Objective To develop and validate a nomogram model for predicting the risk of kinesiophobia in patients after lung cancer surgery.Methods A total of 164 lung cancer patients who underwent surgery in a Grade ⅢA hospital in Xiamen were recruited from October 2022 to May 2023 in this study.Logistic regression was conducted to identify independent risk factors of kinesiophobia in patients who recieved lung cancer surgery.A Nomogram model was developed using R software for predicting the risk of kinesiophobia.The predictive performance of the model was assessed by calculating the receiver-operating-characteristics curve(ROC)and the area under curve(AUC).Results The incidence of postoperative kinesiophobia in lung cancer patients was at 44.51％.Logistic regression analysis showed that pain and fatigue were the risk factors for the occurrence of postoperative kinesiophobia in the patients(P<0.05)and self-efficacy was a protective factor(P<0.05).Validation of the Nomogram model showed that the ROC curve indicated an AUC of 0.888(95％CI 0.836-0.940)for predicting kenesiophobia in patients after lung cancer surgery and the calibration curve presented as a line with a slope close to 1.The Hosmer-Lemeshow goodnee-of-fit test showed that the model could accurately predict the risk of postoperative kinesiophobia in lung cancer patients(χ 2=1.931,P=0.983).Conclusion Self-efficacy,pain and fatigue are the influencing factors for the occurrence of postoperative kinesiophobia in the patients who received lung cancer surgery.The nomogram prediction model has good accuracy and discrimination,and it may assist the healthcare professionals to predict the occurrence of postoperative kinesiophobia in the patients after lung cancer surgery and take pertinent measures to minimise the incidence.

Objective To develop and validate a nomogram model for predicting the risk of kinesiophobia in patients after lung cancer surgery.Methods A total of 164 lung cancer patients who underwent surgery in a Grade ⅢA hospital in Xiamen were recruited from October 2022 to May 2023 in this study.Logistic regression was conducted to identify independent risk factors of kinesiophobia in patients who recieved lung cancer surgery.A Nomogram model was developed using R software for predicting the risk of kinesiophobia.The predictive performance of the model was assessed by calculating the receiver-operating-characteristics curve(ROC)and the area under curve(AUC).Results The incidence of postoperative kinesiophobia in lung cancer patients was at 44.51％.Logistic regression analysis showed that pain and fatigue were the risk factors for the occurrence of postoperative kinesiophobia in the patients(P<0.05)and self-efficacy was a protective factor(P<0.05).Validation of the Nomogram model showed that the ROC curve indicated an AUC of 0.888(95％CI 0.836-0.940)for predicting kenesiophobia in patients after lung cancer surgery and the calibration curve presented as a line with a slope close to 1.The Hosmer-Lemeshow goodnee-of-fit test showed that the model could accurately predict the risk of postoperative kinesiophobia in lung cancer patients(χ 2=1.931,P=0.983).Conclusion Self-efficacy,pain and fatigue are the influencing factors for the occurrence of postoperative kinesiophobia in the patients who received lung cancer surgery.The nomogram prediction model has good accuracy and discrimination,and it may assist the healthcare professionals to predict the occurrence of postoperative kinesiophobia in the patients after lung cancer surgery and take pertinent measures to minimise the incidence.

BACKGROUND: Accurate evaluation of lymph node metastasis in bladder cancer (BCa) is important for disease staging, treatment selection, and prognosis prediction. In this study, we aimed to evaluate the diagnostic accuracy of computed tomography (CT) and magnetic resonance imaging (MRI) for metastatic lymph nodes in BCa and establish criteria of imaging diagnosis. METHODS: We retrospectively assessed the imaging characteristics of 191 BCa patients who underwent radical cystectomy. The data regarding size, shape, density, and diffusion of the lymph nodes on CT and/or MRI were obtained and analyzed using Kruskal-Wallis test and χ test. The optimal cutoff value for the size of metastatic node was determined using the receiver operating characteristic (ROC) curve analysis. RESULTS: A total of 184 out of 3317 resected lymph nodes were diagnosed as metastatic lymph nodes. Among 82 imaging-detectable lymph nodes, 51 were confirmed to be positive for metastasis. The detection rate of metastatic nodes increased along with more advanced tumor stage (P < 0.001). Once the ratio of short- to long-axis diameter ≤ 0.4 or fatty hilum was observed in lymph nodes on imaging, it indicated non-metastases. Besides, lymph nodes with spiculate or obscure margin or necrosis indicated metastases. Furthermore, the short diameter of 6.8 mm was the optimal threshold to diagnose metastatic lymph node, with the area under ROC curve of 0.815. CONCLUSIONS The probability of metastatic nodes significantly increased with more advanced T stages. Once lymph nodes are detected on imaging, the characteristic signs should be paid attention to. The short diameter > 6.8 mm may indicate metastatic lymph nodes in BCa.
Adult ; Aged ; Aged, 80 and over ; Female ; Humans ; Lymph Node Excision ; Lymph Nodes ; pathology ; Lymphatic Metastasis ; diagnostic imaging ; pathology ; Magnetic Resonance Imaging ; Male ; Middle Aged ; Neoplasm Staging ; Pelvic Neoplasms ; diagnostic imaging ; pathology ; secondary ; surgery ; Pelvis ; diagnostic imaging ; pathology ; Tomography, X-Ray Computed ; Urinary Bladder Neoplasms ; diagnostic imaging ; pathology ; surgery

Objective To cstimnate the diagnostic performance of computer tomography (CT) and magnetic resonance imaging (MRI) for detecting metastasis in pelvic lymph nodes with normal size in patients with bladder cancer.Methods hnaging of CT and MRI and clinical data of 118 patients who underwent radical cystectomy and pelvic lymphadenectomy were reviewed.The diagnostic efficacy of CT and MRI were analyzed when taking lymph nodes short axis diameter ≥0.3 cm and ≥ 1.0 cm respectively as diagnostic criterion of metastasis with corTelation of pathological results.Results 22.7％ (27/118) of patients were confirmed lymph nodes malignancies among 118 patients based on pathology.Totally 1 705 lymph nodes were detected in surgery and 119 of them were observed malignancy according to pathological presentation.The malignant nodes were mainly distributed in the perivesical (35.4％,41/119),internal iliac (12.6％,15/119),external iliac (30.3％,36/119),obturator region (21.0％,25/119) and presarcal region (1.7％,2/119).Imaging of CT and MRI showed that when taking nodes with ≥0.3 cm in maximum short-axis diameter (MSAD) as positive,the sensitivity (Se),specificity (Sp),and positive predictive values (PPV) were 16.0％,99.2％,54.2％ and 56.5％,99.2％,86.7％ respectively.While taking MSAD≥1.0 cm as malignant,the Se,Sp and PPV of CT and MRI were 6.2％,99.9％,83.3％ and 13％,100％,100％ respectively.When taking MSAD ≥0.3 cm as positive,the Se and PPV between CT and MR were statistically different(P ＜ 0.001 and P =0.036,respectively).When taking MSAD ≥ 1.0 cm as positive,there was no statistically difference (P =0.275 and 1.000,respectively).Conclusions The incidence of normal-sized lymph node metastasis was higher in patients with bladder cancer.At this phase the MRI evaluation was superior to that of CT.When the MSAD ≥ 1.0 cm,there was no significant difference between CT and MRI.