bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bridging public and private health services to best meet the cardiometabolic needs of people with severe mental illness: a retrospective cohort study
Authors: Esh Nicole , Michael Sarah , Paetzholdt Jonathan , Samaras Katherine 
Published: July 2023

Objective Cardiovascular disease is the leading cause of premature mortality in people with severe mental illness (SMI). Despite this, there lacks consensus regarding the most appropriate platform to monitor and treat cardiometabolic risk factors in this cohort. The current study aims to evaluate the effectiveness of tailored cardiometabolic healthcare in a private, GP-led clinic for people with SMI. Method A total of 63 adults with SMI were referred to a private GP-led cardiometabolic clinic from a neighbouring inner-city mental health service, where they received individualised cardiometabolic healthcare free-of-charge between 2014 and 2020. Paired t test was used to measure change in cardiometabolic data over the course of treatment. Chi-squared and Fisher’s Exact tests were used to examine differences in demographic data and client engagement. Results Over a mean period of 9 months, there was a significant mean reduction of weight (2.1 kg), BMI (0.72 kg/m2) and waist circumference (6 cm). Engagement over a longer period was associated with stable accommodation and improved cardiometabolic outcomes. Conclusions Targeted referral for individualised cardiometabolic interventions can lead to clinically significant improvement in cardiometabolic outcomes, providing a cause for therapeutic optimism when approaching physical health in people with SMI.
Explaining differences in autism detection timing: Age of diagnosis and associated individual and socio-familial factors in Chinese children
Authors: Leng Ling Li , Zhu Yue Wen , Zhou Lin Gang 
Published: July 2023

The timing of autism spectrum disorder detection in research and clinical practice is characterised by substantial heterogeneity ranging from infancy to school age. In this study, we examined the age of diagnosis and its associated individual and socio-familial factors in Chinese children diagnosed with autism spectrum disorder. A sample of 1235 autism spectrum disorder children from 132 rehabilitation organisations in Shenzhen was investigated in 2021. We found a mean age of diagnosis of 31.4 ± 12.7 months and a median of 30.0 months. Although 71.7% of the children received their diagnosis between 25 and 36 months of age, and 13.3% were diagnosed early (⩽24 months), 15.1% did not have their symptoms detected until preschool or later years (>36 months). The diagnosis was likely delayed (>36 months) if the children were older, were less severe and presented with no intellectual impairment. The odds of delayed autism spectrum disorder diagnosis were more than 9 times higher among migrant autism spectrum disorder children than those with local household registrations. The study underscores the importance of identifying culturally sensitive socio-economic determinants in autism spectrum disorder detection in addition to clinical factors, as the former are likely to affect the quality of life of many autism spectrum disorder children and their families. Lay Abstract Timely detection is an issue of paramount importance in the care of children with autism spectrum disorder. Whether the delayed autism spectrum disorder diagnosis can be explained by children’s clinical presentations and socio-familial status in China is a question to be addressed. We investigated 1235 autism spectrum disorder children from 132 rehabilitation organisations in Shenzhen, China. These children were found to have a mean age of diagnosis of 31.4 ± 12.7 months and a median age of diagnosis of 30.0 months. The majority of these children were able to receive their diagnosis during toddlerhood. However, about one in six were not diagnosed until they entered preschool or later, thus missing the golden window of opportunity for early intervention. The age of diagnosis was likely to be late if the children were older, were less severe and presented with no intellectual impairment. The odds of having a delayed autism spectrum disorder diagnosis were more than 9 times higher among migrant autism spectrum disorder children than among those with local household registrations, thus underscoring the importance of identifying culturally sensitive socio-economic determinants in autism spectrum disorder detection, as these factors are likely to affect the quality of life of many autism spectrum disorder children and their families.
Non-operative management of terrible triad injuries of the elbow; not so terrible?
Authors: Baker Megan , Eyre-Brook Alistair , Gokaraju Kishan , Jones Valerie , Thyagarajan David , Ali Amjid , Booker Simon 
Published: July 2023

