bluuebunny/crossref_metadata_2025_split huggingface dataset:
Healthcare providers perception of therapeutic patient education efficacy according to patient and healthcare provider characteristics
Authors: Loyal Deborah , Ricci Laetitia , Villegente Julie , Ayav Carole , Kivits Joelle , Rat Anne-Christine 
Published: December 2021

Objectives Therapeutic patient education improves numerous health and psychological outcomes in patients with chronic diseases. However, little is known about what makes a therapeutic patient education intervention more effective than another one. This study aims to identify in healthcare professionals the perceived determinants of therapeutic patient education efficacy at the individual level. Methods Semi-structured individual interviews have been conducted with healthcare professionals (HCP, n=28, including 20 nurses) involved in therapeutic patient education programs ( n=14) covering various chronic conditions (kidney and cardiovascular diseases, chronic pain, diabetes, etc.). A thematic content analysis following an inductive approach was used (Nvivo.11 software). Results Five themes were retrieved for patient characteristics: understanding and education, personality, readiness and motivation, social environment, and misinformation and beliefs. Four themes were retrieved for healthcare professionals’ characteristics: medical knowledge, appropriate attitude and relational skills, pedagogical skills, and training. Discussion Patient personality is rarely discussed in the literature. Patients who are introverted, lack curiosity, or are not compliant might benefit from specific therapeutic patient education practices or formats. All these potential determinants regarding patients and healthcare professionals should be routinely assessed in future studies about therapeutic patient education efficacy to understand precisely what makes an intervention successful.
The experience of caregivers of chronically ill patients during the COVID-19: A Systematic Review
Authors: Ruksakulpiwat Suebsarn , Zhou Wendie , Phianhasin Lalipat , Benjasirisan Chitchanok , Fan Yuying , Su Tingyu , Chiaranai Chantira 
Published: December 2021

Objectives This study aimed to identify the difficulties that caregivers of chronically ill patients experienced during the COVID-19 pandemic and to provide directions for future studies. Methods Five electronic databases, including PubMed, Web of Science, CINAHL Plus Full Text, EMBASE, and Scopus, were systematically searched from January 2019 to February 2021. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses were employed for the literature screening, inclusion, and exclusion. The Mixed Methods Appraisal Tool was adopted for qualifying appraisal. Results Six studies met the study criteria, including three quantitative studies, two qualitative studies, and one mixed-method study. Mental health, personal experience, financial problems, physical health, and improvement approaches were the major five themes that participants reported regarding the impact of COVID-19 they encountered during the pandemic. Discussion The results could heighten healthcare providers, stakeholders, and policy leaders' awareness of providing appropriate support for caregivers. Future research incorporating programs that support caregivers’ needs is recommended.
Development of the Scientific Research Competency Scale for nurses
Authors: Duru Pınar , Örsal Özlem 
Published: December 2021

Background The planning, implementation, finalisation and reporting of high-quality research depends on the knowledge, skills and competencies of the many individuals who make carrying out the research possible. Aims This study aims to develop a valid and reliable scale in order to identify the scientific research competencies of nursing professionals at undergraduate and graduate level. Methods This methodological study was carried out on 937 nursing personnel, 422 (45%) of whom were academic members and 515 (55%) were undergraduate students. The Anxiety Scale Towards Research and the Attitude Scale Towards Scientific Research were used for the criterion validity. Results The Scientific Research Competency Scale comprises 57 items in four sub-dimensions named as ‘technical skills’, ‘attitude and behaviours’, ‘estimation capacity’ and ‘foreign language skill’. The Cronbach alpha, Guttmann split-half and Spearman Brown reliability coefficients for the scientific research competency scale were, respectively, 0.98, 0.96 and 0.96. The sensitivity and specificity value, by which the research competency of individuals could be determined with minimum error, was indicated to be at 190 breakpoints of the scientific research competency scale. Conclusions As a result, the scientific research competency scale developed is a valid and reliable tool that can be used to determine the scientific research competencies of nursing professionals.
The ‘Cruciform Test’: A diagnostic tool to detect pectoralis major rupture
Authors: Cobb Timothy E , Alexander Susan , Reynolds Andy P , Wallace Andrew L 
Published: December 2021

