Miracle-dz/UniFAR-FTUs huggingface dataset:
Red Cell Distribution Width at Admission Predicts the Frequency of Acute Kidney Injury and 28-Day Mortality in Patients With Acute Respiratory Distress Syndrome

ABSTRACT Objectives: To determine the association of red cell distribution width (RDW) at admission with frequency of acute kidney injury (AKI) and 28-day mortality in acute respiratory distress syndrome (ARDS) patients. Methods: Two hundred fifty-eight ARDS patients were investigated in retrospective and prospective studies. The primary outcome was frequency of AKI. The secondary outcome was 28-day mortality. Results: The retrospective study included 193 ARDS patients, of which 67 (34.7%) were confirmed AKI and 76 (39.4%) died within 28 days. The RDW level in the AKI group was significantly higher than in the non-AKI group ([15.15 ± 2.59]% vs. [13.95 ± 1.89]%). Increased RDW was a significant predictor of frequency of AKI (odds ratio: 1.247, 95% confidence interval [CI]: 1.044, 1.489). The area under the receiver operating characteristic curve of RDW for predicting AKI was 0.687 (95%CI: 0.610, 0.764) and the cut-off value was 14.45 (sensitivity, 56.7%; specificity, 72.8%). In addition, the proportion of patients with RDW ≥ 14.45% in the non-survival group was notably higher compared with the survival group (48.7% vs. 29.1%). Furthermore, cox regression analysis revealed that RDW ≥ 14.45% was associated with 28-day mortality (hazard ratio: 1.817, 95%CI: 1.046, 3.158), while Kaplan–Meier analysis showed patients with RDW ≥ 14.45% had a significantly lower survival rate than those with RDW < 14.45%. The prospective study, on the other hand, included 65 ARDS patients, with frequency of AKI and 28-day mortality in the RDW ≥ 14.45% group significantly higher than in RDW < 14.45%. Conclusion: RDW was a significant, independent predictor for frequency of AKI and 28-day mortality in ARDS patients.
Research Needs for Inpatient Management of Severe Alcohol Withdrawal Syndrome: An Official American Thoracic Society Research Statement

Background: Severe alcohol withdrawal syndrome (SAWS) is highly morbid, costly, and common among hospitalized patients, yet minimal evidence exists to guide inpatient management. Research needs in this field are broad, spanning the translational science spectrum. Goals: This research statement aims to describe what is known about SAWS, identify knowledge gaps, and offer recommendations for research in each domain of the Institute of Medicine T0–T4 continuum to advance the care of hospitalized patients who experience SAWS. Methods: Clinicians and researchers with unique and complementary expertise in basic, clinical, and implementation research related to unhealthy alcohol consumption and alcohol withdrawal were invited to participate in a workshop at the American Thoracic Society 2019 International Conference. The committee was subdivided into four groups on the basis of interest and expertise: T0–T1 (basic science research with translation to humans), T2 (research translating to patients), T3 (research translating to clinical practice), and T4 (research translating to communities). A medical librarian conducted a pragmatic literature search to facilitate this work, and committee members reviewed and supplemented the resulting evidence, identifying key knowledge gaps. Results: The committee identified several investigative opportunities to advance the care of patients with SAWS in each domain of the translational science spectrum. Major themes included 1) the need to investigate non–γ-aminobutyric acid pathways for alcohol withdrawal syndrome treatment; 2) harnessing retrospective and electronic health record data to identify risk factors and create objective severity scoring systems, particularly for acutely ill patients with SAWS; 3) the need for more robust comparative-effectiveness data to identify optimal SAWS treatment strategies; and 4) recommendations to accelerate implementation of effective treatments into practice. Conclusions: The dearth of evidence supporting management decisions for hospitalized patients with SAWS, many of whom require critical care, represents both a call to action and an opportunity for the American Thoracic Society and larger scientific communities to improve care for a vulnerable patient population. This report highlights basic, clinical, and implementation research that diverse experts agree will have the greatest impact on improving care for hospitalized patients with SAWS.
Integrating Domain Knowledge Into Deep Networks for Lung Ultrasound With Applications to COVID-19

