bluuebunny/crossref_metadata_2025_split huggingface dataset:
Antibiotic prophylaxis reduced broad-spectrum antibiotics and length of stay in ICU patients with alcohol withdrawal induced refractory delirium tremens
Authors: Al-Hashimi Dunia , Kåberg Martin , Krifors Anders , Wanecek Michael , Blennow Ola 
Published: November 2024

Background: Pneumonia is a well-known complication in patients with severe alcohol withdrawal syndrome (SAWS). Antibiotic prophylaxis in ICU treated SAWS patients may be beneficial but data is lacking. The aims of this study were to investigate the effect of introduction of trimethoprim-sulfamethoxazole (TMP-SMX) prophylaxis, on use of broad-spectrum antibiotics and ICU length of stay (LOS) in SAWS patients with refractory delirium tremens (rDT). Methods: Retrospective observational cohort study comparing before (control group) and after the introduction of TMP-SMX prophylaxis in patients admitted to a single center ICU because of alcohol withdrawal induced rDT. Results: A total of 108 patients were included, 53 patients in the control group and 55 patients in the TMP-SMX group. Baseline characteristics did not differ between the groups (89% male, median age 52 years). The use of broad-spectrum antibiotics was significantly lower in the TMP-SMX group than in the control group (11 vs 70%, p < 0.001). The only variable associated with decreased use of broad-spectrum antibiotics in multiple logistic regression analysis was receiving TMP-SMX (0.06, 95% CI 0.02, 0.19, p-value: <0.001). Median LOS was shorter in the TMP-SMX group than in the control group (61 vs 72 h, p = 0.004). In multiple linear regression analysis receiving TMP-SMX SMX was associated with shorter LOS (−22.7, 95% CI: −41.3, −4.1, p-value: 0.02) and having one or more comorbidities with longer LOS (37.4, 95% CI: 10.4, 64.5, p-value: <0.01). Conclusion: Prophylaxis with TMP-SMX in ICU-treated rDT patients was associated with reduced use of broad-spectrum antibiotics and reduced ICU LOS.
Predicting Epidural Hematoma Expansion in Traumatic Brain Injury: A Machine Learning Approach
Authors: Hasanpour Mohammad , Elyassirad Danial , Gheiji Benyamin , Vatanparast Mahsa , Keykhosravi Ehsan , Shafiei Mehdi , Daneshkhah Shirin , Fayyazi Arya , Faghani Shahriar 
Published: November 2024

Introduction Traumatic brain injury (TBI) is a leading cause of disability and mortality worldwide, with epidural hematoma (EDH) being a severe consequence. This study focuses on identifying factors predicting EDH volume changes in TBI patients and developing a machine learning (ML) model to predict EDH expansion. Methods The study includes patients with traumatic EDH between 2019 and 2021. Data were gathered from CT scans performed at the time of admission and 6 hours later, and subsequently analyzed. The data was divided into three cohorts: all cases, adults, and pediatrics. To predict EDH volume changes, we used Logistic Regression (LR), Random Forest (RF), XGBoost, and K-Nearest Neighbors (KNN) models. Data was divided into an 80% training set and a 20% test set. Through a rigorous process of parameter optimization and K-fold cross-validation, focusing on the area under the receiving operating curve (AUROC), we identified the best models in all cohorts. The best models were evaluated on the test sets, reporting AUROC, recall, precision, and accuracy using the youden index threshold. Results Results show that age, initial EDH volume, swirl sign, intra-hematoma air bleb, contusion, otorrhagia, subarachnoid hemorrhage, location, and other side extra-axial hematoma have significant effects on changing EDH volume. Based on test AUROC, the best models were RF for adults (82.4%), KNN for pediatrics (90%), and LR for all cases (81.6%). Discussion In this study, we identified key features for predicting EDH expansion as well as developing ML models. Using high sensitive models, can assist clinicians in identifying high-risk patients early. This allows for enhanced monitoring and timely intervention, improving patient outcomes by facilitating quicker decisions for follow-up imaging or treatment.
The Los Angeles Motor Scale is independently associated with cerebral blood flow < 30% volume in large vessel occlusions
Authors: Wang Richard , Lakhani Dhairya A , Balar Aneri B , Sepehri Sadra , Luna Licia P , Cho Andrew , Hillis Argye E , Koneru Manisha , Hoseinyazdi Meisam , Lu Hanzhang , Mei Janet , Faizy Tobias , Xu Risheng , Nabi Mehreen , Mazumdar Ishan , Urrutia Victor C , Chen Kevin , Huang Judy , Nael Kambiz , Hyson Nathan , Yedavalli Vivek S 
Published: November 2024

