bluuebunny/crossref_metadata_2025_split huggingface dataset:
SELF-RATED HEALTH IN INFLAMMATORY BOWEL DISEASE CORRELATES WITH ANXIETY, DEPRESSION, CATASTROPHIC THINKING, AND DISEASE SEVERITY
Authors: Palmer Brooke , Petrik Megan , Tomasino Kathryn 
Published: January 2022

Abstract

BACKGROUND
The construct of self-rated health (SRH) has been found to be strongly associated with objective markers of health status (e.g., disease progression, healthcare utilization, mortality) in both general and disease-specific populations. For individuals with inflammatory bowel disease (IBD), SRH correlates with symptom severity and health-related quality of life. SRH is typically influenced by one’s disease activity, functional status, and coping style, but there is scant research investigating how specific psychological constructs are related to SRH in patients with IBD. This study aimed to examine how SRH correlates with anxiety, depression, and catastrophic thinking patterns. If clarified, results can inform assessment and intervention efforts to improve quality of life in IBD.

METHODS
Participants were recruited from a gastroenterology clinic in a midwestern academic medical center. Questionnaires included: Hospital Anxiety and Depression Scale (HADS), GI-Cognitions Questionnaire, and the 36-Item Short Form Survey (SF-36). SRH was measured from SF-36 item 1, which asked participants to rate their health on a five-point scale ranging from excellent to poor. Physicians also completed a clinician rating of IBD activity (Partial Mayo Index [PMI] for ulcerative colitis and Harvey Bradshaw Index [HBI] for Crohn’s disease). Pearson correlation analyses were conducted comparing SRH ratings to psychological variables and IBD activity.

RESULTS
A total of 117 adults participated (mean age = 38.5 years, 59% female; see Table 1 for demographics). Higher ratings of anxiety, depression, somatization, and catastrophic thinking patterns about GI symptoms were significantly correlated with poorer SRH. There was a significant negative correlation between SRH and IBD activity for patients with Crohn’s disease, but not ulcerative colitis. This is likely due to a restricted range of possible scores on the PMI. Table 2 displays correlation analyses.

DISCUSSION
Results highlight the potential utility of SRH to identify other patient concerns (e.g., anxiety, depression) and allow an additional avenue for medical providers to consider when assessing patients’ illness experience. Assessing SRH could be part of a step-wise screening and referral process in GI clinics. For example, it may be fruitful to assess SRH in a standardized manner such as using the SF-36 item 1, and when poor SRH is detected, additional screening may be warranted such as using the PHQ-9 or GAD-7. If scores are elevated, a referral to a mental health provider with training in psychogastroenterology may help identify psychological factors that could be targeted via behavioral interventions to improve quality of life and coping with illness. Additional clinical recommendations will be discussed.
PREDICTIVE PERFORMANCE OF DIFFERENT POPULATION PHARMACOKINETIC MODELS IN A REAL-WORLD COHORT OF CROHN’S DISEASE PATIENTS
Authors: Samuels Abigail , Punt Nieko , Reifenberg Jack , Mizuno Tomoyuki , Colman Ruben , Menke Frank , Vogt Aaron , Vinks Alexander , Minar Phillip 
Published: January 2022

Abstract

INTRODUCTION
We have previously published the results of an infliximab (IFX) population PK model in children and young adults with Crohn’s disease (CD). We found that prediction accuracy was improved with less unexplained variability when the five covariates of drug clearance were included. We also developed a clinical decision support tool (RoadMABTM) to promote physician driven model-informed precision dosing. As IFX has a relatively long half-life, it is currently unknown under what conditions (Bayesian posterior) model performance would be improved. In this study, the aim is to evaluate the precision and bias of three population PK models in a real-world cohort of CD patients.