Lung ultrasound (LUS) is a cheap, safe and non-invasive imaging modality that can be performed at patient bed-side. However, to date LUS is not widely adopted due to lack of trained personnel required for interpreting the acquired LUS frames. In this work we propose a framework for training deep artificial neural networks for interpreting LUS, which may promote broader use of LUS. When using LUS to evaluate a patient’s condition, both anatomical phenomena (e.g., the pleural line, presence of consolidations), as well as sonographic artifacts (such as A- and B-lines) are of importance. In our framework, we integrate domain knowledge into deep neural networks by inputting anatomical features and LUS artifacts in the form of additional channels containing pleural and vertical artifacts masks along with the raw LUS frames. By explicitly supplying this domain knowledge, standard off-the-shelf neural networks can be rapidly and efficiently finetuned to accomplish various tasks on LUS data, such as frame classification or semantic segmentation. Our framework allows for a unified treatment of LUS frames captured by either convex or linear probes. We evaluated our proposed framework on the task of COVID-19 severity assessment using the ICLUS dataset. In particular, we finetuned simple image classification models to predict per-frame COVID-19 severity score. We also trained a semantic segmentation model to predict per-pixel COVID-19 severity annotations. Using the combined raw LUS frames and the detected lines for both tasks, our off-the-shelf models performed better than complicated models specifically designed for these tasks, exemplifying the efficacy of our framework.
Highly expressed centromere protein L indicates adverse survival and associates with immune infiltration in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is characterized by rapid progression, high recurrence rate and poor prognosis. Early prediction for the prognosis and immunotherapy efficacy is of great significance to improve the survival of HCC patients. However, there is still no reliable predictor at present. This study is aimed to explore the role of centromere protein L (CENPL) in predicting prognosis and its association with immune infiltration in HCC. Methods: The expression of CENPL was identified through analyzing the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data. The association between CENPL expression and clinicopathological features was investigated by the Wilcoxon signed-rank test or Kruskal Wallis test and logistic regression. The role of CENPL in prognosis was examined via Kaplan-Meier method and Log-rank test as well as univariate and multivariate Cox regression analysis. Besides, in TIMER and GEPIA database, we investigated the correlation between CENPL level and immunocyte and immunocyte markers, and the prognostic-related methylation sites in CENPL were identified by MethSurv. Results: CENPL had a high expression in HCC samples. Increased CENPL was prominently associated with unfavorable survival, and maybe an independent prognostic factor of worse overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), progression-free interval (PFI). Additionally, CENPL expression was significantly correlated with immune cell infiltration and some markers. CENPL also contained a methylation site that was notably related to poor prognosis. Conclusions: Elevated CENPL may be a promising prognostic marker and associate with immune infiltration in HCC.
Does the suddenness matter? Antidepressant use before and after a spouse dies suddenly or expectedly of stroke

Aims: Changes in mental health at the time of widowhood may depend on the expectedness of spousal death, but scant evidence is available for spousal deaths attributable to stroke. Methods: Using register-linkage data for Finland, we assessed changes in antidepressant use before and after spousal death for those whose spouses died suddenly of stroke between 1998 and 2003 (N=1820) and for those whose spouses died expectedly of stroke, with prior hospitalisation for cerebrovascular disease (N=1636). We used both population-averaged logit models and individual fixed-effects linear probability models. The latter models control for unobserved time-invariant heterogeneity between the individuals. Results: Our study indicates that the suddenness of a spouse’s death from stroke plays a role in the well-being of the surviving spouse. Increases in antidepressant use appeared larger following widowhood for those whose spouses died suddenly of stroke relative to those whose spouses had a medical history of cerebrovascular disease. Conclusions: The suddenness of a spouse’s death from stroke plays a role for the surviving spouse. The results suggest multifaceted timings of distress surrounding spousal death, depending on the suddenness of a spouse’s death from stroke.
Percutaneous Tibial Nerve Stimulation in Diabetic and Nondiabetic Women With Overactive Bladder Syndrome: A Retrospective Cohort Study

