Objective To identify risk factors associated with lymphatic leakage after laparoscopic radical prostatectomy(LRP)and to develop a machine learning-based nomogram for predicting such outcomes to support clinical prevention strategies.Methods We retrospectively analyzed perioperative data from 248 patients who underwent radical prostatectomy for prostate cancer between January 2020 and January 2024.Independent risk factors were identified through univariate and multivariate logistic regression analyses.A predictive model was developed,and its diagnostic performance was assessed by the area under the receiver operating characteristic curve(AUC).Five-fold cross-validation was performed to evaluate the model's generalizability.A nomogram was subsequently constructed to facilitate individualized risk quantification.Results Among the 248 patients,89(35.9%)developed lymphatic leakage,while 159(64.1%)did not.Independent risk factors for lymphatic leakage included intraopera-tive lymph node dissection(OR=5.415,95%CI:2.167～13.532,P<0.001),intraoperative plasma transfusion(OR=2.952,95%CI:1.524～5.718,P=0.001),and postoperative fasting duration of≥2 days(OR=1.412,95%CI:1.089～1.829,P=0.009).The predictive model showed good discrimination and calibration(AUC=0.711,95%CI:0.647～0.776,P<0.001;sensitivity:0.764;specificity:0.597).Model robustness was confirmed through five-fold cross-validation(training set AUC=0.822;test set AUC=0.829).The nomogram provided a clinically useful tool for quantifying individual risk of lymphatic leakage.Conclusions Intraoperative lymph node dissection,plasma transfusion,and postoperative fasting lasting≥2 days are independent risk factors for lymphatic leakage following radical prostatectomy.The validated predictive model demonstrates favorable clinical utility.

Objective To identify risk factors associated with lymphatic leakage after laparoscopic radical prostatectomy(LRP)and to develop a machine learning-based nomogram for predicting such outcomes to support clinical prevention strategies.Methods We retrospectively analyzed perioperative data from 248 patients who underwent radical prostatectomy for prostate cancer between January 2020 and January 2024.Independent risk factors were identified through univariate and multivariate logistic regression analyses.A predictive model was developed,and its diagnostic performance was assessed by the area under the receiver operating characteristic curve(AUC).Five-fold cross-validation was performed to evaluate the model's generalizability.A nomogram was subsequently constructed to facilitate individualized risk quantification.Results Among the 248 patients,89(35.9%)developed lymphatic leakage,while 159(64.1%)did not.Independent risk factors for lymphatic leakage included intraopera-tive lymph node dissection(OR=5.415,95%CI:2.167～13.532,P<0.001),intraoperative plasma transfusion(OR=2.952,95%CI:1.524～5.718,P=0.001),and postoperative fasting duration of≥2 days(OR=1.412,95%CI:1.089～1.829,P=0.009).The predictive model showed good discrimination and calibration(AUC=0.711,95%CI:0.647～0.776,P<0.001;sensitivity:0.764;specificity:0.597).Model robustness was confirmed through five-fold cross-validation(training set AUC=0.822;test set AUC=0.829).The nomogram provided a clinically useful tool for quantifying individual risk of lymphatic leakage.Conclusions Intraoperative lymph node dissection,plasma transfusion,and postoperative fasting lasting≥2 days are independent risk factors for lymphatic leakage following radical prostatectomy.The validated predictive model demonstrates favorable clinical utility.

