bluuebunny/crossref_metadata_2025_split huggingface dataset:
General surgeon involvement in the care of patients designated with an American Association for the Surgery of Trauma–endorsed ICD-10-CM emergency general surgery diagnosis code in Wisconsin
Authors: Ingraham Angela , Schumacher Jessica , Fernandes-Taylor Sara , Yang Dou-Yan , Godat Laura , Smith Alan , Barbosa Ronald , Cribari Chris , Salim Ali , Schroeppel Thomas , Staudenmayer Kristan , Crandall Marie , Utter Garth ,   on behalf of the AAST Committee on Patient Assessment
Published: August 2021

BACKGROUND
The current national burden of emergency general surgery (EGS) illnesses and the extent of surgeon involvement in the care of these patients remain largely unknown. To inform needs assessments, research, and education, we sought to: (1) translate previously developed International Classification of Diseases (ICD), 9th Revision, Clinical Modification (ICD-9-CM) diagnosis codes representing EGS conditions to ICD 10th Revision, CM (ICD-10-CM) codes and (2) determine the national burden of and assess surgeon involvement across EGS conditions.

METHODS
We converted ICD-9-CM codes to candidate ICD-10-CM codes using General Equivalence Mappings then iteratively refined the code list. We used National Inpatient Sample 2016 to 2017 data to develop a national estimate of the burden of EGS disease. To evaluate surgeon involvement, using Wisconsin Hospital Association discharge data (January 1, 2016 to June 30, 2018), we selected adult urgent/emergent encounters with an EGS condition as the principal diagnosis. Surgeon involvement was defined as a surgeon being either the attending provider or procedural physician.

RESULTS
Four hundred and eighty-five ICD-9-CM codes mapped to 1,696 ICD-10-CM codes. The final list contained 985 ICD-10-CM codes. Nationally, there were 2,977,843 adult patient encounters with an ICD-10-CM EGS diagnosis. Of 94,903 EGS patients in the Wisconsin Hospital Association data set, most encounters were inpatient as compared with observation (75,878 [80.0%] vs. 19,025 [20.0%]). There were 57,780 patients (60.9%) that underwent any procedure. Among all Wisconsin EGS patients, most had no surgeon involvement (64.9% [n = 61,616]). Of the seven most common EGS diagnoses, surgeon involvement was highest for appendicitis (96.0%) and biliary tract disease (77.1%). For the other five most common conditions (skin/soft tissue infections, gastrointestinal hemorrhage, intestinal obstruction/ileus, pancreatitis, diverticular disease), surgeons were involved in roughly 20% of patient care episodes.

CONCLUSION
Surgeon involvement for EGS conditions ranges from highly likely (appendicitis) to relatively unlikely (skin/soft tissue infections). The wide range in surgeon involvement underscores the importance of multidisciplinary collaboration in the care of EGS patients.

LEVEL OF EVIDENCE
Prognostic/epidemiological, Level III.
Rib Fracture Frailty Index: A risk stratification tool for geriatric patients with multiple rib fractures
Authors: Choi Jeff , Marafino Ben J. , Vendrow Edward B. , Tennakoon Lakshika , Baiocchi Michael , Spain David A. , Forrester Joseph D. 
Published: August 2021

BACKGROUND
Rib fractures are consequential injuries for geriatric patients (age, ≥65 years). Although age and injury patterns drive many rib fracture management decisions, the impact of frailty—which baseline conditions affect rib fracture-specific outcomes—remains unclear for geriatric patients. We aimed to develop and validate the Rib Fracture Frailty (RFF) Index, a practical risk stratification tool specific for geriatric patients with rib fractures. We hypothesized that a compact list of frailty markers can accurately risk stratify clinical outcomes after rib fractures.

METHODS
We queried nationwide US admission encounters of geriatric patients admitted with multiple rib fractures from 2016 to 2017. Partitioning around medoids clustering identified a development subcohort with previously validated frailty characteristics. Ridge regression with penalty for multicollinearity aggregated baseline conditions most prevalent in this frail subcohort into RFF scores. Regression models with adjustment for injury severity, sex, and age assessed associations between frailty risk categories (low, medium, and high) and inpatient outcomes among validation cohorts (odds ratio [95% confidence interval]). We report results according to Transparent Reporting of Multivariable Prediction Model for Individual Prognosis guidelines.

