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Background The epidemiology of HF in India is largely unexplored. Current resources are based on a few hospital-based and a community-based registry from North India. Thus, we present the data from a single hospital-based registry in South India. Patients admitted with acute heart failure over a period of 1 year were enrolled in the registry and were characterized based on their ejection fraction (EF) measured by echocardiogram. The clinical profile of the patients was assessed, including their in-hospital outcomes. One-way ANOVA and univariate analysis were performed for comparison between three EF-based groups and for the assessment of in-hospital outcomes. Results A total of 449 patients were enrolled in the registry, of which 296, 90, and 63 patients were categorized as, HFrEF, HFmrEF, and HFpEF, respectively. The prevalence of HFrEF was higher (65.99%). The mean age (SD) of the study cohort was 59.9±13.3. The majority of the patients presented with acute denovo HF (67%) and were more likely to be males (65.9%). The majority of patients presented with warm and wet clinical phenotype (86.4%). In hospital mortality was higher in HFmrEF (3.3%). Conclusion Patients with HFrEF had high adherence to guideline-directed medical therapy (GDMT). HFrEF patients were also likely to have longer hospital stay along with a worsening of renal function. The in-hospital mortality was comparable between the EF-based groups. Additionally, the association of clinical phenotypes with outcome highlighted that patients in warm and wet phenotype had a longer length of hospital stay, whereas the mortality and worsening renal function rates were found to be significantly higher in the cold and wet group.

Background: The adoption of guideline recommendations of pharmacotherapy to improve the clinical course of Heart Failure (HF) remains below par. Our objective is to evaluate the impact of clinical audit on adherence to the Guideline-Directed Medical Therapy (GDMT) in patients admitted with acute heart failure with reduced ejection fraction (EF). Methods: A prospective interventional study was conducted over a period of 12 months from June 2018 to May 2019 in all patients admitted with acute heart failure with reduced ejection fraction. The discharge prescriptions of patients who met the inclusion criteria were audited for appropriateness in the usage of neurohormonal blockers and Ivabradine, by a clinical pharmacist on a monthly basis. Audit results were presented to the practicing physicians every month and feedback was given. Results: Discharge prescriptions of 716 patients who presented with HF were audited for the reasonable or unreasonable omission of neurohormonal blocking drugs. The first-month audit revealed that the unreasonable omission of Angiotensin-Converting Enzyme Inhibitors/ Angiotensin Receptor Blockers/ Angiotensin Receptor Neprilisin Inhibitors ( ACEI/ARB/ARNI), Betablockers and Mineralocorticoid Receptor Antagonists (MRA) were 24.5%, 13.1%, and 9.09% respectively, which reduced to nil at the end of the study period (p=0.00). Initiation of Ivabradine before prescribing or achieving the target dose of Betablocker was noted in 38.18% of patients in the first month, which was also reduced to nil (p=0.00) at the end of the study. Conclusion: This study reveals that periodic clinical audit improves adherence to GDMT in patients admitted with heart failure with reduced ejection fraction.

This paper presents HotSpot-a modeling methodology for developing compact thermal models based on the popular stacked-layer packaging scheme in modern very large-scale integration systems. In addition to modeling silicon and packaging layers, HotSpot includes a high-level on-chip interconnect self-heating power and thermal model such that the thermal impacts on interconnects can also be considered during early design stages. The HotSpot compact thermal modeling approach is especially well suited for preregister transfer level (RTL) and presynthesis thermal analysis and is able to provide detailed static and transient temperature information across the die and the package, as it is also computationally efficient.