Background and Purpose Mechanical thrombectomy (MT) is the treatment standard for large vessel occlusion (LVO) stroke. Under current guidelines, only patients with smaller ischemic core volumes (ICV) are eligible for MT. Thus, it is of interest to quickly estimate ICV in stroke patients. The Los Angeles Motor Scale (LAMS) is a validated tool used to assess stroke severity directly in the field. This study aims to determine whether LAMS score is also associated with ICV, as defined by the CBF <30% volume on CT perfusion imaging. Methods We performed a retrospective, multicenter cohort study of consecutive patients presenting with LVO stroke from 9/1/2017 to 10/1/2023. The inclusion criteria were patients with (1) stroke caused by large vessel occlusion confirmed on CTA and (2) diagnostically adequate, multimodal pretreatment CT imaging. Demographic, clinical, and imaging data was collected through manual chart review. Both univariate and multivariate analyses were applied to assess associations. A p-value <.05 was considered significant. Results A total of 283 patients (median age: 69, IQR: 61–78) were included in the study. On multivariate logistic regression analysis, we found that lower admission LAMS score (adjusted OR: 0.511, 95% CI: 0.313–0.834, p = .007) was independently associated with a CBF <30% volume of less than 50cc. Conclusions Admission LAMS is an independent predictor of a CBF <30% volume of less than 50cc. This demonstrates that LAMS can be used to estimate ICV, which will aid in the early triaging of LVO patients to thrombectomy-capable centers.
The influence of digital literacy on mHealth app usability: The mediating role of patient expertise
Authors: Durmuş Ayhan 
Published: November 2024

Objective Mobile health (mHealth) applications are emerging as important healthcare technologies that can provide cost savings, better access to care, contribute to improved clinical outcomes, and support public health. An increasing number of mobile health (mHealth) applications are becoming available to download and use on mobile devices. However, unlocking this potential requires ensuring widespread acceptance and adoption of these applications. In this context, the aim of the study is to determine the impact of individuals’ digital literacy levels on mobile health application usability and the mediating role of patient expertise in this impact. Methods The population of our study consists of individuals who reside in Yozgat city center and are 18 years old and over. Within the scope of the study, 647 individuals who agreed to participate in the research were reached. A survey form consisting of four sections (Socio-demographic characteristics, Digital Literacy Scale, mHealth App Usability Questionnaire, and Patient Expertise Scale) was used as a data collection tool in the study. Descriptive statistical methods were used to analyze the data and partial least squares path analysis (PLS-SEM) was used to analyze the research model. Results Digital literacy affects both patient expertise (β = 0.790, t = 35.560, p = 0.000) and mHealth app usability (β = 0.831, t = 46.020, p = 0.000). Additionally, it has been determined that patient expertise has a mediating role in the effect of digital literacy on mHealth app usability (β = 0.536, t = 17.477, p = 0.000). Conclusions It appears that individuals’ digital literacy is an important precursor to the usability of mHealth apps and increases their usage experience. In this sense, it is thought that the concept of digital literacy can be used to increase the usability of mHealth apps for individuals. Overall, the findings provide new evidence for the healthcare context by integrating user diversity, particularly individuals’ digital literacy, mHealth apps, and prior experience with mHealth.
Previous Surgical Exposure and the Onset of Degenerative Cervical Myelopathy: A Propensity-Matched Case-Control Analysis Nested Within the UK Biobank Cohort
Authors: Grodzinski Ben , Stubbs Daniel J. , Davies Benjamin M. 
Published: November 2024