RESULTS
Development cohort (n = 55,540) cluster analysis delineated 13 baseline conditions constituting the RFF Index. Among external validation cohort (n = 77,710), increasing frailty risk (low [reference group], moderate, high) was associated with stepwise worsening adjusted odds of mortality (1.5 [1.2–1.7], 3.5 [3.0–4.0]), intubation (2.4 [1.5–3.9], 4.7 [3.1–7.5]), hospitalization ≥5 days (1.4 [1.3–1.5], 1.8 [1.7–2.0]), and disposition to home (0.6 [0.5–0.6], 0.4 [0.3–0.4]). Locally weighted scatterplot smoothing showed correlations between increasing RFF scores and worse outcomes.

CONCLUSION
The RFF Index is a practical frailty risk stratification tool for geriatric patients with multiple rib fractures. The mobile app we developed may facilitate rapid implementation and further validation of RFF Index at the bedside.

LEVEL OF EVIDENCE
Prognostic study, level III.
Survivors of SARS-CoV-2 Infection Show Neuropsychiatric Sequelae Measured by Surveys, Neurocognitive Testing, and Magnetic Resonance Imaging: Preliminary Results
Authors: Hack Laura M. , Brawer Jacob , Chesnut Megan , Zhang Xue , Wintermark Max , Jiang Bin , Grant Philip , Bonilla Hector , Stetz Patrick , Yesavage Jerome A. , Subramanian Aruna , Williams Leanne M. 
Published: August 2021

AbstractA significant number of individuals experience physical, cognitive, and mental health symptoms in the months after acute infection with SARS-CoV-2, the virus that causes COVID-19. This study assessed depressive and anxious symptoms, cognition, and brain structure and function in participants with symptomatic COVID-19 confirmed by PCR testing (n=100) approximately three months following infection, leveraging self-report questionnaires, objective neurocognitive testing, and structural and functional neuroimaging data. Preliminary results demonstrated that over 1/5 of our cohort endorsed clinically significant depressive and/or anxious symptoms, and >40% of participants had cognitive impairment on objective testing across multiple domains, consistent with ‘brain-fog’. While depression and one domain of quality of life (physical functioning) were significantly different between hospitalized and non-hospitalized participants, anxiety, cognitive impairment, and most domains of functioning were not, suggesting that the severity of SARS-CoV-2 infection does not necessarily relate to the severity of neuropsychiatric outcomes and impaired functioning in the months after infection. Furthermore, we found that the majority of participants in a subset of our cohort who completed structural and functional neuroimaging (n=15) had smaller olfactory bulbs and sulci in conjunction with anosmia. We also showed that this subset of participants had dysfunction in attention network functional connectivity and ventromedial prefrontal cortex seed-based functional connectivity. These functional imaging dysfunctions have been observed previously in depression and correlated with levels of inflammation. Our results support and extend previous findings in the literature concerning the neuropsychiatric sequelae associated with long COVID. Ongoing data collection and analyses within this cohort will allow for a more comprehensive understanding of the longitudinal relationships between neuropsychiatric symptoms, neurocognitive performance, brain structure and function, and inflammatory and immune profiles.
Unexplained longitudinal variability in COVID-19 antibody status by Lateral Flow Immuno-Antibody testing
Authors: Davis Katrina , Oetzmann Carolin , Carr Ewan , Lavelle Grace , Leightley Daniel , Malim Michael , Vitiello Valentina , Wickersham Alice ,   KCL-CHECK team, Razavi Reza , Hotopf Matthew 
Published: August 2021