METHODS
We investigated CD subjects who were anti-TNF naïve and started IFX induction between 2019-2020 at Cincinnati Children’s Hospital Medical Center. All subjects had a minimum of four IFX doses and a minimum of two IFX concentrations measured with a drug-tolerant assay (Esoterix, LabCorp specialty lab, Calabasas, CA) as a part of their clinical care. We measured the mean predictive error (MPE) and the root mean squared error (RMSE) for describing the bias and precision, respectively, of the prediction of the most recent IFX level (which was excluded from the Bayesian estimation). Predictions were based on the selected PK mode, the available covariates of drug clearance (weight, serum albumin, erythrocyte sedimentation rate, neutrophil CD64 expression and antibody to IFX concentration) and prior IFX levels. Two modes were used to compare model performance. In RoadMABTM, the poly-exponential (POLY-1) mode enables last known covariates (if &lt;182 days) and last known IFX level. The ordinary differential equations (ODE-N) mode enables all covariates within the last 182 days and the last N (-1, -2, -3) IFX levels (Figure 1).

RESULTS
We identified 105 subjects who met study criteria. The median (IQR) age at first IFX infusion was 14.6 years (11.8-16.8). The median (IQR) starting dose was 8.6 mg/kg (5.4-10) and 47% were female. For all 3 PK models, we found minimal bias and improved precision in the ODE-1 mode (Table1). While there was little difference in the precision (RMSE) when the POLY-1 mode was used, we found an improvement in bias (MPE) in this mode. In a smaller subset (n=36), we also compared model performance to predict an infusion5 or infusion6 level when an infusion4 (week14) level was known. All three models performed equally well in the POLY-1 mode with the Xiong et al. model showing superior precision with ODE-1. Finally, we compared model performance to predict an infusion3 (week6) level from the start of IFX (n=38) based on the covariates of drug clearance alone.

CONCLUSION
Based on our data, in CD patients, precision dosing for IFX should be largely based on the last known IFX concentration and the most recent covariates of drug clearance.
COMBINATION BIOLOGIC AND SMALL MOLECULE THERAPY FOR REFRACTORY ULCERATIVE COLITIS
Authors: Hickman Kaitlyn , Jordan Ronald , Sonnier William 
Published: January 2022

Abstract

INTRODUCTION
Some inflammatory bowel disease (IBD) patients do not achieve remission with maximal medical therapy. We present a case of refractory UC who achieved clinical, endoscopic, and histologic remission after combining biologic and small molecule therapy.

CASE DESCRIPTION
A 25-year-old Caucasian male was referred to our clinic for refractory UC. Since diagnosis four years prior, he failed mesalamine, azathioprine (intolerant), adalimumab (secondary nonresponse), vedolizumab (secondary nonresponse) with inability to taper prednisone. Upon presentation to our clinic he was at week 14 of infliximab therapy without clinical improvement. Therapeutic drug monitoring revealed adequate infliximab levels without antibodies. Colonoscopy revealed mayo 2-3 disease with discrete ulcerations (Figure 1). Due to primary non-response, he was initiated on ustekinumab (UST). He remained clinically active despite dose escalation up to evey four weeks and prednisone use. Tofacitinib was initiated with initial clinical improvement, then worsening after 3 months. The Tofacitinib dosing was increased from twice daily to three times daily and repeat colonoscopy revealed pan-colitis with Mayo 2 disease. Due to refractory disease the patient was started on combined therapy of tofacitinib twice daily with UST. On dual therapy the patient experienced progressive clinical improvement. After a year of dual treatment colonoscopy showed no disease activity, and biopsies showed no evidence of cryptitis, or crypt abscesses or active inflammatory infiltrate (Figure 2).

DISCUSSION
This case highlights the benefit of combination biologic therapy with small molecule therapy in medically refractory IBD. There are limited prospective data to endorse the widespread implementation of combination therapy. A meta-analysis of thirty studies, involving 279 patients, reported 59% were able to achieve clinical remission and 34% achieved endoscopic remission with treatment of dual biologic or small molecule therapy1. Concerns involving safety of combination biologic and small molecule therapy continue to be evaluated. In our case, the patient achieved clinical, endoscopic, and histologic remission with tofacitinib and UST without adverse effects. We present this case to support the safety and efficacy of combination therapy in medically refractory patients.

