bluuebunny/crossref_metadata_2025 huggingface dataset:
Standardization of Pediatric Noncardiac Operating Room to Intensive Care Unit Handoffs Improves Communication and Patient Care
Authors: Hebballi Nutan B. , Gupta Vikas S. , Sheppard Kyle , Kubanda Ann , Salley Danielle , Ostovar-Kermani Tiffany , Bryndzia Christina , Khan Amir M. , Wadhwa Nitin , Tsao KuoJen , Jain Ranu , Kawaguchi Akemi L.
Published: February 2022

Objectives

Handoffs are critical points in transitioning care between multidisciplinary teams, yet data regarding intensive care unit (ICU) handoffs in pediatric noncardiac surgical patients are lacking. We hypothesized that standardized handoffs from the pediatric operating room (OR) to the ICU would improve physician presence, communication, and patient care parameters.

Methods

This quality improvement initiative was performed at a tertiary children’s hospital. Stakeholders (anesthesiologists, nurses, intensivists, and surgeons) developed a standardized OR to pediatric and neonatal ICU handoff process based on common goals and outcomes of interest. Baseline data were collected before intervention. Implementation was carried out in 2 phases, phase 1 with a written handoff and Phase 2 with a scripted handoff process. Data collected by trained observers included handoff attendance, distractions, and transfer of essential patient information. As a surrogate for outcomes, patient care parameter data were collected for 6 hours after transfer.

Results

After phase 1, surgery and ICU physician attendance increased significantly, distractions decreased, and communication of essential patient data improved. In phase 2 (scripted handoff), attendance continued to rise, distractions remained decreased, and transfer of essential information was still improved compared with baseline. Mean handoff duration did not significantly change throughout the study. Certain patient care parameters (escalation of respiratory support, additional laboratory studies, vasopressor administration, antibiotic administration and timing) remained unchanged compared with baseline. However, the need for resuscitative fluid bolus or blood products significantly decreased after implementation phase 2.

Conclusions

Standardized handoffs for pediatric noncardiac surgical patients from the OR to the ICU can improve provider attendance and communication.
Survey of physical activity in persons with limb loss during the COVID-19 pandemic in the United States
Authors: Lee Daniel Joseph , Miller Carol A , Gambale Albert , Nisani Maya , Marra Matthew , Leung Elizabeth R , Chillianis Daniel , Rodgers Madeline
Published: February 2022

Background:

Physical activity has been shown to be fundamental in the prevention of numerous diseases and disorders. Achieving and maintaining physical activity levels can be particularly challenging in those with impairments, such as those experiencing a lower limb amputation. To slow the spread of the virus, COVID-19 lockdown mandates imposed by the US state governments may have inadvertent consequences on physical activity levels of those dependent on specific forms of exercise. Understanding how physical activity levels may have affected persons with limb loss can inform intervention strategies for this vulnerable population.

Objectives:

Examine the effects of the COVID-19 pandemic on physical activity levels in persons with limb loss.

Study design:

Mixed-method design.

Methods:

A 20-item logic web-based survey and semistructured interviews were administered to individuals who were 18 years or older, spoke English, and had a history of lower limb loss. Quantitative data were analyzed using SPSS v25, whereas qualitative data were analyzed using constant comparison to formulate themes.

Results:

There were a significant effect on the amount of physical activity minutes performed per day, a negative effect on the ability to exercise and participate in societal engagements, and a series of barriers to performing physical activity because of the pandemic.

Conclusion:

Physical activity was reduced significantly in persons with limb loss during the COVID-19 pandemic. A combination of health concerns, fitness center closures, and social distancing mandates were the primary drivers behind the decrease in activity.
Single Cell Characterization of Myeloma and its Precursor Conditions Reveals Transcriptional Signatures of Early Tumorigenesis
Authors: Boiarsky Rebecca , Haradhvala Nicholas J. , Alberge Jean-Baptiste , Sklavenitis-Pistofidis Romanos , Mouhieddine Tarek H , Zavidij Oksana , Shih Ming-Chieh , Firer Danielle , Miller Mendy , El-Khoury Habib , Anand Shankara K. , Aguet François , Sontag David , Ghobrial Irene M. , Getz Gad
Published: February 2022

Multiple myeloma is a plasma cell malignancy almost always preceded by precursor conditions, but low tumor burden of these early stages has hindered the study of their molecular programs through bulk sequencing technologies. Here, we generated and analyzed single cell RNA-sequencing of plasma cells from 26 patients at varying disease stages and 9 healthy donors. In silico dissection and comparison of normal and transformed plasma cells from the same bone marrow biopsy enabled discovery of novel, patient-specific transcriptional changes. Using Bayesian Non-Negative Matrix Factorization, we discovered 15 gene expression signatures which represent transcriptional modules relevant to myeloma biology, and identified a signature that is uniformly lost in neoplastic cells across disease stages. Finally, we demonstrated that tumors contain heterogeneous subpopulations expressing distinct transcriptional patterns. Our findings characterize transcriptomic alterations present at the earliest stages of myeloma, paving the way for exploration of personalized treatment approaches prior to malignant disease.
Using the Dynamic Forward Scattering Signal for Optical Coherence Tomography based Blood Flow Quantification
Authors: Nam Ahhyun Stephanie , Braaf Boy , Vakoc Benjamin J.
Published: February 2022