BackgroundCOVID-19 antibody testing allows population studies to classify participants by previous SARS-CoV-2 infection status. Home lateral flow immune-antibody testing devices offer a very convenient way of doing this, but relatively little is known about how measurement and antibody variability will affect consistency in results over time. We examined consistency by looking at the outcome of two tests three months apart while COVID-19 infection rates were low (summer 2020 in the UK).MethodsThe KCL-Coronavirus Health and Experiences in Colleagues at King’s is an occupational cohort of staff and postgraduate research students. Lateral flow immune-antibody testing kits were sent to participant’s homes in late June 2020 and late September 2020. Participants also completed regular surveys that included asking about COVID-19 symptoms and whether they thought they had been infected.ResultsWe studied 1489 participants returned valid results in both June and September (59% of those sent kits). Lateral flow immune-antibody test was positive for 7.2% in June and 5.9% in September, with 3.9% positive in both. Being more symptomatic or suspecting infection increased the probability of ever being positive. Of those positive in June, 46% (49/107) were negative in September (seroreversion), and this was similar regardless of symptom characteristics, suspicion, and timing of possible infection. A possible outlier was those aged over 55 years, where only 3 of 13 (23%) had seroreversion.DiscussionThese results do not follow the pattern reported from studies specifically designed to monitor seropositivity, which have found greater consistency over time and the influence of presence, timing and severity of symptoms on seroreversion. We suggest several factors that may have contributed to this difference: our low bar in defining initial seropositivity (single test); a non-quantitative test known to have relatively low sensitivity; participants carrying out testing. We would encourage other studies to use these real-world performance characteristics alongside those from laboratory studies to plan and analyse any antibody testing.
The impact of studies with no events in both arms on meta-analysis of rare events: a simulation study using generalized linear mixed model
Authors: Xu Chang , Lin Lifeng 
Published: August 2021

AbstractObjectiveThe common approach to meta-analysis with double-zero studies is to remove such studies. Our previous work has confirmed that exclusion of these studies may impact the results. In this study, we undertook extensive simulations to investigate how the results of meta-analyses would be impacted in relation to the proportion of such studies.MethodsTwo standard generalized linear mixed models (GLMMs) were employed for the meta-analysis. The statistical properties of the two GLMMs were first examined in terms of percentage bias, mean squared error, and coverage. We then repeated all the meta-analyses after excluding double-zero studies. Direction of estimated effects and p-values for including against excluding double-zero studies were compared in nine ascending groups classified by the proportion of double-zero studies within a meta-analysis.ResultsBased on 50,000 simulated meta-analyses, the two GLMMs almost achieved unbiased estimation and reasonable coverage in most of the situations. When excluding double-zero studies, 0.00% to 4.47% of the meta-analyses changed the direction of effect size, and 0.61% to 8.78% changed direction of the significance of p-value. When the proportion of double-zero studies increased in a meta-analysis, the probability of the effect size changed the direction increased; when the proportion was about 40% to 60%, it has the largest impact on the change of p-values.ConclusionDouble-zero studies can impact the results of meta-analysis and excluding them may be problematic. The impact of such studies on meta-analysis varies by the proportion of such studies within a meta-analysis.
Comparative Analysis of the Chemotherapy-related Cognitive Impairments in Patients with Breast Cancer: a Community-based Research
Authors: Owrangi Maryam , Gholamzadeh Mohammad Javad , Gharamaleki Maryam Vasaghi , Mousavi Seyedeh Zahra , Kamali Ali-Mohammad , Dehghani Mehdi , Chakrabarti Prasun , Nami Mohammad 
Published: August 2021

AbstractPurposeWith increasing breast cancer (BC) survival rates, the survivors’ quality of life (QoL) has become an important issue. Chemotherapy-induced cognitive impairment, known as “chemobrain” has been addressed recently. Therefore, cognitive function as one of the determinants of QoL should be considered while prescribing chemotherapeutics. In this study, we aimed to evaluate the effects of two common chemotherapy regimens on BC survivors’ cognition.MethodsThe participants comprised 35 BC patients who underwent two common chemotherapy regimens, AC-T and TAC, and 24 matched healthy volunteers. The participants were assessed regarding anxiety, depression, general health status, and cognitive function including aspects of concentration, verbal ability, reasoning, memory, and visuospatial skill through Addenbrooke’s Cognitive Examination (ACE-P) and Cambridge Brain Science (CBS) tests.ResultsRegarding depression and anxiety, there were no significant differences between the three groups. However, BC patients significantly complained of chronic fatigue compared to healthy volunteers (P-value = 0.027). Besides, ACE-P revealed the language domain to be affected in the AC-T group in comparison with the TAC-treated cases (P-value = 0.036). Moreover, the patients receiving the AC-T regimen had worse performance in visuospatial working memory and attention domains compared to the TAC group considering CBS tests (P-value = 0.031 and 0.008, respectively).ConclusionThe results represent the AC-T regimen to be more toxic than the TAC in domains of language, concentration, and visuospatial working memory.Implications for cancer survivorsThe AC-T regimen should be prescribed with caution in BC patients suffering from baseline cognitive impairments to improve post-chemotherapy QoL.Graphical Abstract
Disruption of spatiotemporal clustering in dengue cases bywMelWolbachiain Yogyakarta, Indonesia
Authors: Dufault Suzanne M. , Tanamas Stephanie K. , Indriani Citra , Utarini Adi , Ahmad Riris Andono , Jewell Nicholas P. , Simmons Cameron P. , Anders Katherine L. 
Published: August 2021

