Community-based incidence of acute renal failure

There is limited information about the true incidence of acute renal failure (ARF). Most studies could not quantify disease frequency in the general population as they are hospital-based and confounded by variations in threshold and the rate of hospitalization. Earlier studies relied on diagnostic codes to identify non-dialysis requiring ARF. These underestimated disease incidence since the codes have low sensitivity. Here we quantified the incidence of non-dialysis and dialysis-requiring ARF among members of a large integrated health care delivery system – Kaiser Permanente of Northern California. Non-dialysis requiring ARF was identified using changes in inpatient serum creatinine values. Between 1996 and 2003, the incidence of non-dialysis requiring ARF increased from 322.7 to 522.4 whereas that of dialysis-requiring ARF increased from 19.5 to 29.5 per 100 000 person-years. ARF was more common in men and among the elderly, although those aged 80 years or more were less likely to receive acute dialysis treatment. We conclude that the use of serum creatinine measurements to identify cases of non-dialysis requiring ARF resulted in much higher estimates of disease incidence compared with previous studies. Both dialysis-requiring and non-dialysis requiring ARFs are becoming more common. Our data underscore the public health importance of ARF

Vastus lateralis/vastus medialis cross-sectional area ratio impacts presence and degree of knee joint abnormalities and cartilage T2 determined with 3T MRI – an analysis from the incidence cohort of the Osteoarthritis Initiative

SummaryObjectiveTo study the role of vastus lateralis/vastus medialis cross-sectional area CSA ratio (VL/VM CSA ratio) in preclinical knee osteoarthritis (OA) using magnetic resonance imaging (MRI)-based cartilage T2 mapping technique and morphological analysis at 3.0T in non-symptomatic, middle-aged subjects.Material and methods174 non-symptomatic individuals aged 45–55 years with OA risk factors were selected from the Osteoarthritis Initiative (OAI) incidence cohort. OA-related knee abnormalities were analyzed using the whole-organ magnetic resonance imaging score (WORMS). Knee cartilage T2 maps were generated using sagittal 2D multi-echo spin-echo images of the right knee. CSA of thigh muscles was measured using axial T1W images of the right mid thigh. Spline-based segmentation of cartilage and muscles was performed on a SUN/SPARC workstation. Muscle measurements were normalized to body size using body surface area (BSA). Statistical significance was determined using Student’s t-test, Pearson correlation test, and multiple regression models. To correct for multiple testing, Bonferroni adjustments were applied across all tests within each of the primary results tables (Tables III–VII).ResultsHigher T2 values were associated with increased prevalence and severity of cartilage degeneration. In our study, male and female subjects with higher VL/VM CSA ratio demonstrated significantly lower mean cartilage T2 values (all compartments combined) (mean 44.10 vs 45.17, P=0.0017), and significantly lower WORMS scores (mean 14.12 vs 18.68, P=0.0316). Regression analyses of combined mean cartilage T2 using VL/VM CSA ratio as a continuous predictor showed a significant curvilinear relationship between these two variables (P=0.0082).ConclusionOur results suggested that higher VL/VM CSA ratio is associated with lower T2 values and decreased presence and severity of OA-related morphological changes. Additional studies will be needed to determine causality

A bayesian multilevel modeling approach for data query in wireless sensor networks

In power-limited Wireless Sensor Network (WSN), it is important to reduce the communication load in order to achieve energy savings. This paper applies a novel statistic method to estimate the parameters based on the realtime data measured by local sensors. Instead of transmitting large real-time data, we proposed to transmit the small amount of dynamic parameters by exploiting both temporal and spatial correlation within and between sensor clusters. The temporal correlation is built on the level-1 Bayesian model at each sensor to predict local readings. Each local sensor transmits their local parameters learned from historical measurement data to their cluster heads which account for the spatial correlation and summarize the regional parameters based on level-2 Bayesian model. Finally, the cluster heads transmit the regional parameters to the sink node. By utilizing this statistical method, the sink node can predict the sensor measurements within a specified period without directly communicating with local sensors. We show that this approach can dramatically reduce the amount of communication load in data query applications and achieve significant energy savings

