bluuebunny/crossref_metadata_2025_split huggingface dataset:
Patient-Identified Problems and Influences Associated With Diagnostic Delay of Acromegaly: A Nationwide Cross-Sectional Study
Authors: Wang Kailu , Guo Xiaopeng , Yu Siyue , Gao Lu , Wang Zihao , Zhu Huijuan , Xing Bing , Zhang Shuyang , Dong Dong 
Published: October 2021

BackgroundInsidious-onset acromegaly may easily be overlooked by non-specialists of acromegaly and cause diagnostic delay. This study aims to examine the association between diagnostic delay and advice from doctors before any confirmed diagnosis and subsequent comorbidities, and elicit patient-perceived reasons for misdiagnoses.MethodsAn online nationwide cross-sectional study was conducted through China Acromegaly Patient Association. Growth Hormone (GH) and Insulin-like Growth Factor 1 (IGF-1) levels at diagnosis and cancerous, endocrine-metabolic, musculoskeletal, cardiovascular, respiratory, and psychiatric comorbidities were reported by patients. The association between diagnostic delay and pre-diagnostic advice from doctors as well as subsequent comorbidities after diagnosis were examined.ResultsIn total, 447 valid responses were collected. Overall, 58.8% patients experienced misdiagnoses, and 22.6% had diagnostic delay. Before arriving at any diagnosis, patients without treatment (adjusted odds ratio [AOR]: 3.66, 95% confidence interval [CI]: 1.30-10.33) or receiving treatment to symptoms only (AOR: 7.05, 95%CI: 4.09-12.17) had greater chance of being misdiagnosed, and hence had diagnostic delay. Patients believed insufficient specialists, limited awareness of acromegaly of non-specialists and poor doctor-patient communications were major reasons of misdiagnosis. Diagnostic delay were associated with higher GH level at diagnosis and endocrine-metabolic, musculoskeletal and cardiovascular comorbidities (all P&lt;0.05).ConclusionsSuboptimal pre-diagnostic advice for patients, reflecting limited awareness of acromegaly among non-specialists, may delay the diagnosis and increase comorbidities. Feedbacks on the patients’ final diagnosis from specialists to non-specialists should be considered, and doctor-patient communication and clinical decision-making process should be improved. Comorbidities should be screened and monitored particularly for patients with diagnostic delay.
Practice Patterns and Learning Curve in Transoral Endoscopic Thyroidectomy Vestibular Approach With Neuromonitoring
Authors: Kuo Ting-Chun , Duh Quan-Yang , Wang Yi-Chia , Lai Chieh-Wen , Chen Kuen-Yuan , Lin Ming-Tsan , Wu Ming-Hsun 
Published: October 2021

ObjectivesIntraoperative neuromonitoring has not been routinely applied in early experience with the transoral endoscopic thyroidectomy vestibular approach (TOETVA). Because the preparation and surgical interventions are much different from conventional thyroidectomies, most endocrine surgeons willing to adapt to TOETVA lack access to information regarding the practice pattern and proficiency in the learning curve. We aimed to investigate the outcomes and to define the learning curve for TOETVA in this study.MethodsA retrospective analysis was used on patients who underwent TOETVA at our hospital between December 2016 and July 2019. The cumulative sum graphic model was used to implement the learning curve as a surrogate for procedural proficiency.ResultsThe 119 patients had a mean age of 44.65 years and a mean body mass index of 22.49 k/m2, including 107 women, 20 thyroiditis, and 106 hemithyroidectomy. The learning curve revealed two phases, an initial (35 cases) and a mature (84 cases) phase, for surgeons based on operation time (144.2 vs. 114.2 min, p = 0.0001). There were more bilateral thyroidectomies (15.5% vs. 0, p = 0.0100), larger indicated nodules (6.06 cm3vs. 3.32 cm3, p = 0.0468), or larger thyroids to resect (16.38 cm3vs. 8.75 cm3, p = 0.0001) in the mature phase. Procedure-related complications decreased significantly in the mature phase in comparison to the initial phase (3.57% vs. 31.43%, p = 0.0001).ConclusionsThe learning curve of TOETVA with neuromonitoring is 35 cases. With the accumulation of proficiency, the indications will expand. Step-by-step improvements from the experience of each case can reduce procedure-related complications.
Role of TLR4 in Neutrophil Dynamics and Functions: Contribution to Stroke Pathophysiology
Authors: Durán-Laforet Violeta , Peña-Martínez Carolina , García-Culebras Alicia , Cuartero María Isabel , Lo Eng H. , Moro María Ángeles , Lizasoain Ignacio 
Published: October 2021