Study Design Case-control study. Objectives Degenerative Cervical Myelopathy (DCM) is a progressive neurological condition caused by mechanical stress on the cervical spine. Surgical exposure in the preceding months to a DCM diagnosis is a common theme of Patient and Public Involvement (PPI) discussions. Such a relationship has biological plausibility (e.g. neck positioning, cord perfusion) but evidence to support this association is lacking. Methods We analysed UK Hospital Episode Statistics (HES) data for participants in the UK BioBank cohort. We defined cases as those episodes with a primary diagnosis of DCM and generated controls using non-DCM HES episodes. Cases and controls were propensity score-matched by age, sex and date of episode, and a directed acyclic graph was used to robustly control for confounders. We defined the exposure as any surgical procedure under general or regional anaesthetic occurring within the 6-24 months prior to the episode. Results We analysed 806 DCM and 2287432 non-DCM hospital episodes. On multivariable logistic regression analysis, the odds ratio (95% CI) for the effect of a binarised (0 vs ≥ 1) exposure on risk of developing DCM was 1.20 (1.02-1.41), and for categorised (0 vs 1 and 0 vs ≥ 2) exposure was 1.11 (0.882-1.39) & 1.33 (1.075-1.65). Conclusions This study supports the patient narrative of surgery as a risk factor for the development of DCM. The association displays temporality, dose-response relationship, and biological plausibility. Further work is needed to confirm this in other cohorts, explore mediating mechanisms, and identify those at greatest risk.
Seven Years of GST: Time to Move Beyond the Exuberance
Authors: Dwivedi Hari K. 
Published: November 2024

The introduction of the Goods and Services Tax (GST) in the country in July 2017 marked a watershed in the history of indirect tax reforms in the country. The dual structure of GST in India, with all its infirmities, has had significant positive outcomes. It has reduced multiplicity of taxes, cascading of tax, created uniform tax structure on a common base, a uniform GST architecture, rules and processes, and seamless flow of credit across different tax jurisdictions, across the country. But like any other major tax reform, GST in India initially had its fair share of glitches, some of them still continue, although to a much lesser degree and intensity. Due to constraints imposed by the federal nature of our polity, the centre and the states opted for an ‘imperfect GST’ in place of ‘flawless GST’, with the hope that the design flaws would be corrected once the GST stabilizes. While we celebrate the success of GST in the country, we need to usher in the second-generation GST reforms that will broadly encompass; first, the rationalization of tax slabs, and second, expansion of the tax base by pruning exemptions and bringing petroleum products, electricity, alcohol and real estate under GST. The feasibility of inclusion of excluded items, which constitute around 43% of the state’s own tax revenues, in GST, remains bleak at this stage as it will greatly impact the fiscal autonomy of the states. A beginning can, however, be made to rationalize the rate structure which will remedy many of the complexities and problems being faced at present. But, to even address the issue of rate rationalization, the trust deficit between the centre and the states that has suffered a huge dent during the intervening years has to be bridged. JEL Classification: H21, H77
Deep learning model using continuous skin temperature data predicts labor onset
Authors: Basavaraj Chinmai , Grant Azure D. , Aras Shravan G. , Erickson Elise N. 
Published: November 2024

Abstract
Background
Changes in body temperature anticipate labor onset in numerous mammals, yet this concept has not been explored in humans. We investigated if continuous body temperature exhibits similar changes in women and whether these changes may be linked to hormonal status. Finally, we developed a deep learning model using temperature patterning to provide a daily forecast of time to labor onset.

Methods
We evaluated patterns in continuous skin temperature data in 91 (n = 54 spontaneous labors) pregnant women using a wearable smart ring. In a subset of 28 pregnancies, we examined daily steroid hormone samples leading up to labor to analyze relationships among hormones and body temperature trajectory. Finally, we applied an autoencoder long short-term memory (AE-LSTM) deep learning model to provide a novel daily estimation of days until labor onset.

Results
Features of temperature change leading up to labor were associated with urinary hormones and labor type. Spontaneous labors exhibited greater estriol to α-pregnanediol ratio, as well as lower body temperature and more stable circadian rhythms compared to pregnancies that did not undergo spontaneous labor. Skin temperature data from 54 pregnancies that underwent spontaneous labor between 34 and 42 weeks of gestation were included in training the AE-LSTM model, and an additional 37 pregnancies that underwent artificial induction of labor or Cesarean without labor were used for further testing. The input to the pipeline was 5-min skin temperature data from a gestational age of 240 days until the day of labor onset. During cross-validation AE-LSTM average error (true – predicted) dropped below 2 days at 8 days before labor, independent of gestational age. Labor onset windows were calculated from the AE-LSTM output using a probabilistic distribution of model error. For these windows AE-LSTM correctly predicted labor start for 79% of the spontaneous labors within a 4.6-day window at 7 days before true labor, and 7.4-day window at 10 days before true labor.