Introduction Terrible triad injuries (TTIs) of the elbow have traditionally been reported to have poor outcomes, hence requiring surgical stabilisation. We identified and reviewed patients with TTIs treated non-operatively within our department. Methods We retrospectively reviewed patients with TTI treated non-operatively with standardised elbow-instability rehabilitation from 2010 to 2020. We used Mason and Morrey classifications for radial head and coronoid fractures, respectively. Non-operative indications included a congruent joint on CT, significant co-morbidities pre-disposing to high-risk surgery and/or patient preference. Outcomes included Oxford Elbow Score (OES), ROM and complications. Results Nineteen patients were included (mean age 49; 37% female). At an average of 6 years (range 2–11 years) post-treatment, mean OES was 46 ± 7. At last clinic review, mean 6 months (2–15), average ROM was 131 ± 11° flexion, 8 ± 10° extension, 85 ± 12° supination and 85 ± 13° pronation. One patient required arthrolysis and another had an incongruent ulnohumeral joint which developed clicking with a functional ROM. Conclusion Our report suggests non-operatively managed and appropriately rehabilitated TTI injuries can achieve good function and ROM. We recommend conservative management as a viable option in cases with joint congruency and no mechanical block in patients with significant co-morbidities or those refusing surgery but patients must be assessed on a case-by-case basis.
Polycythemia vera disease profile in an African population—experience from a tertiary facility in Ghana
Authors: Gyabaah Solomon , Ahmed Eunice Agyemang , Adu-Gyamfi Adwoa Agyemang , Gyabaah Frederick Nkrumah , Bonsu Afia Serwaa , Addo Ameyaw Prince , Opare Sem Ohene Kwaku 
Published: July 2023

Objectives: The study describes the clinical and laboratory profile of the patients with polycythemia vera at Komfo Anokye Teaching Hospital in Kumasi, Ghana. Methods and design: This was a retrospective hospital-based cohort study conducted from September 2020 to August 2022. Hematology clinic entry book was used to identify the patient’s unique hospital code. Using these unique codes, retrospective data were collected using an Excel spreadsheet from the Hospital Lightwave health information management system (LHIMS) database. Results: A total of 20 participants were recruited over the period of 2 years. The overall mean age was 51.53 ± 16.39 years. The hematological profile of the male participants revealed a mean hemoglobin of 18.25 ± 1.373 g/dl, mean hematocrit of 52 ± 3.47%, and a mean platelet of 345.5 ± 180.82. Comparatively, the mean hemoglobin, hematocrit, and platelet for the female participants were higher with figures of 19.26 ± 1.43 g/dl, 53 ± 3.61%, and 816 ± 935.32, respectively. Headache, tiredness, numbness, splenomegaly, and abnormal labs were the most common reasons why participants sought medical attention. Majority (60%) of the study participants had Janus Kinase 2 mutation. New-onset hypertension was identified in 45% of the study participants during follow-up. Thromboembolism was seen in 10% of the study population. Conclusion: Polycythemia vera is an uncommon disease in Ghana mostly found in older males above 50 years. It is important to recognize it early to initiate therapy aimed at preventing common complications such as hypertension and thromboembolism. Polycythemia vera should be considered a differential diagnosis for patients with secondary hypertension.
Sensing, seizing, and reconfiguring dynamic capabilities in innovative firms: Why does strategic leadership make a difference?
Authors: Bornay-Barrachina Mar , López-Cabrales Álvaro , Salas-Vallina Andrés 
Published: July 2023

Despite existing evidence indicating that organizational learning positively influences dynamic capabilities, the complex and dynamic interplay of leadership in this process still remains incomplete. Organizational learning models note that leadership is embedded in the development of dynamic capabilities, and this research empirically investigates the interplay of organizational learning (exploitative and exploratory learning) and strategic leadership (transformational and transactional leadership) in developing dynamic capabilities (sensing, seizing, and reconfiguring). A survey questionnaire on a sample of 106 firms is carried out, and results of hierarchical linear regressions indeed reveal that organizational learning shows a direct or indirect influence on dynamic capabilities through transactional or transformational leadership, depending on the type of department. This study is an innovative attempt to distinguish different antecedents for each type of dynamic capability on the basis of the type of learning and strategic leadership involved.JEL classification: M12
Explanatory factors relating to medication error reporting among emergency medicine clinicians: A qualitative study
Authors: Bakhshi Fatemeh , Nasrabadi Alireza Nikbakht , Mitchell Rebecca , Bagherabadi Mehdi , Saghafi Fatemeh , Varaei Shokoh 
Published: July 2023

