FastDocFastDoc: Domain-Specific Fast Pre-training Technique using Document-Level Metadata and Taxonomy

As the demand for sophisticated Natural Language Processing (NLP) models continues to grow, so does the need for efficient pre-training techniques. Current NLP models undergo resource-intensive pre-training. In response, we introduce $FastDoc$ (Fast Pre-training Technique using Document-Level Metadata and Taxonomy), a novel approach designed to significantly reduce computational demands. $FastDoc$ leverages document metadata and domain-specific taxonomy as supervision signals. It involves continual pre-training of an open-domain transformer encoder using sentence-level embeddings, followed by fine-tuning using token-level embeddings. We evaluate $FastDoc$ on six tasks across nine datasets spanning three distinct domains. Remarkably, $FastDoc$ achieves remarkable compute reductions of approximately 1,000x, 4,500x, 500x compared to competitive approaches in Customer Support, Scientific, and Legal domains, respectively. Importantly, these efficiency gains do not compromise performance relative to competitive baselines. Furthermore, reduced pre-training data mitigates catastrophic forgetting, ensuring consistent performance in open-domain scenarios. $FastDoc$ offers a promising solution for resource-efficient pre-training, with potential applications spanning various domains.Comment: 38 pages, 7 figure

Use of the Palliative Performance Scale to estimate survival among home hospice patients with heart failure

AimsEstimating survival is challenging in the terminal phase of advanced heart failure. Patients, families, and health‐care organizations would benefit from more reliable prognostic tools. The Palliative Performance Scale Version 2 (PPSv2) is a reliable and validated tool used to measure functional performance; higher scores indicate higher functionality. It has been widely used to estimate survival in patients with cancer but rarely used in patients with heart failure. The aim of this study was to identify prognostic cut‐points of the PPSv2 for predicting survival among patients with heart failure receiving home hospice care.Methods and resultsThis retrospective cohort study included 1114 adult patients with a primary diagnosis of heart failure from a not‐for‐profit hospice agency between January 2013 and May 2017. The primary outcome was survival time. A Cox proportional‐hazards model and sensitivity analyses were used to examine the association between PPSv2 scores and survival time, controlling for demographic and clinical variables. Receiver operating characteristic curves were plotted to quantify the diagnostic performance of PPSv2 scores by survival time. Lower PPSv2 scores on admission to hospice were associated with decreased median (interquartile range, IQR) survival time [PPSv2 10 = 2 IQR: 1–5 days; PPSv2 20 = 3 IQR: 2–8 days] IQR: 55–207. The discrimination of the PPSv2 at baseline for predicting death was highest at 7 days [area under the curve (AUC) = 0.802], followed by an AUC of 0.774 at 14 days, an AUC of 0.736 at 30 days, and an AUC of 0.705 at 90 days.ConclusionsThe PPSv2 tool can be used by health‐care providers for prognostication of hospice‐enrolled patients with heart failure who are at high risk of near‐term death. It has the greatest utility in patients who have the most functional impairment.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148390/1/ehf212398_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148390/2/ehf212398.pd

Papillary muscle infarction in relation to left ventricular infarct distribution and transmurality - assessment by delayed enhancement cardiac magnetic resonance imaging

This study used delayed enhancement CMR (DE-CMR) and invasive angiography to evaluate relationships between papillary muscle and left ventricular (LV) chamber wall infarction following ST segment elevation MI (STEMI). Results demonstrate that papillary muscle infarction (PMI) parallels infarct transmurality and contractile dysfunction within the adjacent LV wall

Causes and timing of 30-day rehospitalization from skilled nursing facilities after a hospital admission for pneumonia or sepsis