To our knowledge, all existing optical coherence tomography approaches for quantifying blood flow, whether Doppler-based or decorrelation-based, analyze light that is back-scattered by moving red blood cells (RBCs). This work investigates the potential advantages of basing these measurements on light that is forward-scattered by RBCs, i.e., by looking at the signals back-scattered from below the vessel. We show experimentally that this results in a flowmetry measure that is insensitive to vessel orientation for vessels that are approximately orthogonal to the imaging beam. We further provide proof-of-principle demonstrations that DFS can be used to measure flow in human retinal and choroidal vessels.
Information theory rules out the reflex-chain model of C. elegans locomotion
Authors: Webb John , Kato Saul
Published: February 2022

Despite decades of research, whether the C. elegans traveling-wave sinusoidal body pattern during locomotion is produced (a) by the undulations of the head followed by wave propagation down the body, or (b) via centrally coordinated posture control along the body, is still under debate. By studying relationships between the time series of postural angles along the body extracted from videos of moving worms, we find that the reflex-chain model can be refuted, in both forward and backward locomotion as well as during swimming and crawling behaviors. We show that information theory applied to animal behavior can yield insights into the neural control of behavior.
An interpretable and versatile machine learning approach for oocyte phenotyping
Authors: Letort Gaelle , Eichmuller Adrien , Silva Christelle Da , Nikalayevich Elvira , Labrune Elsa , Wolf Jean-Philippe , Terret Marie-Emilie , Verlhac Marie-Hélène
Published: February 2022

Meiotic maturation is a crucial step of oocyte development allowing its potential fertilization and embryo development. Elucidating this process is important both for fundamental research and assisted reproductive technology. However, only few computational tools, based on non-invasive measurements, are currently available to characterize oocyte meiotic maturation. Here, we develop a computational framework to phenotype oocytes based on images or movies acquired exclusively in transmitted light. We first trained neural networks to segment the contours of oocytes and their zona pellucida using a diverse cohort of both mouse and human oocytes. We then defined a comprehensive set of morphological features to describe a single oocyte. We have implemented these steps in a versatile and user-friendly open source Fiji plugin available to the mouse and human oocyte community. Then, we present a machine learning pipeline based on selected features to automatically recognize oocyte populations and determine their morphological differences. Its first application is a novel approach to screen oocyte strains and automatically identify their morphological characteristics. We demonstrate its potential by phenotyping a well characterized genetically modified mouse oocyte strain. Its second application is to predict and characterize the maturation potential of oocytes. Importantly, we identify two new features to assess mouse oocyte maturation potential, consisting in the texture of the zona pellucida and the cytoplasmic particles size. Eventually, we tested whether these mouse oocyte quality features were applicable to human oocyte’s developmental potential.
Tandem Walk in Simulated Martian Gravity and Visual Environment
Authors: Rosenberg Marissa J. , Koslovsky Matthew , Noyes Matthew , Reschke Millard F. , Clément Gilles
Published: February 2022

Astronauts returning from long-duration spaceflights experience visual-vestibular conflicts that causes motion sickness, perceptions that the environment is moving when it is not, problems with walking, and other functional tasks. To evaluate whether astronauts will have similar decrements associated with visual-vestibular conflicts after they land on Mars following exposure to weightlessness, participants were held by a device that offloads their weight; first entirely (0 G) for 10 minutes, and then partially (0.38 G) or not at all (1 G) for 15 minutes. Tandem (heel-to-toe) walk was used to assess the subjects walking performance. Ten subjects performed 2 trials of 10 steps on a medium-density foam surface. Four conditions were investigated: (a) 1 G in virtual reality (VR); (b) 1 G in VR with a superimposed disorienting optokinetic simulation (VR+DOS); (c) 0.38 G in VR; and (d) 0.38 G in VR+DOS. Tandem walk performance decreased in VR+DOS compared to VR in both 1 G and simulated 0.38 G. Tandem walking performance in VR+DOS was better in 0.38 G compared to 1 G. Tandem walking performance in VR+DOS in 1 G was not significantly different from tandem walking performance after spaceflight or bed rest. The increased tandem walking performance in 0.38 G compared to 1 G was presumably due to an increased cone of stability, allowing larger amplitude of body sway without resulting in a fall. Tandem walking on a compliant foam surface in VR+DOS is a potential analog for simulating postflight dynamic balance deficits in astronauts.
Joint coding of visual input and eye/head position in V1 of freely moving mice
Authors: Parker Philip R. L. , Abe Elliott T. T. , Leonard Emmalyn S. P. , Martins Dylan M. , Niell Cristopher M.
Published: February 2022

Visual input to the brain during natural behavior is highly dependent on movements of the eyes, head, and body. Neurons in mouse primary visual cortex (V1) respond to eye and head movements, but how information about eye and head position is integrated with visual processing during free movement is unknown, since visual physiology is generally performed under head-fixation. To address this, we performed single-unit electrophysiology in V1 of freely moving mice while simultaneously measuring the mouse’s eye position, head orientation, and the visual scene from the mouse’s perspective. Based on these measures we were able to map spatiotemporal receptive fields during free movement, using a generalized linear model (GLM) that predicted the activity of V1 neurons based on gaze-corrected visual input. Furthermore, we found that a significant fraction of visually-responsive neurons showed tuning for eye position and head orientation. Incorporating these variables into the GLM revealed that visual and positional signals are integrated through a multiplicative mechanism in the majority of modulated neurons, consistent with computation via gain fields and nonlinear mixed selectivity. These results provide new insight into coding in mouse V1, and more generally provide a paradigm for performing visual physiology under natural conditions, including active sensing and ethological behavior.