Objectives We used an in-depth qualitative approach to investigate the factors that contribute to medication error (ME) reporting among emergency department (ED) clinicians. More specifically, we explored the explanatory factors relating to underreporting by the different staff involved in ED medication management, the underlying processes involved in clinician and manager responses to MEs, and programmatic factors that impede and facilitate ME reporting. Methods We applied a purposive maximum variation sampling to recruit interview participants in nursing, medical, and pharmacy roles. We conducted semistructured interviews based on an interview guide. We performed a thematic analysis of all data and developed a general content model. Results The developed model shows how the series of extracted themes—norms of reporting, reporting culture, and evaluation and feedback—affect one another. The theme norms of reporting were mainly influenced by clinicians’ knowledge and attitudes. The theme of reporting culture directly affected ME reporting. Evaluation and feedback affected all factors that contributed to ME reporting. Participants’ intention to report was mainly affected by the extent to which the reporting led to an obvious outcome. Conclusions The comprehensive model of ME reporting provides guidance for healthcare leaders who strive to increase such reporting. The model encompasses broad concepts that are not limited to ME reporting and may be applicable to improving reporting for all kinds of medical errors.
A machine learning approach to improve implementation monitoring of family-based preventive interventions in primary care
Authors: Berkel Cady , Knox Dillon C. , Flemotomos Nikolaos , Martinez Victor R. , Atkins David C. , Narayanan Shrikanth S. , Rodriguez Lizeth Alonso , Gallo Carlos G. , Smith Justin D. 
Published: July 2023

Background Evidence-based parenting programs effectively prevent the onset and escalation of child and adolescent behavioral health problems. When programs have been taken to scale, declines in the quality of implementation diminish intervention effects. Gold-standard methods of implementation monitoring are cost-prohibitive and impractical in resource-scarce delivery systems. Technological developments using computational linguistics and machine learning offer an opportunity to assess fidelity in a low burden, timely, and comprehensive manner. Methods In this study, we test two natural language processing (NLP) methods [i.e., Term Frequency-Inverse Document Frequency (TF-IDF) and Bidirectional Encoder Representations from Transformers (BERT)] to assess the delivery of the Family Check-Up 4 Health (FCU4Health) program in a type 2 hybrid effectiveness-implementation trial conducted in primary care settings that serve primarily Latino families. We trained and evaluated models using 116 English and 81 Spanish-language transcripts from the 113 families who initiated FCU4Health services. We evaluated the concurrent validity of the TF-IDF and BERT models using observer ratings of program sessions using the COACH measure of competent adherence. Following the Implementation Cascade model, we assessed predictive validity using multiple indicators of parent engagement, which have been demonstrated to predict improvements in parenting and child outcomes. Results Both TF-IDF and BERT ratings were significantly associated with observer ratings and engagement outcomes. Using mean squared error, results demonstrated improvement over baseline for observer ratings from a range of 0.83–1.02 to 0.62–0.76, resulting in an average improvement of 24%. Similarly, results demonstrated improvement over baseline for parent engagement indicators from a range of 0.81–27.3 to 0.62–19.50, resulting in an approximate average improvement of 18%. Conclusions These results demonstrate the potential for NLP methods to assess implementation in evidence-based parenting programs delivered at scale. Future directions are presented. Trial registration NCT03013309 ClinicalTrials.gov.
It is worth the weight: obesity and the transition from monoclonal gammopathy of undetermined significance to multiple myeloma
Authors: Choa Ruth , Panaroni Cristina , Bhatia Roma , Raje Noopur 
Published: July 2023