Objectives The primary objective of this study was to compare optimal response (“very much better” or “much better” on the Patient Global Impression of Improvement [PGI-I] index) to posterior tibial nerve stimulation (PTNS) for overactive bladder (OAB) in patients with and without diabetes mellitus. Secondary outcomes included longitudinal data regarding PTNS use in patients with diabetes and controls. Methods We performed a retrospective cohort analysis of women in our tertiary care center who completed at least 10 weekly and 1 maintenance PTNS treatments for OAB, excluding patients who were treated with PTNS for a non-OAB primary diagnosis. Participants were grouped into those with diabetes mellitus and those without. Previous research demonstrated a 20% difference in subjective response to anticholinergics in persons with diabetes versus persons without diabetes with OAB. To demonstrate a 20% difference in optimal PGI-I with 80% power, our analysis required 92 patients in each group. Results We identified 356 patients: 96 with diabetes mellitus, and 260 controls. There was no statistically significant difference in the primary outcome, with 43 (44.8%) of 96 persons with diabetes versus 115 (44.2%) of 260 controls demonstrating optimal PGI-I response (P = 0.92). Among patients with diabetes, no baseline variables were found to predict treatment response, including hemoglobin A1c greater than 7%, diabetes with sequelae, or higher Charlson Comorbidity Index. Conclusions In women undergoing PTNS for OAB, the optimal PGI-I response rate is similar in patients with and without diabetes.
The effects of induced optical blur on visual search performance and training

Visual search is a task often used in the rehabilitation of patients with cortical and non-cortical visual pathologies such as visual field loss. Reduced visual acuity is often comorbid with these disorders, and it remains poorly defined how low visual acuity may affect a patient’s ability to recover visual function through visual search training. The two experiments reported here investigated whether induced blurring of vision (from 6/15 to 6/60) in a neurotypical population differentially affected various types of feature search tasks, whether there is a minimal acceptable level of visual acuity required for normal search performance, and whether these factors affected the degree to which participants could improve with training. From the results, it can be seen that reducing visual acuity did reduce search speed, but only for tasks where the target was defined by shape or size (not colour), and only when acuity was worse than 6/15. Furthermore, searching behaviour was seen to improve with training in all three feature search tasks, irrespective of the degree of blurring that was induced. The improvement also generalised to a non-trained search task, indicating that an enhanced search strategy had been developed. These findings have important implications for the use of visual search as a rehabilitation aid for partial visual loss, indicating that individuals with even severe comorbid blurring should still be able to benefit from such training.
Artificial intelligence versus expert endoscopists for diagnosis of gastric cancer in patients who have undergone upper gastrointestinal endoscopy

Introduction and aims: To compare endoscopy gastric cancer images diagnosis rate between artificial intelligence (AI) and expert endoscopists. Patients and methods: We used the retrospective data of 500 patients, including 100 with gastric cancer, matched 1:1 to diagnosis by AI or expert endoscopists. We retrospectively evaluated the non-inferiority (prespecified margin 5%) of the per-patient rate of gastric cancer diagnosis by AI and compared the per-image rate of gastric cancer diagnosis. Results: Gastric cancer was diagnosed in 49 of 49 patients (100%) in the AI group and 48 of 51 patients (94.12%) in the expert endoscopist group (difference 5.88, 95% confidence interval: −0.58 to 12.3). The per-image rate of gastric cancer diagnosis was higher in the AI group (99.87%, 747/748 images) than in the expert endoscopist group (88.17%, 693/786 images) (difference 11.7%). Conclusions: Non inferiority of the rate of gastric cancer diagnosis by AI was demonstrated but superiority is not demonstrated.
Tufts Dental Database: A Multimodal Panoramic X-Ray Dataset for Benchmarking Diagnostic Systems