Conclusion
Continuous skin temperature reflects progression toward labor and hormonal change during pregnancy. Deep learning using continuous temperature may provide clinically valuable tools for pregnancy care.
Socio-cultural practices and experience of mothers’ post stillbirth and newborn death: a population-based perspective from India
Authors: Majumder Moutushi , Kumar G Anil , Ali Sarah Binte , George Sibin , Dora Siva Prasad , Akbar Md. , Akhouri Shuchi Sree , Kumari Sweta , Mahapatra Tanmay , Dandona Rakhi ,   ENHANCE 2020 Team, Paul Arpita , Das Arup Kumar , Dandona Lalit , Kumar Vimal , Bhattacharjee Debrupa , Bhatt Dinesh 
Published: November 2024

Abstract
Introduction
We report on post stillbirth and newborn death socio-cultural experience of women from a population-based representative sample in the Indian state of Bihar.

Methods
A state-representative sample of 7,270 births between July 2020 and June 2021 was sampled, including 582 stillbirths and 831 newborn deaths. Detailed confidential interviews were conducted with the consenting women with stillbirth and newborn death to understand their post-birth experience.

Results
A total of 501 (86.1% participation) women with stillbirth and 717 (86.3% participation) with neonatal death provided interview. Able to talk to someone about their baby and receiving support to cope with their loss were reported by 369 (74.2%) and 398 (80.2%) women with stillbirth; these proportions were 76.7% and 77.3% for women with newborn deaths, respectively. More than 80% of these women reported spouses as their main source of support. At least one negative experience was reported by 150 (30.9%) and 233 (32.5%) women with stillbirth and newborn death, respectively. The most commonly reported negative experience was receiving insensitive/hurtful comments about the baby (18.6% for stillbirth and 20.4% for newborn deaths), followed by being blamed for the baby’s death (14.3% for stillbirths and 15.0% for newborn deaths). The majority of women reported being verbally abused by the mother-in-law for both stillbirth (24, 63.2%) and newborn death (49, 64.5%); while 48 (67.6%) and 66 (61.7%) women were blamed by the mother-in-law for stillbirth and neonatal death, respectively. Most women with stillbirth (72.7%) and with neonatal death (77.1%) were asked to forget about their babies as a means to cope with their loss. Naming, seeing, and holding the stillborn were reported by 56 (11.2%), 229 (45.9%), and 64 (12.8%) women with a stillborn.

Conclusion
With one-third women with adverse birth outcome reporting negative experience, this translates into a significant number of women in India as it accounts for high numbers of stillbirths and newborn deaths globally. These population-based data can facilitate in designing interventions to improve post-partum experience for women with adverse birth outcomes in India.
Perceived unmet needs and impact on quality of life of patients living with advanced bladder cancer and their caregivers: results of a social media listening study conducted in five European countries
Authors: Schuck Stephane , Loussikian Paul , Mebarki Adel , Malaab Joelle , Foulquié Pierre , Talmatkadi Manissa , Kearney Mairead 
Published: November 2024

Abstract
Background
Advanced bladder cancer (aBC) is a significant health concern in Europe and has a poor prognosis. Patients with aBC face numerous unmet needs and challenges that significantly impact their quality of life (QoL). This study aims to analyze social media data from five European countries to address gaps in our understanding of the unmet needs, challenges, and impact on QoL in European patients with aBC and their caregivers.

Methods
This retrospective, real-world study includes public social media posts geolocated in France, Italy, Germany, Spain, and the UK, posted between October 2017 and January 2022. To enhance the filtering process, natural language processing methods and specific algorithms were used to remove irrelevant content and retain posts from patients and caregivers. QoL impacts were identified using a deep-learning algorithm, followed by qualitative analysis. Unmet needs were analyzed via annotation of messages and the saturation method.

Results
A total of 1670 posts from 1396 users (699 posts from 546 patients and 971 posts from 850 caregivers) discussing aBC in 91 publicly available online sources were identified. Half of patients were male (n = 272, 49.8%) while more caregivers were female (n = 474, 55.8%), with an average age of 58.2 and 35.2 years, respectively. Patients and caregivers expressed an impact on QoL, wherein 40.0% (558/1396) of users mentioned at least an impact on one aspect of QoL. Among those, 56.8% (317/558) and 48.6% (271/558) of users expressed physical and psychological challenges, respectively. Most unmet needs identified belonged to two main categories: transversal, i.e., arising throughout the patient’s care pathway (307/1092 [28.1%]), and disease specific (295/1092 [27.0%]). Main challenges included worsening of the disease (n = 141, 12.9%), psychological impact (n = 112, 10.3%), and need to share experiences and seek support (n = 94, 8.6%).

