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Background: Quality of life (QoL) is a very subjective construct that cannot be directly measured. It needs to be converted to valid and reliable indicators of its component dimensions and domains to be quantified and measured... more
Background: Quality of life (QoL) is a very subjective construct that cannot be directly measured. It needs to be converted to valid and reliable indicators of its component dimensions and domains to be quantified and measured objectively. Quality of life studies of adults have progressed over time now but literature regarding adolescents remains scarce. Objectives: To assess the QoL among adolescents studying in Bengali and English medium schools and explore the factors related to its variations. Material and methods: A cross-sectional descriptive study is conducted by pre-tested and pre-designed self-administered anonymous questionnaire (WHO-QOL BREF) which is divided in four domains.Result: It was found that the students from the Bengali medium school had better quality of life than their counterparts in the English medium school with respect to all the four domains. It was also revealed that students in their late adolescence and female gender had better quality of life. Conclus...
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<p>Comparison of prognostic models in the validation cohort.</p
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Background Blood pressure (BP) elevations are commonly treated in hospitalized patients; however, treatment is not guideline directed. Our objective was to assess BP response to commonly prescribed antihypertensives after the development... more
Background Blood pressure (BP) elevations are commonly treated in hospitalized patients; however, treatment is not guideline directed. Our objective was to assess BP response to commonly prescribed antihypertensives after the development of severe inpatient hypertension (HTN). Methods This is a cohort study of adults, excluding intensive care unit patients, within a single healthcare system admitted for reasons other than HTN who developed severe HTN (systolic BP>180 or diastolic BP >110 mmHg at least 1 hour after admission). We identified the most commonly administered antihypertensives given within 6 hours of severe HTN (given to >10% of treated patients). We studied the association of treatment with each antihypertensive vs. no treatment on BP change in the 6 hours following severe HTN development using mixed-effects model after adjusting for demographics and clinical characteristics. Results Among 23,147 patients who developed severe HTN, 9,166 received antihypertensive...
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Severe hypertension (HTN) that develops during hospitalization is more common than admission for HTN; however, it is poorly studied, and treatment guidelines are lacking. Our goal is to characterize hospitalized patients who develop... more
Severe hypertension (HTN) that develops during hospitalization is more common than admission for HTN; however, it is poorly studied, and treatment guidelines are lacking. Our goal is to characterize hospitalized patients who develop severe HTN and assess blood pressure (BP) response to treatment. This is a multi‐hospital retrospective cohort study of adults admitted for reasons other than HTN who developed severe HTN. The authors defined severe inpatient HTN as the first documented BP elevation (systolic BP > 180 or diastolic BP > 110) at least 1 hour after admission. Treatment was defined as receiving antihypertensives (intravenous [IV] or oral) within 6h of BP elevation. As a measure of possible overtreatment, the authors studied the association between treatment and time to mean arterial pressure (MAP) drop ≥ 30% using the Cox proportional hazards model. Among 224 265 hospitalized adults, 10% developed severe HTN of which 40% were treated. Compared to patients who did not develop severe HTN, those who did were older, more commonly women and black, and had more comorbidities. Incident MAP drop ≥ 30% among treated and untreated patients with severe HTN was 2.2 versus 5.7/1000 person‐hours. After adjustment, treated versus. untreated patients had lower rates of MAP drop ≥ 30% (hazard rate [HR]: 0.9 [0.8, 0.99]). However, those receiving only IV treatment versus untreated had greater rates of MAP drop ≥ 30% (1.4 [1.2, 1.7]). Overall, the authors found that clinically significant MAP drop is observed among inpatients with severe HTN irrespective of treatment, with greater rates observed among patients treated only with IV antihypertensives. Further research is needed to phenotype inpatients with severe HTN.
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In-memory computing (IMC) architectures have emerged as a promising alternative to deal with data-intensive applications. Proposals based on analog or digital IMC require multiple word lines to be activated for performing computation.... more
In-memory computing (IMC) architectures have emerged as a promising alternative to deal with data-intensive applications. Proposals based on analog or digital IMC require multiple word lines to be activated for performing computation. Specifically, in wide SRAM IMC architectures, the word line pulse shaper circuits need to be carefully investigated as pulsewidth degradation affects multiple rows, resulting in incorrect output, loss in linearity in results, or degraded performance. This paper implements compares and contrasts multiple word line shaper proposals for a wide SRAM array. Detailed post-layout simulation results of $512\times 256$ array show that for 1-bit analog dot product, the standard deviation is improved by 0.19×, 0.21×, 0.21× 0.15× for 1,4,8, and 16bit word respectively. Further, word line shaping techniques improve the access time and compute delay by 2.86× and 3×, respectively for $128\times 256$ array.
