The relationship between BP and downstream ischemia during hemodialysis has not been characterized. We studied the dynamic relationship between BP, real-time symptoms, and cerebral oxygenation during hemodialysis, using continuous BP and cerebral oxygenation measurements prospectively gathered from 635 real-world hemodialysis sessions in 58 prevalent patients. We examined the relationship between BP and cerebral ischemia (relative drop in cerebral saturation >15%) and explored the lower limit of cerebral autoregulation at patient and population levels. Furthermore, we estimated intradialytic exposure to cerebral ischemia and hypotension for each patient, and entered these values into multivariate models predicting change in cognitive function. In all, 23.5% of hemodialysis sessions featured cerebral ischemia; 31.9% of these events were symptomatic. Episodes of hypotension were common, with mean arterial pressure falling by a median of 22 mmHg (interquartile range, 14.3-31.9 mmHg) and dropping below 60 mmHg in 24% of sessions. Every 10 mmHg drop from baseline in mean arterial pressure associated with a 3% increase in ischemic events (<0.001), and the incidence of ischemic events rose rapidly below an absolute mean arterial pressure of 60 mmHg. Overall, however, BP poorly predicted downstream ischemia. The lower limit of cerebral autoregulation varied substantially (mean 74.1 mmHg, SD 17.6 mmHg). Intradialytic cerebral ischemia, but not hypotension, correlated with decreased executive cognitive function at 12 months (=0.03). This pilot study demonstrates that intradialytic cerebral ischemia occurs frequently, is not easily predicted from BP, and may be clinically significant.

In a cohort of IgAN patients receiving no immunosuppression, endocapillary proliferation and tubular atrophy/interstitial fibrosis are independent predictors of rate of loss of renal function. The lack of predictive value of E score in other clinicopathological studies is most likely a result of immunosuppression-associated bias. Our findings provide evidence to support immunosuppressive treatment of endocapillary-pattern IgAN.

Aims The Oxford Classification E score (endocapillary hypercellularity) predicts renal functional decline in IgA nephropathy (IgAN) patients free from steroid/immunosuppressive (IS) therapy, but is poorly reproducible. We hypothesise that endocapillary hypercellularity reflects glomerular inflammation and that the presence of CD68‐positive cells is a more robust marker of E score. Methods and results CD68‐positive cells were quantified in glomeruli and tubulointerstitium in biopsies from 118 IgAN patients, and cell counts were correlated with the criteria of the Oxford Classification, assigned on PAS‐stained serial sections. There was a strong correlation between median glomerular CD68 count and the percentage of glomeruli showing endocapillary hypercellularity (r = 0.67; P < 0.001; r2 = 0.45), while there was no correlation between CD68‐positive cells and mesangial hypercellularity, % segmental sclerosis, % of crescents and % tubular atrophy/interstitial fibrosis (TA/IF). ROC curve analysis demonstrated that a maximum glomerular CD68 count of 6 is the best cut‐off for distinguishing E0 from E1 (sensitivity 94.1%, specificity 71%, area under the curve = 89%). Identification of biopsies with a maximum glomerular CD68‐count >6 was reproducible (kappa score 0.8), and there was a strong correlation between glomerular CD68 counts obtained by conventional light microscopy and by image analysis (r = 0.80, r2 = 0.64, P < 0.0001). Digital image analysis revealed that tubulointerstitial CD68‐positive cells correlated moderately with % TA/IF (r = 0.59, r2 = 0.35, P < 0.001) and GFR at the time of biopsy (r = 0.54, r2 = 0.29, P < 0.0001), but not with mesangial and endocapillary hypercellularity. Conclusions While glomerular CD68‐positive cells emerge as markers of endocapillary hypercellularity, their tubulointerstitial counterparts are associated with chronic damage.

Intra-arterial thombolysis, mechanical clot aspiration, intravenous abciximab, neurointensive care support, rehabilitation at a specialist stroke unit.