Conclusions
This social media listening study demonstrated the profound emotional and physical burden on patients with aBC and their caregivers, and a genuine need for support and an outlet to discuss their challenges, particularly in terms of managing the illness. These results underscore the importance of enhancing education for both patients and caregivers and the necessity for more effective systemic cancer therapies and better palliative care alternatives.
Parent’s acceptance of advanced behavior management techniques on children during dental treatment
Authors: Salerno Claudia , Cirio Silvia , Maspero Cinzia , Roner Margerita , D’Avola Valeria , Cagetti Maria Grazia 
Published: November 2024

Abstract
Aim
This study explores the acceptance of Advanced Behavior Management Techniques (ABMTs) by parents during their children’s dental treatments, comparing the opinion of parents of neurotypical children with that of parents of children with autism spectrum disorders (ASDs).

Methods
An observational cross-sectional study was conducted involving 440 parents, divided into two groups: 236 parents of neurotypical children and 204 parents of children with ASDs, recruited from pediatricians’ centers and centers for ASDs children in Northern and Southern Italy. A survey assessed their familiarity and acceptance of ABMTs, including protective stabilization, conscious sedation, and deep sedation/general anesthesia. Discrete variables were expressed as absolute and relative frequencies (%) and compared with Pearson’s chi-squared or Fisher’s exact test. Continue variables were expressed as mean ± SD and compared with the one-way ANOVA test. Heatmap and PCA analysis were used to determine possible correlations between items.

Results
Parents of children with ASDs showed a higher acceptance rate of ABMTs compared to parents of neurotypical children. Overall, only 30.68% of parents knew ABMTs before the survey. Differences between the two groups of parents in acceptance of Active Stabilization in emergency settings, Passive Stabilization in routine settings, and Deep sedation/general anesthesia in both settings were observed (p < 0.01). Only 6.82% of parents ever used at least one ABMT on their children. Heatmap analysis revealed that parents who have accepted one of the ABMTs tend to accept the others as well.

Conclusion
Differences in parental acceptance of different ABMTs was noted among the two groups of parents, with greater acceptance of ABMTs observed in the group of parents of children with ASDs. Parents of both groups have significant gaps in their knowledge of ABMTs. Therefore, increased awareness and personalized communication strategies are needed to increase acceptance of the studied techniques and, thus, facilitate access to dental care for uncooperative pediatric patients. Patient-centered behavior management strategies that meet children’s needs and parents’ preferences can contribute to the achievement of good oral health.
De-normalizing sugar-sweetened beverage consumption: effects of tax measures on social norms and attitudes in the California Bay Area
Authors: Altman Emily , Schillinger Dean , Villas-Boas Sofia , Schmidt Laura , Falbe Jennifer , Madsen Kristine A. 
Published: November 2024

Abstract
Background
Social norms can influence individual health behaviors. Shifts in social norms for smoking were critical for the effectiveness of tobacco control efforts such as excise taxes. Sugar-sweetened beverage (SSB) excise taxes have been implemented in municipalities across the United States to reduce SSB intake and improve health. We sought to identify trends in social norms and attitudes about healthfulness of sugar-sweetened beverage (SSB) consumption in the California Bay Area and examine whether social norms and attitudes changed following SSB taxes.

Methods
Data came from annual (2016–2019, 2021) cross-sectional surveys (n = 9128) in lower-income neighborhoods in Oakland, San Francisco, Berkeley, and Richmond. We assessed overall trends and compared pre-post tax changes in Oakland and San Francisco with comparison cities.

Results
We observed a 28% reduction in social norms for SSB consumption (people’s perceptions of peers’ consumption) and variable reductions in attitudes about the healthfulness of SSBs. Relative to comparison cities, post-tax, perceptions of peers’ consumption of sports drinks declined in Oakland; attitudes about the healthfulness of sugar-sweetened fruit drinks declined in San Francisco.

Conclusions
Among lower-income populations, social norms and attitudes towards the healthfulness of SSBs meaningfully declined over time, with smaller tax-related effects. SSB taxes as well as the local media attention they generate appear to affect people’s perceptions of SSBs. Pairing SSB taxes with messaging campaigns may be more effective in de-normalizing SSB consumption.