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Heart failure (HF) is one of the most common causes of hospitalization in the United States and carries a significant risk of morbidity and mortality. Use of evidence-based interventions may improve outcomes, but their use is encumbered... more
Heart failure (HF) is one of the most common causes of hospitalization in the United States and carries a significant risk of morbidity and mortality. Use of evidence-based interventions may improve outcomes, but their use is encumbered in part by limitations in accurate prognostication. The REVeAL-HF (Risk EValuation And its Impact on ClinicAL Decision Making and Outcomes in Heart Failure) trial is the first to definitively evaluate the impact of knowledge about prognosis on clinical decision making and patient outcomes. The REVeAL-HF trial is a pragmatic, completely electronic, randomized controlled trial that has completed enrollment of 3,124 adults hospitalized for HF, defined as having an N-terminal pro-B-type natriuretic peptide level of >500 pg/ml and receiving intravenous diuretic agents within 24 h of admission. Patients randomized to the intervention had their risk of 1-year mortality generated with information in the electronic health record and presented to their providers, who had the option to give feedback on their impression of this risk assessment. The authors are examining the impact of this information on clinical decision-making (use of HF pharmacotherapies, referral to electrophysiology, palliative care referral, and referral for advanced therapies like heart transplantation or mechanical circulatory support) and patient outcomes (length of stay, post-discharge 30-day rehospitalizations, and 1-year mortality). The REVeAL-HF trial will definitively examine whether knowledge about prognosis in HF has an impact on clinical decision making and patient outcomes. It will also examine the relationship between calculated, perceived, and real risk of mortality in this patient population. (Risk EValuation And Its Impact on ClinicAL Decision Making and Outcomes in Heart Failure [REVeAL-HF]; NCT03845660).
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Systematic delineation of complex biological systems is an ever-challenging and resource-intensive process. Single-cell transcriptomics allows us to study cell-to-cell variability in complex tissues at an unprecedented resolution.... more
Systematic delineation of complex biological systems is an ever-challenging and resource-intensive process. Single-cell transcriptomics allows us to study cell-to-cell variability in complex tissues at an unprecedented resolution. Accurate modeling of gene expression plays a critical role in the statistical determination of tissue-specific gene expression patterns. In the past few years, considerable efforts have been made to identify appropriate parametric models for single-cell expression data. The zero-inflated version of Poisson/negative binomial and log-normal distributions have emerged as the most popular alternatives owing to their ability to accommodate high dropout rates, as commonly observed in single-cell data. Although the majority of the parametric approaches directly model expression estimates, we explore the potential of modeling expression ranks, as robust surrogates for transcript abundance. Here we examined the performance of the discrete generalized beta distribut...
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The continuous quest for reversible computation that could be extensively used in applications such as digital signal processing, quantum computing, quantum-dot cellular automata, and nanotechnology has recently discovered its optical... more
The continuous quest for reversible computation that could be extensively used in applications such as digital signal processing, quantum computing, quantum-dot cellular automata, and nanotechnology has recently discovered its optical implementation as light tenders high-speed computing with the slightest information loss. The electro-optic effect of a lithium-niobate-based Mach–Zehnder interferometer is explored to configure a 4 × 4 modified Fredkin gate, capable of furnishing as many as 16 logical combinations, and thus showing potential of curbing the area overhead. The optical design is carried out using the beam propagation method. We have also performed the mathematical modeling and analyzed the results in MATLAB.
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Background: BP elevations in the hospital are commonly treated with intravenous medications, specifically hydralazine. However, treatment guidelines are lacking. Our goal is to assess the effect of intravenous hydralazine on BP following... more
Background: BP elevations in the hospital are commonly treated with intravenous medications, specifically hydralazine. However, treatment guidelines are lacking. Our goal is to assess the effect of intravenous hydralazine on BP following severe inpatient HTN development. Methods: This is a cohort study of adults admitted for reasons other than HTN and developed severe HTN within a single healthcare system. We defined severe inpatient HTN as the first documentation of BP elevation (>180 systolic or >110 diastolic) at least 1 hour after admission. Pregnant women were excluded. Mixed-effects models with nonlinear time trend were used to assess and visualize the time-dependent effect of intravenous hydralazine on BP within 6 hours of BP elevation. Results: Of the 23,147 inpatients who developed severe HTN, 13,753 were untreated and 9,166 were treated of which 12% received intravenous hydralazine. Of the treated and untreated patients, 57 and 46% had a severe MAP reduction (drop ≥3...
