bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validation of general pain scores from multidomain assessment tools in stroke
Authors: Ali Myzoon , Tibble Holly , Brady Marian C. , Quinn Terence J. , Sunnerhagen Katharina S. , Venketasubramanian Narayanaswamy , Shuaib Ashfaq , Pandyan Anand , Mead Gillian 
Published: January 2024

PurposeWe describe how well general pain reported in multidomain assessment tools correlated with pain-specific assessment tools; associations between general pain, activities of daily living and independence after stroke.Materials and methodsAnalyses of individual participant data (IPD) from the Virtual International Stroke Trials Archive (VISTA) described correlation coefficients examining (i) direct comparisons of assessments from pain-specific and multidomain assessment tools that included pain, (ii) indirect comparisons of pain assessments with the Barthel Index (BI) and modified Rankin Scale (mRS), and (iii) whether pain identification could be enhanced by accounting for reported usual activities, self-care, mobility and anxiety/depression; factors associated with pain.ResultsEuropean Quality of Life 3- and 5-Level (EQ-5D-3L and EQ-5D-5L), RAND 36 Item Health Survey 1.0 (SF-36) or the 0–10 Numeric Pain Rating Scale (NPRS) were available from 10/94 studies (IPD = 10,002). The 0–10 NPRS was the only available pain-specific assessment tool and was a reference for comparison with other tools. Pearson correlation coefficients between the 0–10 NPRS and (A) the EQ-5D-3L and (B) EQ5D-5 L were r = 0.572 (n = 436) and r = 0.305 (n = 1,134), respectively. mRS was better aligned with pain by EQ-5D-3L (n = 8,966; r = 0.340) than by SF-36 (n = 623; r = 0.318). BI aligned better with pain by SF-36 (n = 623; r = −0.320). Creating a composite score using the EQ-5D 3 L and 5 L comprising pain, mobility, usual-activities, self-care and anxiety/depression did not improve correlation with the 0–10 NPRS.DiscussionThe EQ-5D-3L pain domain aligned better than the EQ-5D-5L with the 0–10 NPRS and may inform general pain description where resources and assessment burden hinder use of additional, pain-specific assessments.
Mononeuritis multiplex following immune checkpoint inhibitors in malignant pleural mesothelioma
Authors: Farina Antonio , Escalere Manon , Dion Matthias , Moussy Martin , Pegat Antoine , Villagrán-García Macarena , Devic Perrine , Lamiral Anaïde , Seyve Antoine , Aure Karine , Wang Adrien , Gorza Lucas , Streichenberger Nathalie , Maisonobe Thierry , Honnorat Jerome , Birzu Cristina , Psimaras Dimitri , Weisenburger-Lile David , Joubert Bastien 
Published: January 2024

IntroductionMononeuritis multiplex is frequently related to vasculitic neuropathy and has been reported only sporadically as an adverse event of immune checkpoint inhibitors.MethodsCase series of three patients with mononeuritis multiplex—all with mesothelioma—identified in the databases of two French clinical networks (French Reference Center for Paraneoplastic Neurological Syndromes, Lyon; OncoNeuroTox, Paris; January 2015–October 2022) set up to collect and investigate n-irAEs on a nationwide level.ResultsThree patients (male; median age 86 years; range 72–88 years) had pleural mesothelioma and received 10, 4, and 6 cycles, respectively, of first-line nivolumab plus ipilimumab combined therapy. In patient 1, the neurological symptoms involved the median nerves, and in the other two patients, there was a more diffuse distribution; the symptoms were severe (common terminology criteria for adverse events, CTCAE grade 3) in all patients. Nerve conduction studies indicated mononeuritis multiplex in all patients. Peripheral nerve biopsy demonstrated necrotizing vasculitis in patients 1 and 3 and marked IgA deposition without inflammatory lesions in patient 2. Immune checkpoint inhibitors were permanently withdrawn, and corticosteroids were administered to all patients, leading to complete symptom regression (CTCAE grade 0, patient 2) or partial improvement (CTCAE grade 2, patients 1 and 3). During steroid tapering, patient 1 experienced symptom recurrence and spreading to other nerve territories (CTCAE grade 3); he improved 3 months after rituximab and cyclophosphamide administration.DiscussionWe report the occurrence of mononeuritis multiplex, a very rare adverse event of immune checkpoint inhibitors, in the three patients with mesothelioma. Clinicians must be aware of this severe, yet treatable adverse event.
The effects of different intermittent fasting regimens in people with type 2 diabetes: a network meta-analysis
Authors: Xiaoyu Wen , Yuxin Xiao , Li Lai 
Published: January 2024