This paper describes a thermal-modeling approach that is easy to use and computationally efficient for modeling thermal effects and thermal-management techniques at the processor architecture level. Our approach is based on modeling thermal behavior of the microprocessor die and its package as a circuit of thermal resistances and capacitances that correspond to functional blocks at the architecture level. This yields a simple compact model, yet heat dissipation within all major functional blocks and the heat flow among blocks and through the package are accounted for. The model is parameterized, boundary- and initial-conditions independent, and is derived by a structure assembly approach. The architecture community has demonstrated growing interest in thermal management, but currently lacks a way to model on-chip temperatures in a tractable way. Our model can be used for initial exploration of the design space at the architecture level. The model can easily be integrated into popular power/performance simulators, can be used to determine how thermal stress is correlated to the architecture, and how architecture-level design decisions influence thermal behavior and related effects.

This study was aimed to find out the differences in the pregnancy outcome of PIH women treated with the antihypertensive drugs methyldopa and nifedipine. The prospective observational study was conducted in a multi specialty hospital at Coimbatore with 161 PIH diagnosed women. Women were categorised into the no-drug group, methyldopa group, nifedipine group and methyldopa with nifedipine group. All the women were monitored from diagnosis to delivery. The maternal and neonatal data were collected and analysed. The drugs were significantly controlled the blood pressure (BP) from base to end (P90%) and preterm delivery were high across all the groups. No significant difference was seen between these groups. The AGA (Average for gestational age) babies were significantly higher with a no-drug group (83%) and lower with nifedipine group (40%). Two women were reported with HELLP syndrome in methyldopa with nifedipine group. No significant difference was found in terms of pregnancy outcome between these groups except for eclampsia and AGA. Eclampsia was affected more with 14% in methyldopa with nifedipine group. We found similar outcomes; there were no significant changes between methyldopa, nifedipine, and the no-drug treatment. The antihypertensive drugs nifedipine and methyldopa both were significantly reduced the BP. The maternal and neonatal complications were similar between these two drugs. No beneficial effect can be identified one over another.

FPGA logic densities continue to increase at a tremendous rate. This has had the undesired consequence of increased power density, which manifests itself as higher on-die temperatures and local hotspots. Sophisticated packaging techniques have become essential to maintain the health of the chip. In addition to static techniques to reduce the temperature, dynamic thermal management techniques are essential. Such techniques rely on accurate on-chip temperature information. In this paper, we present the design of a system that monitors the temperatures at various locations on the FPGA. This system is composed of a controller interfacing to an array of temperature sensors that are implemented on the FPGA fabric. Such a system can be used to implement dynamic thermal management techniques. We cross validate the sensor readings with values obtained from HotSpot, a pre-RTL architectural level thermal modeling tool.

In current day microprocessors, exponentially increasing power densities, leakage, cooling costs, and reliability concerns have resulted in temperature becoming a first class design constraint like performance and power. Hence, virtually every high performance microprocessor uses a combination of an elaborate thermal package and some form of Dynamic Thermal Management (DTM) scheme that adaptively controls its temperature. While DTM schemes exploit the important variable of power density to control temperature, this paper attempts to show that there is a significant peak temperature reduction potential in managing lateral heat spreading through floorplanning. It argues that this potential warrants consideration of the temperature-performance trade-off early in the design stage at the microarchitectural level using floorplanning. As a demonstration, it uses previously proposed wire delay model and floorplanning algorithm based on simulated annealing to present a profile-driven, thermal-aware floorplanning scheme that significantly reduces peak processor temperature with minimal performance impact that is quite competitive with DTM.

With power density and hence cooling costs rising exponentially, processor packaging can no longer be designed for the worst case, and there is an urgent need for runtime processor-level techniques that can regulate operating temperature when the package's capacity is exceeded. Evaluating such techniques, however, requires a thermal model that is practical for architectural studies.This paper describes HotSpot, an accurate yet fast model based on an equivalent circuit of thermal resistances and capacitances that correspond to microarchitecture blocks and essential aspects of the thermal package. Validation was performed using finite-element simulation. The paper also introduces several effective methods for dynamic thermal management (DTM): "temperature-tracking" frequency scaling, localized toggling, and migrating computation to spare hardware units. Modeling temperature at the microarchitecture level also shows that power metrics are poor predictors of temperature, and that sensor imprecision has a substantial impact on the performance of DTM.