REFERENCES
Ahmed W, Galati J, Kumar A et al. Dual Biologic or Small Molecule Therapy for Treatment of Inflammatory Bowel Disease: A Systematic Review and Meta-analysis. Clin Gastroenterol Hepatol 2021. https://doi.org/10.1016/j.cgh.2021.03.034.
Do Birds of a Feather Flock Together? Rebel Constituencies and Civil War Alliances
Authors: Balcells Laia , Chen Chong , Pischedda Costantino 
Published: January 2022

AbstractChallenging influential perspectives that downplay the role of shared rebel constituencies, we argue that they represent important causes of rebel alliances. Yet, we theorize distinct effects for different types of constituency. While compatible political aspirations push both organizations with a common ideological constituency and those with a common ethnic constituency to ally, for co-ethnic organizations this cooperation-inducing effect is offset by a cooperation-suppressing effect due to their higher risk of inter-rebel war. Leveraging a novel dataset of alliances in multiparty civil wars (1946–2015), we find support for our theoretical expectations. Shared ideological constituencies have a larger and more robust positive effect on the probability of alliances than shared ethnic constituencies. Furthermore, we find that co-ethnic rebel organizations tend to establish informal alliances only, while organizations sharing an ideological constituency are drawn to formal alliances.
Biology and Transmission Dynamics of Aedes flavivirus
Authors: Peinado Stephen A , Aliota Matthew T , Blitvich Bradley J , Bartholomay Lyric C 
Published: January 2022

Abstract
Aedes albopictus (Skuse) and Aedes aegypti (Linnaeus) (Diptera: Culicidae) mosquitoes transmit pathogenic arthropod-borne viruses, including dengue, chikungunya, and Zika viruses, with significant global health consequences. Both Ae. albopictus and Ae. aegypti also are susceptible to Aedes flavivirus (AEFV), an insect-specific flavivirus (ISF) first isolated in Japan from Ae. albopictus and Ae. flavopictus. ISFs infect only insect hosts and evidence suggests that they are maintained by vertical transmission. In some cases, ISFs interfere with pathogenic flavivirus infection, and may have potential use in disease control. We explored the host range of AEFV in 4 genera of mosquitoes after intrathoracic injection and observed greater than 95% prevalence in the species of Aedes and Toxorhynchites tested. Anopheles and Culex species were less permissive to infection. Vertical transmission studies revealed 100% transovarial transmission and a filial infection rate of 100% for AEFV in a persistently-infected colony of Ae. albopictus. Horizontal transmission potential was assessed for adult and larval mosquitoes following per os exposures and in venereal transmission experiments. No mosquitoes tested positive for AEFV infection after blood feeding, and infection with AEFV after sucrose feeding was rare. Similarly, 2% of adult mosquitoes tested positive for AEFV after feeding on infected cells in culture as larvae. Venereal transmission of AEFV was most frequently observed from infected males to uninfected females as compared with transmission from infected females to uninfected males. These results reveal new information on the infection potential of AEFV in mosquitoes and expand our understanding of both vertical and horizontal transmission of ISFs.
Development of a Simple Trap That Captures Ticks (Acari) on Their Dorsal Surface
Authors: Yans Matthew W , Branca Alyssa S , Hahn Noel G , Crawley Sydney E , Figurskey Anastasia C , Hobson Kenneth R , Banfield Michael G , Borden John H 
Published: January 2022

Abstract
We tested two versions of a trap that captures climbing ticks on their dorsum. A prototype based on a decades old model had three components, a truncated pyramidal base with steep sloping walls, downward facing sticky-tape extending beyond and spanning the boundary of the flat upper surface, on which ticks become dorsally immobilized, and a reservoir for gaseous CO2 emission from dry ice that rests on the flat upper surface. A preoperational trap was made of thermoformed plastic and differed from the prototype by its circular structure, a central depression suitable for future housing of a biotic CO2 generator and supplemental volatile lures and a transparent sticky ceiling that enables ticks to exhibit a phototactic response and allows users to see captured ticks without disturbing the traps. Field testing of the prototype in Florida and both trap types in Oklahoma and North Carolina achieved high catches of lone star ticks, Amblyomma americanum (L.) (Acari: Ixodidae), e.g. mean catches of &gt;70 ticks (adults plus nymphs) in 4 h in both the prototype and preoperational traps in North Carolina, and significantly higher yields of ticks than on dry ice baited 1 m2 white sheets.
The rapid identification and diagnosis of meniscus tear by Magnetic Resonance Imaging using a deep learning model
Authors: Li Jie , Qian Kun , Liu Jinyong , Huang Zhijun , Zhang Yuchen , Zhao Guoqian , Wang Huifen , Li Meng , Liang Xiaohan , Zhou Fang , Yu Xiuying , Li Lan , Wang Xingsong , Yang Xianfeng , Jiang Qing 
Published: January 2022