HIGHLIGHTS

Neurons in mouse V1 respond to both vision and self-motion, but it is unclear how these are combined.

We record neural activity in V1 concurrent with measurement of the visual input from the mouse’s perspective during free movement.

These data provide the first measurement of visual receptive fields in freely moving animals.

We show that many V1 neurons are tuned to eye position and head orientation, and these contribute a multiplicative gain on visual responses in the majority of modulated neurons.
How exposure to land use impacts and climate change may prune the tetrapod tree of life
Authors: Beaumont Linda J , Nipperess David A , Wilson Peter D , Baumgartner John B , Esperon-Rodriguez Manuel
Published: February 2022

Human domination of landscapes is a key driver of biodiversity loss, with the fingerprint of climate change becoming increasingly pronounced. Frameworks and tools for identifying threats to biodiversity are required to meet Post-2020 Global Biodiversity Framework targets for 2030 that call for, among other things, reducing or halting species extinction rates (1). Hence, we compiled a phylogenetic tree for terrestrial tetrapods, mapped hotspots of geographically restricted and evolutionarily distinct lineages, and identified which hotspots may simultaneously face the highest magnitudes of land use impacts and climate change. Across a quarter of Earth’s surface, hotspots contain the entire ranges of 45% of tetrapods, representing 39% of terrestrial tetrapod evolutionary heritage. By 2070, we estimate 8–13% of this heritage to occur entirely within hotspots highly exposed to climate change, with 13–29% of hotspots projected to experience high exposure to both stressors simultaneously. Most hotspots at highest risk occur in countries least able to take action. Our analysis highlights the need for global ambition and coordination to avoid catastrophic loss of tetrapod evolutionary heritage.
Scalable microbial strain inference in metagenomic data using StrainFacts
Authors: Smith Byron J. , Li Xiangpeng , Shi Zhou Jason , Abate Adam , Pollard Katherine S.
Published: February 2022

While genome databases are nearing a complete catalog of species commonly inhabiting the human gut, their representation of intraspecific diversity is lacking for all but the most abundant and frequently studied taxa. Statistical deconvolution of allele frequencies from shotgun metagenomic data into strain genotypes and relative abundances is a promising approach, but existing methods are limited by computational scalability. Here we introduce StrainFacts, a method for strain deconvolution that enables inference across tens of thousands of metagenomes. We harness a “fuzzy” genotype approximation that makes the underlying graphical model fully differentiable, unlike existing methods. This allows parameter estimates to be optimized with gradient-based methods, speeding up model fitting by two orders of magnitude. A GPU implementation provides additional scalability. Extensive simulations show that StrainFacts can perform strain inference on thousands of metagenomes and has comparable accuracy to more computationally intensive tools. We further validate our strain inferences using single-cell genomic sequencing from a human stool sample. Applying StrainFacts to a collection of more than 10,000 publicly available human stool metagenomes, we quantify patterns of strain diversity, biogeography, and linkage-disequilibrium that agree with and expand on what is known based on existing reference genomes. StrainFacts paves the way for large-scale biogeography and population genetic studies of microbiomes using metagenomic data.
Single-Cell Transcriptome Analysis Identifies Novel Biomarkers Involved in Major Liver Cancer Subtypes
Authors: Swain Asish Kumar , Pandey Prashant , Sera Riddhi , Yadav Pankaj
Published: February 2022

Liver cancers including hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are leading cause of death worldwide. Single-cell transcriptomics studies have vast potential in advancing our understanding of cancers by defining the cellular composition of different solid tumor types. We peformed an integrated analysis using single-cell RNA sequencing (scRNA-seq) data from cancerous and healthy liver tissues in order to identify the molecular progression and intercellular heterogeneity across cell types in the liver cancer. Moreover, we performed a subtype specific analyses, separately for HCC and ICC, to identify any molecular drivers uniquely associated with these liver cancers. The scRNA-seq dataset comprising 5 healthy controls and 19 liver cancer patients were collected from Human Cell Atlas and Gene Expression Omnibus (GEO), respectively. Our analyses confirmed upregulation of four previously known malignant cell marker genes, namely, EPCAM, KRT19, KRT7 and S100P in the cancerous liver cells. Of these, KRT7 gene has been reported to be associated with ovarian cancer in the past studies. Noteworthy, four marker genes specific to the G1/S (MCM5 and PCNA) and G2/M phases (HMGB2 and CKS2) of the cell cycle were upregulated in the cancerous liver cells. This indicates that these four marker genes are actively dividing in these two phases in cancerous cells as compared to normal liver cells. Our differential expression analysis identified 2 upregulated genes (ATF3 and S100A11) and 2 downregulated genes (FCN3 and FGB) in the liver cancer. Our subtype based differential expression analysis identified 4 genes (HSPA6, LMNA, ATP1B1 and DCXR) specific to HCC and 3 genes (HSPB1, APOC3 and APOA1) specific to ICC. CD4+ T-cell, Hepatocyte, neutrophil, mesenchymal cells and liver bud hepatic cells are the predominant cell-types in liver cells. Our scRNA-seq study revealed the mesenchymal cells as potential malignant cell types in liver cancers. Our work suggests future research on developing liver cancer subtypes therapies could target these cell types and associated molecular markers.
Melanoma Skin Cancer Detection using Deep Learning
Authors: Santos Dheiver
Published: February 2022

Data from the World Health Organization (WHO) indicate a worldwide occurrence of 2 to 3 million cases of non-melanoma skin cancer annually. The American Cancer Society estimates that the incidence reaches 5.4 million in the United States alone. In cases of fatal diseases, early detection received great attention from the population and the media due to the premise that the earlier a cancer is identified, the greater the chances of cure. It is to be believed that the application of automated methods will help in early diagnosis, especially with the set of images with a variety of diagnoses. Thus, this article presents a system for recognizing dermatological diseases through images with lesions, a machine intervention in contrast to conventional detection based on medical personnel. Our model is designed in three phases, committing to data collection and augmentation, model development, and finally, prediction. We used various AI algorithms such as ANN with image processing tools to form a better structure, leading to higher accuracy of 89%.