AbstractDengue exhibits focal clustering in households and neighborhoods, driven by local mosquito population dynamics, human population immunity, and fine scale human and mosquito movement. We tested the hypothesis that spatiotemporal clustering of homotypic dengue cases is disrupted by introduction of the arbovirus-blocking bacteriumWolbachia(wMel-strain) into theAedes aegyptimosquito population. We analysed 318 serotyped and geolocated dengue cases (and 5,921 test-negative controls) from a randomized controlled trial in Yogyakarta, Indonesia ofwMel deployments. We find evidence of spatial clustering up to 300m among the 265 dengue cases (3,083 controls) in the untreated trial arm. Participant pairs enrolled within 30 days and 50m had a 4.7-fold increase (compared to 95% CI on permutation-based null distribution: 0.1, 1.2) in the odds of being homotypic (i.e. potentially transmission-related) as compared to pairs occurring at any distance. In contrast, we find no evidence of spatiotemporal clustering among the 53 dengue cases (2,838 controls) resident in thewMel-treated arm. Introgression ofwMelWolbachiaintoAedes aegyptimosquito populations interrupts focal dengue virus transmission leading to reduced case incidence; the true intervention effect may be greater than the 77% efficacy measured in the primary analysis of the Yogyakarta trial.
COVID-19 in Scottish care homes: A metapopulation model of spread among residents and staff
Authors: Baister Matthew , McTaggart Ewan , McMenemy Paul , Megiddo Itamar , Kleczkowski Adam 
Published: August 2021

AbstractCare homes in the UK were disproportionately affected by the first wave of the COVID-19 pandemic, accounting for almost half of COVID-19 deaths over the course of the period from 6th March – 15th June 2020. Understanding how infectious diseases establish themselves throughout vulnerable communities is crucial for minimising deaths and lowering the total stress on the National Health Service (NHS Scotland). We model the spread of COVID-19 in the health-board of NHS Lothian, Scotland over the course of the first wave of the pandemic with a compartmental Susceptible - Exposed - Infected reported - Infected unreported - Recovered - Dead (SEIARD), metapopulation model. Care home residents, care home workers and the rest of the population are modelled as subpopulations, interacting on a network describing their mixing habits. We explicitly model the outbreak’s reproduction rate and care home visitation level over time for each subpopulation, and execute a data fit and sensitivity analysis, focusing on parameters responsible for intra-subpopulation mixing: staff sharing, staff shift patterns and visitation. The results suggest that hospital discharges were not predominantly responsible for the early outbreak in care homes, and that only a few such cases led to infection seeding in care homes by the 6th of March Sensitivity analysis show the main mode of entry into care homes are infections by staff interacting with the general population. Visitation (before cancellation) and staff sharing were less significant in affecting outbreak size. Our model suggests that focusing on the protection and monitoring of staff, followed by reductions in staff sharing and quick cancellations of visitation can significantly reduce future infection attack rates of COVID-19 in care homes.
Nomogram-Based Prognostic Model to predict the High blood pressure in Children and Adolescents —— Finding from 342,736 individual in China
Authors: Liang Jing-hong , Zhao Yu , Chen Yi-can , Huang Shan , Zhang Shu-xin , Jiang Nan , Kakaer Aerziguli , Chen Ya-jun 
Published: August 2021