Background and PurposeThe immune response subsequent to an ischemic stroke is a crucial factor in its physiopathology and outcome. It is known that TLR4 is implicated in brain damage and inflammation after stroke and that TLR4 absence induces neutrophil reprogramming toward a protective phenotype in brain ischemia, but the mechanisms remain unknown. We therefore asked how the lack of TLR4 modifies neutrophil function and their contribution to the inflammatory process.MethodsIn order to assess the role of the neutrophilic TLR4 after stroke, mice that do not express TLR4 in myeloid cells (TLR4loxP/Lyz-cre) and its respective controls (TLR4loxP/loxP) were used. Focal cerebral ischemia was induced by occlusion of the middle cerebral artery and infarct size was measured by MRI. A combination of flow cytometry and confocal microscopy was used to assess different neutrophil characteristics (circadian fluctuation, cell surface markers, cell complexity) and functions (apoptosis, microglia engulfment, phagocytosis, NETosis, oxidative burst) in both genotypes.ResultsAs previously demonstrated, mice with TLR4 lacking-neutrophils had smaller infarct volumes than control mice. Our results show that the absence of TLR4 keeps neutrophils in a steady youth status that is dysregulated, at least in part, after an ischemic insult, preventing neutrophils from their normal circadian fluctuation. TLR4-lacking neutrophils showed a higher phagocytic activity in the basal state, they were preferentially engulfed by the microglia after stroke, and they produced less radical oxygen species (ROS) in the first stage of the inflammatory process.ConclusionsTLR4 is specifically involved in neutrophil dynamics under physiological conditions as well as in stroke-induced tissue damage. This research contributes to the idea that TLR4, especially when targeted in specific cell types, is a potential target for neuroprotective strategies.
Growth Factors and Their Roles in Multiple Sclerosis Risk
Authors: Lu Hui , Wu Peng-Fei , Ma Deng-Lei , Zhang Wan , Sun Meichen 
Published: October 2021

BackgroundPrevious studies have suggested essential roles of growth factors on the risk of Multiple Sclerosis (MS), but it remains undefined whether the effects are causal.ObjectiveWe applied Mendelian randomization (MR) approaches to disentangle the causal relationship between genetically predicted circulating levels of growth factors and the risk of MS.MethodsGenetic instrumental variables for fibroblast growth factor (FGF) 23, growth differentiation factor 15 (GDF15), insulin growth factor 1 (IGF1), insulin-like growth factor binding proteins 3 (IGFBP3) and vascular endothelial growth factor (VEGF) were obtained from up-to-date genome-wide association studies (GWAS). Summary-level statistics of MS were obtained from the International Multiple Sclerosis Genetics Consortium, incorporating 14,802 subjects with MS and 26,703 healthy controls of European ancestry. Inverse-variance weighted (IVW) MR was used as the primary method and multiple sensitivity analyses were employed in this study.ResultsGenetically predicted circulating levels of FGF23 were associated with risk of MS. The odds ratio (OR) of IVW was 0.63 (95% confidence interval [CI], 0.49–0.82; p &lt; 0.001) per one standard deviation increase in circulating FGF23 levels. Weighted median estimators also suggested FGF23 associated with lower MS risk (OR = 0.67; 95% CI, 0.51-0.87; p = 0.003). While MR-Egger approach provided no evidence of horizontal pleiotropy (intercept = -0.003, p = 0.95). Results of IVW methods provided no evidence for causal roles of GDF1, IGF1, IGFBP3 and VEGF on MS risks, and additional sensitivity analyses confirmed the robustness of these null findings.ConclusionOur results implied a causal relationship between FGF23 and the risk of MS. Further studies are warranted to confirm FGF23 as a genetically valid target for MS.
Progression of Fatigue in Early Parkinson’s Disease: A 3-Year Prospective Cohort Study
Authors: Ou Ruwei , Hou Yanbing , Liu Kuncheng , Lin Junyu , Jiang Zheng , Wei Qianqian , Zhang Lingyu , Cao Bei , Zhao Bi , Song Wei , Shang Huifang 
Published: October 2021