Contact

dheiver.santos@ictbridge.org, dheiver.santos@gmail.com
LGE-MRI for diagnosis of left atrial cardiomyopathy as identified in high-definition endocardial voltage and conduction velocity mapping
Authors: Nairn Deborah , Eichenlaub Martin , Müller-Edenborn Björn , Lehrmann Heiko , Nagel Claudia , Azzolin Luca , Luongo Giorgio , Figueras Ventura Rosa M. , Forcada Barbara Rubio , Colomer Anna Vallès , Arentz Thomas , Dössel Olaf , Loewe Axel , Jadidi Amir
Published: February 2022

Background

Electro-anatomical voltage, conduction velocity (CV) mapping and late-gadolinium-enhancement-magnetic-resonance-imaging (LGE-MRI) are different diagnostic modalities for atrial cardiomyopathy (ACM). However, discordances remain in the location and extent of detected ACM.

Objectives

(1) Comparison of ACM extent and location between current modalities. (2) Development of new estimated optimised image-intensity-thresholds (EOIIT) for LGE-MRI identifying patients with ACM.

Methods

Thirty-six ablation-naive persistent AF patients underwent LGE-MRI and high-definition electro-anatomical mapping in sinus rhythm. Significant ACM was defined as low-voltage-substrate (LVS) extent≥5% of the left atrium (LA) surface at <0.5 mV. LGE areas were classified using the Utah, image-intensity-ratio (IIR>1.20) and new EOIIT method for comparison to LVS and slow-conductionareas <0.2 m/s. ROC-analysis determined the LGE-extent enabling accurate diagnosis of ACM.

Results

The degree and distribution of detected pathological substrate varied significantly (p<0.001) across the mapping modalities: 3% (IQR 0-12%) of the LA displayed LVS<0.5 mV vs. 14% (3-25%) slow-conduction-areas<0.2 m/s vs. 16% (6-32%) LGE with Utah method vs. 17%(11-24%) using IIR>1.20, with enhanced discrepancies on posterior LA. A linear correlation was found between the OIIT and each patient’s mean blood pool intensity (R2=0.89, p<0.001). LGE-MRI-based ACM-diagnosis improved with the novel EOIIT (83% sensitivity, 88% specificity, AUC:0.94) in comparison to the Utah method (60% sensitivity, 75% specificity, AUC:0.76), and IIR>1.20 (58% sensitivity, 75% specificity, AUC:0.71)

Conclusion

Important discordances in distribution of pathological substrate exist between LA-LVS, CV and LGE-MRI, irrespective of the LGE-detection protocol that is used. However, the new EOIIT method improves LGE-MRI-based ACM-diagnosis in ablation-naive AF-patients.
A large outbreak of COVID-19 in a UK prison, October 2020 to April 2021
Authors: Adamson James P. , Smith Christopher , Pacchiarini Nicole , Connor Thomas Richard , Wallsgrove Janet , Coles Ian , Frost Clare , Edwards Angharad , Sinha Jaisi , Moore Catherine , Perrett Steph , Craddock Christie , Sawyer Clare , Waldram Alison , Barrasa Alicia , Thomas Daniel Rh. , Daniels Philip , Lewis Heather
Published: February 2022

Introduction

Prisons are susceptible to outbreaks. Control measures focusing on isolation and cohorting negatively affect wellbeing. We present an outbreak of COVID-19 in a large male prison in Wales, UK, October 2020 to April 2021, and discuss control measures.

Methods

We gathered case-information, including demographics, staff-residence postcode, resident cell number, work areas/dates, test results, staff interview dates/notes and resident prison-transfer dates. Epidemiological curves were mapped by prison location. Control measures included isolation (exclusion from work or cell-isolation), cohorting (new admissions and work-area groups), asymptomatic testing (case-finding), removal of communal dining and movement restrictions. Facemask use and enhanced hygiene were already in place. Whole genome sequencing (WGS) and interviews determined genetic relationship between cases plausibility of transmission.

Results

Of 453 cases, 53% (n=242) were staff, most aged 25-34 years (11.5% females, 27.15% males) and symptomatic (64%). Crude attack-rate was higher in staff (29%, 95%CI: 26-64%) than in residents (12%, 95%CI: 9-15%).