BACKGROUND: Pneumonia and sepsis are among the most common causes of hospitalization in the United States and often result in discharges to a skilled nursing facility (SNF) for rehabilitation. We described the timing and most common causes of 30-day unplanned hospital readmission following an index hospitalization for pneumonia or sepsis. METHODS AND FINDINGS: This national retrospective cohort study included adults ≥65 years who were hospitalized for pneumonia or sepsis and were discharged to a SNF between July 1, 2012 and July 4, 2015. We quantified the ten most common 30-day unplanned readmission diagnoses and estimated the daily risk of first unplanned rehospitalization for four causes of readmission (circulatory, infectious, respiratory, and genitourinary). The index hospitalization was pneumonia for 92,153 SNF stays and sepsis for 452,254 SNF stays. Of these SNF stays, 20.9% and 25.9%, respectively, resulted in a 30-day unplanned readmission. Overall, septicemia was the single most common readmission diagnosis for residents with an index hospitalization for pneumonia (16.7% of 30-day readmissions) and sepsis (22.4% of 30-day readmissions). The mean time to unplanned readmission was approximately 14 days overall. Respiratory causes displayed the highest daily risk of rehospitalization following index hospitalizations for pneumonia, while circulatory and infectious causes had the highest daily risk of rehospitalization following index hospitalizations for sepsis. The day of highest risk for readmission occurred within two weeks of the index hospitalization discharge, but the readmission risk persisted across the 30-day follow-up. CONCLUSION: Among older adults discharged to SNFs following a hospitalization for pneumonia or sepsis, hospital readmissions for infectious, circulatory, respiratory, and genitourinary causes occurred frequently throughout the 30-day post-discharge period. Our data suggests further study is needed, perhaps on the value of closer monitoring in SNFs post-hospital discharge and improved communication between hospitals and SNFs, to reduce the risk of potentially preventable hospital readmissions

Perspectives on Implementing a Multidomain Approach to Caring for Older Adults With Heart Failure

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153220/1/jgs16183_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153220/2/jgs16183-sup-0001-supinfo.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153220/3/jgs16183.pd

The Prevalence of Cognitive Impairment Among Adults With Incident Heart Failure: The “Reasons for Geographic and Racial Differences in Stroke” (REGARDS) Study

Background Cognitive impairment (CI) is estimated to be present in 25%–80% of heart failure (HF) patients, but its prevalence at diagnosis is unclear. To improve our understanding of cognition in HF, we determined the prevalence of CI among adults with incident HF in the REGARDS study. Methods and Results REGARDS is a longitudinal cohort study of adults ≥45 years of age recruited in the years 2003–2007. Incident HF was expert adjudicated. Cognitive function was assessed with the Six-Item Screener. The prevalence of CI among those with incident HF was compared with the prevalence of CI among an age-, sex-, and race-matched cohort without HF. The 436 participants with incident HF had a mean age of 70.3 years (SD 8.9), 47% were female, and 39% were black. Old age, black race, female sex, less education, and anticoagulation use were associated with CI. The prevalence of CI among participants with incident HF (14.9% [95% CI 11.7%–18.6%]) was similar to the non-HF matched cohort (13.4% [11.6%–15.4%]; P < .43). Conclusions A total of 14.9% of the adults with incident HF had CI, suggesting that the majority of cognitive decline occurs after HF diagnosis. Increased awareness of CI among newly diagnosed patients and ways to mitigate it in the context of HF management are warranted

Improved Left Ventricular Mass Quantification with Partial Voxel Interpolation – In-Vivo and Necropsy Validation of a Novel Cardiac MRI Segmentation Algorithm

Background—CMR typically quantifies LV mass (LVM) via manual planimetry (MP), but this approach is time consuming and does not account for partial voxel components - myocardium admixed with blood in a single voxel. Automated segmentation (AS) can account for partial voxels, but this has not been used for LVM quantification. This study used automated CMR segmentation to test the influence of partial voxels on quantification of LVM. Methods and Results—LVM was quantified by AS and MP in 126 consecutive patients and 10 laboratory animals undergoing CMR. AS yielded both partial voxel (ASPV) and full voxel (ASFV) measurements. Methods were independently compared to LVM quantified on echocardiography (echo) and an ex-vivo standard of LVM at necropsy. AS quantified LVM in all patients, yielding a 12-fold decrease in processing time vs. MP (0:21±0:04 vs. 4:18±1:02 min; pFV mass (136±35gm) was slightly lower than MP (139±35; Δ=3±9gm, pPV yielded higher LVM (159±38gm) than MP (Δ=20±10gm) and ASFV (Δ=23±6gm, both pPV and ASFV correlated with larger voxel size (partial r=0.37, pPV yielded better agreement with echo (Δ=20±25gm) than did ASFV (Δ=43±24gm) or MP (Δ=40±22gm, both pPV and ex-vivo results were similar (Δ=1±3gm, p=0.3), whereas ASFV (6±3g, P\u3c0.001) and MP (4±5 g, P=0.02) yielded small but significant differences with LVM at necropsy

