bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of the Patient Global Impression of Symptom Severity (PGISS) Score as a Subjective and Objective Measure of Disease Activity in Chronic Rhinosinusitis
Authors: Lim Subin , Trotier Daniel , Karpov Matvey , Han Joseph , Lam Kent 
Published: January 2025

Background The Sino-nasal Outcome Test (SNOT-22) is a 22-question survey that is utilized to evaluate health-related quality of life of patients with chronic rhinosinusitis (CRS). The Patient Global Impression Symptom Severity (PGISS) is a similar yet versatile instrument that combines features of both a Likert scale and a visual analog to assess symptom severity in CRS patients. While previous studies have evaluated the validity of SNOT-22 as an instrument to measure CRS patients’ symptom severity, no studies have evaluated PGISS scale's ability to evaluate and guide treatment plans for CRS patients. Objective The primary objective of this study was to analyze the clinical utility of PGISS in assessing subjective symptom severity and objective disease status in CRS patients. We additionally aimed to investigate if PGISS scores could serve as predictors for treatment strategies in CRS patients. Methods Electronic medical records of CRS patients were retrospectively reviewed between January 2020 and January 2021 from Eastern Virginia Medical School and Sentara Healthcare. Information on demographics, objective disease metrics, treatment, and labs were collected. Statistical analyses were conducted using SAS 9.4 software. Results A total of 150 patients were included in our study. A statistically significant positive correlation was found between PGISS and SNOT-22 scores (r(131) = 0.701, P < .0001). Patients with moderate to severe PGISS scores had significantly higher odds of changing their treatment course (odds ratio [OR] = 6.813, P = .001, and OR = 5.491, P = .018, respectively). Additionally, patients with severe PGISS scores had decreased odds of receiving biological intervention (OR = 0.048, P = .043), but they had considerably higher odds of pursuing surgery (OR = 15.939, P = .046). No significant associations were seen between PGISS scores and receiving topical steroids, systematic steroids, nonsteroidal medical treatment, or imaging interventions ( P > .05). Conclusion Clinicians may consider using the PGISS scale as an alternative method to the SNOT-22 to evaluate subjective symptom severity and guide treatment plans for patients with CRS.
The holistic and local perspectives in teaching spinal arteriovenous malformations
Authors: Lv Xianli 
Published: January 2025

Background The spinal arteriovenous malformations (sAVMs) have been challenging entities to diagnose and treat. The small structure, important function, and complex vascular anatomy of the spinal cord increase the difficulty of treating sAVMs. Objective The combining holistic and local perspectives in the diagnosis and treatment of sAVMs were provided to teach spinal vascular anatomy and AVMs. Methods and Results A holistic view is to fully understand the anatomical and physiological effects of intracranial vascular lesions on the spinal cord circulatory system, as well as the anatomical and physiological effects of local sAVM on the entire spinal cord circulatory system, such as the relationship between lesions and surrounding blood vessels. The local view is to fully understand the macroscopic and microscopic vascular architectural characteristics of the lesion. The local view is closely related to the treatment of lesions and the holistic view is closely related to the effectiveness and side effects of treatment, which should be given attention in current clinical practice. The early diagnosis and treatment of sAVMs may improve outcomes. Conclusion A holistic and local perspective is essential to developing an understanding of the angioarchitecture, pathophysiology, natural history, treatment options, and classification of the different types of sAVMs.
The potential role of machine learning and deep learning in differential diagnosis of Alzheimer’s disease and FTD using imaging biomarkers: A review
Authors: Mirabian Sara , Mohammadian Fatemeh , Ganji Zohreh , Zare Hoda , Hasanpour Khalesi Erfan 
Published: January 2025