Introduction Pectoralis major (PM) rupture is a severe injury that untreated can lead to a profound functional deficit. Early surgical repair can greatly improve outcomes and give a more predictable timetable for recovery, making this the goal of current treatment. Surgical intervention is also essential to return professional athletes to their previous level of competition. However, there is no single, reliable and easily reproducible test that can be used to establish the diagnosis. We describe ‘The Cruciform Test’; a method of identifying PM rupture that can be used for initial diagnosis either in clinic or a pitch-side environment, or to assess restoration of normal anatomy and function post-operatively. Methods We studied a series of 14 patients who underwent open PM repair in order to evaluate this method of assessment. Results All patients had a positive test pre-operatively. 5 were formally tested at post-operative follow-up and all had a negative result. Discussion The Cruciform Test is a simple and reproducible diagnostic tool that has potential as a clinical indicator of both PM rupture and successful repair. It can therefore contribute to earlier diagnosis, prompt surgical intervention and facilitate return to play at the earliest opportunity.
Angled BIO-RSA leads to better inclination and clinical outcomes compared to Standard BIO-RSA and eccentric reaming: A comparative study
Authors: Franceschetti Edoardo , Giovannetti de Sanctis Edoardo , Gregori Pietro , Paciotti Michele , Palumbo Alessio , Franceschi Francesco 
Published: December 2021

Background Two surgical techniques were compared : Standard BIO-RSA, performed with a glenoid eccentric reaming along with a cylindric bone graft augmentation vs. the Angled BIO-RSA, performed with a glenoid concentric reaming and a defect correction with an angled bone graft. Methods Patients undergoing RSA from January 2016 to April 2019, with one of the two techniques being performed, were retrospectively reviewed. Glenoids were classified according to Favard. Clinical (Constant-Murley, VAS and ROM) and radiographic (superior tilt correction) data were collected pre-operatively and at 12 months post-operatively. Results 141 shoulders were included. Angled BIO-RSA group showed statistically significant better outcomes in terms of forward flexion (149.9° Vs 139.3°) and abduction (136.4° Vs 126.7°). The use of an Angled BIO-RSA showed a statistically significant better superior tilt correction (1.252° Vs 4.09°). Angled BIO-RSA, leads to a better inclination correction and a mean postoperative tilt value inferior to 5° in E1 and E3 differently from standard BIO-RSA. Discussion Both techniques were able to correct glenoid superior inclination with excellent postoperative short-term results. However, angled BIO-RSA technique appears to be more effective in ensuring a correct inclination of the prosthetic glenoid component with better clinical outcomes.
The risk of being culpable for or involved in a road crash after using cannabis: A systematic review and meta-analyses
Authors: White Michael A. , Burns Nicholas R. 
Published: December 2021

Background The development of drug driving policies should rest on sound epidemiological evidence as to the crash risks of driving after using psychoactive drugs. The findings from individual studies of the increased risk of crashing from the acute use of cannabis range in size from no increase (and perhaps even a protective effect) to a 10-fold increase. Coherent cannabis-driving policies cannot readily be developed from such an incoherent evidence base. A weighted average measure of risk, as provided by a meta-analysis, might be useful. However, if the range of risks found in the cannabis-crash studies reflects the different ways that a variety of biases are being expressed, then the simple application of a meta-analysis might provide little more than an average measure of bias. In other words, if the biases were predominantly inflationary, the meta-analysis would give an inflated estimate of crash risk; and if the biases were predominantly deflationary, the meta-analysis would give a deflated estimate of risk. Review We undertook a systematic search of electronic databases, and identified 13 culpability studies and 4 case–control studies from which cannabis-crash odds ratios could be extracted. Random-effects meta-analyses gave summary odds ratios of 1.37 (1.10–1.69) for the culpability studies and 1.45 (0.94–2.25) for the case–control studies. A tool was designed to identify and score biases arising from: confounding by uncontrolled covariates; inappropriate selection of cases and controls; and the inappropriate measurement of the exposure and outcome variables. Each study was scrutinised for the presence of those biases, and given a total ‘directional bias score’. Most of the biases were inflationary. A meta-regression against the total directional bias scores was performed for the culpability studies, giving a bias-adjusted summary odds ratio of 0.68 (0.45–1.05). The same analysis could not be performed for the case–control studies because there were only four such studies. Nonetheless, a monotonic relationship was found between the total bias scores and the cannabis-crash odds ratios, with Spearman's rho  =  0.95, p  =  0.05, indicating that the summary odds ratio of 1.45 is an overestimate. It is evident that the risks from driving after using cannabis are much lower than from other behaviours such as drink-driving, speeding or using mobile phones while driving. With the medical and recreational use of cannabis becoming more prevalent, the removal of cannabis-presence driving offences should be considered (while impairment-based offences would remain).
Risk Factors for Postpartum Depression During COVID-19 Pandemic: A Systematic Literature Review
Authors: Usmani Sadia , Greca Elona , Javed Sana , Sharath Medha , Sarfraz Zouina , Sarfraz Azza , Salari Syeda Wajiha , Hussaini Syed Sameer , Mohammadi Asma , Chellapuram Nikitha , Cabrera Erik , Ferrer Gerardo 
Published: December 2021

