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OBJECTIVE: Nucleotide metabolic reprogramming as a hallmark of cancer is closely related to the occurrence and progression of cancer. We aimed to comprehensively analyze the nucleotide metabolism-related gene set and clinical significance in gliomas. METHODS: The RNA sequencing data of 702 gliomas from the Cancer Genome Atlas (TCGA) dataset were included as the training set, and the RNA sequencing data from the other three datasets (CGGA, GSE16011, and Rembrandt) were used as independent validation sets. Survival curve, Cox regression analysis, time-dependent ROC curve and nomogram model were performed to evaluate prognostic power of signature. R language was the main tool for bioinformatic analysis and graphical work. RESULTS: Based on the expression profiles of nucleotide metabolism-related genes, consensus clustering identified two robust clusters with different prognosis. We then developed a nucleotide metabolism-related signature that was closely related to clinical, pathological, and genomic characteristics of gliomas. And ROC curve showed that our signature was a potential biomarker for mesenchymal subtype. Survival curve and Cox regression analysis revealed signature as an independent prognostic factor for gliomas. In addition, we constructed a nomogram model to predict individual survival. Finally, functional analysis showed that nucleotide metabolism not only affected cell division and cell cycle, but also was associated with immune response in gliomas. CONCLUSION: We developed a nucleotide metabolism-related signature to predict prognosis and provided new insights into the role of nucleotide metabolism in gliomas.
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OBJECTIVES: To construct a combined model based on bi-regional quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), as well as clinical-radiological (CR) features for predicting microvascular invasion (MVI) in solitary Barcelona Clinic Liver Cancer (BCLC) stage A hepatocellular carcinoma (HCC), and to assess its ability for stratifying the risk of recurrence after hepatectomy. METHODS: Patients with solitary BCLC stage A HCC were prospective collected and randomly divided into training and validation sets. DCE perfusion parameters were obtained both in intra-tumoral region (ITR) and peritumoral region (PTR). Combined DCE perfusion parameters (CDCE) were constructed to predict MVI. The combined model incorporating CDCE and CR features was developed and evaluated. Kaplan-Meier method was used to investigate the prognostic significance of the model and the survival benefits of different hepatectomy approaches. RESULTS: A total of 133 patients were included. Total blood flow in ITR and arterial fraction in PTR exhibited the best predictive performance for MVI with areas under the curve (AUCs) of 0.790 and 0.792, respectively. CDCE achieved AUCs of 0.868 (training set) and 0.857 (validation set). A combined model integrated with the α-fetoprotein, corona enhancement, two-trait predictor of venous invasion, and CDCE could improve the discrimination ability to AUCs of 0.966 (training set) and 0.937 (validation set). The combined model could stratify the prognosis of HCC patients. Anatomical resection was associated with a better prognosis in the high-risk group (p < 0.05). CONCLUSION: The combined model integrating DCE perfusion parameters and CR features could be used for MVI prediction in HCC patients and assist clinical decision-making. CRITICAL RELEVANCE STATEMENT: The combined model incorporating bi-regional DCE-MRI perfusion parameters and CR features predicted MVI preoperatively, which could stratify the risk of recurrence and aid in optimizing treatment strategies. KEY POINTS: Microvascular invasion (MVI) is a significant predictor of prognosis for hepatocellular carcinoma (HCC). Quantitative DCE-MRI could predict MVI in solitary BCLC stage A HCC; the combined model improved performance. The combined model could help stratify the risk of recurrence and aid treatment planning.