Objective: To explore the frequency, evolution, associated factors, and risk factors of fatigue over 3-year of prospective follow-up in a cohort of patients with early Parkinson’s disease (PD).Methods: A total of 174 PD patients in the early stage were enrolled and quantitively assessed motor and non-motor symptoms using comprehensive scales including the Fatigue Severity Scale (FSS) annually. Each subject was categorized as PD with and without fatigue based on a cut-off mean value of 4 using FSS. The generalized estimating equation (GEE) was utilized to investigate the associated factors, and the stepwise binary logistic regression model was performed to explore the predictors.Results: The frequency of fatigue was slightly changed (ranging from 35.1 to 40.4%) during the 3-year follow-up. The changed pattern of the frequency of fatigue was similar to that of anxiety. Fatigue was significantly associated with nocturnal sleep disorders (B 2.446, P &lt; 0.001), high Hamilton Anxiety Rating Scale (HAMA) score (B 1.072, P = 0.011), and high Unified PD Rating Scale (UPDRS) III score (B 1.029, P = 0.003) over time. High UPDRS III score [odds ratio (OR) 1.051, P = 0.015] at baseline increased the risk of developing fatigue after 1-year; high LEDD (OR 1.002, P = 0.037) increased the risk of developing fatigue after 2-year; and high LEDD (OR 1.003, P = 0.049) and high HAMA score (OR 1.077, P = 0.042) increased the risk of developing fatigue after 3-year.Conclusion: Our present study provided evidence of the longitudinal evolution of fatigue in patients with early PD and help clinical management of fatigue.
Joint Effects of Carbon Black Exposure and Dietary Antioxidant Vitamin Intake on Small Airway Dysfunction
Authors: Wang Tao , Li Jianyu , Liang Yi , Han Wei , Tang Jinglong , Cheng Guo , Zheng Yuxin 
Published: October 2021

Objectives: Small airway dysfunction is considered as a precursor of chronic obstructive pulmonary disease and asthma. Our aim was to explore the joint effects of carbon black (CB) exposure and antioxidant vitamin intake on small airway dysfunction.Methods: A total of 70 CB packers (CBPs) and 107 non-CBPs were enrolled from an established cohort of CBP. Carbon content in airway macrophage (CCAM) quantified in induced sputum was used as a bio-effective dosimetry for exposure to CB. Logistic regression models were used to examine the odds ratios (ORs) of CB and dietary intake of antioxidant vitamins on small airway dysfunction, and the dose–response association.Results: The prevalence of small airway dysfunction was 32.9% (23 of 70) among CBPs, and 19.6% (21 of 107) among non-CBPs. For each 2.72-fold increase in CCAM, the OR of small airway dysfunction was 2.31 (95% CI = 1.20–4.44). For every 10 mg day−1 increase of the vitamin C intake, the risk of small airway dysfunction decreased by 6% (OR = 0.94, 95% CI = 0.88–0.99). Compared to non-CB exposure and higher vitamin C intake, CB exposure and lower vitamin C intake (OR = 7.56, 95% CI = 1.80 to 31.81) were associated with an increased risk of small airway dysfunction.Conclusions: Chronic exposure to a high level of CB aerosol increased the risk of small airway dysfunction in CB baggers. Dietary intake of vitamin C might be a modifiable factor for preventing small airway dysfunction.
Impact of Sarcopenia on Survival and Clinical Outcomes in Patients With Liver Cirrhosis
Authors: Topan Mirabela-Madalina , Sporea Ioan , Dănilă Mirela , Popescu Alina , Ghiuchici Ana-Maria , Lupuşoru Raluca , Şirli Roxana 
Published: October 2021