Abstract
The overweight/obesity epidemic is a serious public health concern that affects &gt;40% of adults globally and increases the risk of numerous chronic diseases, such as type 2 diabetes, heart disease, and various cancers. Multiple myeloma (MM) is a lymphohematopoietic cancer caused by the uncontrolled clonal expansion of plasma cells. Recent studies have shown that obesity is a risk factor not only for MM but also monoclonal gammopathy of undetermined significance (MGUS), a precursor disease state of MM. Furthermore, obesity may promote the transition from MGUS to MM. Thus, in this review, we summarize the epidemiological evidence regarding the role of obesity in MM and MGUS, discuss the biologic mechanisms that drive these disease processes, and detail the obesity-targeted pharmacologic and lifestyle interventions that may reduce the risk of progression from MGUS to MM.
Enabling endpoint development for interventional clinical trials in individuals with Angelman syndrome: a prospective, longitudinal, observational clinical study (FREESIAS)
Authors: Tjeertes Jorrit , Bacino Carlos A. , Bichell Terry Jo , Bird Lynne M. , Bustamante Mariana , Crean Rebecca , Jeste Shafali , Komorowski Robert W. , Krishnan Michelle L. , Miller Meghan T. , Nobbs David , Ochoa-Lubinoff Cesar , Parkerson Kimberly A. , Rotenberg Alexander , Sadhwani Anjali , Shen Mark D. , Squassante Lisa , Tan Wen-Hann , Vincenzi Brenda , Wheeler Anne C. , Hipp Joerg F. , Berry-Kravis Elizabeth 
Published: July 2023

Abstract
Background
Angelman syndrome (AS) is a rare neurodevelopmental disorder characterized by the absence of a functional UBE3A gene, which causes developmental, behavioral, and medical challenges. While currently untreatable, comprehensive data could help identify appropriate endpoints assessing meaningful improvements in clinical trials. Herein are reported the results from the FREESIAS study assessing the feasibility and utility of in-clinic and at-home measures of key AS symptoms.

Methods
Fifty-five individuals with AS (aged < 5 years: n = 16, 5–12 years: n = 27, ≥ 18 years: n = 12; deletion genotype: n = 40, nondeletion genotype: n = 15) and 20 typically developing children (aged 1–12 years) were enrolled across six USA sites. Several clinical outcome assessments and digital health technologies were tested, together with overnight 19-lead electroencephalography (EEG) and additional polysomnography (PSG) sensors. Participants were assessed at baseline (Clinic Visit 1), 12 months later (Clinic Visit 2), and during intermittent home visits.

Results
The participants achieved high completion rates for the clinical outcome assessments (adherence: 89–100% [Clinic Visit 1]; 76–91% [Clinic Visit 2]) and varied feasibility of and adherence to digital health technologies. The coronavirus disease 2019 (COVID-19) pandemic impacted participants’ uptake of and/or adherence to some measures. It also potentially impacted the at-home PSG/EEG recordings, which were otherwise feasible. Participants achieved Bayley-III results comparable to the available natural history data, showing similar scores between individuals aged ≥ 18 and 5–12 years. Also, participants without a deletion generally scored higher on most clinical outcome assessments than participants with a deletion. Furthermore, the observed AS EEG phenotype of excess delta-band power was consistent with prior reports.

Conclusions
Although feasible clinical outcome assessments and digital health technologies are reported herein, further improved assessments of meaningful AS change are needed. Despite the COVID-19 pandemic, remote assessments facilitated high adherence levels and the results suggested that at-home PSG/EEG might be a feasible alternative to the in-clinic EEG assessments. Taken altogether, the combination of in-clinic/at-home clinical outcome assessments, digital health technologies, and PSG/EEG may improve protocol adherence, reduce patient burden, and optimize study outcomes in AS and other rare disease populations.
Using pre-selected variants from large-scale whole-genome sequence data for single-step genomic predictions in pigs
Authors: Jang Sungbong , Ros-Freixedes Roger , Hickey John M. , Chen Ching-Yi , Holl Justin , Herring William O. , Misztal Ignacy , Lourenco Daniela 
Published: July 2023

Abstract
Background
Whole-genome sequence (WGS) data harbor causative variants that may not be present in standard single nucleotide polymorphism (SNP) chip data. The objective of this study was to investigate the impact of using preselected variants from WGS for single-step genomic predictions in maternal and terminal pig lines with up to 1.8k sequenced and 104k sequence imputed animals per line.