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OBJECTIVES: To investigate the value of extracellular volume (ECV) derived from portal-venous phase (PVP) in predicting prognosis in locally advanced pancreatic cancer (LAPC) patients receiving intraoperative radiotherapy (IORT) with initial stable disease (SD) and to construct a risk-scoring system based on ECV and clinical-radiological features. MATERIALS AND METHODS: One hundred and three patients with LAPC who received IORT demonstrating SD were enrolled and underwent multiphasic contrast-enhanced CT (CECT) before and after IORT. ECV maps were generated from unenhanced and PVP CT images. Clinical and CT imaging features were analyzed. The independent predictors of progression-free survival (PFS) determined by multivariate Cox regression model were used to construct the risk-scoring system. Time-dependent receiver operating characteristic (ROC) curve analysis and the Kaplan-Meier method were used to evaluate the predictive performance of the scoring system. RESULTS: Multivariable analysis revealed that ECV, rim-enhancement, peripancreatic fat infiltration, and carbohydrate antigen 19-9 (CA19-9) response were significant predictors of PFS (all p < 0.05). Time-dependent ROC of the risk-scoring system showed a satisfactory predictive performance for disease progression with area under the curve (AUC) all above 0.70. High-risk patients (risk score ≥ 2) progress significantly faster than low-risk patients (risk score < 2) (p < 0.001). CONCLUSION: ECV derived from PVP of conventional CECT was an independent predictor for progression in LAPC patients assessed as SD after IORT. The scoring system integrating ECV, radiological features, and CA19-9 response can be used as a practical tool for stratifying prognosis in these patients, assisting clinicians in developing an appropriate treatment approach. CRITICAL RELEVANCE STATEMENT: The scoring system integrating ECV fraction, radiological features, and CA19-9 response can track tumor progression in patients with LAPC receiving IORT, aiding clinicians in choosing individual treatment strategies and improving their prognosis. KEY POINTS: Predicting the progression of LAPC in patients receiving IORT is important. Our ECV-based scoring system can risk stratifying patients with initial SD. Appropriate prognostication can assist clinicians in developing appropriate treatment approaches.
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Sarcopenia can lead to more postoperative complications and poorer prognosis in patients with colorectal cancer; however there is limited research exploring the incidence and influencing factors of different stages of sarcopenia in patients with colorectal cancer. We investigated 312 patients with colorectal cancer. Sarcopenia was determined by measuring muscle mass, grip strength, and gait speed. According to the European Working Group on Sarcopenia in Older People (EWGSOP) 2010, patients were classified into four groups: nonsarcopenia, presarcopenia, sarcopenia, and severe sarcopenia. The incidence of sarcopenia and severe sarcopenia was 10.3% and 8.7%, respectively. Multivariate logistic regression analysis showed that age, TNM stage smoking history, total protein, upper arm circumference, waist circumference, and Patient-Generated Subjective Global Assessment (PG-SGA) score were independently associated with sarcopenia at different stages. This study suggests that routine data should be used to provide targeted care during hospitalization for patients with colorectal cancer in order to reduce the incidence of sarcopenia and improve prognosis.
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Neoplasias Colorrectales , Sarcopenia , Humanos , Anciano , Sarcopenia/diagnóstico , Sarcopenia/epidemiología , Sarcopenia/etiología , Fuerza de la Mano , Neoplasias Colorrectales/complicaciones , Neoplasias Colorrectales/epidemiología , Neoplasias Colorrectales/cirugíaRESUMEN
Transition-metal-atom anchored graphdiynes (TM@GDY, TM = Mn, Fe, Co, Ni and Cu) have already been synthesized and found applications in hydrogen evolution, nitrogen fixation and etc. By means of first-principle predictions and test experiments, we propose here that Fe@GDY and Co@GDY are efficient catalysts for the sustainable conversion of O3 to O2. These two catalysts can spontaneously chemisorb O3 with zero reaction barrier and have low O3 conversion barriers (0.31 eV and 0.19 eV, respectively). The O3 decomposition experiment in a continuous flow membrane reactor and electron paramagnetic resonance results verify that Fe@GDY and Co@GDY are efficient catalysts under humid conditions. Raman spectra prove the formation of the key Fe-O/Co-O and FeOO and CoOO intermediates. The hydrophobic nature of graphdiyne and the strongest chemisorption of O3 among tested ambient gases, make Fe@GDY and Co@GDY ideal catalysts under both dry and humid conditions. These findings would stimulate future explorations on metal anchored GDY-based catalysts for applications of toxic gas decomposition or fixation.