Hemodialysis patients have multiple risk factors for small vessel cerebrovascular disease and cognitive dysfunction. Hemodialysis itself may cause clinically significant neurological injury through repetitive cerebral ischemia. However, supporting evidence to date consists of epidemiological associations, expert opinion, and small, single-centre studies of variable methodological quality. Isolating the impact of intra-dialytic hemodynamic instability from underlying renal and vascular disease on clinically relevant functional outcomes would require very large, controlled studies, given the heterogeneity and confounding comorbidities of the population, and the complex relationship between blood pressure and cerebral oxygen delivery. There has been an increase in complementary physiological studies looking directly at intra-dialytic cerebral oxygen balance, which have provided supporting evidence for the occurrence of cerebral ischemia, often independently of hemodynamics. Data suggesting a relationship between these measures of oxygen balance and functional outcomes is only hypothesis-generating at this stage. We advocate the testing of interventions that aim to reduce intra-dialytic cerebral hypoxia (rather than hypotension) in sufficiently powered studies, followed by correlation with validated, longitudinal assessment of clinically relevant neurological damage.

No abstract

The management of patient well-being can be performed by monitoring continuous time-series vital-sign data via low-cost wearable devices. Automated algorithms may then be used with the resulting data to provide early warning of deterioration of the health of an individual. Such algorithms are typically trained for a large population without considering the time-variability and inter-subject variability of the data being collected. In the case where limited numbers of subjects are available, it is difficult to create a generalized population model from a small sample size. Furthermore, some ''normal'' patients may exhibit different physiological patterns when compared to other ''normal'' patients, forming multiple ''normal'' clusters/subgroups. This also makes inferring a population model difficult. It is, therefore, preferable to develop patient/subgroup-specific time-series models to overcome these challenges. We propose using Bayesian hierarchical Gaussian processes to infer the hidden latent structure of the vital sign's trajectory for each individual patient or group of patients who share similar patterns. We further demonstrate the feasibility of such a model in novelty detection, using the symmetric Kullback-Leibler divergence. This allows us to identify any patterns that correspond to ''normal'' or ''abnormal'' physiology, and further classifying ''abnormal'' patterns from a model of ''normal'' latent trajectories. We tested our approach using two real datasets for different monitoring scenarios. Our model was compared to the performance of the state-ofthe-art unsupervised clustering algorithms, demonstrating at least 10% improvement in accuracy. We further benchmarked against two one-class classifiers and showed at least 5% accuracy improvement when using the proposed metrics in identifying abnormal physiological episodes. INDEX TERMS Physiology, patient monitoring, pattern analysis, Bayes methods.

Whilst prolonging hemofilter (circuit) life, heparin increases bleeding risk. The impact of achieved activated partial thromboplastin time (APTT) on circuit life and bleeding risk has not been assessed in a modern critically ill cohort. Lowering filtration fraction may be an alternative means of prolonging circuit life, but is often overlooked in critical care. An observational study of 309 consecutive circuits in a general intensive care unit was conducted using a wide target APTT range. Multilevel modeling was used to predict circuit life and bleeding according to achieved APTT and filtration fraction. Independent predictors of circuit failure (i.e. unplanned ending of treatment) included filtration fraction (P<0.001, HR 1.07 per 1% increase), peak APTT (P<0.001, HR 0.8 per 10 s increase or 0.3 APTR increase) and baseline PT (P=0.014, HR 0.91 for every 50% increase). The only significant predictor of bleeding was peak APTT (P=0.017, OR 1.05 per 10 s increase). Every 10 s APTT increase was associated with a 20% reduction in circuit failure, but a 5% increase in hemorrhage. A 3% reduction in filtration fraction was associated with the same improvement in circuit life as a 10 s increase in APTT. Increasing APTT prolongs circuit life but carries a substantial risk of bleeding even in modern practice. Filtration fraction has a large impact on circuit life in the critically ill: a 3% reduction in filtration fraction, e.g. by increasing blood flow or delivering some of the clearance via dialysis, would be expected to reduce circuit failure as much as a 10 s increase in APTT.