ObjectiveTo compare the effects of four intermittent fasting regimens on blood glucose and insulin sensitivity in people with type 2 diabetes.MethodsRandomized controlled trials of intermittent fasting in the treatment of patients with type 2 diabetes mellitus in PubMed, the Cochrane Library, Embase, ScienceDirect, Web of Science, CNKI, VIP Database, and WANFANG Database were searched for from the library to September 2023. 2 review authors independently screened studies and extracted data. RevMan 5.4 was used for direct comparison of meta-results. Network meta-analysis was performed using Stata16 software.Results13 studies with a total of 867 patients were included. The intervention effects of twice-per-week fasting, fasting-mimicking diet, time-restricted eating, and peridic fasting were better than that of conventional diet. The results of the network comparison showed that there was no significant difference in the intervention effect of the intermittent fasting regimens. SUCRA ranking results showed that the twice-per-week fasting was best for comprehensive interventions for improvement.ConclusionFrom the perspective of fasting blood glucose, glycated hemoglobin and insulin resistance, the twice-per-week fasting intervention has a good effect, which can be used as a reference for patients with inter-type 2 diabetes to choose intermittent fasting regimen. However, more clinical trials are needed to verify this at a later stage.
Daratumumab-based immunotherapy vs. lenalidomide, bortezomib and dexamethasone in transplant-ineligible newly diagnosed multiple myeloma: a systemic review
Authors: Tang Wenjiao , Zhang Li , Zheng Yuhuan , Pan Ling , Niu Ting 
Published: January 2024

BackgroundSince no randomized controlled trials have directly compared the efficacy and safety of immunotherapy with daratumumab versus lenalidomide/bortezomib/dexamethasone (RVD) in the frontline treatment of transplant-ineligible newly diagnosed multiple myeloma (TIE-NDMM), this study systematically reviewed the clinical studies regarding immunotherapy with daratumumab and RVD regimen in the treatment of TIE-NDMM to explore the optimization direction of the best first-line therapy.MethodsThe Cochrane Library, PubMed, Embase, and Web of Science databases were searched to collect studies on regimens containing daratumumab or RVD/RVD-lite for TIE-NDMM. Pooled and meta-analysis was then performed to compare the overall response rate (ORR), stringent complete remission (sCR) and CR rate, progression-free survival (PFS), overall survival (OS) and treatment-related discontinuation rate between daratumumab-containing immunotherapy regimen and RVD/RVD-lite regimen by using R 4.3.1 software.ResultsNine prospective clinical trials were included, including 1795 TIE-NDMM or NDMM without intent for immediate ASCT. Among them, 938 patients were treated with daratumumab-based immunotherapy and 857 with RVD/RVD-lite regimens. Meta-analysis results showed that The daratumumab-based regimen showed a significantly higher CR/sCR rate than RVD/RVD-lite for TIE-NDMM (47% vs. 24%, P&lt;0.01). The median PFS of the daratumumab-based and RVD/RVD-lite groups were 52.6 months and 35.1 months respectively (HR 0.77, 95%CI, 0.66-0.90). The median OS of both groups was not reached, and there were no significant differences in OS between the two groups (HR 1.03, 95%CI, 0.86-1.23). The therapy discontinuation rate led by adverse events was significantly higher in the RVD/RVD-lite group than in the daratumumab-based regimen group for the TIE-NDMM (16% vs. 7%, P=0.03).ConclusionThis meta-analysis suggests that daratumumab-containing immunotherapy is superior to RVD in the depth of treatment efficacy, progression-free survival, and lower treatment-related discontinuation rates. Limited by the lack of head-to-head clinical trials, this conclusion needs to be verified by concurrent cohort studies.
Accuracy of radiomics in the diagnosis and preoperative high-risk assessment of endometrial cancer: a systematic review and meta-analysis
Authors: He Junmei , Liu Yurong , Li Jinzhu , Liu Shuang 
Published: January 2024