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PURPOSE: Preoperative diagnosis of filum terminale ependymomas (FTEs) versus schwannomas is difficult but essential for surgical planning and prognostic assessment. With the advancement of deep-learning approaches based on convolutional neural networks (CNNs), the aim of this study was to determine whether CNN-based interpretation of magnetic resonance (MR) images of these two tumours could be achieved. METHODS: Contrast-enhanced MRI data from 50 patients with primary FTE and 50 schwannomas in the lumbosacral spinal canal were retrospectively collected and used as training and internal validation datasets. The diagnostic accuracy of MRI was determined by consistency with postoperative histopathological examination. T1-weighted (T1-WI), T2-weighted (T2-WI) and contrast-enhanced T1-weighted (CE-T1) MR images of the sagittal plane containing the tumour mass were selected for analysis. For each sequence, patient MRI data were randomly allocated to 5 groups that further underwent fivefold cross-validation to evaluate the diagnostic efficacy of the CNN models. An additional 34 pairs of cases were used as an external test dataset to validate the CNN classifiers. RESULTS: After comparing multiple backbone CNN models, we developed a diagnostic system using Inception-v3. In the external test dataset, the per-examination combined sensitivities were 0.78 (0.71-0.84, 95% CI) based on T1-weighted images, 0.79 (0.72-0.84, 95% CI) for T2-weighted images, 0.88 (0.83-0.92, 95% CI) for CE-T1 images, and 0.88 (0.83-0.92, 95% CI) for all weighted images. The combined specificities were 0.72 based on T1-WI (0.66-0.78, 95% CI), 0.84 (0.78-0.89, 95% CI) based on T2-WI, 0.74 (0.67-0.80, 95% CI) for CE-T1, and 0.81 (0.76-0.86, 95% CI) for all weighted images. After all three MRI modalities were merged, the receiver operating characteristic (ROC) curve was calculated, and the area under the curve (AUC) was 0.93, with an accuracy of 0.87. CONCLUSIONS: CNN based MRI analysis has the potential to accurately differentiate ependymomas from schwannomas in the lumbar segment.
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Cauda Equina , Ependimoma , Neurilemoma , Humanos , Estudios Retrospectivos , Cauda Equina/diagnóstico por imagen , Imagen por Resonancia Magnética/métodos , Redes Neurales de la Computación , Neurilemoma/diagnóstico por imagen , Neurilemoma/cirugía , Ependimoma/diagnóstico por imagenRESUMEN
Perception plays a crucial role in ensuring the safety and reliability of autonomous driving systems. However, the recognition and localization of small objects in complex scenarios still pose challenges. In this paper, we propose a point cloud object detection method based on dynamic sparse voxelization to enhance the detection performance of small objects. This method employs a specialized point cloud encoding network to learn and generate pseudo-images from point cloud features. The feature extraction part uses sliding windows and transformer-based methods. Furthermore, multi-scale feature fusion is performed to enhance the granularity of small object information. In this experiment, the term "small object" refers to objects such as cyclists and pedestrians, which have fewer pixels compared to vehicles with more pixels, as well as objects of poorer quality in terms of detection. The experimental results demonstrate that, compared to the PointPillars algorithm and other related algorithms on the KITTI public dataset, the proposed algorithm exhibits improved detection accuracy for cyclist and pedestrian target objects. In particular, there is notable improvement in the detection accuracy of objects in the moderate and hard quality categories, with an overall average increase in accuracy of about 5%.