Introduction The prevalence of neurodegenerative diseases has significantly increased, necessitating a deeper understanding of their symptoms, diagnostic processes, and prevention strategies. Frontotemporal dementia (FTD) and Alzheimer’s disease (AD) are two prominent neurodegenerative conditions that present diagnostic challenges due to overlapping symptoms. To address these challenges, experts utilize a range of imaging techniques, including magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), functional MRI (fMRI), positron emission tomography (PET), and single-photon emission computed tomography (SPECT). These techniques facilitate a detailed examination of the manifestations of these diseases. Recent research has demonstrated the potential of artificial intelligence (AI) in automating the diagnostic process, generating significant interest in this field. Materials and Methods This narrative review aims to compile and analyze articles related to the AI-assisted diagnosis of FTD and AD. We reviewed 31 articles published between 2012 and 2024, with 23 focusing on machine learning techniques and 8 on deep learning techniques. The studies utilized features extracted from both single imaging modalities and multi-modal approaches, and evaluated the performance of various classification models. Results Among the machine learning studies, Support Vector Machines (SVM) exhibited the most favorable performance in classifying FTD and AD. In deep learning studies, the ResNet convolutional neural network outperformed other networks. Conclusion This review highlights the utility of different imaging modalities as diagnostic aids in distinguishing between FTD and AD. However, it emphasizes the importance of incorporating clinical examinations and patient symptom evaluations to ensure comprehensive and accurate diagnoses.
A nomogram based on InLDH and InNLR for predicting disseminated intravascular coagulation in patients with heat stroke
Authors: Wan Lulu , Lin Gan , Yang Jiale , Liu Anwei , Shi Xuezhi , Li Jinhu , Xie Lian , Chen Ronglin , Tong Huasheng 
Published: January 2025

Background: Heat stroke (HS), a potentially fatal heat-related illness, is often accompanied by disseminated intravascular coagulation (DIC) early, resulting in a poorer prognosis. Unfortunately, diagnosis by current DIC scores is often too late to identify DIC. This study aims to investigate the predictors and predictive model of DIC in HS to identify DIC early. Methods: This retrospective study analyzed clinical data of patients with HS in a tertiary hospital from January 1, 2008 to December 31, 2020. Univariate and multivariate logistic regression analyses were employed to identify the risk factors for DIC in HS. The predictive models based on these risk factors were constructed and externally validated, and their predictive efficacy was evaluated using receiver operating characteristic curves. Results: A total of 219 HS patients, including 49 with DIC, were included. The independent risk factors for DIC were identified as follows: neutrophil percentage (Neu%), lymphocyte count, lymphocyte percentage (Lym%), creatine kinase-MB (CKMB), lactate dehydrogenase (LDH), aspartate aminotransferase (AST), neutrophil–lymphocyte ratio (NLR), monocyte–lymphocyte ratio (MLR), and rhabdomyolysis (RM). After logarithmization, the final predictive model based on the logarithm of lactate dehydrogenase (InLDH; odds ratio (OR) = 9.266, 95% confidence interval (95%CI; 4.379–19.607), p < 0.0001) and the logarithm of neutrophil–lymphocyte ratio (InNLR; OR = 3.393, 95%CI (1.834–6.277), p < 0.0001) was constructed with the largest area under the curve (0.928). A nomogram incorporating InLDH and InNLR was developed and showed excellent discrimination and calibration capabilities. Conclusion: Nine independent risk factors were identified for the occurrence of DIC in HS patients. The predictive model based on InLDH and InNLR can effectively predict the incidence of DIC. A nomogram based on InLDH and InNLR was developed to facilitate early identification and timely treatment of DIC in HS patients.
Factors associated with ABCDEF bundle implementation for critically ill patients: An international cross-sectional survey in 54 countries
Authors: Haruna Junpei , Unoki Takeshi , Liu Keibun , Nakamura Kensuke , Inoue Shigeaki , Nishida Osamu 
Published: January 2025

