ObjectiveTo explore the application effect of standardized management on video-electroencephalogram (VEEG) monitoring.MethodsIn January 2018, a multidisciplinary standardized management team composed with doctors, technicians, and nurses was established. The standardized management plan for VEEG monitoring from outpatient, pre-hospital appointment, hospitalization and post-discharge follow-up was developed; the special quilt for epilepsy patients was designed and customized, braided for the patient instead of shaving head, standardized the work flow of the staff, standardized the health education of the patients and their families, and standardized the quality control of the implementation process. The standardized managemen effect carried out from January to December 2018 (after standardized managemen) was compared with the management effect from January to December 2017 (before standardized managemen).ResultsAfter standardized management, the average waiting time of patients decreased from (2.08±1.13) hours to (0.53±0.21) hours, and the average hospitalization days decreased from (6.63±2.54) days to (6.14±2.17) days. The pass rate of patient preparation increased from 63.14% to 90.09%. The capture rate of seizure onset increased from 73.37% to 97.08%. The accuracy of the record increased from 33.12% to 94.10%, the doctor’s satisfaction increased from 76.34±29.53 to 97.99±9.27, and the patient’s satisfaction increased from 90.04±18.97 to 99.03±6.51. The difference was statistically significant (P<0.05).ConclusionStandardization management is conducive to ensuring the homogeneity of clinical medical care, reducing the average waiting time and the average hospitalization days, improving the capture rate and accuracy of seizures, ensuring the quality of medical care and improving patient’s satisfaction.
ObjectiveTo analyze the details and efficacy of neoadjuvant therapy of colorectal cancer in the current version of Database from Colorectal Cancer (DACCA).MethodsThe DACCA version selected for this data analysis was the updated version on July 28th, 2020. The data items included “planned strategy of neoadjuvant therapy” “compliance of neoadjuvant therapy”, and “cycles of neoadjuvant therapy”. Item of “planned strategy of neoadjuvant therapy” included “accuracy of neoadjuvant therapy” and “once included in researches”. Item of “the intensity of neoadjuvant therapy” included “chemotherapy” “cycles of neoadjuvant therapy” “targeted drugs”, and “neoadjuvant radiotherapy”. Item of “effect of neoadjuvant therapy” included CEA value of “pre-neoadjuvant therapy” and “post-neoadjuvant therapy”“variation of tumor markers” “variation of symptom” “variation of gross” “variation of radiography”, and tumor regression grade (TRG). The selected data items were statistically analyzed.ResultsThe total number of medical records (data rows) that met the criteria was 7 513, including 2 539 (33.8%) valid data on the “accuracy of neoadjuvant therapy”, 498 (6.6%) valid data on “once included in researches”, 637 (8.5%) valid data on the “compliance of neoadjuvant therapy”, 2 077 (27.6%) valid data on “neoadjuvant chemotherapy”, 614 (8.2%) valid data on “cycles of neoadjuvant therapy”, 455 (6.1%) valid data on “targeted drugs”, 135 (1.8%) valid data on “neoadjuvant radiotherapy”, 5 022 (66.8%) valid data on “pre-neoadjuvant therapy CEA value”, 818 (10.9%) valid data on “post-neoadjuvant therapy CEA value ”, 614 (8.2%) valid data on “variation of tumor marker”, 464 (6.2%) valid data on “variation of symptom”, 478 (6.4%) valid data on “variation of gross”, 492 (6.5%) valid data on “variation of radiography”, and 459 (6.1%) valid data on TRG. During the correlation analysis, it appeared that “variation of tumor marker” and “variation of gross” (χ2=6.26, P=0.02), “variation of symptom” and “variation of gross”, “radiography” and TRG (χ2=53.71, P<0.01; χ2=38.41, P<0.01; χ2=8.68, P<0.01), “variation of gross” and “variation of radiography”, and TRG (χ2=44.41, P<0.01; χ2=100.37, P<0.01), “variation of radiography” and TRG (χ2=31.52, P<0.01) were related with each other.ConclusionsThe protocol choosing of neoadjuvant therapy has a room for further research and DACCA can provide data support for those who is willing to perform neoadjuvant therapy. The efficacy indicators of neoadjuvant therapy have association with each other, the better understand of it will provide more valuable information for the establishment of therapeutic prediction model.