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Handheld robots offer accessible solutions with a short learning curve to enhance operator capabilities. However, their controllable degree-of-freedoms are limited due to scarce space for actuators. Inspired by muscle movements stimulated by nerves, we report a handheld time-share driven robot. It comprises several motion modules, all powered by a single motor. Shape memory alloy (SMA) wires, acting as "nerves", connect to motion modules, enabling the selection of the activated module. The robot contains a 202-gram motor base and a 0.8 cm diameter manipulator comprised of sequentially linked bending modules (BM). The manipulator can be tailored in length and integrated with various instruments in situ, facilitating non-invasive access and high-dexterous operation at remote surgical sites. The applicability was demonstrated in clinical scenarios, where a surgeon held the robot to conduct transluminal experiments on a human stomach model and an ex vivo porcine stomach. The time-share driven mechanism offers a pragmatic approach to build a multi-degree-of-freedom robot for broader applications.
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Robótica , Porcinos , Animales , Humanos , Movimiento (Física)RESUMEN
RATIONALE AND OBJECTIVES: To explore and compare the performance of LI-RADS® and radiomics from multiparametric MRI in predicting microvascular invasion (MVI) preoperatively in patients with solitary hepatocellular carcinoma (HCC)< 5 cm. METHODS: We enrolled 143 patients with pathologically proven HCC and randomly stratified them into training (n = 100) and internal validation (n = 43) cohorts. Besides, 53 patients were enrolled to constitute an independent test cohort. Clinical factors and imaging features, including LI-RADS and three other features (non-smooth margin, incomplete capsule, and two-trait predictor of venous invasion), were reviewed and analyzed. Radiomic features from four MRI sequences were extracted. The independent clinic-imaging (clinical) and radiomics model for MVI-prediction were constructed by logistic regression and AdaBoost respectively. And the clinic-radiomics combined model was further constructed by logistic regression. We assessed the model discrimination, calibration, and clinical usefulness by using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision-curve analysis respectively. RESULTS: Incomplete tumor capsule, corona enhancement, and radiomic features were related to MVI in solitary HCCï¼5 cm. The clinical model achieved AUC of 0.694/0.661 (training/internal validation). The single-sequence-based radiomic model's AUCs were 0.753-0.843/0.698-0.767 (training/internal validation). The combination model exhibited superior diagnostic performance to the clinical model (AUC: 0.895/0.848 [training/ internal validation]) and yielded an AUC of 0.858 in an independent test cohort. CONCLUSION: Incomplete tumor capsule and corona enhancement on preoperative MRI were significantly related to MVI in solitary HCCï¼5 cm. Multiple-sequence radiomic features potentially improve MVI-prediction-model performance, which could potentially help determining HCC's appropriate therapy.
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Carcinoma Hepatocelular , Neoplasias Hepáticas , Imagen por Resonancia Magnética , Microvasos , Invasividad Neoplásica , Humanos , Carcinoma Hepatocelular/diagnóstico por imagen , Carcinoma Hepatocelular/patología , Neoplasias Hepáticas/diagnóstico por imagen , Neoplasias Hepáticas/patología , Masculino , Femenino , Persona de Mediana Edad , Invasividad Neoplásica/diagnóstico por imagen , Microvasos/diagnóstico por imagen , Microvasos/patología , Imagen por Resonancia Magnética/métodos , Anciano , Estudios Retrospectivos , Adulto , Valor Predictivo de las Pruebas , Imágenes de Resonancia Magnética Multiparamétrica/métodos , RadiómicaRESUMEN
PURPOSE: Lower urinary tract symptoms (LUTS) are a challenge to the healthy nursing workforce. Nurses confront various objective and subjective nursing workloads which contribute to their LUTS, but less is known about how nursing workloads influence their LUTS. This study is designed to test hypotheses that delayed voiding behaviors mediate the relationships between nursing workloads and LUTS in female nurses. MATERIALS AND METHODS: This study analyzed the baseline data collected from an ongoing cohort study named Nurse Urinary Related Health Study in China. LUTS of nurses in 20 tertiary hospitals were assessed with the International Consultation on Incontinence QuestionnaireâFemale Lower Urinary Tract Symptoms. Objective nursing workloads including working environment, working hours, and working schedule were collected, and perceived stress, the proxy of the subjective nursing workload, was assessed with the Perceived Stress Scale. Delayed voiding behaviors were assessed with 3 questions adapted from the Taiwan Nurse Bladder Survey. Structural equation modeling was used to run the mediation model. RESULTS: More than half (51%) of 13,191 female nurses had LUTS. Median age was 31 years (IQR 27-37). When delayed voiding behaviors served as a mediator, the direct effects of subjective nursing workload rather than objective nursing workloads on LUTS were significant. CONCLUSIONS: Nursing workloads influence nurses' LUTS via delayed voiding behaviors. Strategies tailored to delayed voiding behaviors should be developed, and these may work with stress-reducing strategies as the gatekeepers for nurses' bladder health.