The application of Artificial Intelligence in dental healthcare has a very promising role due to the abundance of imagery and non-imagery-based clinical data. Expert analysis of dental radiographs can provide crucial information for clinical diagnosis and treatment. In recent years, Convolutional Neural Networks have achieved the highest accuracy in various benchmarks, including analyzing dental X-ray images to improve clinical care quality. The Tufts Dental Database, a new X-ray panoramic radiography image dataset, has been presented in this paper. This dataset consists of 1000 panoramic dental radiography images with expert labeling of abnormalities and teeth. The classification of radiography images was performed based on five different levels: anatomical location, peripheral characteristics, radiodensity, effects on the surrounding structure, and the abnormality category. This first-of-its-kind multimodal dataset also includes the radiologist's expertise captured in the form of eye-tracking and think-aloud protocol. The contributions of this work are 1) publicly available dataset that can help researchers to incorporate human expertise into AI and achieve more robust and accurate abnormality detection; 2) a benchmark performance analysis for various state-of-the-art systems for dental radiograph image enhancement and image segmentation using deep learning; 3) an in-depth review of various panoramic dental image datasets, along with segmentation and detection systems. The release of this dataset aims to propel the development of AI-powered automated abnormality detection and classification in dental panoramic radiographs, enhance tooth segmentation algorithms, and the ability to distill the radiologist's expertise into AI.
Unusual Findings in Trials Evaluating Adjuncts to Scaling and Root Planing: Meta-analysis (Part 1)

Background: A number of studies in patients with periodontitis have compared scaling and root planning (SRP) combined with an adjunctive treatment to SRP alone. Within that literature, an array of studies with overlapping investigators has consistently yielded substantially greater effects of adjunctive treatments than had been previously noted. This report investigates discrepancies between that cluster of research and the most recent American Dental Association (ADA) systematic review. Methods: This review was preregistered at https://osf.io/4meyd/. A search using the Scopus platform identified 32 articles published from 2010 to 2017 by investigators affiliated with the Government Dental College and Research Institute (GDCRI) in Bangalore, India. The primary outcome used in this meta-analysis was the change in clinical attachment level (CAL) after 6 mo. Effect sizes were estimated using Comprehensive Meta-Analysis software after categorizing agents into groups based on pharmacologic similarity. Results: The search identified 32 studies encompassing 5 sets of adjunctive agents. Across the GDCRI studies, the CAL averaged 1.67 mm (95% confidence interval [CI]: 1.43–1.91 mm), substantially exceeding values reported in the ADA review (mean: 0.39 mm, 95% CI: 0.27–0.51 mm). For categories of studies in which comparable subgroup estimates were available, the evaluations yielded overlapping estimates of SRP alone, but CAL estimates were discrepant for both locally delivered antimicrobials (GDCRI studies: mean: 1.45 mm, 95% CI: 0.63–2.27 mm; ADA review: mean: 0.38 mm, 95% CI: 0.16 –0.60 mm) and systemic antibiotics (GDCRI studies: mean: 1.35 mm, 95% CI: 0.97–1.73 mm; ADA review: mean: 0.39 mm, 95% CI: 0.21–0.57 mm). Conclusion: In the literature on adjunctive agents supplementing SRP, findings from investigators linked to GDCRI stand out as having significantly more favorable estimated effects. Meanwhile, some agents studied by GDCRI-linked investigators have not been investigated by other researchers. In the absence of a clear explanation for discrepant results, it is recommended that unusually favorable reported effects of adjunctive agents be viewed with caution. Knowledge Transfer Statement: The present meta-analysis observed an unusually large effect size of adjunctive agents to scaling and root planning in studies conducted by the same research group. These results were not consistent with trials on adjunctive agents and previous reports. As this research group has exclusively tested most of the agents, their results must be viewed with caution until other independent groups replicate the studies and reproduce the effect size.
Conceptus interferon gamma is essential for establishment of pregnancy in the pig