Background: Sarcopenia is now recognized more and more as a biomarker with poor outcomes in cirrhotic patients.Aims: The purpose of this study was to investigate the prevalence of sarcopenia in patients with liver cirrhosis and prospectively investigate the association between sarcopenia and different complications and its impact on survival.Material and Methods: This prospective study included patients with liver cirrhosis admitted to our department from 2018 to 2020. Sarcopenia was assessed according to EWGSOP2 criteria, incorporating low Handgrip strength (&lt;27 kg for men and &lt;16 kg for women) with low skeletal muscle index evaluated by CT (&lt;50 for men and &lt;39 for women). Associations between sarcopenia and portal hypertension-related complications, infectious complications, and risk of hepatocellular carcinoma, the number of in-hospital days, 30-day readmission, and survival over the next 6 and 12 months were analyzed.Results: A total of 201 patients were enrolled in the study, 63.2% male, mean age 61.65 ± 9.49 years, 79.6% Child-Pugh class B and C. The primary etiology of liver cirrhosis was alcohol consumption (55.2%). The prevalence of sarcopenia was 57.2 %, with no significant differences between the male and female groups. Significant associations were found between sarcopenia and portal hypertension-related complications, infectious complications, and risk of hepatocellular carcinoma. In multivariate analysis, sarcopenia was assessed as a risk factor alone, increasing the risk for ascites 3.78 times, hepatocellular carcinoma by 9.23 times, urinary tract infection by 4.83 times, and spontaneous peritonitis 2.49 times. Sarcopenia was associated with more extended hospital stay and higher 30 days readmission. Six months and 1-year survival were reduced in the sarcopenia group than in the non-sarcopenia group (p &lt; 0.0001).Conclusion: Sarcopenia is a common complication of liver cirrhosis and associates with adverse health-related outcomes and poor survival rates.
Prediction of Breast Cancer Recurrence Using a Deep Convolutional Neural Network Without Region-of-Interest Labeling
Authors: Phan Nam Nhut , Hsu Chih-Yi , Huang Chi-Cheng , Tseng Ling-Ming , Chuang Eric Y. 
Published: October 2021

PurposeThe present study aimed to assign a risk score for breast cancer recurrence based on pathological whole slide images (WSIs) using a deep learning model.MethodsA total of 233 WSIs from 138 breast cancer patients were assigned either a low-risk or a high-risk score based on a 70-gene signature. These images were processed into patches of 512x512 pixels by the PyHIST tool and underwent color normalization using the Macenko method. Afterward, out of focus and pixelated patches were removed using the Laplacian algorithm. Finally, the remaining patches (n=294,562) were split into 3 parts for model training (50%), validation (7%) and testing (43%). We used 6 pretrained models for transfer learning and evaluated their performance using accuracy, precision, recall, F1 score, confusion matrix, and AUC. Additionally, to demonstrate the robustness of the final model and its generalization capacity, the testing set was used for model evaluation. Finally, the GRAD-CAM algorithm was used for model visualization.ResultsSix models, namely VGG16, ResNet50, ResNet101, Inception_ResNet, EfficientB5, and Xception, achieved high performance in the validation set with an overall accuracy of 0.84, 0.85, 0.83, 0.84, 0.87, and 0.91, respectively. We selected Xception for assessment of the testing set, and this model achieved an overall accuracy of 0.87 with a patch-wise approach and 0.90 and 1.00 with a patient-wise approach for high-risk and low-risk groups, respectively.ConclusionsOur study demonstrated the feasibility and high performance of artificial intelligence models trained without region-of-interest labeling for predicting cancer recurrence based on a 70-gene signature risk score.
Predictive Value of Multiparametric MRI for Response to Single-Cycle Induction Chemo-Immunotherapy in Locally Advanced Head and Neck Squamous Cell Carcinoma
Authors: Hellwig Konstantin , Ellmann Stephan , Eckstein Markus , Wiesmueller Marco , Rutzner Sandra , Semrau Sabine , Frey Benjamin , Gaipl Udo S. , Gostian Antoniu Oreste , Hartmann Arndt , Iro Heinrich , Fietkau Rainer , Uder Michael , Hecht Markus , Bäuerle Tobias 
Published: October 2021