AbstractObjectiveThe meniscus tear is a common problem in sports trauma. The imaging diagnosis mainly depends on the MRI. To improve the diagnostic accuracy and efficiency, a deep learning model was employed in this study and the identification efficiency has been evaluated.MethodsThe standard knee MRI images of 924 individual patients were used to complete the training, validation, and testing process. The Mask R-CNN was considered as the deep learning network structure, and the ResNet50 was considered as the backbone network. The deep learning model was trained and validated with a dataset containing 504 and 220 patients, respectively. The accuracy testing was performed on a dataset of 200 patients and reviewed by an experienced radiologist and a sports medicine physician.ResultsAfter training and validation, the deep learning model effectively recognized the healthy and injured meniscus. The overall average precision of the bounding box and pixel mask was more than 88% when the IoU threshold value was 0.75. The detailed average precision of three types of menisci (healthy, torn, and degenerated) was ranged from 68% to 80%. The overall sensitivity of the bounding box and pixel mask was more than 74% at the IoU threshold from 0.50 to 0.95. The diagnosis accuracy for the healthy, torn, and degenerated meniscus was 87.50%, 86.96%, and 84.78%, respectively.ConclusionThe Mask R-CNN recognized effectively and predicted the meniscus injury, especially for the tears that occurred at different parts of the meniscus. The recognition accuracy was admirable. The diagnostic accuracy can be further improved with the increase of the training sample size. Therefore, this tool has great potential in the application for the diagnosis of meniscus injury.The translational potential of this articleDeep learning model has unique effect in reducing doctors’ workload and improving diagnosis accuracy. It can identify and classify injured and healthy meniscus more accurately after training and learning datasets. The torn and degenerated meniscus can also be distinguished by this model. This technology could serve as an effective tool for clinical MRI-assisted diagnostics in meniscus injury.
Safety Profile of Sinopharm COVID-19 Vaccine and Breakthrough Infections in Pakistan
Authors: Rizwan Wajiha , Qureshi Ahmad Uzair , Rana Muhammad Nasir , Duggal Mubeen Nazar , Sohaib Muhammad , Sadiq Masood 
Published: January 2022

AbstractBackgroundTo determine the safety profile of Sinopharm COVID-19 vaccine and identify breakthrough infections.MethodThe study design was analytical cross sectional. An online questionnaire was filled by 1033 respondentsbetween 16th and 22nd April 2021. Adults who had received both doses of Sinopharm COVID-19 vaccine more than a week ago or only a single dose with serious side effect were included in the study. The frequency and severity of vaccination related side effects were assessed and breakthrough infection identified.ResultsThe mean age of participants was 36.7 ± 12.91(18 – 92) years. Ninety one percent of participants (n=946) were health care professionals. One fifth (n=225/1033, 21.8%) had suffered from COVID-19 infection prior to vaccination, confirmed using the nasal RT-PCR test. None of the participants reported serious (grade III) or life threatening (grade IV) adverse reactions after either of the two doses. The most common side effects after the first dose were pain at injection site (20.3%), fatigue (20.3%), headache (13.9%), myalgia (12.5%) and fever (9.3%) whereas after the second dose were fatigue (16.8%), pain at injection site (15.8%), myalgia (14%) and fever (6.7%). The side effects were more common in participants who had previous history of COVID-19 infection. Of 225 previously infected participants, 97(43.1%) (p value=0.020) and 90 (40%) (p value=0.001) participants had side effects after 1st and 2nd dose respectively. 16 participants (1.55%) developed PCR positive COVID-19 infection two weeks after the second dose while 3(0.29%) participants had a re-infection. There was one case of probable severe COVID-19 infection, 2 weeks after the second dose and recovered completely with treatment.ConclusionOur study shows that Sinopharm COVID-19 vaccine is generally safe with no serious side effects. The side effects were however, more common in inviduals who already had COVID-19 infection. The COVID-19 breakthrough infection and reinfection could occur after the vaccination.
Effectiveness of the EPA-based ‘Toolbox Family Medicine’ on students’ learning satisfaction: study protocol for a controlled trial
Authors: Amarell Nicola , Wehner Maximilian , Schroeder Johanna , Wild Dorothea , Welchowski Thomas , Weltermann Birgitta 
Published: January 2022