Objective To investigate the clinical effect of continuous language rehabilitation nursing on the language function in patients with stroke motor aphasia. Methods A total of 60 motor aphasia patients with a brain stroke were recruited and divided into experimental group and control group with 30 cases each by random digits table method. The control group was treated with the routine stroke care in traditional Chinese medicine, while the experimental group with the continuing language rehabilitation nursing base on the routine stroke care. The language function of both groups were detected by the Chinese Rehabilitation Research Center Standard Aphasia Examination before and after 3 months treatment, and a survey of nursing satisfaction of patients when discharged was conducted. Results The right rate of hear and understand, retelling, say, read aloud, reading comprehension, transcription, description, dictation, calculation in the Chinese Rehabilitation Research Center Standard Aphasia Examination was (44.35 ± 18.69), (32.37 ± 22.25), (21.49 ± 14.91), (27.63 ± 12.54), (46.87 ± 15.30), (14.25 ± 6.11), (7.33±3.23), (11.63±4.82), (18.93±6.82)%before the treatment and (62.14±10.81), (55.36±19.53), (41.42 ± 13.75), (59.16 ± 11.05), (55.57 ± 13.90), (32.39 ± 7.12), (9.73 ± 3.92), (27.45 ± 4.71), (37.46 ± 6.91)%after the treatment in the experimental group, except for description, the differences were significant ( t=2.096-14.540, P<0.01 or 0.05). The right rate of hear and understand, retelling, say, read aloud, reading comprehension, transcription, description, dictation, calculation in the Chinese Rehabilitation Research Center Standard Aphasia Examination was (43.86±15.89), (34.28±20.27), (22.84±15.40), (28.63±12.45), (47.23±11.30), (13.40±6.24), (7.27±3.70), (11.10±4.73), (19.50±6.80)%before the treatment and (49.46± 14.27), (42.36±20.58), (30.33±13.36), (40.31±11.88), (49.97±10.13), (15.37±5.59), (8.50±3.74), (12.83± 4.36), (21.47 ± 7.74)% after the treatment in the control group, the differences of hear and understand, retelling, say, read aloud were significant (t=2.263-3.991, P<0.05 or 0.01). There were significant differences in hear and understand, retelling, say, read aloud, transcription, dictation, calculation after the treatment between two groups (t=2.510-10.298, all P<0.05). The score of satisfaction was (94.36 ± 5.55) in the experimental group and (88.25 ± 5.46) points in the control group, and there was significant difference (t=4.299, P<0.01). Conclusions Continuing language rehabilitation nursing can improve the recovery of the language function of the motor aphasia patients with a brain stroke.

BACKGROUNDTo investigate the expression features of the heterogeneous nuclear ribonucleoprotein A2/B1 (hnRNP A2/B1) in non-small cell lung cancer and its clinical significance.

METHODShnRNP A2/B1 expression of cancer tissues, paracancerous lung tissues, resected bronchial stump epithelium tissues was detected in 58 non-small cell lung cancer patients and pulmonary tissues in 30 patients with benigh pulmonary lesions as control by immunohistochemistry methods.

RESULTSThe positive expressive rate of hnRNP A2/B1 in lung cancer tissue (63.79%) was significantly higher than those in paracancerous lung tissue (43.10%) and benign pulmonary lesion tissues (20.00%) (P=0.000), and the positive rate in paracancerous lung tissue was also significantly higher than that in benign pulmonary lesion tissues (P < 0.05). The positive rate of hnRNP A2/B1 in the hyperplastic and dysplastic epithelium (40.00%) of resected bronchial stump was remarkably higher than that in normal bronchial epithelium (15.15%) in lung cancer patients (P=0.032). The positive rate of hnRNP A2/B1 in poor differentiated lung cancer (78.13%) was remarkably higher than that in moderate and well differentiated lung cancer (46.15%) (P < 0.05). The positive rate of hnRNP A2/B1 in lung cancer with lymph node metastasis (75.00%) was significantly higher than that without lymph node metastasis (50.00%) (P < 0.05). The positive rate of hnRNP A2/B1 in stage III+IV disease (78.57%) was significantly higher than that in stage I+II disease (50.00%) (P < 0.05). The positive rate of hnRNP A2/B1 in T3+T4 cancer (77.42%) was significantly higher than that in T1+T2 cancer (48.15%) (P < 0.05). The positive rate of hnRNP A2/B1 expression in lung cancer tissues was not related to histological classification of the cancer (P > 0.05).

CONCLUSIONSThe overexpression of hnRNP A2/B1 in cancer tissues may play an important role in the oncogenesis, development and metastasis of lung cancer. Detection of hnRNP A2/B1 expression may be helpful to diagnose lung cancer and to predict prognosis of the patients with lung cancer.