Objective To explore the safety and clinical efficacy of right chest minithoracotomy for left atrial myxoma resection. Methods We retrospectively analyzed clinical data of 32 patients with left atrial myxoma resection by right chest minithoracotomy (a small incision group, 9 males, 23 females at age of 59.1±9.5 years) in our hospital from July 2011 through March 2015. Meanwhile, we selected 17 patients with left atrial myxoma treated by conventional chest median sternotomy as a control group (7 males, 10 females at age of 60.0±9.0 years). Clinical results of the two groups were compared. Results There was no statistical difference in preoperative clinical data of the patients between the two groups. All the patients were successfully operated. Patients in the small incision group had longer aortic clamping time than that in the control group. But there were shorter postoperative mechanical ventilation time (9.5±4.9 h), shorter ICU stay time (18.6 ± 6.2 h), less amount of thoracic cavity drainage 24 h after drainage (103.8±19.4 ml), lower bleeding reoperation rate (0.0), less blood transfusion after surgery (1.4±1.1U), shorter ambulation time (38.5±6.9 h), shorter hospital stay (8.1 ± 0.9 d), lower postoperative complication rate (0.0) than those of the control group (P<0.05). Conclusion Right chest minithoracotomy left atrial myxoma resection is feasible, safe and effective, is worth promoting.
Objective To systematically review the health state utility values in patients with schizophrenia, and to provide references for subsequent studies on the health economics of schizophrenia. Methods The PubMed, EMbase, The Cochrane Library, Web of Science, CNKI, WanFang Data, and VIP databases were searched from inception to December 1st, 2021 to collect studies on health state utility values in patients with schizophrenia. Two reviewers independently screened literature, extracted data, and assessed the risk of bias of the included studies. Meta-analysis was then performed by Stata 15.0 software. Results A total of 19 studies were included. Patients’ utility values were 0.68 (95%CI 0.59 to 0.77) for direct measures, and 0.77 (95%CI 0.75 to 0.80) and 0.66 (95%CI 0.61 to 0.70) for indirect measures with the EQ-5D-5L and EQ-5D-3L as the primary scales. Utility values varied with measures, tariffs, regions, and populations. Conclusion Studies on health state utility value in schizophrenia are diversified in measurement methods, showing high inter-study heterogeneity. Therefore, it is necessary to promote the study on utility value measurement in schizophrenia in China.
ObjectiveTo investigate the relationship of 24-hour ambulatory pulse pressure (24hPP) with left ventricular mass index (LVMI) in elderly essential hypertension patients. MethodsThe data of 110 elderly patients with essential hypertension from January to December 2012 were collected in the study. All patients received 24-hour ambulatory blood pressure monitoring and echoeardiographic examination 24hPP and LVMI were calculated according to the results of 24-hour ambulatory blood pressure monitoring and echocardiographic measurements. The patients were divided into group A [24hPP<60 mm Hg (1 mm Hg=0.133 kPa), n=70] and group B (24hPP≥60 mm Hg, n=40). ResultsThe 24-hour systolic blood pressure and 24hPP for patients in group B were significantly higher than those in group A (P<0.001). Compared with group A patients, the interventricular septal thickness, left ventricular posterior wall thickness, left ventricular mass and left ventricular mass index were significantly higher in group B (P<0.05). Pearson correlation analysis showed that 24hPP had a positive correlation with LVMI in the elderly essential hypertension patients (r=0.33, P<0.001). Multiple stepwise regression analysis showed that 24hPP was the main factor for the increase of LVMI in elderly essential hypertension patients (β=0.90, P<0.001). ConclusionThe 24hPP is positively correlated with LVMI in elderly essential hypertension patients. The 24hPP is an important risk factor for left ventricular structural damage in elderly essential hypertensive patients.