Treatment‐related changes in bone turnover and fracture risk reduction in clinical trials of antiresorptive drugs: proportion of treatment effect explained

Few analyses of antiresorptive (AR) treatment trials relate short‐term changes in bone turnover markers (BTMs) to subsequent fracture reduction seeking to estimate the proportion of treatment effect explained (PTE) by BTMs. Pooling such information would be useful to assess new ARs or novel dosing regimens. In the Foundation for the National Institutes of Health (FNIH) Bone Quality project, we analyzed individual‐level data from up to 62,000 participants enrolled in 12 bisphosphonate (BP) and four selective estrogen receptor modulator (SERM) placebo‐controlled fracture endpoint trials. Using BTM results for two bone formation markers (bone‐specific alkaline phosphatase [bone ALP] and pro‐collagen I N‐propeptide [PINP]) and one bone resorption marker (C‐terminal telopeptide of type I collagen [CTX]) and incident fracture outcome data, we estimated the PTE using two different models. Separate analyses were performed for incident morphometric vertebral, nonvertebral, and hip fractures over 1 to 5 years of follow‐up. For vertebral fracture, the results showed that changes in all three BTMs at 6 months explained a large proportion of the treatment effect of ARs (57 to >100%), but not for and non‐vertebral or hip fracture. We conclude that short‐term AR treatment‐related changes in bone ALP, PINP, and CTX account for a large proportion of the treatment effect for vertebral fracture. Change in BTMs is a useful surrogate marker to study the anti‐fracture efficacy of new AR compounds or novel dosing regiments with approved AR drugs. © 2020 The Authors. Journal of Bone and Mineral Research published by American Society for Bone and Mineral Research

Prevalence of HIV and disease outcomes on the medical and surgical wards at Kamuzu Central Hospital, Lilongwe, Malawi

Introduction: The World Health Organization (WHO) recommends HIV Counseling and Testing (HCT) in a range of clinical settings. We describe the characteristics of patients diagnosed with HIV on the medical and surgical wards at a tertiary care hospital in Malawi. Methods: Under the universal opt-out HCT protocol we characterized the number of new HIV/AIDS infections and associated clinical features among hospitalized surgical and medical patients diagnosed during the course of admission. Results: All 2985 and 3959 medical and surgical patients, respectively, admitted between April 2012 and January 2013 were screened for HCT. 62% and 89% of medical and surgical patients, respectively, had an unknown status on admission and qualified for testing. Of the patients with an unknown status, a new HIV diagnosis was made in 20% and 7% of medical and surgical patients, respectively. Of the newly diagnosed patients with a CD4 count recorded, 91% and 67% of medical and surgical patients, respectively, had a count less than 350, qualifying for ART by Malawi ART guidelines. Newly HIV-diagnosed medical and surgical patients had an inpatient mortality of 20% and 2%, respectively. Discussion: While newly diagnosed HIV-positive medical patients had high inpatient mortality and higher rates of WHO stage 3 or 4 conditions, surgical patients presented with less advanced HIV, though still meeting ART initiation guidelines. The medical inpatient wards are an obvious choice for implementing voluntary counseling and testing (VCT), but surgical patients present with less advanced disease and starting treatment in this group could result in more years of life gained

GLMMLasso: An Algorithm for High-Dimensional Generalized Linear Mixed Models Using L1-Penalization

We propose an L1-penalized algorithm for fitting high-dimensional generalized linear mixed models. Generalized linear mixed models (GLMMs) can be viewed as an extension of generalized linear models for clustered observations. This Lasso-type approach for GLMMs should be mainly used as variable screening method to reduce the number of variables below the sample size. We then suggest a refitting by maximum likelihood based on the selected variables only. This is an effective correction to overcome problems stemming from the variable screening procedure which are more severe with GLMMs. We illustrate the performance of our algorithm on simulated as well as on real data examples. Supplemental materials are available online and the algorithm is implemented in the R package glmmixedlasso