AbstractBackgroundPredicting the potential risk factors of High blood pressure(HBP) among children and adolescents is still a knowledge gap. Our study aimed to establish and validate a nomogram-based model for identifying children and adolescents at risk of developing HBP based on a population-based prospective study.MethodsHypertension was defined as systolic blood pressure or diastolic blood pressure above 95th percentile, using age, gender and height-specific cut-points. Penalized regression with Lasso was used to identify the strongest predictors of hypertension. Internal validation was conducted by 5-fold cross-validation and bootstrapping approach. The predictive variables were identified along with the advanced nomogram plot by conducting univariate and multivariate logistic regression analyses. A nomogram was constructed by training group comprised of 239,546(69.89%)participants and subsequently validated by externally group with 103,190(30.11%)participants.ResultsOf 342,736 children and adolescents, a total of 55,480(16.19%) youths were identified with HBP with mean age 11.51±1.45 year and 183,487 were boys(53.5%). Nine significant relevant predictors were identified including: age, gender, weight status, birthweight, breastfeeding, gestational hypertension, family history of obesity, family history of hypertension and physical activity. An acceptable discrimination[Area under the receiver operating characteristic curve(AUC):0.742(Development group), 0.740(Validation group)] and good calibration(Hosmer and Lemeshow statistics, P > 0.05) were observed in our models. An available web-based nomogram was built online.ConclusionsThis model composed of age, gender, early life factors, family history of disease, and lifestyle factors may predict the risk of HBP among children and adolescents, which has developed a promising nomogram that may aid in more accurately for identifying the HBP among youths in primary care.Funding SourcesThe work was supported by the National Natural Science Foundation of China (No. 81673193).
A community based case-control study to determine the risk factors of dengue fever in Bangladesh
Authors: Rahman Md. Sahidur , Mehejabin Fatema , Rashid Rumana 
Published: August 2021

AbstractIn a tropical country like Bangladesh where the climatic condition favors the growth of Aedes mosquito vectors, the success of dengue prevention depends largely on the proper identification and controlling of the socio-demographic and lifestyle-related risk factors. A case-control study including 150 cases and 150 controls were conducted aimed to explore the potential risk and protective factors and their association with dengue virus infection in the Chattogram district of Bangladesh. Cases were confirmed for dengue patients admitted in Chattogram medical college hospital and Bangladesh institute of tropical and infectious diseases during August and September 2019. Whereas, controls were non-dengue patients admitted in other departments of the same hospitals through gender age and location matching. The questionnaire data were collected through telephone-based interviews which included information regarding general demography, daily life activities, housing with its surroundings status. Chi-square and binary logistic regression were performed for identifying potential risk factors and their association with the occurrences of dengue fever.The study found that travel history to the high incidence area, the place of staying most of the time, living in 21 to 40 years old houses, and the temporary residence of the city were statistically significant risk factors for getting the dengue infection. On contrary, Quality of indoor daylight, ventilation, bus stand/garage, stagnant water, and any construction site around 250 meters of the house did not show significant association with dengue fever.
Single-Cell Multiome Sequencing Clarifies Enteric Glial Cell Diversity and Identifies an Intraganglionic Population Poised for Neurogenesis
Authors: Guyer Richard A. , Stavely Rhian S. , Robertson Keiramarie , Bhave Sukhada , Hotta Ryo , Kaltschmidt Julia A. , Goldstein Allan M. 
Published: August 2021

SummaryThe enteric nervous system (ENS) consists of glial cells (EGCs) and neurons derived from neural crest precursors. EGCs retain capacity for large-scale neurogenesis in culture, and in vivo lineage tracing has identified neurons derived from glial cells in response to inflammation. We thus hypothesize that EGCs possess a chromatin structure poised for neurogenesis. We use single-cell multiome sequencing to assess EGCs undergoing spontaneous neurogenesis in culture, as well as freshly isolated small intestine myenteric plexus EGCs. Cultured EGCs maintain open chromatin at genomic loci accessible in neurons, and neurogenesis from EGCs involves dynamic chromatin rearrangements with a net decrease in accessible chromatin. Multiome analysis of freshly isolated EGCs reveals transcriptional diversity, with open chromatin at neuron-associated genomic elements. A subset of EGCs, highly enriched within the myenteric ganglia, has a gene expression program and chromatin state consistent with neurogenic potential.