Conclusions

Whole genome sequencing can help differentiate multiple introductions from person-to-person transmission in prisons. It should be introduced alongside asymptomatic testing as soon as possible to control prison outbreaks. Timely epidemiological investigation, including data visualisation, allowed dynamic risk assessment and proportionate control measures, minimising reduction in resident welfare.
Evaluating binary classifiers: extending the Efficiency Index
Authors: Larner Andrew J
Published: February 2022

An “efficiency index” (EI) for the evaluation of binary classifiers was recently characterised, where EI is the ratio of classifier accuracy to inaccuracy. The purpose of this study was to further develop EI by substituting balanced accuracy and unbiased accuracy in place of accuracy, and their respective complements in place of inaccuracy, to construct balanced EI and unbiased EI measures. Additional investigations, using the dataset of a prospective pragmatic test accuracy study of a cognitive screening instrument, explored use of the log method to calculate confidence intervals for the various EI formulations; the dependence of EI formulations on prevalence; and comparison of EI formulations with analogous formulations based on the Identification Index (II), a previously described metric which is also based on accuracy and inaccuracy, where II is accuracy minus inaccuracy. EI formulations are shown to have advantages over II formulations, in particular their boundary values (0 and ∞) mean that negative values never occur, unlike the case for II, and the inflection point of 1 demarcates likelihood of correct versus incorrect classification.
Croup during the COVID-19 Omicron Variant Surge
Authors: Tunҫ Emine M. , Shin Cassandra Koid Jia , Usoro Etiowo , Thomas-Smith Siobhan E. , Trehan Indi , Migita Russell T. , Keilman Ashley E.
Published: February 2022

Croup is a common upper respiratory disease usually associated with parainfluenza virus, resulting in stridor, hoarse voice, barky cough, and variable respiratory distress. Here we examine the data at our center confirming a sharp increase in cases of croup associated with the Omicron variant. Data was retrospectively extracted from patient charts among those seen in the Emergency Department at Seattle Children’s Hospital. Inclusion criteria were patients who were assigned a diagnosis containing “croup” during either 5/30/2021-11/30/2021, a time period correlating with predominance of the COVID-19 Delta variant (B.1.617.2), or the initial phase of the Omicron variant surge (12/1/2021-1/15/2022). Contemporaneous publicly available local data on the proportion of SARS-CoV-2 samples in surrounding King County, Washington, with spike gene target failure on TaqPath PCR assays was used as a proxy for the proportion of infections caused by the Omicron variant. A total of 401 patients were diagnosed with croup during the Delta surge and 107 patients were diagnosed with croup during the Omicron surge. Patients who presented during the Omicron surge were more likely to test positive for COVID-19 (48.2% vs 2.8%, p < 0.0001). Children with a clinical diagnosis of croup during the Omicron surge were more likely to be prescribed racemic epinephrine as part of their care (21.5% vs 13.0%, p = 0.032). There were no differences in presenting age, rate of admission, rate of return to the ED within 72 hours, or admission among those who returned within 72 hours. During the Omicron surge, the incidence of croup nearly doubled compared to the rate in prior months, while at the same time the number of cases of parainfluenza virus identified decreased. Consistent with prior case reports, we have identified a sharp rise in cases of croup seen in our pediatric ED in parallel with the replacement of the SARS-CoV-2 Delta variant by Omicron as the dominant variant in our community.
Risk factors for severe COVID-19 differ by age: a retrospective study of hospitalized adults
Authors: Molani Sevda , Hernandez Patricia V. , Roper Ryan T. , Duvvuri Venkata R. , Baumgartner Andrew M. , Goldman Jason D. , Ertekin-Taner Nilüfer , Funk Cory C. , Price Nathan D. , Rappaport Noa , Hadlock Jennifer J.
Published: February 2022

Background

Risk stratification for hospitalized adults with COVID-19 is essential to inform decisions for individual patients and allocation of potentially scarce resources. So far, risk models for severe COVID outcomes have included age but have not been optimized to best serve the needs of either older or younger adults. Additionally, existing risk models have been limited to either small sample sizes, or modeling mortality over an entire hospital admission. Further, previous models were developed on data from early in the pandemic, before improvements in COVID-19 treatment, the SARS-CoV-2 delta variant, and vaccination. There remains a need for early, accurate identification of patients who may need invasive mechanical ventilation (IMV) or die, considering multiple time horizons.

Methods

This retrospective study analyzed data from 6,906 hospitalized adults with COVID-19 from a community health system with 51 hospitals and 1085 clinics across five states in the western United States. Risk models were developed to predict mechanical ventilation illness or death across one to 56 days of hospitalization, using clinical data collected available within the first hour after either admission with COVID-19 or a first positive SARS-CoV-2 test. The relative importance of predictive risk factors features for all models was determined using Shapley additive explanations.

Findings

The percentage of patients who required mechanical ventilation or died within seven days of admission to the hospital due to COVID-19 was 10.82%. For the seven-day interval, models for age ≥ 18 and < 50 years reached AUROC 0.80 (95% CI: 0.70-0.89) and models for age ≥ 50 years reached AUROC 0.83 (95% CI: 0.79-0.88). Models revealed differences in the statistical significance and relative predictive value of risk factors between older and younger patients, including age, BMI, vital signs, and laboratory results. In addition, sex and chronic comorbidities had lower predictive value than vital signs and laboratory results.

Interpretation

For hospitalized adults, baseline data that is readily available within one hour after hospital admission or a first positive inpatient SARS-CoV-2 test can predict critical illness within one day, and up to 56 days later. Further, the relative importance of risk factors differs between older and younger patients.
Recovery Time and Its Predictors among Women Admitted with Obstetric Fistula in Jimma University Medical Center Southwest, Ethiopia: A Retrospective Cohort Study
Authors: Areba Abriham Shiferaw , Akessa Geremew Muleta , Tadesse Megersa , Haile Arega , Abire Belayneh Genoro , Eritero Aneleay Cherinet , Gondol Belay Negassa , Akiso Denebo Ersulo , Kanno Girum Gebremeskel , Abame Desta Erkalo , Soboksa Negasa Eshete
Published: February 2022

Background

Obstetric fistula is one of the most shocking medical disabilities that women face as a result of problems caused by a lack of surgical intervention.