ObjectivesTo assess the predictive value of multiparametric MRI for treatment response evaluation of induction chemo-immunotherapy in locally advanced head and neck squamous cell carcinoma.MethodsTwenty-two patients with locally advanced, histologically confirmed head and neck squamous cell carcinoma who were enrolled in the prospective multicenter phase II CheckRad-CD8 trial were included in the current analysis. In this unplanned secondary single-center analysis, all patients who received contrast-enhanced MRI at baseline and in week 4 after single-cycle induction therapy with cisplatin/docetaxel combined with the immune checkpoint inhibitors tremelimumab and durvalumab were included. In week 4, endoscopy with representative re-biopsy was performed to assess tumor response. All lesions were segmented in the baseline and restaging multiparametric MRI, including the primary tumor and lymph node metastases. The volume of interest of the respective lesions was volumetrically measured, and time-resolved mean intensities of the golden-angle radial sparse parallel-volume-interpolated gradient-echo perfusion (GRASP-VIBE) sequence were extracted. Additional quantitative parameters including the T1 ratio, short-TI inversion recovery ratio, apparent diffusion coefficient, and dynamic contrast-enhanced (DCE) values were measured. A model based on parallel random forests incorporating the MRI parameters from the baseline MRI was used to predict tumor response to therapy. Receiver operating characteristic (ROC) curves were used to evaluate the prognostic performance.ResultsFifteen patients (68.2%) showed pathologic complete response in the re-biopsy, while seven patients had a residual tumor (31.8%). In all patients, the MRI-based primary tumor volume was significantly lower after treatment. The baseline DCE parameters of time to peak and wash-out were significantly different between the pathologic complete response group and the residual tumor group (p &lt; 0.05). The developed model, based on parallel random forests and DCE parameters, was able to predict therapy response with a sensitivity of 78.7% (95% CI 71.24–84.93) and a specificity of 78.6% (95% CI 67.13–87.48). The model had an area under the ROC curve of 0.866 (95% CI 0.819–0.914).ConclusionsDCE parameters indicated treatment response at follow-up, and a random forest machine learning algorithm based on DCE parameters was able to predict treatment response to induction chemo-immunotherapy.
Association of Myometrial Invasion With Lymphovascular Space Invasion, Lymph Node Metastasis, Recurrence, and Overall Survival in Endometrial Cancer: A Meta-Analysis of 79 Studies With 68,870 Patients
Authors: Wang Jianzhang , Xu Ping , Yang Xueying , Yu Qin , Xu Xinxin , Zou Gen , Zhang Xinmei 
Published: October 2021