BackgroundWith the increasing use of radiomics in cancer diagnosis and treatment, it has been applied by some researchers to the preoperative risk assessment of endometrial cancer (EC) patients. However, comprehensive and systematic evidence is needed to assess its clinical value. Therefore, this study aims to investigate the application value of radiomics in the diagnosis and treatment of EC.MethodsPubmed, Cochrane, Embase, and Web of Science databases were retrieved up to March 2023. Preoperative risk assessment of EC included high-grade EC, lymph node metastasis, deep myometrial invasion status, and lymphovascular space invasion status. The quality of the included studies was appraised utilizing the RQS scale.ResultsA total of 33 primary studies were included in our systematic review, with an average RQS score of 7 (range: 5–12). ML models based on radiomics for the diagnosis of malignant lesions predominantly employed logistic regression. In the validation set, the pooled c-index of the ML models based on radiomics and clinical features for the preoperative diagnosis of endometrial malignancy, high-grade tumors, lymph node metastasis, lymphovascular space invasion, and deep myometrial invasion was 0.900 (95%CI: 0.871–0.929), 0.901 (95%CI: 0.877–0.926), 0.906 (95%CI: 0.882–0.929), 0.795 (95%CI: 0.693–0.897), and 0.819 (95%CI: 0.705–0.933), respectively.ConclusionsRadiomics shows excellent accuracy in detecting endometrial malignancies and in identifying preoperative risk. However, the methodological diversity of radiomics results in significant heterogeneity among studies. Therefore, future research should establish guidelines for radiomics studies based on different imaging sources.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=364320 identifier CRD42022364320.
Time to recovery from neonatal sepsis and its determinants among neonates admitted in Woldia comprehensive specialized hospital, Northeast Ethiopia: a retrospective cohort study
Authors: Ambaye Kassawmar , Yimer Ali , Mislu Esuyawkal , Wendimagegn Zeru , Kumsa Henok 
Published: January 2024

BackgroundNeonatal sepsis is the most serious problem in neonates. It is the leading cause of neonatal death in developing countries, particularly in sub-Saharan Africa. The Ethiopian 2016 Demographic Health Survey report revealed that a high number of neonatal deaths are associated with neonatal sepsis. However, limited studies are available on exposure and time to recovery inferences in Ethiopia. Therefore, this study aimed to assess the time to recovery from neonatal sepsis and its determinants among neonates admitted to Woldia Comprehensive Specialized Hospital (WCSH), Northeast Ethiopia.MethodsA retrospective cohort study was conducted, including 351 neonates, using systematic random sampling at WCSH from 7 to 30 March 2023. The data were entered into Epi data version 4.6 and exported to STATA 14 for analysis. Cox regression was used to identify the determinants of time to recovery from neonatal sepsis, and a variable with a p-value of less than 0.05, was used to declare significant association at a 95% confidence interval.ResultAmong 351 neonates with sepsis, 276 (78.63%) recovered, and the median time to recovery was 6 days. Induced labor (AHR = 0.54, 95% CI: 0.369, 0.78) and resuscitation at birth (AHR = 0.7, 95% CI: 0.51, 0.974) were significantly associated with the recovery time of neonatal sepsis.Conclusions and recommendationThe time to recovery from neonatal sepsis is comparable to previous studies' results. The 25th and 75th percentiles were 4 and 8 days, respectively. Health professionals working in the NICU need to pay special attention to neonates born from mothers who had induced labor and those who were resuscitated at birth.
Strengths and opportunities to clinical trial enrollment among BIPOC, rural dwelling patients in the northwest United States: a retrospective study
Authors: Nelson Jamie M. , Johnson Elizabeth , Kiesow Becky , McCrory Bernadette , Ma Jiahui 
Published: January 2024

