, blood‐free method for tracking potassium would be an important clinical advance. Methods and Results Two groups of hemodialysis patients (development group, n=26; validation group, n=19) underwent high‐resolution digital ECG recordings and had 2 to 3 blood tests during dialysis. Using advanced signal processing, we developed a personalized regression model for each patient to noninvasively calculate potassium values during the second and third dialysis sessions using only the processed single‐channel ECG . In addition, by analyzing the entire development group's first‐visit data, we created a global model for all patients that was validated against subsequent sessions in the development group and in a separate validation group. This global model sought to predict potassium, based on the T wave characteristics, with no blood tests required. For the personalized model, we successfully calculated potassium values with an absolute error of 0.36±0.34 mmol/L (or 10% of the measured blood potassium). For the global model, potassium prediction was also accurate, with an absolute error of 0.44±0.47 mmol/L for the training group (or 11% of the measured blood potassium) and 0.5±0.42 for the validation set (or 12% of the measured blood potassium). Conclusions The signal‐processed ECG derived from a single lead can be used to calculate potassium values with clinically meaningful resolution using a strategy that requires no blood tests. This enables a cost‐effective, noninvasive, unobtrusive strategy for potassium assessment that can be used during remote monitoring.

Encephalopathy is a rare side effect of third and fourth generation cephalosporins. Renal failure and preexisting neurological disease are notable risk factors. Recognition is important as discontinuing the offending agent usually resolves symptoms. We present a case of acute encephalopathy in a patient with end stage renal disease (ESRD) treated with peritoneal dialysis (PD) who received intravenous ceftriaxone for peritonitis. This case illustrates the potential severe neurologic effects of cephalosporins, which are recommended by international guidelines as first-line antimicrobial therapy for spontaneous bacterial peritonitis.

AbstractAimsThe number of elderly persons with end‐stage renal disease is increasing with many requiring hospitalizations. This study examines the causes and predictors of hospitalization in older haemodialysis patients.MethodsWe reviewed hospitalizations of older (≥65 years) incident chronic haemodialysis patients initiating therapy between 1 January 2007 and 31 December 2009 under the care of a single Midwestern United States dialysis provider.ResultsOf 125 patients, the mean age was 76 ± 7 years and 72% were male. At first dialysis, 68% used a central venous catheter (CVC) and 51% were in the hospital. Mean follow‐up was 1.8 ± 1.0 years. At least one hospitalization occurred in 89 (71%) patients and half of all patients were hospitalized once within the first 223 days. Total hospital admission rate was 1.48 per patient year with hospital days totalling 8.54 days per patient year. The three most common reasons for first admission were cardiac (33%), infection (18%) and gastrointestinal (12%). Predictors of future hospitalization included the first dialysis occurring in hospital (hazard ratios (HR) 2.1, 95% CI 1.4–3.3, P = 0.0005) and the use of a CVC at first haemodialysis (HR 2.6, CI 1.6–4.4, P < 0.0001).ConclusionHospitalizations are common in older incident haemodialysis patients. Access preparation and overall burden of illness leading to the initial hospitalization appear to play a role. Identification of additional factors associated with hospitalization will allow for focused interventions to reduce hospitalization rates and increase the value of care.