BackgroundMyometrial invasion has been demonstrated to correlate to clinicopathological characteristics and prognosis in endometrial cancer. However, not all the studies have the consistent results and no meta-analysis has investigated the association of myometrial invasion with lymphovascular space invasion (LVSI), lymph node metastasis (LNM), recurrence, and overall survival (OS). Therefore, a meta-analysis was performed to evaluate the relationship between myometrial invasion and clinicopathological characteristics or overall survival in endometrial cancer.Materials and MethodsA search of Pubmed, Embase, and Web of Science was carried out to collect relevant studies from their inception until June 30, 2021. The quality of each included study was evaluated using Newcastle–Ottawa scale (NOS) scale. Review Manager version 5.4 was employed to conduct the meta-analysis.ResultsA total of 79 articles with 68,870 endometrial cancer patients were eligible including 9 articles for LVSI, 29 articles for LNM, 8 for recurrence, and 37 for OS in this meta-analysis. Myometrial invasion was associated with LVSI (RR 3.07; 95% CI 2.17–4.35; p &lt; 0.00001), lymph node metastasis (LNM) (RR 4.45; 95% CI 3.29–6.01; p &lt; 0.00001), and recurrence (RR 2.06; 95% CI 1.58–2.69; p &lt; 0.00001). Deep myometrial invasion was also significantly related with poor OS via meta-synthesis of HRs in both univariate survival (HR 3.36, 95% CI 2.35–4.79, p &lt; 0.00001) and multivariate survival (HR 2.00, 95% CI 1.59–2.53, p &lt; 0.00001). Funnel plot suggested that there was no significant publication bias in this study.ConclusionDeep myometrial invasion correlated to positive LVSI, positive LNM, cancer recurrence, and poor OS for endometrial cancer patients, indicating that myometrial invasion was a useful evaluation criterion to associate with clinical outcomes and prognosis of endometrial cancer since depth of myometrial invasion can be assessed before surgery. The large scale and comprehensive meta-analysis suggested that we should pay more attention to myometrial invasion in clinical practice, and its underlying mechanism also deserves further investigation.
Multiparameter MRI Radiomics Model Predicts Preoperative Peritoneal Carcinomatosis in Ovarian Cancer
Authors: Yu Xiao Yu , Ren Jialiang , Jia Yushan , Wu Hui , Niu Guangming , Liu Aishi , Gao Yang , Hao Fene , Xie Lizhi 
Published: October 2021

ObjectivesTo evaluate the predictive value of radiomics features based on multiparameter magnetic resonance imaging (MP-MRI) for peritoneal carcinomatosis (PC) in patients with ovarian cancer (OC).MethodsA total of 86 patients with epithelial OC were included in this retrospective study. All patients underwent FS-T2WI, DWI, and DCE-MRI scans, followed by total hysterectomy plus omentectomy. Quantitative imaging features were extracted from preoperative FS-T2WI, DWI, and DCE-MRI images, and feature screening was performed using a minimum redundancy maximum correlation (mRMR) and least absolute shrinkage selection operator (LASSO) methods. Four radiomics models were constructed based on three MRI sequences. Then, combined with radiomics characteristics and clinicopathological risk factors, a multi-factor Logistic regression method was used to construct a radiomics nomogram, and the performance of the radiomics nomogram was evaluated by receiver operating characteristic curve (ROC) curve, calibration curve, and decision curve analysis.ResultsThe radiomics model from the MP-MRI combined sequence showed a higher area under the curve (AUC) than the model from FS-T2WI, DWI, and DCE-MRI alone (0.846 vs. 0.762, 0.830, 0.807, respectively). The radiomics nomogram (AUC=0.902) constructed by combining radiomics characteristics and clinicopathological risk factors showed a better diagnostic effect than the clinical model (AUC=0.858) and the radiomics model (AUC=0.846). The decision curve analysis shows that the radiomics nomogram has good clinical application value, and the calibration curve also proves that it has good stability.ConclusionRadiomics nomogram based on MP-MRI combined sequence showed good predictive accuracy for PC in patients with OC. This tool can be used to identify peritoneal carcinomatosis in OC patients before surgery.