Methods

From January 2011 to February 2017, a retrospective analysis was undertaken on obstetric fistula participants who received undergone surgical repair at the Jimma University Medical Center.

Results

81.4% of fistula patients were reported to have recovered. The results of lognormal inverse-Gaussian frailty model revealed that weight ≥50kg (Ф= 0.86, 95% CI: 0.747, 0.99), divorced (Ф=1.2, 95% CI: 1.028, 1.413), urban residence (Ф= 1.56, 95% CI: 01.046, 2.317), urine incontinence >3 months (Ф=1.2, 95% CI: 1.056, 1.371), no antenatal care (Ф=1.189, 95% CI:1.023, 1.382), duration of labor <2days (Ф= 0.86, 95% CI: 0.758, 0.986), health center delivery (Ф= 0.76, 95% CI: 0.576, 0.989), vaginal delivery (Ф= 1.5, 95% CI: 1.125, 1.996), and partially damaged urethra (Ф=1.59, 95% CI: 1.168, 2.166) and recto-vaginal fistula(Ф= 0.735, 95%CI: 0.6045, 0.894) were associated with the recovery time.

Conclusion

Patients with a weight < 50 kg, delivery at a health center, labor lasting <2 days, urinary incontinence lasting <3 months, antenatal care follow-up, cesarean section delivery, urethra status not damaged, and recto-vaginal fistula had a faster recovery period.
Machine learning-based prediction of cognitive outcomes in de novo Parkinson’s disease
Authors: Harvey Joshua , Reijnders Rick A , Cavill Rachel , Duits Annelien , Köhler Sebastian , Eijssen Lars , Rutten Bart PF , Shireby Gemma , Torkamani Ali , Creese Byron , Leentjens Albert FG , Lunnon Katie , Pishva Ehsan
Published: February 2022

Cognitive impairment is a debilitating symptom in Parkinson’s disease (PD). We aimed to establish an accurate multivariate machine learning (ML) model to predict cognitive outcome in newly diagnosed PD cases from the Parkinson’s Progression Markers Initiative (PPMI). Annual cognitive assessments over an eight-year time span were used to define two cognitive outcomes of i) cognitive impairment, and ii) dementia conversion. Selected baseline variables were organized into three subsets of clinical, biofluid and genetic/epigenetic measures and tested using four different ML algorithms. Irrespective of the ML algorithm used, the models consisting of the clinical variables performed best and showed better prediction of cognitive impairment outcome over dementia conversion. We observed a marginal improvement in the prediction performance when clinical, biofluid, and epigenetic/genetic variables were all included in one model. Several cerebrospinal fluid measures and an epigenetic marker showed high predictive weighting in multiple models when included alongside clinical variables.
Idiopathic subglottic stenosis arises at the interface of host and pathogen
Authors: Gelbard Alexander , Shilts Meghan H. , Strickland Britton , Motz Kevin , Tsai Hsiu-Wen , Boone Helen , Drake Wonder P. , Wanjalla Celestine , Smith Paula Marincola , Brown Hunter , Ramierez Marisol , Atkinson James B. , Powell Jason , Simpson A John , Rajagopala Seesandra V. , Mallal Simon , Sheng Quanhu , Hillel Alexander T. , Das Suman R.
Published: February 2022

Idiopathic subglottic stenosis (iSGS) is a rare fibrotic disease of the proximal airway affecting adult Caucasian women nearly exclusively. Life-threatening ventilatory obstruction occurs secondary to pernicious subglottic mucosal scar. Diverse diseases in divergent organ systems are associated with fibrosis, suggesting common biologic mechanisms. One well characterized pathway is chronic inflammation secondary to pathogen. In the present study, we explored the role of the proximal airway microbiome in iSGS pathogenesis. In human samples, abundant bacteria are detectable in iSGS scar as well as in health subglottic controls or patients that developed subglottic stenosis following endotracheal intubation. Interestingly, the community structure of the iSGS proximal airway microbiome does not appear disrupted. Rather, in iSGS defects in the airway epithelial barrier allow displacement of the native microbiome into the immunoprivileged lamina propria and are associated with adaptive immune activation. Animal models of iSGS confirm both bacteria and an adaptive immune response are necessary for pathologic proximal airway fibrosis. Single cell RNA sequencing of the affected airway in iSGS offers an unbiased characterization of the observed epithelial barrier dysfunction. The airway scar in iSGS patients demonstrates basal cell depletion and epithelial acquisition of a mesenchymal phenotype. The epithelial alterations are associated with the observed microbiome displacement, dysregulated immune activation, and localized fibrosis. These results refine our understanding of iSGS and implicate shared pathogenic mechanisms with distal airway fibrotic diseases.
Single-cell genomics improves the discovery of risk variants and genes of Atrial Fibrillation
Authors: Selewa Alan , Luo Kaixuan , Wasney Michael , Smith Linsin , Sun Xiaotong , Tang Chenwei , Eckart Heather , Moskowitz Ivan P. , Basu Anindita , He Xin , Pott Sebastian
Published: February 2022