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Síntomas del Sistema Urinario Inferior , Pruebas Psicológicas , Autoinforme , Carga de Trabajo , Humanos , Femenino , Adulto , Estudios de Cohortes , Síntomas del Sistema Urinario Inferior/epidemiología , Encuestas y Cuestionarios , China/epidemiologíaRESUMEN
BACKGROUND: Gastric adenocarcinoma is a highly heterogeneous malignancy with varying prognoses. In clinicopathological practice, we noticed a special tubular adenocarcinoma with diffuse neutrophils infiltrating (TADNI). However, the proportion and characteristics of TADNI remain unclear. This study aimed to evaluate the features of TADNI and explore probable treatments. METHODS: We divided 289 tubular adenocarcinoma cases into the TADNI and non-TADNI (nTADNI) groups by histological neutrophil quantity and performed immunohistochemistry of treatment-associated markers (CXCR1, CXCR2, PD-L1, CD8, HER2 and VEGFR2). Then we evaluated the clinical and morphological features in these cases. We also compared the value of histological features and peripheral blood neutrophil test. In addition, multiomics bioinformatic analyses were performed using the public datasets. RESULTS: In our cohort, TADNI accounted for 10.4% of all tubular adenocarcinoma cases. These cases had worse prognoses (especially the neutrophils mainly outside the tubes) than nTADNI cases. The histological identification of TADNI had more prognostic value than peripheral blood neutrophils. CXCR1/CXCR2 expression was significantly high in TADNI group which indicated that CXCR1/CXCR2 inhibitors might be beneficial for TADNI patients. There were no significant differences in the expression of PD-L1, CD8, HER2 and VEGFR2. The analyses of TCGA data confirmed that TADNI cases had poorer prognoses and higher CXCR1/CXCR2 expression. Bioinformatic results also revealed molecular features (more hsa-mir-223 expression, fewer CD8-positive T cells and regulatory T cells, tighter communication between tumor cells' CXCR1/CXCR2 and neutrophils' CXCL5/CXCL8) of this type. CONCLUSIONS: TADNI is a special morphological subtype with poorer prognoses and unique molecular characteristics, which might benefit from CXCR1/CXCR2 inhibitors.
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Adenocarcinoma , Neoplasias Gástricas , Humanos , Neutrófilos , Antígeno B7-H1/metabolismo , Neoplasias Gástricas/genética , Neoplasias Gástricas/metabolismo , Adenocarcinoma/genética , Adenocarcinoma/metabolismoRESUMEN
BACKGROUND: Coronavirus disease 2019 (COVID-19) has potential risks for both clinically worsening pulmonary hypertension (PH) and increasing mortality. However, the data regarding the protective role of vaccination in this population are still lacking. This study aimed to assess the safety of approved vaccination for patients with PH. METHODS: In this national prospective cohort study, patients diagnosed with PH (World Health Organization [WHO] groups 1 and 4) were enrolled from October 2021 to April 2022. The primary outcome was the composite of PH-related major adverse events. We used an inverse probability weighting (IPW) approach to control for possible confounding factors in the baseline characteristics of patients. RESULTS: In total, 706 patients with PH participated in this study (mean age, 40.3 years; mean duration after diagnosis of PH, 8.2 years). All patients received standardized treatment for PH in accordance with guidelines for the diagnosis and treatment of PH in China. Among them, 278 patients did not receive vaccination, whereas 428 patients completed the vaccination series. None of the participants were infected with COVID-19 during our study period. Overall, 398 patients received inactivated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine, whereas 30 received recombinant protein subunit vaccine. After adjusting for baseline covariates using the IPW approach, the odds of any adverse events due to PH in the vaccinated group did not statistically significantly increase (27/428 [6.3%] vs. 24/278 [8.6%], odds ratio = 0.72, P = 0.302). Approximately half of the vaccinated patients reported at least one post-vaccination side effects, most of which were mild, including pain at the injection site (159/428, 37.1%), fever (11/428, 2.6%), and fatigue (26/428, 6.1%). CONCLUSIONS: COVID-19 vaccination did not significantly augment the PH-related major adverse events for patients with WHO groups 1 and 4 PH, although there were some tolerable side effects. A large-scale randomized controlled trial is warranted to confirm this finding. The final approval of the COVID-19 vaccination for patients with PH as a public health strategy is promising.