AbstractBackgroundFamily practices constitute an important learning environment for medical students. However, teaching situations markedly vary between practices, and students frequently find rotations underwhelming. Especially, students’ active participation in patient care varies profoundly, although it has a significant impact on students’ interest in primary care careers. To standardize and improve learning situations in practices, we developed the so-called ‘Toolbox Family Medicine (TFM)’ using the concept of entrustable professional activities. It provides standardized learning content appropriate for students’ levels and allows teaching adaptable to actual practice conditions.MethodsUsing a controlled trial with a waiting list control arm, we will evaluate the effectiveness of the toolbox on students’ learning satisfaction. A total of 94 students will be allocated 1:1 to intervention and control practices. The teaching concept ‘Toolbox Family Medicine (TFM)’ comprises a didactic workshop for supervising physicians and a toolbox with practice-specific tasks for medical students. The primary outcome is students’ overall satisfaction with their learning progress after the rotation. Secondary outcomes include the kind and number of tasks performed, the entrusted level per task, the feasibility of implementing the toolbox in actual practice settings, and students’ motivation to pursue a career in primary care.DiscussionWe assume an improvement in learning satisfaction with the intervention. The study will begin with the next practice rotations.Administrative information
Effect of removing race correction factor in glomerular filtration rate estimation on predicting acute kidney injury after percutaneous coronary intervention
Authors: Huang Chenxi , Murugiah Karthik , Li Xumin , Masoudi Frederick A. , Messenger John C. , Mortazavi Bobak J. , Krumholz Harlan M 
Published: January 2022

ABSTRACTBackgroundRace is a social and not a biological construct. Major societies have recommended removing a race correction factor when estimating glomerular filtration rate (eGFR). eGFR is a strong predictor for acute kidney injury (AKI) after percutaneous coronary intervention (PCI). We assessed the effect of removal of the race correction factor in eGFR calculation on the predictive ability of contemporary models for AKI after PCI.MethodsWe used data from the American College of Cardiology’s National Cardiovascular Data Registry (NCDR) CathPCI registry to assess the effect of removing a race correction in eGFR calculation on two previously published AKI models developed using NCDR data – a logistic regression-based model and a gradient boosting machine learning (ML) model. We first assessed the calibration and discrimination of these models with and without race correction and subsequently included race as an independent predictor in a model without race-corrected eGFR. We assessed model performance overall, and stratified by Black and non-Black subgroups. The models were trained on the same cohort used to develop the NCDR models and validated with a contemporaneous validation data set.ResultsWe included 947,091 PCI procedures in 915,223 patients (mean age 64.8 years; 7.9% were Black and 32.8% women) with an AKI rate of 7.4%. In the NCDR model, inclusion of race correction in eGFR significantly underestimated AKI risk among Black patients (predicted 7.6% vs observed 10.2%) while slightly overestimating risk among non-Black patients (predicted 7.4% vs observed 7.1%). Removing the race correction partially corrected the underestimation among Black patients (predicted 8.2%). Including race as an independent predictor and introducing interaction terms further reduced the underestimation (predicted 10.1%). The receiver-operating-characteristic curve (AUC) was similar among these models, but was consistently lower in Black patients. Compared with the logistic model, the ML model had better calibration in Black patients (with race correction predicted 8.6% and without 8.7%) but still underestimated AKI risk. With race included as a predictor, the ML model achieved similarly good calibration in Black patients (predicted 10.1%). The AUCs of ML models were better than the logistic models but did not differ based on the inclusion of the race correction.ConclusionRemoving the race correction in eGFR calculation has a positive effect of reducing the underestimation of the risk of AKI following PCI for Black patients. However, despite the reduction in underestimation, Black patients remain at elevated risk for AKI compared to non-Black patients. There is a need to better capture the determinants of this higher AKI risk through richer data and advanced modeling techniques.