Methods
Two maternal and four terminal lines were investigated for eight and seven traits, respectively. The number of sequenced animals ranged from 1365 to 1491 for the maternal lines and 381 to 1865 for the terminal lines. Imputation to sequence occurred within each line for 66k to 76k animals for the maternal lines and 29k to 104k animals for the terminal lines. Two preselected SNP sets were generated based on a genome-wide association study (GWAS). Top40k included the SNPs with the lowest p-value in each of the 40k genomic windows, and ChipPlusSign included significant variants integrated into the porcine SNP chip used for routine genotyping. We compared the performance of single-step genomic predictions between using preselected SNP sets assuming equal or different variances and the standard porcine SNP chip.

Results
In the maternal lines, ChipPlusSign and Top40k showed an average increase in accuracy of 0.6 and 4.9%, respectively, compared to the regular porcine SNP chip. The greatest increase was obtained with Top40k, particularly for fertility traits, for which the initial accuracy based on the standard SNP chip was low. However, in the terminal lines, Top40k resulted in an average loss of accuracy of 1%. ChipPlusSign provided a positive, although small, gain in accuracy (0.9%). Assigning different variances for the SNPs slightly improved accuracies when using variances obtained from BayesR. However, increases were inconsistent across the lines and traits.

Conclusions
The benefit of using sequence data depends on the line, the size of the genotyped population, and how the WGS variants are preselected. When WGS data are available on hundreds of thousands of animals, using sequence data presents an advantage but this remains limited in pigs.
Incidence and prevalence of heart failure in England: a descriptive analysis of linked primary and secondary care data – the PULSE study
Authors: Bellanca Leana , Linden Stephan , Farmer Ruth 
Published: July 2023

Abstract
Background
Heart failure (HF) is associated with high morbidity and mortality, yet data on HF subtype (HF with reduced ejection fraction [HFrEF] and preserved ejection fraction [HFpEF]) in broad populations are lacking. Additionally, it is unknown whether current HF incidence and prevalence rates are consistent with historical data. Here, we estimate the incidence and prevalence of HF in England and describe the characteristics of patients with HF, both overall and by subtype.

Methods
This was a non-interventional cohort study based on data from the UK Clinical Practice Research Datalink (CPRD), linked to Hospital Episode Statistics data and Office for National Statistics mortality data. Patients aged ≥ 18 years who were registered in the CPRD Aurum database between 1st January 2015 and 31st December 2019 formed the base cohort, from which patients with a recorded chronic HF diagnosis (historical or incident) from 2015–2019 contributed to the incidence and prevalence calculations.

Results
The eligible denominator over the study period comprised 11,414,490 patients, from which 383,896 patients with HF were included as prevalent or incident HF cases. From 2015 to 2019, the incidence rate of newly diagnosed HF increased from 4.1/1,000 person-years to 4.9/1,000 person-years, and HF prevalence increased from 2.1% to 2.4%. Phenotype data were available for 100,224 (26.1%) patients, of which 68,780 patients had HFrEF and 31,444 had HFpEF (HFrEF/HFpEF ratio: 70.1%/29.9%). Comorbidity levels were high and broadly similar across HF subgroups.

Conclusions
Primary care recording of HF subtype is suboptimal, with more than 7/10 patients with HF lacking subtype data. In patients with a recorded subtype (n = 100,224), a HFrEF/HFpEF ratio of 70%/30% was observed. Comorbidity levels were high regardless of subtype. Between 2015 and 2019, we observed modest but consistent increases in the incidence and prevalence of chronic HF in adults, in line with historical data.