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Background: Incident severe HTN during hospitalization is far more common than admission for HTN, however treatment guidelines are lacking. Severe inpatient HTN is poorly studied, therefore our goal is to characterize inpatients who... more
Background: Incident severe HTN during hospitalization is far more common than admission for HTN, however treatment guidelines are lacking. Severe inpatient HTN is poorly studied, therefore our goal is to characterize inpatients who develop severe HTN and assess BP response to antihypertensive treatment. Methods: This is a cohort study of adults admitted for reasons other than HTN and developed severe HTN within a single healthcare system. We defined severe inpatient HTN as the first documentation of BP elevation (>180 systolic or >110 diastolic) at least 1 hour after hospital admission. Treatment was defined as receiving antihypertensive medications within 6 hours of BP elevation. We studied the association between treatment and BP drop ≥30%. Results: Among 224,265 hospitalized adults, 23,147 developed severe HTN of which 40% were treated. Compared to inpatients who did not develop severe HTN, those who did were older, more commonly women and Black, and had more comorbidities...
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ImportanceFalse negative SARS-CoV-2 tests can lead to spread of infection in the inpatient setting to other patients and healthcare workers. However, the population of patients with COVID who are admitted with false negative testing is... more
ImportanceFalse negative SARS-CoV-2 tests can lead to spread of infection in the inpatient setting to other patients and healthcare workers. However, the population of patients with COVID who are admitted with false negative testing is unstudied.ObjectiveTo characterize and develop a model to predict true SARS-CoV-2 infection among patients who initially test negative for COVID by PCR.DesignRetrospective cohort study.SettingFive hospitals within the Yale New Haven Health System between 3/10/2020 and 9/1/2020. Participants: Adult patients who received diagnostic testing for SARS-CoV-2 virus within the first 96 hours of hospitalization.ExposureWe developed a logistic regression model from readily available electronic health record data to predict SARS-CoV-2 positivity in patients who were positive for COVID and those who were negative and never retested.Main Outcomes and MeasuresThis model was applied to patients testing negative for SARS-CoV-2 who were retested within the first 96 ho...
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Rationale and objective While COVID-19 infection has been associated with acute kidney injury (AKI), it is unclear whether this association is independent of traditional risk factors such as hypotension, nephrotoxin exposure, and... more
Rationale and objective While COVID-19 infection has been associated with acute kidney injury (AKI), it is unclear whether this association is independent of traditional risk factors such as hypotension, nephrotoxin exposure, and inflammation. We tested the independent association of COVID-19 with AKI. Study Design Multicenter, observational, cohort study. Setting and participants Patients admitted to one of six hospitals within the Yale-New Haven Health System between 3/10/2020 and 8/31/2020 and tested for SARS-CoV-2 via nasopharyngeal PCR test. Exposure Positive test for SARS-CoV-2. Outcome AKI by Kidney Disease: Improving Global Outcomes criteria. Analytic approach Evaluated the association of COVID-19 with AKI after controlling for time-invariant factors at admission (e.g., demographics, comorbidities) and time-varying factors updated continuously during hospitalization (e.g., vital signs, medications, laboratory results, respiratory failure) using time-updated Cox proportional hazard models. Results Of the 22,122 patients hospitalized between, 2,600 tested positive and 19,522 tested negative for SARS-CoV-2. Compared to patients who tested negative, patients with COVID-19 had more AKI [30.6% vs. 18.2%, absolute risk difference 12.5 (95% CI, 10.6, 14.3)%] and dialysis-requiring AKI (8.5% vs. 3.6%) and lower recovery from AKI (58% vs. 69.8%]. Compared to patients who tested negative, patients with COVID-19 had higher inflammatory markers (C-reactive protein, ferritin), and greater use of vasopressors and diuretics. Compared to patients who tested negative, patients with COVID-19 had higher rate of AKI in univariable analysis (HR, 1.84 [1.73, 1.95]). In fully adjusted model controlling for demographics, comorbidities, vital signs, medications, and laboratory results, COVID-19 remained associated with a high rate of AKI (adjusted HR, 1.40 [1.29-1.53]). Limitations Possibility of residual confounding. Conclusions COVID-19 is associated with high rates of AKI not fully explained by adjustment for known risk factors. This suggests the presence of mechanisms of AKI not accounted for in this analysis, which may include a direct effect of COVID-19 on the kidney or other unmeasured mediators. Future studies should evaluate the possible unique pathways by which COVID-19 may cause AKI.