Introduction: Clinical trials investigating the safety and efficacy of experimental drugs and devices are the cornerstone of medicinal advancement. Enrolling sufficient participants in these trials is vital to ensure adequate statistical power and generalizability. Clinical trial participation is particularly low among certain populations, including medically underserved communities (i.e., rural areas) and Black, Indigenous, and People of Color (BIPOC).Methods: A retrospective study design was used to understand patient outcomes and access/barriers to clinical trial participation in the rural northwest United States. A quantitatively focused retrospective chart review was conducted for adult participants enrolled in at least one clinical trial in a single northwest health system between 1999 and 2022. Descriptive and inferential statistical analyses were performed to assess trial outcomes at a significance level 0.05.Results: The retrospective chart review yielded 833 clinical trial records with 753 individual enrolled participants. The all-cause relative frequency of death at last known follow-up amongst clinical trial participants was 8.90% (n = 67). Based on logistic regression, the death was significantly associated with the participants’ age at initial trial screening (β = 0.09, p-value &lt;0.001), those that resided in non-metro areas (β = −0.86, p-value = 0.045), and those that lived in Northeastern Montana (β = 1.27, p-value = 0.025). Additionally, death at last known follow-up was significantly associated with enrollment in 2021–2022 (β = −1.52, p-value &lt;0.001), enrolled in more than one study (β = 0.84, p-value = 0.023), in internationally sponsored trials (β = −2.08, p-value &lt;0.001), in Phase I (β = 5.34, p-value &lt;0.001), in Phase II trials (β = 1.37, p-value = 0.013), diabetes as a primary trial target (β = −2.04, p-value = 0.003).Conclusion: As decentralized trial design and remote or virtual elements of traditional trials become normative, representation of rural and frontier populations is imperative to support the generalizability of trial data encouraged by the FDA.
A novel dilated contextual attention module for breast cancer mitosis cell detection
Authors: Li Zhiqiang , Li Xiangkui , Wu Weixuan , Lyu He , Tang Xuezhi , Zhou Chenchen , Xu Fanxin , Luo Bin , Jiang Yulian , Liu Xingwen , Xiang Wei 
Published: January 2024

Background and object: Mitotic count (MC) is a critical histological parameter for accurately assessing the degree of invasiveness in breast cancer, holding significant clinical value for cancer treatment and prognosis. However, accurately identifying mitotic cells poses a challenge due to their morphological and size diversity.Objective: We propose a novel end-to-end deep-learning method for identifying mitotic cells in breast cancer pathological images, with the aim of enhancing the performance of recognizing mitotic cells.Methods: We introduced the Dilated Cascading Network (DilCasNet) composed of detection and classification stages. To enhance the model’s ability to capture distant feature dependencies in mitotic cells, we devised a novel Dilated Contextual Attention Module (DiCoA) that utilizes sparse global attention during the detection. For reclassifying mitotic cell areas localized in the detection stage, we integrate the EfficientNet-B7 and VGG16 pre-trained models (InPreMo) in the classification step.Results: Based on the canine mammary carcinoma (CMC) mitosis dataset, DilCasNet demonstrates superior overall performance compared to the benchmark model. The specific metrics of the model’s performance are as follows: F1 score of 82.9%, Precision of 82.6%, and Recall of 83.2%. With the incorporation of the DiCoA attention module, the model exhibited an improvement of over 3.5% in the F1 during the detection stage.Conclusion: The DilCasNet achieved a favorable detection performance of mitotic cells in breast cancer and provides a solution for detecting mitotic cells in pathological images of other cancers.
Prototyping the implementation of a suicide prevention protocol in primary care settings using PDSA cycles: a mixed method study
Authors: Minian Nadia , Gayapersad Allison , Coroiu Adina , Dragonetti Rosa , Zawertailo Laurie , Zaheer Juveria , O’Neill Braden , Lange Shannon , Thomson Nicole , Crawford Allison , Kennedy Sidney H. , Selby Peter 
Published: January 2024