Genome-wide association studies (GWAS) have linked hundreds of loci to cardiac diseases. However, in most loci the causal variants and their target genes remain unknown. We developed a combined experimental and analytical approach that integrates single cell epigenomics with GWAS to prioritize risk variants and genes. We profiled accessible chromatin in single cells obtained from human hearts and leveraged the data to study genetics of Atrial Fibrillation (AF), the most common cardiac arrhythmia. Enrichment analysis of AF risk variants using cell-type-resolved open chromatin regions (OCRs) implicated cardiomyocytes as the main mediator of AF risk. We then performed statistical fine-mapping, leveraging the information in OCRs, and identified putative causal variants in 122 AF-associated loci. Taking advantage of the fine-mapping results, our novel statistical procedure for gene discovery prioritized 46 high-confidence risk genes, highlighting transcription factors and signal transduction pathways important for heart development. In summary, our analysis provides a comprehensive map of AF risk variants and genes, and a general framework to integrate single-cell genomics with genetic studies of complex traits.
Clustering analysis based on PiCCO parameters in patients with septic shock
Authors: Shen Yanfei , Hu Caibao , Cai Guolong , Yan Jing
Published: February 2022

The current study identified three septic shock phenotypes according to the pulse index continuous cardiac output parameters: Phenotype-1: normal cardiac output and vascular resistance, high blood volume; Phenotype-2: low cardiac output, normal blood volume, and high vascular resistance. Phenotype-3: normal vascular resistance and blood volume, high cardiac output. The mortality was significantly high in phenotype-1, but comparable between phenotype-2 and phenotype-3 (13/17 (76.4) vs. 13/35 (37.1) vs. 16/46 (34.7), p <0.001). Compared to phenotype 1 and 3, phenotype 2 had a higher AKI incidence and higher creatinine level at discharge.
Estimation and interpretation of vaccine efficacy in COVID-19 randomized clinical trials
Authors: Michiels Hege , Vandebosch An , Vansteelandt Stijn
Published: February 2022

An exceptional effort by the scientific community has led to the development of multiple vaccines against COVID-19. Efficacy estimates for these vaccines have been widely communicated to the general public, but are nonetheless challenging to compare because they are based on phase 3 trials that differ in study design, definition of vaccine efficacy and in the handling of cases arising shortly after vaccination. In this work, we investigate the impact of these choices on vaccine efficacy estimates, both theoretically and by re-analyzing the Janssen and Pfizer COVID-19 trial data under a uniform protocol. We moreover study the causal interpretation that can be assigned to per-protocol analyses typically performed in vaccine trials. Finally, we propose alternative estimands to measure the intrinsic vaccine efficacy in settings with delayed immune response.
Changes to hypothalamic volume and associated subfields during gender-affirming hormone treatment in gender dysphoria
Authors: Konadu ME , Reed MB , Kaufmann U , Handschuh PA , Spies M , Spurny-Dworak B , Klöbl M , Ritter V , Godbersen GM , Seiger R , Baldinger-Melich P , Kranz GS , Lanzenberger R
Published: February 2022

1.

Sex steroid hormones influence hypothalamic micro- and macrostructure in humans and animal models. Neuroimaging studies have suggested that estrogen and anti-androgen treatment decreases volumes of multiple cortical and subcortical brain areas in transgender individuals, including total hypothalamus volume. Here, we aim to further explore potential effects of gender-affirming hormone treatment (GHT) in transgender individuals on hypothalamic volume by providing additional information on hypothalamic subfields.

38 transgender men (TM) and 15 transgender women (TW), with gender dysphoria (DSM-5), as well as 32 cisgender women (CW) and 21 cisgender men (CM) underwent two magnetic resonance imaging (MRI) measurements with an interval of at least four months (median interval TM= 134.5 days (interquartile range (IQR): 126-152.25); TW= 149 days (IQR: 126-178.5); CW= 147 days (IQR: 139.75-170.5); CM= 146 days (IQR: 132-247)) between both sessions. In transgender individuals GHT, consisting of estrogen and anti-androgen treatment in TW and testosterone treatment in TM, was initiated directly after the first measurement. To assess how GHT interacts with hypothalamic structures, the hypothalamus and its subunits were segmented using FreeSurfer. Subject group x time interaction effects were evaluated using repeated measures ANCOVA models. The Bonferroni method was used to correct for multiple comparisons.

Significant decreases of total hypothalamic volume and associated subunits were detected in TW after estrogen and anti-androgen treatment compared to cisgender groups. Effects were found in the total hypothalamus volume (pcorr= 0.001), the left and right hypothalamus (pcorr= 0.002), the inferior tubular subunit bilaterally (right: pcorr= 0.001; left: pcorr= 0.001), the left superior tubular subunit (pcorr= 0.003) the right anterior inferior subunit (pcorr= 0.002), as well as the right anterior superior subunit (pcorr= 0.0002) of the hypothalamus.

Here, we observed significant volumetric effects on the adult human hypothalamus after an interval of at least four months of estrogen and anti-androgen treatment in TW and added knowledge on associated subfields. Further studies investigating influences of sex steroid hormones on brain structure and functional connections are still needed.
Accessing Medical Care for Infertility: A Study of Women in Mexico
Authors: Farland Leslie V. , Khan Sana , Missmer Stacey A. , Stern Dalia , Lopez-Ridaura Ruy , Chavarro Jorge E. , Catzin-Kuhlmann Andres , Sanchez-Serrano Ana Paola , Rice Megan S. , Lajous Martín
Published: February 2022

Background

Investigating the burden of access to infertility treatment has primarily been conducted in high-income countries, with little known for low- and middle-income countries, which comprise 80% of the world’s population. The objective of this study was to investigate access to infertility care in Mexico.

Methods

This was a cross-sectional analysis in the Mexican Teachers’ Cohort (MTC), a prospective cohort study of 115,307 Mexican female public school teachers from 12 states in Mexico. Log-binomial models, adjusted for age, hormonal contraceptive use, teaching in a rural school, and speaking an indigenous language, were used to estimate the prevalence ratio (PR) and 95% confidence intervals (95% CI) of accessing medical care for infertility among women reporting a history of infertility.