Introduction: The COVID-19 pandemic has had a devastating worldwide effect on mental health. Recent studies correlate the spreading of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with symptoms of depression, most prominent in postpartum women. Our systematic literature review scope is to identify the risk factors and predictors for postpartum depression (PPD) and describe the steps that should be taken to help postpartum women. This study will help clinicians, researchers, and policymakers to elucidate the predictors of PPD during this pandemic and prevent these adverse outcomes in future crises. Methods: We conducted a systematic search by employing databases PubMed, Google Scholar, Scopus, and Embase to identify articles published before March 2021. About 463 publications were generated during our search process and from those, 36 were reviewed, summarized, and synthesized. Studies qualified the criteria if they (1) utilized qualitative or quantitative design, (2) explored the risk factors for PPD, and (3) were written in English. Quality evaluation of each study was achieved by using criteria set by Lincoln and Guba. Results: Prevalence of depression symptoms ranged from 7% to 80.8% in postpartum women during the SARS-COV 2 pandemic. The risk factors for PPD were classified into 6 major categories: socio-demographic, psychological, pre-existing pathology, metabolic factors, previous events of miscarriage, and media misinformation. Conclusion: It is extremely vital to care for women’s mental health during pregnancy and after childbirth during these unprecedented times. This review urges the need to design adequate interventions for this vulnerable population to prevent negative consequences of PPD.
Prediction of Postoperative Delirium in Geriatric Hip Fracture Patients: A Clinical Prediction Model Using Machine Learning Algorithms
Authors: Oosterhoff Jacobien H. F. , Karhade Aditya V. , Oberai Tarandeep , Franco-Garcia Esteban , Doornberg Job N. , Schwab Joseph H. 
Published: December 2021

Introduction Postoperative delirium in geriatric hip fracture patients adversely affects clinical and functional outcomes and increases costs. A preoperative prediction tool to identify high-risk patients may facilitate optimal use of preventive interventions. The purpose of this study was to develop a clinical prediction model using machine learning algorithms for preoperative prediction of postoperative delirium in geriatric hip fracture patients. Materials & Methods Geriatric patients undergoing operative hip fracture fixation were queried in the American College of Surgeons National Surgical Quality Improvement Program database (ACS NSQIP) from 2016 through 2019. A total of 28 207 patients were included, of which 8030 (28.5%) developed a postoperative delirium. First, the dataset was randomly split 80:20 into a training and testing subset. Then, a random forest (RF) algorithm was used to identify the variables predictive for a postoperative delirium. The machine learning-model was developed on the training set and the performance was assessed in the testing set. Performance was assessed by discrimination (c-statistic), calibration (slope and intercept), overall performance (Brier-score), and decision curve analysis. Results The included variables identified using RF algorithms were (1) age, (2) ASA class, (3) functional status, (4) preoperative dementia, (5) preoperative delirium, and (6) preoperative need for mobility-aid. The clinical prediction model reached good discrimination (c-statistic = .79), almost perfect calibration (intercept = −.01, slope = 1.02), and excellent overall model performance (Brier score = .15). The clinical prediction model was deployed as an open-access web-application: https://sorg-apps.shinyapps.io/hipfxdelirium/ . Discussion & Conclusions We developed a clinical prediction model that shows promise in estimating the risk of postoperative delirium in geriatric hip fracture patients. The clinical prediction model can play a beneficial role in decision-making for preventative measures for patients at risk of developing a delirium. If found to be externally valid, clinicians might use the available web-based application to help incorporate the model into clinical practice to aid decision-making and optimize preoperative prevention efforts.
Swing Type and Batting Grip Affect Peak Pressures on the Hook of Hamate in Collegiate Baseball Players
Authors: Flynn Lindsay S. , Richard George J. , Vincent Heather K. , Bruner Michelle , Chen Cong , Matthias Robert C. , Zaremski Jason L. , Farmer Kevin W. 
Published: December 2021