Abstract Establishment and maintenance of pregnancy in the pig is a complex process that relies on conceptus regulation of the maternal proinflammatory response to endometrial attachment. Following elongation, pig conceptuses secrete interferon gamma (IFNG) during attachment to the endometrial luminal epithelium. The objective here was to determine if conceptus production of IFNG is important for early development and establishment of pregnancy. CRISPR/Cas9 gene editing and somatic cell nuclear transfer technologies were used to create an IFNG loss-of-function study in pigs. Wild-type (IFNG+/+) and null (IFNG–/–) fibroblast cells were used to create embryos through somatic cell nuclear transfer. IFNG expression was not detected in IFNG–/– conceptuses on either day 15 or day 17 of pregnancy. Ablation of conceptus IFNG production resulted in the reduction of stromal CD3+ and mast cells, which localized to the site of conceptus attachment on day 15. The uteri of recipients with IFNG–/– conceptuses were inflamed, hyperemic and there was an abundance of erythrocytes in the uterine lumen associated with the degenerating conceptuses. The endometrial stromal extracellular matrix was altered in the IFNG–/– embryo pregnancies and there was an increased endometrial mRNA levels for collagen XVII (COL17A1), matrilin 1 (MATN1), secreted phosphoprotein 1 (SPP1), and cysteine-rich secretory protein 3 (CRISP3), which are involved with repair and remodeling of the extracellular matrix. These results indicate conceptus IFNG production is essential in modulating the endometrial proinflammatory response for conceptus attachment and survival in pigs. Summary sentence Ablation of IFNG in the pig conceptus causes conceptus degeneration and endometrial inflammation.
#Botox 101: Subgroup Analysis of Twitter's Top 101 Neurotoxin Influencers

Supplemental Digital Content is Available in the Text. BACKGROUND Recent studies demonstrate that board-certified plastic surgeons and dermatologists are underrepresented in posting public-directed marketing content about botulinum toxin A on YouTube. However, educational content and peer-to-peer social media influence regarding the topic of neurotoxins has not been studied. Twitter is a social media platform that has emerged as a unique network for public education and for the exchange of ideas among physicians. OBJECTIVE The purpose of this study is to identify Twitter's top social media influencers on #botox, to describe their characteristics and to relate their social media influence to academic influence. METHODS Twitter influence scores for the topic search #botox were collected in January 2019 with Right Relevance software. #Botox was the only neurotoxin term with sufficient activity to generate an influencer list. The user accounts associated with top influencers were connected to individual names, identification as a plastic surgeon or dermatologist, board certification status, location, and academic h-index. RESULTS The top 101 Twitter influencers on #botox are presented. Seventy-five percent of influencers are physically located in the United States. Academic h-index of #botox social media influencers ranged from 0 to 62 (mean, 8.6). CONCLUSION This study shows that the top #botox social media influencers on Twitter and primarily board-certified or eligible plastic surgeons located in the United States. This study also elucidates the influencer network within which other plastic surgeons and dermatologists can interact to augment their own influence within the social media network. This is the first study to describe social media influencers in this way.
Pancretic Fat Accummulation is Associated with Subclinical Atherosclerosis

We investigated the relationship between pancreatic fat accumulation and markers of atherosclerosis among patients with nonalcoholic fatty liver disease (NAFLD). Patients with NAFLD have been reported to be at an increased risk of vascular events. We grouped 183 patients in whom we detected and graded hepatosteatosis (HS) on transabdominal ultrasonography into 2 groups based on the presence/absence of pancreatic fat. There were 85 participants (50 female; mean age: 53.6 ± 9.7 years) who were nonalcoholic fatty pancreas disease (NAFPD) positive and 98 participants (56 female; mean age: 51.4 ± 9.3 years) who were NAFPD negative. Carotid intima media thickness (cIMT) was significantly greater in the group where HS was accompanied by NAFPD (0.51 [0.40–0.62] vs 0.45 [0.35–0.55] mm; P < .001). Multivariable analyses showed that the independent predictors of increased cIMT were age (odds ratio [OR]: 1.108; 95% CI: 1.059–1.158, P = .001), hypertension (OR: 2.244; 95% CI: 1.099–4.579, P = .026), and the presence of NAFPD (OR: 3.078; CI 95% CI: 1.531–6.190, P = .0002). In the present study we demonstrated that, in patients with NAFLD, pancreatic fat accumulation was significantly associated with cIMT, a marker of early atherosclerosis. NAFPD may increase the risk of vascular events associated with NAFLD.