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COVID-19 , Hipertensión Pulmonar , Adulto , Humanos , COVID-19/prevención & control , Vacunas contra la COVID-19/efectos adversos , Estudios Prospectivos , SARS-CoV-2 , VacunaciónRESUMEN
Surgical site infection (SSI) is one of the common postoperative complications after craniotomy for glioblastoma patients. Previous studies have investigated the risk factors for SSI in patients with glioblastoma. Whereas big differences in research results exist, and the correlation coefficients of different research results are quite different. A meta-analysis was conducted to examine the risk factors related to surgical site infection in patients with glioblastoma. We searched English databases to collect case-control studies or cohort studies published before 15 October 2023 including PubMed, Web of Science, Embase. The risk of bias of the included studies was assessed via Newcastle-Ottawa Scale. The analysis was performed using RevMan 5.4.1 tool. A total of 4 articles (n = 2222) were selected in this meta-analysis. The following risk factors were presented to be correlated with SSI in glioblastoma: irradiation (OR = 1.88, 95% CI [0.46, 7.60]), more than 3 surgeries (OR = 2.99, 95% CI [1.47, 6.08]). Occurrence of SSI is influenced by a variety of factors. Thus, we should pay close attention to high-risk subjects and take crucial targeted interventions to lower the SSI risk following craniotomy. Owing to the limited quality and quantity of the included studies, more rigorous studies with adequate sample sizes are needed to verify the conclusion.
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Cancer of the central nervous system (CNS) can crosstalk systemically and locally in the tumor microenvironment and has become a topic of attention for tumor initiation and advancement. Recently studied neuronal and cancer interaction fundamentally altered the knowledge about glioma and metastases, indicating how cancers invade complex neuronal networks. This review systematically discussed the interactions between neurons and cancers and elucidates new therapeutic avenues. We have overviewed the current understanding of direct or indirect communications of neuronal cells with cancer and the mechanisms associated with cancer invasion. Besides, tumor-associated neuronal dysfunction and the influence of cancer therapies on the CNS are highlighted. Furthermore, interactions between peripheral nervous system and various cancers have also been discussed separately. Intriguingly and importantly, it cannot be ignored that exosomes could mediate the "wireless communications" between nervous system and cancer. Finally, promising future strategies targeting neuronal-brain tumor interactions were reviewed. A great deal of work remains to be done to elucidate the neuroscience of cancer, and future more research should be directed toward clarifying the precise mechanisms of cancer neuroscience, which hold enormous promise to improve outcomes for a wide range of malignancies.