IntroductionIn Canada, approximately 4,500 individuals die by suicide annually. Approximately 45% of suicide decedents had contact with their primary care provider within the month prior to their death. Current versus never smokers have an 81% increased risk of death by suicide. Those who smoke have additional risks for suicide such as depression, chronic pain, alcohol, and other substance use. They are more likely to experience adverse social determinants of health. Taken together, this suggests that smoking cessation programs in primary care could be facilitators of suicide prevention, but this has not been studied.Study objectivesThe objectives of the study are to understand barriers/facilitators to implementing a suicide prevention protocol within a smoking cessation program (STOP program), which is deployed by an academic mental health and addiction treatment hospital in primary care clinics and to develop and test implementation strategies to facilitate the uptake of suicide screening and assessment in primary care clinics across Ontario.MethodsThe study employed a three-phase sequential mixed-method design. Phase 1: Conducted interviews guided by the Consolidated Framework for Implementation Research exploring barriers to implementing a suicide prevention protocol. Phase 2: Performed consensus discussions to map barriers to implementation strategies using the Expert Recommendations for Implementing Change tool and rank barriers by relevance. Phase 3: Evaluated the feasibility and acceptability of implementation strategies using Plan Do Study Act cycles.ResultsEleven healthcare providers and four research assistants identified lack of training and the need of better educational materials as implementation barriers. Participants endorsed and tested the top three ranked implementation strategies, namely, a webinar, adding a preamble before depression survey questions, and an infographic. After participating in the webinar and reviewing the educational materials, all participants endorsed the three strategies as acceptable/very acceptable and feasible/very feasible.ConclusionAlthough there are barriers to implementing a suicide prevention protocol within primary care, it is possible to overcome them with strategies deemed both acceptable and feasible. These results offer promising practice solutions to implement a suicide prevention protocol in smoking cessation programs delivered in primary care settings. Future efforts should track implementation of these strategies and measure outcomes, including provider confidence, self-efficacy, and knowledge, and patient outcomes.
Can adverse childhood experiences predict chronic health conditions? Development of trauma-informed, explainable machine learning models
Authors: Afzal Hanin B. , Jahangir Tasfia , Mei Yiyang , Madden Annabelle , Sarker Abeed , Kim Sangmi 
Published: January 2024

IntroductionDecades of research have established the association between adverse childhood experiences (ACEs) and adult onset of chronic diseases, influenced by health behaviors and social determinants of health (SDoH). Machine Learning (ML) is a powerful tool for computing these complex associations and accurately predicting chronic health conditions.MethodsUsing the 2021 Behavioral Risk Factor Surveillance Survey, we developed several ML models—random forest, logistic regression, support vector machine, Naïve Bayes, and K-Nearest Neighbor—over data from a sample of 52,268 respondents. We predicted 13 chronic health conditions based on ACE history, health behaviors, SDoH, and demographics. We further assessed each variable’s importance in outcome prediction for model interpretability. We evaluated model performance via the Area Under the Curve (AUC) score.ResultsWith the inclusion of data on ACEs, our models outperformed or demonstrated similar accuracies to existing models in the literature that used SDoH to predict health outcomes. The most accurate models predicted diabetes, pulmonary diseases, and heart attacks. The random forest model was the most effective for diabetes (AUC = 0.784) and heart attacks (AUC = 0.732), and the logistic regression model most accurately predicted pulmonary diseases (AUC = 0.753). The strongest predictors across models were age, ever monitored blood sugar or blood pressure, count of the monitoring behaviors for blood sugar or blood pressure, BMI, time of last cholesterol check, employment status, income, count of vaccines received, health insurance status, and total ACEs. A cumulative measure of ACEs was a stronger predictor than individual ACEs.DiscussionOur models can provide an interpretable, trauma-informed framework to identify and intervene with at-risk individuals early to prevent chronic health conditions and address their inequalities in the U.S.