We present DR-Train, the first long-term open-access dataset recording dynamic responses from in-service light rail vehicles. Specifically, the dataset contains measurements from multiple sensor channels mounted on two in-service light rail vehicles that run on a 42.2-km light rail network in the city of Pittsburgh, Pennsylvania. This dataset provides dynamic responses of in-service trains via vibration data collected by accelerometers, which enables a low-cost way of monitoring rail tracks more frequently. Such an approach will result in more reliable and economical ways to monitor rail infrastructure. The dataset also includes corresponding GPS positions of the trains, environmental conditions (including temperature, wind, weather, and precipitation), and track maintenance logs. The data, which is stored in a MAT-file format, can be conveniently loaded for various potential uses, such as validating anomaly detection and data fusion as well as investigating environmental influences on train responses.
Shared decision making (SDM)-when clinicians and patients make medical decisions together-is moving swiftly from an ethical ideal toward widespread clinical implementation affecting millions of patients through recent policy initiatives. We argue that policy initiatives to promote SDM implementation in clinical practice carry the risk of several unintended negative consequences if limitations in defining and measuring SDM are not addressed. We urge policy makers to include prespecified definitions of desired outcomes, offer guidance on the tools used to measure SDM in the multitude of contexts in which it occurs, evaluate the impact of SDM policy initiatives over time, review that impact at regular intervals, and revise SDM measurement tools as needed.
This study characterizes the prevalence and content of US state statutes governing treatment decisions for decisionally incapacitated pregnant women.
BACKGROUND: Recipients of implantable cardioverter defibrillator (ICD) generator replacement with multiple medical comorbidities may be at higher risk of adverse outcomes that attenuate the benefit of ICD replacement. The aim of this investigation was to study the association between the Charlson comorbidity index (CCI) and outcomes after ICD generator replacement.
METHODS: All patients undergoing first ICD generator replacement at Mayo Clinic, Rochester and Beth Israel Deaconess Medical Center, Boston between 2001 and 2011 were identified. Outcomes included: (a) all-cause mortality, (b) appropriate ICD therapy, and (c) death prior to appropriate therapy. Multivariable Cox regression analysis was performed to assess association between CCI and outcomes.
RESULTS: We identified 1421 patients with mean age of 69.6 ± 12.1 years, 81% male and median (range) CCI of 3 (0-18). During a mean follow-up of 3.9 ± 3 years, 52% of patients died, 30.6% experienced an appropriate therapy, and 23.6% died without experiencing an appropriate therapy. In multivariable analysis, higher CCI score was associated with increased all-cause mortality (Hazard ratio, HR 1.10 [1.06-1.13] per 1 point increase in CCI, P < .001), death without prior appropriate therapy (HR 1.11 [1.07-1.15], P < .0001), but not associated with appropriate therapy (HR 1.01 [0.97-1.05], P = .53). Patients with CCI ≥5 had an annual risk of death of 12.2% compared to 8.7% annual rate of appropriate therapy.
CONCLUSIONS: CCI is predictive of mortality following ICD generator replacement. The benefit of ICD replacement in patients with CCI score ≥5 should be investigated in prospective studies.