Objectives: This study investigated the implementation of the ABCDEF bundle and the factors associated with its implementation according to national income levels. Methods: This study is cross-sectional research. We conducted a secondary analysis of an international 1-day point-prevalence study that investigated the implementation of the ABCDEF bundle in critically ill patients. All patients admitted to the ICU were eligible. This study was conducted across 135 ICUs in 54 countries, including data from 664 patients. Outcomes were categorized according to the income level of the country (high-income, middle-income, and low-income countries) in which each ICU was located. A multilevel generalized linear model was developed to identify the factors associated with ABCDEF bundle implementation for each income level. Results: We identified 664 patients in 79 high-income countries, 278 in 26 middle-income countries, and 287 in 30 low-income countries ICUs. Implementation rates of the ABCDEF bundle were low for all income levels but varied. Few individuals completed the entire bundle on the survey date. Common factors associated with the implementation among all income levels were a multidisciplinary team approach for Element A (pain) and mechanical ventilation use for Element C (sedation), which were also associated with lower Element E (mobility). The existence of a protocol was frequently identified as a promoting factor associated with ABCDEF bundle implementation. The associated factors varied by income level; for example, dedicated intensivists were only identified in high-income countries, but not in middle-income countries or low-income countries. Conclusions: The overall low ABCDEF bundle implementation rates necessitate action. As factors associated with its implementation vary according to national income level, tailored strategies are essential for improving ICU care quality. Trial registration: NA.
Construction of a health literacy prediction model for diabetic patients: A multicenter study
Authors: Wang Zepeng , Shi Junyi , Jiang Fangyuan , Jiang Kui , Chen Yalan 
Published: January 2025

Objectives To achieve a rapid assessment of health literacy (HL) levels among diabetic patients. Methods A questionnaire survey was conducted among diabetic patients from nine communities in Nantong City, Jiangsu Province, China, using convenient sampling. Based on the survey results, data from three communities were randomly selected as the test set, with the remaining data used as the training set. Feature selection was performed using recursive feature elimination. Predictive models were established and compared using logistic regression (LR), random forest (RF), and support vector machine (SVM). Calibration curves, decomposition plots, and partial dependence plots were drawn to evaluate and interpret the models. Results In November 2023, a total of 802 valid questionnaires were received. Eight variables were selected for modeling: educational level, exercise habits, average monthly household income, dietary control, age, medication for blood sugar control, duration of diabetes, and number of cohabitants. The recall for LR in the three communities was 0.778, 0.800, and 0.862 [area under the curve (AUC): 0.810, 0.792, and 0.775]. For RF, the recall values were 0.879, 0.877, and 0.923 (AUC: 0.781, 0.710, and 0.710). For SVM, the recall values were 0.859, 0.862, and 0.877 (AUC: 0.813, 0.759, and 0.770). Model evaluation showed that as the data volume increased, the calibration curves became more ideal. Conclusions As one of the few HL prediction models for diabetic patients in mainland China that is built based on multi-center survey data and evaluated through multi-center assessment, this model can quickly identify patients with insufficient HL using a small amount of objective personal information.
Seeking support and treatment: A thematic analysis of tweets about the experience of endometriosis
Authors: Tragantzopoulou Panagiota , Giannouli Vaitsa 
Published: January 2025

Background: Endometriosis significantly affects women’s quality of life, yet remains underrepresented in public discourse. This study aimed to explore the lived experiences and challenges of women with endometriosis as expressed on Twitter/X. Methods: A total of 2000 tweets were collected between September 2023 to November 2023 using relevant hashtags. Tweets were thematically analyzed using NVivo to identify recurring patterns in women’s experiences with endometriosis. Results: Findings indicated that 35% of the tweets described chronic pain, difficulty completing daily tasks, and concerns about infertility. In 30% of the tweets, women also discussed various treatments, including surgery, medication, and dietary modifications, with a notable focus on weight loss and healthy eating. However, a problematic preoccupation with food and weight was observed in discussions about dietary changes. A recurring theme observed in the remaining tweets was the feeling of being dismissed by healthcare providers, with many addressing gender dynamics and bias in the medical field. Conclusion: This study highlights the power of Twitter/X as a platform for raising awareness about endometriosis. The findings underscore the need for improved healthcare services and the development of supportive communities for women with the condition.
Continuous Glucose Monitoring Attrition in Youth With Type 1 Diabetes
Authors: Meighan Seema , Lipman Terri H. , VanGraafeiland Brigit , Marks Brynn E. 
Published: January 2025