Results

19,580 (17%) participants reported a history of infertility. Of those who experienced infertility, 12,470 (63.7%) reported seeking medical care for infertility, among whom 8,467 (67.9%) reported undergoing fertility treatments. Among women who reported a history of infertility, women who taught in a rural school (PR:0.95;0.92-0.97), spoke an indigenous language (PR:0.88; 0.84-0.92), or had less than a university degree (PR:0.93; 0.90-0.97) were less likely to access medical care for fertility. Women who had ever had a mammogram (PR:1.07; 1.05-1.10), had a pap-smear in the past year (PR:1.08;1.06-1.10), or who had utilized private healthcare regularly or in times of illness were more likely to access medical care for fertility.

Conclusion

Utilization of infertility care varied by demographic and access characteristics, including speaking an indigenous language, teaching in a rural school, and having a private healthcare provider.
Global and local ancestry modulateAPOEassociation with Alzheimer’s neuropathology and cognitive outcomes in an admixed sample
Authors: Naslavsky Michel Satya , Suemoto Claudia K. , Brito Luciano Abreu , Scliar Marília Oliveira , Ferretti-Rebustini Renata Eloah , Rodriguez Roberta Diehl , Leite Renata E. P. , Araujo Nathalia Matta , Borda Victor , Tarazona-Santos Eduardo , Jacob-Filho Wilson , Pasqualucci Carlos , Nitrini Ricardo , Yaffe Kristine , Zatz Mayana , Grinberg Lea T.
Published: February 2022

Dementia is more prevalent in Blacks than in Whites, likely due to a combination of environmental and biological factors. Paradoxically, clinical studies suggest an attenuation ofAPOEε4 risk of dementia in African ancestry (AFR), but lack of neuropathological data preclude the interpretation of the biological factors underlying these findings, including the association betweenAPOEε4 risk and Alzheimer’s disease (AD) pathology, the most frequent cause of dementia. We investigated the interaction between African ancestry, AD-related neuropathology,APOE genotype, and functional cognition in a postmortem sample of 400 individuals with a range of AD pathology severity and lack of comorbid neuropathology from a cohort of community-dwelling, admixed Brazilians. Increasing proportions of African ancestry (AFR) correlated with a lower burden of neuritic plaques (NP). However, for individuals with high levels of NP and neurofibrillary tangles (NFT), AFR proportion was associated with worse Clinical Dementia Rating sum of boxes (CDR-SOB). AmongAPOEε4 carriers, the association between AFR proportion and CDR-SOB disappeared.APOElocal ancestry inference of a subset of 309 individuals revealed that, inAPOEε4 noncarriers, non-EuropeanAPOEbackground associated with lower NP burden, but with worst cognitive outcomes compared to EuropeanAPOEwhen adjusting by the similar NP burden. Finally,APOEε4 was associated with worse AD neuropathological burden only in a EuropeanAPOEbackground.APOEgenotype and its association with AD neuropathology and clinical pattern are highly influenced by ancestry, with AFR associated with lower NP burden and attenuatedAPOE4risk compared to European ancestry.
PSMA-Hornet: fully-automated, multi-target segmentation of healthy organs in PSMA PET/CT images
Authors: Klyuzhin Ivan S. , Chaussé Guillaume , Bloise Ingrid , Ferres Juan Lavista , Uribe Carlos , Rahmim Arman
Published: February 2022

Prostate-specific membrane antigen (PSMA) PET imaging represents a valuable source of information reflecting disease stage, response rate, and treatment optimization options, particularly with PSMA radioligand therapy. Quantification of radiopharmaceutical uptake in healthy organs from PSMA images has the potential to minimize toxicity by extrapolation of the radiation dose delivery towards personalization of therapy. Furthermore, factors affecting biodistribution of PSMA radiotracers that remain mostly unknown can be investigated by analyzing PSMA PET images with segmented organs. However, segmentation and quantification of uptake in organs requires labor-intensive organ delineations that are often not feasible in the clinic nor scalable for large clinical trials. In this work we have developed and tested the PSMA Healthy organ segmentation network (PSMA-Hornet), a fully-automated deep neural net for effective and robust segmentation and labelling of 14 healthy organs representing the normal biodistribution of [18F]DCFPyL on PET/CT images.

Methods

The study used manually-segmented [18F]DCFPyL PET/CT images from 100 subjects, and 526 similar images without segmentations. The unsegmented images were used for self-supervised model pretraining. For supervised training, 3-fold cross-validation was used to evaluate the network performance, with 85 subjects reserved for model training, 5 for validation, and 10 for testing. Image segmentation and quantification metrics were evaluated on the test set with respect to manual segmentations by a nuclear medicine physician.

Results

With our best model, the lowest mean Dice coefficient on the test set was 0.826 for the sublingual gland, and the highest was 0.964 for liver. The highest mean error in tracer uptake quantification was 13.9% in the sublingual gland. Self-supervised pretraining improved training convergence, train-to-test generalization, and segmentation quality. In addition, we found that a multi-target network produced significantly higher segmentation accuracy than single-organ networks.

Conclusion

The developed network can be used to automatically obtain high-quality organ segmentations for PSMA image analysis tasks. It can be used to reproducibly extract imaging data, and holds promise for clinical applications such as personalized radiation dosimetry and improved radioligand therapy.