Medicine
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Induction chemotherapy (IC) prior to concurrent chemo-radiotherapy is the recommended treatment for unresectable stage III non-small cell lung cancer (NSCLC). However, the optimum number of IC cycles for improved survival outcomes is still not known. Here, we assessed the efficacy of 2 or more cycles of IC for unresectable stage III NSCLC patients from our hospital. ⋯ Distant metastasis free survival, loco-regional recurrence free survival and progression free survival were also not significant, (90.0% vs 86.1%, P = .068), 97.8% vs 97.2%, P = .056), and (73.3% vs 66.7%, P = .446) respectively. Univariate and multivariate Cox regression analysis revealed smoking, T_stage, N_stage, and IC_regimen as independent prognostic factor for overall survival, while drinking and T_stage were risk factors for progression free survival. In summary, 2 cycles of platinum-based IC was effective for stage III unresectable NSCLC and adding more than 2 cycles did not offer extra survival benefits.
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It is difficult to differentiate between non-complicated acute cholecystitis (NCAC) and complicated acute cholecystitis (CAC) preoperatively, which are two separate pathologies with different management. The aim of this study was to create an algorithm that distinguishes between CAC and NCAC using the decision tree method, which includes simple examinations. In this retrospective study, the patients were divided into 2 groups: CAC (149 patients) and NCAC (885 patients). ⋯ In statistical analysis, significant differences were found groups in terms of gender (34.8% vs 51.7% male), ASA score (P < .001), Tokyo grade (P < .001), comorbidity (P < .001), albumin (4 vs 3.4 g/dL), and CAR (2.4 vs 38.4). By means of this algorithm, which includes low-cost examinations, NCAC and CAC distinction can be made easily and quickly within limited possibilities. Preoperative prediction of pathologies that are difficult to manage, such as CAC, can minimize patient morbidity and mortality.
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Public hospitals in Thailand recently adopted a new nutrition screening tool to satisfy documentation requirements for reimbursements through the diagnosis-related group system. However, data on the performance of this instrument remains limited. This study was designed to assess the validity and cutoff points of the Society of Parenteral and Enteral Nutrition of Thailand (SPENT) nutrition screening tool against the patient-generated subjective global assessment (PG-SGA) and malnutrition diagnostic criteria proposed by the global leadership initiative on malnutrition (GLIM) in cancer patients receiving outpatient radiation therapy. ⋯ Against PG-SGA and GLIM malnutrition diagnosis, the SPENT nutrition screening tool demonstrated good sensitivity (85.3% and 82.8%), specificity (84.1% and 59.4%), positive predictive value (90.5% and 64.0%), negative predictive value (76.3% and 79.9%), with moderate strength of agreement (Cohen kappa 0.678, P < .001 and 0.414, P < .001). Using only the first 2 out of 4 questions revealed an acceptable sensitivity and specificity. The SPENT nutrition screening tool is an accurate, sensitive, and specific tool for malnutrition screening in cancer patients receiving outpatient radiotherapy.
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Deep learning is an advanced machine learning technique that is used in several medical fields to diagnose diseases and predict therapeutic outcomes. In this study, using anteroposterior ankle radiographs, we developed a convolutional neural network (CNN) model to diagnose osteochondral lesions of the talus (OLTs) using ankle radiographs as input data. We evaluated whether a CNN model trained on anteroposterior ankle radiographs could help diagnose the presence of OLT. ⋯ We then used the Visual Geometry Group Network model to determine whether the input image was OLT or non-OLT. The performance of the CNN model for the area under the curve, accuracy, positive predictive value, and negative predictive value on the test data were 0.774 (95% confidence interval [CI], 0.673-0.875), 81.58% (95% CI, 0.729-0.903), 80.95% (95% CI, 0.773-0.846), and 81.82% (95% CI, 0.804-0.832), respectively. A CNN model trained on anteroposterior ankle radiographs achieved meaningful accuracy in diagnosing OLT and demonstrated that it could help diagnose OLT.
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Intravenous thrombolysis can significantly improve the neurological function of patients with acute ischemic stroke. However, the expected early dramatic recovery (EDR) of neurological function after thrombolysis is not achieved in some patients with branch atheromatous disease (BAD). Here we evaluated the factors associated with EDR after thrombolysis in BAD patients. ⋯ Diabetes is not conducive to EDR of neurological function in patients with BAD, especially in patients with paramedian pontine infraction. Low NIHSS score and short OTT after thrombolysis may be closely related to EDR after intravenous thrombolysis.