Purpose The purpose of the study was to identify the most common reasons for and timing of continuous glucose monitoring (CGM) attrition in youth with type 1 diabetes (T1DM). Methods This single center retrospective chart review included youth with T1DM <22 years seen between November 1, 2021, and October 31, 2022. Data were gathered from CGM cloud-based software and the electronic medical record. Results Among 2663 youth, 88.3% (n = 2351) actively used CGM, and 5.9% (n = 311) had CGM attrition. Those who discontinued CGM were older (17.0 vs 14.9 years, P = .0001), had a longer T1DM duration (7.4 vs 5.1 years), higher A1C (9% vs 7.4%), and were non-Hispanic Black (NHB; 34.0% vs 11.5%). The odds of CGM attrition were 5.0 and 2.8 times higher in NHB and Latine youth, respectively, compared to non-Hispanic White youth. Median time to CGM discontinuation was 4 months, 21 days after initiation; 57% of youth who discontinued did so in the first 6 months of use. The most common reasons for CGM attrition were problems with device adhesion (18.4%), dislike device on the body (10.8%), insurance problems (9.5%), pain with device use (8.3%), and system mistrust due to inaccurate readings (8.2%). NHB and Latine youth were more likely to discontinue CGM due to insurance problems (3.2% vs 15.1% vs 16.7%). Conclusions To support equitable, uninterrupted CGM use, education at CGM initiation should address practical approaches to improve adhesion and wearability and provide a clear pathway to obtaining supplies. Interventions to support sustained CGM use should occur within the first 6 months of initiation.
Pre-biologic disease trajectories are associated with morbidity burden and biologic treatment response in severe asthma
Authors: Soendergaard Marianne Baastrup , Hjortdahl Frederikke , Hansen Susanne , Bjerrum Anne-Sofie , von Bülow Anna , Hilberg Ole , Bonnesen Bertelsen Barbara , Johnsen Claus Rikard , Lock-Johansson Sofie , Vijdea Roxana , Rasmussen Linda Makowska , Schmid Johannes Martin , Ulrik Charlotte Suppli , Porsbjerg Celeste , Håkansson Kjell Erik Julius 
Published: January 2025

BackgroundBiologics can induce remission in some patients with severe asthma, however, little is known about pre-biologic disease trajectories and their association with outcomes from biological treatment. We aimed to identify long-term trajectories of disease progression in patients initiating biologics and investigate trajectory associations with disease burden and impact on biologic therapy efficacy.MethodsPatients in the Danish Severe Asthma Registry initiating biologic therapy between 2016–2022 were included and followed retrospectively in prescription databases starting 1995. We performed sequence analysis for inhaled corticosteroid (ICS) treatment intensity over time combined with unsupervised trajectory clustering.ResultsIn total, 755 patients were included and three pre-biologic disease trajectories were identified: Chronic severe asthma (26%), Gradual onset severe asthma (35%), Recent, sudden onset severe asthma (39%). Chronic severe asthma patients were older, had the longest disease duration (35 years), the most impaired pulmonary function, the highest comorbidity prevalence and the lowest employment rate.Recent, sudden onset severe asthmapatients were younger, had shorter disease duration (5 years), more tobacco exposure and the least impaired lung function.Gradual onset severe asthmahad an intermediate burden of disease. TheChronic severe asthmacluster demonstrated the lowest prevalence of remission (17%) compared to theGradual onset severe asthma(29%) andRecent onset severe asthma(32%) clusters.ConclusionsThree pre-biologic disease trajectories were identified, with increased disease duration and activity associating with asthma- and comorbidity burden. Early intervention may be key to prevent irreversible adverse outcomes for patients with severe asthma.
A composite score of polygraphic oximetry parameters predicts left ventricular hypertrophy in patients with obstructive sleep Apnea
Authors: Landolfo Matteo , Giulietti Federico , Spannella Francesco , Sarnari Silvia , Di Pentima Chiara , Giordano Piero , Sarzani Riccardo 
Published: January 2025