Predicting the impact of climate change on range and genetic diversity patterns of the endangered endemic Nilgiri tahr (Nilgiritragus hylocrius) in the western Ghats, India

[Context] Climate change is considered an important factor affecting the distribution and genetic diversity of species. While many studies have described the influence of climate change on population structure at various scales, little is known about the genetic consequences of a changing climate on endemic species.[Objectives] To assess possible changes in the distribution and genetic structure of the endangered Nilgiri tahr (Nilgiritragus hylocrius), which is endemic to the Western Ghats in India, under climate change and human disturbances.[Methods] We integrated tahr occurrence and nuclear DNA data with environmental geo-datasets to project the response of tahr populations to future climate change with respect to its distribution, genetic diversity and population structure. We screened the environmental variables using MaxEnt to identify a manageable set of predictors to be used in an ensemble approach, based on ten species distribution modelling techniques, to quantify the current tahr distribution. We then projected the distribution and genetic structure under two climate change scenarios.[Results] We found that suitable habitat for tahr (9,605 km2) is determined predominantly by a combination of climatic, human disturbance and topographic factors that result in a highly fragmented habitat throughout its distribution range in the Western Ghats. Under the severe high emissions RCP8.5 scenario tahr populations may lose more than half of their available habitat (55.5%) by 2070. Application of spatial Bayesian clustering suggests that their current genetic structure comprise four genetic clusters, with three of them reflecting a clear geographic structure. However, under climate change, two of these clusters may be lost, and in the future a homogenization of the genetic background of the remaining populations may arise due to prevalence of one gene pool cluster in the remaining populations.[Conclusions] Our interdisciplinary approach that combines niche modelling and genetic data identified the climate refugia (i.e., the remaining stable habitats that overlap with the current suitable areas), where the tahr populations would be restricted to small, isolated and fragmented areas. Essential factors to avert local extinctions of vulnerable tahr populations are a reduction of human disturbances, dispersal of tahr between fragmented populations, and the availability of corridors.This research was supported by the Department of Biotechnology, Ministry of Science and Technology, Government of India, and by a German Research Foundation (DFG) fellowship awarded to RK (project number 273837911).Peer reviewe

Tigers of Sundarbans in India: Is the Population a Separate Conservation Unit?

The Sundarbans tiger inhabits a unique mangrove habitat and are morphologically distinct from the recognized tiger subspecies in terms of skull morphometrics and body size. Thus, there is an urgent need to assess their ecological and genetic distinctiveness and determine if Sundarbans tigers should be defined and managed as separate conservation unit. We utilized nine microsatellites and 3 kb from four mitochondrial DNA (mtDNA) genes to estimate genetic variability, population structure, demographic parameters and visualize historic and contemporary connectivity among tiger populations from Sundarbans and mainland India. We also evaluated the traits that determine exchangeability or adaptive differences among tiger populations. Data from both markers suggest that Sundarbans tiger is not a separate tiger subspecies and should be regarded as Bengal tiger (P. t. tigris) subspecies. Maximum likelihood phylogenetic analyses of the mtDNA data revealed reciprocal monophyly. Genetic differentiation was found stronger for mtDNA than nuclear DNA. Microsatellite markers indicated low genetic variation in Sundarbans tigers (He= 0.58) as compared to other mainland populations, such as northern and Peninsular (Hebetween 0.67- 0.70). Molecular data supports migration between mainland and Sundarbans populations until very recent times. We attribute this reduction in gene flow to accelerated fragmentation and habitat alteration in the landscape over the past few centuries. Demographic analyses suggest that Sundarbans tigers have diverged recently from peninsular tiger population within last 2000 years. Sundarbans tigers are the most divergent group of Bengal tigers, and ecologically non-exchangeable with other tiger populations, and thus should be managed as a separate "evolutionarily significant unit" (ESU) following the adaptive evolutionary conservation (AEC) concept.Wildlife Institute of India, Dehra Dun (India)