Background: Bat swing and grip type may contribute to hook of hamate fractures in baseball players. Purpose: To compare the effects of swing type and batting grip on the pressure and rate of pressure development over the hook of hamate in collegiate baseball players. Study Design: Descriptive laboratory study. Level of evidence, 3. Methods: This was an experimental quasi-randomized study of bat grip and swing differences in National Collegiate Athletic Association Division I baseball players (N = 14; age, 19.6 ± 1.1 years [mean ± SD]). All participants performed swings under 6 combinations: 3 grip types (all fingers on the bat shaft [AO], one finger off the bat shaft [OF], and choked up [CU]) and 2 swing types (full swing and check swing). Peak pressure and rate of pressure generation over the area of the hamate were assessed using a pressure sensor fitted to the palm of the bare hand over the area of the hamate. Wrist angular velocities and excursions of radial ulnar deviation were obtained using 3-dimensional motion analysis. Results: The OF–check swing combination produced the highest peak pressure over the hamate (3.72 ± 2.64 kg/cm2) versus the AO–full swing (1.36 ± 0.73 kg/cm2), OF–full swing (1.68 ± 1.17 kg/cm2), and CU–full swing (1.18 ± 0.96 kg/cm2; P < .05 for all). There was a significant effect of condition on rate of pressure development across the 6 conditions ( P = .023). Maximal wrist angular velocities were 44% lower in all check swing conditions than corresponding full swing conditions ( P < .0001). The time to achieve the maximal wrist angular velocity was longest with the AO–full swing and shortest with the CU–check swing (100.1% vs 7.9% of swing cycle; P = .014). Conclusion: The OF–check swing condition produced the highest total pressure reading on the hook of hamate. Check swing conditions also had the steepest rate of pressure development as compared with the full swing conditions. Clinical Relevance: Batters who frequently check their swings and use an OF or AO grip may benefit from bat modifications or grip adjustment to reduce stresses over the hamate. Athletic trainers and team physicians should be aware of these factors to counsel players in the context of previous or ongoing hand injury.
Comparison of Dental Injury Rates in Perioperative Intubation and Suspension Laryngoscopy for Otolaryngology Procedures
Authors: Wilson Caleb P. , Romano Erica , Vasan Nilesh R. 
Published: December 2021

ObjectiveDirect laryngoscopy is an essential skill during perioperative intubation and otolaryngology procedures. Dental injury is a common complication of direct laryngoscopy. However, the technique and tools used by anesthesiologists, nurse anesthetists, and others during perioperative intubation and by ear, nose, and throat surgeons for their procedures are different. The purpose of this review is to explore the literature for all studies detailing rates of dental injury in each of these settings and to compare them to see if the approaches have a significant difference in rate of dental injury.Data SourcesPubMed.Review MethodsA comprehensive search of PubMed was performed through February 2021 with search terms “dental” and “intubation” or “laryngoscopy.” PRISMA guidelines were followed. Studies documenting rates of dental injuries during intubation or during laryngologic procedures were included, and the 2 groups were compared.ResultsTwenty‐three studies met inclusion criteria: 17 in the perioperative intubation group and 6 in the suspension laryngoscopy group. There was an increased incidence of dental injury in the perioperative intubation group (4.86%) as compared with the suspension laryngoscopy group (1.70%).ConclusionsThe difference in dental injury rate between the groups could be due to the differences in direct laryngoscopy technique or tools used, the presence vs absence of a dental guard, or a combination of these factors. More studies need to be performed to develop definitive and specific conclusions to recommend changes that prevent dental injury.
JLAN: medical code prediction via joint learning attention networks and denoising mechanism
Authors: Li Xingwang , Zhang Yijia , Islam Faiz ul , Dong Deshi , Wei Hao , Lu Mingyu 
Published: December 2021

AbstractBackgroundClinical notes are documents that contain detailed information about the health status of patients. Medical codes generally accompany them. However, the manual diagnosis is costly and error-prone. Moreover, large datasets in clinical diagnosis are susceptible to noise labels because of erroneous manual annotation. Therefore, machine learning has been utilized to perform automatic diagnoses. Previous state-of-the-art (SOTA) models used convolutional neural networks to build document representations for predicting medical codes. However, the clinical notes are usually long-tailed. Moreover, most models fail to deal with the noise during code allocation. Therefore, denoising mechanism and long-tailed classification are the keys to automated coding at scale.ResultsIn this paper, a new joint learning model is proposed to extend our attention model for predicting medical codes from clinical notes. On the MIMIC-III-50 dataset, our model outperforms all the baselines and SOTA models in all quantitative metrics. On the MIMIC-III-full dataset, our model outperforms in the macro-F1, micro-F1, macro-AUC, and precision at eight compared to the most advanced models. In addition, after introducing the denoising mechanism, the convergence speed of the model becomes faster, and the loss of the model is reduced overall.ConclusionsThe innovations of our model are threefold: firstly, the code-specific representation can be identified by adopted the self-attention mechanism and the label attention mechanism. Secondly, the performance of the long-tailed distributions can be boosted by introducing the joint learning mechanism. Thirdly, the denoising mechanism is suitable for reducing the noise effects in medical code prediction. Finally, we evaluate the effectiveness of our model on the widely-used MIMIC-III datasets and achieve new SOTA results.