BackgroundObstructive sleep apnea (OSA) is linked to cardiovascular diseases (CVD). The obstructive apnea-hypopnea index (oAHI) used for diagnosing and grading OSA has limitations in predicting CVD. The present study assessed and compared the association between nocturnal hypoxemia parameters and left ventricular hypertrophy (LVH).MethodsA cross-sectional study was conducted on 187 consecutive adult outpatients diagnosed with OSA after home cardiorespiratory polygraphy. Blood pressure (BP) control was tested with ambulatory blood pressure monitoring (ABPM). A standard transthoracic cardiac ultrasound examination assessed LVH. Oximetry parameters were grouped into a single parameter (Oxy-score) using factor analysis (the higher the Oxy-score, the better nocturnal oxygenation), which was tested for association with LVH.ResultsMean age: 60±12 years. Male sex: 75%. Overweight/obese: 94%. The prevalence of arterial hypertension and LVH were 92% and 75%, respectively. The prevalence of severe OSA was 44%, with a mean oAHI of 32±19. Patients with LVH had significantly higher oAHI (34±19versus27±18, p=0.030), oxygen desaturation index (ODI) (41±23versus30±18, p=0.004), and worse oximetry parameters. Oxy-score results were independently associated with LVH (adj. OR=0.45, p=0.044). oAHI lost its independent relationship with LVH when the model included the Oxy-score. ROCs showed that oAHI was less accurate in predicting LVH than Oxy-score [AUC 0.63 (95% CI 0.59–0.68)versusAUC 0.70 (95% CI 0.65–0.74), respectively, p=0.005].ConclusionNocturnal oximetry parameters, grouped into a single parameter as a proxy of the global hypoxic burden, proved to be a better and independent predictor of LVH than oAHI, supporting the pivotal relevance of oximetry parameters in OSA patients beyond oAHI.
Modified 1-min sit-to-stand test for evaluating exercise capacity in pulmonary fibrosis
Authors: Berger Ingrid , Mortada Sadek , Gachie Clémence , Beaussier Hélène , Sacco Emmanuelle , Chatellier Gilles , Fels Audrey , Cachanado Marine , Naccache Jean-Marc 
Published: January 2025

QuestionThe reference test for the functional evaluation of pulmonary fibrosis (PF) during exercise is the 6-minute walk test (6MWT). However, the 6MWT involves temporal and spatial constraints that the 1-minute sit-to-stand test (1-MSTST) does not have. Previous studies have not validated 1-MSTST use in this context, mainly because of far less oxygen desaturation. We hypothesize that the modified 1-MSTST (m1-MSTST), taking into account the recovery phase, could compensate this shortcoming.Patients and MethodsRandomized, cross-over, single-center trial conducted in 36 patients with PF. 6MWT and 1-MSTST were performed 30 min apart for each patient in a randomized order. An equivalence test was performed on the saturation (SpO2) nadir.ResultsThe 36 patients included 8 idiopathic pulmonary fibrosis, 5 nonspecific idiopathic pneumonia, 8 collagen tissue disease-associated PF, 4 hypersensitivity pneumonitis, 2 sarcoidosis and 9 other PF. Mean±sdnadir desaturation was 84.9±4.3% at 6MWT and 88±3.5% at m1-MSTST with a strong correlation between both tests. 33 patients (91.7%) had concordant result in the two tests regarding significant desaturation (SpO2 delta>4% or nadir<88%) known as prognosis factor.ConclusionThe m1-MSTST, taking into account the recovery phase, is a sensible compromise to the 6MWT in measuring exercise performance in people with PF. As many clinical endpoints are transferring from hospital to outpatient care, m1-MSTST is technically easier and more practical for patients. Further studies are warranted for determination of minimal clinically important difference and norms in healthy subjects.