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Timely detection and management of daylily diseases are crucial to prevent yield reduction. However, detection models often struggle with handling the interference of complex backgrounds, leading to low accuracy, especially in detecting small targets. To address this problem, we propose DaylilyNet, an object detection algorithm that uses multi-task learning to optimize the detection process. By incorporating a semantic segmentation loss function, the model focuses its attention on diseased leaf regions, while a spatial global feature extractor enhances interactions between leaf and background areas. Additionally, a feature alignment module improves localization accuracy by mitigating feature misalignment. To investigate the impact of information loss on model detection performance, we created two datasets. One dataset, referred to as the 'sliding window dataset', was obtained by splitting the original-resolution images using a sliding window. The other dataset, known as the 'non-sliding window dataset', was obtained by downsampling the images. Experimental results in the 'sliding window dataset' and the 'non-sliding window dataset' demonstrate that DaylilyNet outperforms YOLOv5-L in mAP@0.5 by 5.2% and 4.0%, while reducing parameters and time cost. Compared to other models, our model maintains an advantage even in scenarios where there is missing information in the training dataset.
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Hemerocallis , Algoritmos , Aprendizaje , Mantenimiento , Hojas de la PlantaRESUMEN
Background: Various inherited traits contribute to the overall risk of venous thromboembolism (VTE). In addition, the epidemiology of thrombophilia in the East-Asian VTE population remains unclear; thus, we aimed to assess the proportion of hereditary thrombophilia via a meta-analysis. Methods: Publications from PubMed, EMBASE, web of science, and Cochrane before December 30, 2022, were searched. Studies from Japan, Korea, China, Hong Kong, Taiwan, Singapore, Thailand, Vietnam, Myanmar, and Cambodia were included. Congenital thrombophilia was described as diseases including protein C (PC) deficiency, protein S (PS) deficiency, antithrombin (AT) deficiency, factor (F)V Leiden (FVL), and prothrombin G20210A mutations. Studies were selected by 2 reviewers for methodological quality analysis. A random-effects model was used for the meta-analysis, assuming that estimated effects in the different studies are not identical. Results: Forty-four studies involving 6453 patients from 7 counties/regions were included in the meta-analysis. The prevalence of PC, PS, and AT deficiencies were 7.1%, 8.3%, and 3.8%, respectively. Among 2924 patients from 22 studies, 5 patients were carriers of FVL mutation. Among 2196 patients from 10 studies, 2 patients were carriers of prothrombin G20210A mutation in a Thailand study. Conclusion: The prevalence of PC, PS, and AT deficiencies was relatively high, while a much lower prevalence of FVL and prothrombin G20210A mutations were identified in East-Asian patients with VTE. Our data stress the relative higher prevalence of PC, PS, and AT deficiencies for thrombophilia in the East-Asian VTE population.
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OBJECTIVE: To construct and validate a prediction model based on dual-layer detector spectral CT (DLCT) and clinico-radiologic features to predict the microsatellite instability (MSI) status of gastric cancer (GC) and to explore the relationship between the prediction results and patient prognosis. METHODS: A total of 264 GC patients who underwent preoperative DLCT examination were randomly allocated into the training set (n = 187) and validation set (n = 80). Clinico-radiologic features and DLCT parameters were used to build the clinical and DLCT model through multivariate logistic regression analysis. A combined DLCT parameter (CDLCT) was constructed to predict MSI. A combined prediction model was constructed using multivariate logistic regression analysis by integrating the significant clinico-radiologic features and CDLCT. The Kaplan-Meier survival analysis was used to explore the prognostic significant of the prediction results of the combined model. RESULTS: In this study, there were 70 (26.52%) MSI-high (MSI-H) GC patients. Tumor location and CT_N staging were independent risk factors for MSI-H. In the validation set, the area under the curve (AUC) of the clinical model and DLCT model for predicting MSI status was 0.721 and 0.837, respectively. The combined model achieved a high prediction efficacy in the validation set, with AUC, sensitivity, and specificity of 0.879, 78.95%, and 75.4%, respectively. Survival analysis demonstrated that the combined model could stratify GC patients according to recurrence-free survival (p = 0.010). CONCLUSION: The combined model provides an efficient tool for predicting the MSI status of GC noninvasively and tumor recurrence risk stratification after surgery. CRITICAL RELEVANCE STATEMENT: MSI is an important molecular subtype in gastric cancer (GC). But MSI can only be evaluated using biopsy or postoperative tumor tissues. Our study developed a combined model based on DLCT which could effectively predict MSI preoperatively. Our result also showed that the combined model could stratify patients according to recurrence-free survival. It may be valuable for clinicians in choosing appropriate treatment strategies to avoid tumor recurrence and predicting clinical prognosis in GC. KEY POINTS: ⢠Tumor location and CT_N staging were independent predictors for MSI-H in GC. ⢠Quantitative DLCT parameters showed potential in predicting MSI status in GC. ⢠The combined model integrating clinico-radiologic features and CDLCT could improve the predictive performance. ⢠The prediction results could stratify the risk of tumor recurrence after surgery.