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Significance Statement Because AKI in hospitalized children is associated with poor outcomes, a tool allowing early identification of children at risk of developing AKI may facilitate timely interventions. The authors describe various... more
Significance Statement Because AKI in hospitalized children is associated with poor outcomes, a tool allowing early identification of children at risk of developing AKI may facilitate timely interventions. The authors describe various machine learning techniques used to build a parsimonious model predictive of pediatric AKI. From an initial pool of 720 potential variables, they evaluated multiple feature selection techniques to create a ten-feature logistic regression model that could predict, in time-updated fashion, the risk of AKI in the next 48 hours. A machine learning-based genetic algorithm (reflecting the process of natural selection) was the best variable selection method, using ten factors extracted from electronic health records to use for AKI prediction. Risk-stratifying hospitalized children might allow clinicians to implement targeted and timely interventions prior to AKI development. Background Timely prediction of AKI in children can allow for targeted interventions,...
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IntroductionAcute kidney injury (AKI) is common among hospitalised patients and under-recognised by providers and yet carries a significant risk of morbidity and mortality. Electronic alerts for AKI have become more common despite a lack... more
IntroductionAcute kidney injury (AKI) is common among hospitalised patients and under-recognised by providers and yet carries a significant risk of morbidity and mortality. Electronic alerts for AKI have become more common despite a lack of strong evidence of their benefits. We designed a multicentre, randomised, controlled trial to evaluate the effectiveness of AKI alerts. Our aim is to highlight several challenges faced in the design of this trial, which uses electronic screening, enrolment, randomisation, intervention and data collection.Methods and analysisThe design and implementation of an electronic alert system for AKI was a reiterative process involving several challenges and limitations set by the confines of the electronic medical record system. The trial will electronically identify and randomise 6030 adults with AKI at six hospitals over a 1.5–2 year period to usual care versus an electronic alert containing an AKI-specific order set. Our primary outcome will be a compo...
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SummarySingle cell transcriptomics provides a window into cell-to-cell variability in complex tissues. Modeling single cell expression is challenging due to high noise levels and technical bias. In the past years, considerable efforts... more
SummarySingle cell transcriptomics provides a window into cell-to-cell variability in complex tissues. Modeling single cell expression is challenging due to high noise levels and technical bias. In the past years, considerable efforts have been made to devise suitable parametric models for single cell expression data. We use Discrete Generalized Beta Distribution (DGBD) to model read counts corresponding to a gene as a function of rank. Use of DGBD yields better overall fit across genes compared to the widely used mixture model comprising Poisson and Negative Binomial density functions. Further, we use Wald’s test to probe into differential expression across cell sub-types. We package our implementation as a standalone software called ROSeq. When applied on real data-sets, ROSeq performed competitively compared to the state of the art methods including MAST, SCDE and ROTS.Software AvailabilityThe Windows, macOS and Linux - compatible softwares are available for download at https://m...
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Electronic alerts for heterogenous conditions such as AKI may not provide benefit for all eligible patients and can lead to alert fatigue, suggesting that personalized alert targeting may be useful. Uplift-based alert targeting may be... more
Electronic alerts for heterogenous conditions such as AKI may not provide benefit for all eligible patients and can lead to alert fatigue, suggesting that personalized alert targeting may be useful. Uplift-based alert targeting may be superior to purely prognostic-targeting of interventions because uplift models assess marginal treatment effect rather than likelihood of outcome. This is a secondary analysis of a clinical trial of 2278 adult patients with AKI randomized to an automated, electronic alert system versus usual care. We used three uplift algorithms and one purely prognostic algorithm, trained in 70% of the data, and evaluated the effect of targeting alerts to patients with higher scores in the held-out 30% of the data. The performance of the targeting strategy was assessed as the interaction between the model prediction of likelihood to benefit from alerts and randomization status. The outcome of interest was maximum relative change in creatinine from the time of randomiz...
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Objective To determine whether electronic health record alerts for acute kidney injury would improve patient outcomes of mortality, dialysis, and progression of acute kidney injury. Design Double blinded, multicenter, parallel, randomized... more
Objective To determine whether electronic health record alerts for acute kidney injury would improve patient outcomes of mortality, dialysis, and progression of acute kidney injury. Design Double blinded, multicenter, parallel, randomized controlled trial. Setting Six hospitals (four teaching and two non-teaching) in the Yale New Haven Health System in Connecticut and Rhode Island, US, ranging from small community hospitals to large tertiary care centers. Participants 6030 adult inpatients with acute kidney injury, as defined by the Kidney Disease: Improving Global Outcomes (KDIGO) creatinine criteria. Interventions An electronic health record based “pop-up” alert for acute kidney injury with an associated acute kidney injury order set upon provider opening of the patient’s medical record. Main outcome measures A composite of progression of acute kidney injury, receipt of dialysis, or death within 14 days of randomization. Prespecified secondary outcomes included outcomes at each ho...