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Objectives: Sarcopenia is associated with a poor prognosis in patients with colorectal cancer. However, the clinical factors that lead to colorectal cancer patients with sarcopenia are still unclear. The objective of this study is to develop and validate a nomogram for predicting the occurrence of sarcopenia and to provide healthcare professionals with a reliable tool for early identification of high-risk patients with colorectal cancer associated sarcopenia. Methods: A total of 359 patients diagnosed with colorectal cancer from July 2021 to May 2022 were included. All patients were randomly divided into a training (n = 287) cohort and a validation cohort (n = 72) at the ratio of 80/20. Univariate and multivariate logistic analysis were performed to evaluate the factors associated with sarcopenia. The diagnostic nomogram of sarcopenia in patients with colorectal cancer was constructed in the training cohort and validated in the validation cohort. Various evaluation metrics were employed to assess the performance of the developed nomogram, including the ROC curve, calibration curve, and Hosmer-Lemeshow test. Results: Smoking history, drinking history, diabetes, TNM stage, nutritional status, and physical activity were included in the nomogram for the prediction of sarcopenia. The diagnostic nomograms demonstrated excellent discrimination, with AUC values of 0.971 and 0.922 in the training and validation cohorts, respectively. Moreover, the calibration performance of the nomogram is also excellent, as evidenced by the Hosmer-Lemeshow test result of 0.886. Conclusions: The nomogram consisting of preoperative factors was able to successfully predict the occurrence of sarcopenia in colorectal cancer patients, aiding in the early identification of high-risk patients and facilitating timely implementation of appropriate intervention measures.
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Because the 6-minute walking test (6MWT) is a self-paced submaximal test, the 6-minute walking distance (6MWD) is substantially influenced by individual effort level and physical condition, which is difficult to quantify. We aimed to explore the optimal indicator reflecting the perceived effort level during 6MWT. We prospectively enrolled 76 patients with pulmonary arterial hypertension and 152 healthy participants; they performed 2 6MWTs at 2 different speeds: (1) at leisurely speed, as performed in daily life without extra effort (leisure 6MWT) and (2) an increased walking speed, walking as the guideline indicated (standard 6MWT). The factors associated with 6MWD during standard 6MWT were investigated using a multiple linear regression analysis. The heart rate (HR) and Borg score increased and oxygen saturation (SpO2) decreased after walking in 2 6MWTs in both groups (all p <0.001). The ratio of difference in HR before and after each test (ΔHR) to HR before walking (HRat rest) and the difference in SpO2 (ΔSpO2) and Borg (ΔBorg) before and after each test were all significantly higher in both groups after standard 6MWT than after leisure 6MWT (all p <0.001). Multiple linear regression analysis revealed that ΔHR/HRat rest was an independent predictor of 6MWD during standard 6MWT in both groups (both p <0.001, adjusted R2 = 0.737 and 0.49, respectively). 6MWD and ΔHR/HRat rest were significantly lower in patients than in healthy participants (both p <0.001) and in patients with cardiac functional class III than in patients with class I/II (both p <0.001). In conclusion, ΔHR/HRat rest is a good reflector of combined physical and effort factors. HR response should be incorporated into 6MWD to better assess a participant's exercise capacity.