ObjectiveTo describe the constructive process of neoadjuvant therapy for colorectal cancer part in the West China Colorectal Cancer Database (DACCA).MethodWe used the form of text description.ResultsThe specific concept of neoadjuvant therapy for colorectal cancer including neoadjuvant treatment therapies, compliance of patients with neoadjuvant therapy, neoadjuvant therapy intensity scheme, the CEA value of patients during neoadjuvant therapy, changes of symptoms, changes of primary tumor size in colorectal cancer, and TRG grading of the DACCA in the West China Hospital were defined. Then the neoadjuvant therapies were detailed for their definition, label, structure, error correction, and update.ConclusionThrough detailed description and specification of neoadjuvant therapy for colorectal cancer in DACCA in West China Hospital, it can provide a reference for the standardized treatment of colorectal cancer and also provide experiences for the peers who wish to build a colorectal cancer database.
ObjectiveTo analyze the characteristics of colorectal cancer surgery in the current version of Database from Colorectal Cancer (DACCA).MethodsThe DACCA version selected for this data analysis was the updated version on July 16th, 2020. The data items included operative duration, anatomy (anatomical difficulty), pelvis (pelvic stenosis), obesity (abdominal obesity), adhesion (adhesion in surgical area), mesentery (abnormal mesenteric status), hypertrophy (tissue hypertrophy or organ hypertrophy), intestinal quality, death (risk of death), injury (risk of tissue injury), recurrence (tumor recurrence), metastasis (tumor metastasis), anastomotic leakage (risk of anastomotic leakage), difficulty of operation, prognosis, quality of operation. The selected data items were statistically analyzed.ResultsThetotal number of medical records (data rows) that met the criteria was 6 116. Spearman correlation text showed a negative correlation between operative duration and years (rs=–0.433, P<0.001). In anatomy, pelvis, obesity, adhesion, mesentery, and hypertrophy, the most cases were “normal or basically normal”, and the percentages were 32.55%, 44.52%, 48.68%, 55.79%, 53.36%, and 57.72%, respectively. In quality of intestinal, the highest proportion was “bad” (43.25%). In risk of death, risk of tissue injury, and tumor recurrence, the most cases were “very small”, and the percentages were 69.00%, 94.41%, and 68.21%, respectively. In tumor metastasis, risk of anastomotic leakage, difficulty of operation, prognosis, and quality of operation, the highest proportion were “small” (48.58%), “average” (49.25%), “average” (32.96%), “uncertain” (45.65%), and “very good” (39.85%).ConclusionsIn the DACCA, the intestinal quality is characteristic of difficulty in operation, and in the evaluation of operation quality, the judgment of anastomotic leakage deserves much more attention. However, the relationship between the difficulty of operation and postoperative effects, and the relationship between the quality of operation and the prognosis still need to be further studied.
ObjectiveTo explain details of the adjuvant therapy of colorectal cancer in detail as well as their tags and structures of Database from Colorectal Cancer (DACCA) in the West China Hospital.MethodThe article was described in words.ResultsThe details of the adjuvant therapy of colorectal cancer included adjuvant treatment therapies, the necessity of adjuvant intravenous chemotherapy, the acceptance of adjuvant chemotherapy, the number of courses of adjuvant chemotherapy, the toxicity of adjuvant chemotherapy, the evaluation of curative effect after adjuvant chemotherapy, the standardized degree of adjuvant chemotherapy, targeted therapy, the necessity of adjuvant radiotherapy, the availability of specialty physicians recommending adjuvant radiotherapy to patients with colorectal cancer, the acceptance of adjuvant radiotherapy, radiotherapy related adverse reactions, and effect evaluation after adjuvant radiotherapy of the DACCA in the West China Hospital were defined. The data labels corresponding to each item in the database and the structured ways needed for the big data application stage in detail were explained. And the error correction notes for all classification items were described.ConclusionsThrough the detailed description of the details of the adjuvant therapy of colorectal cancer of DACCA in West China Hospital, it provides the standard and basis for the clinical application of DACCA in the future, and provides reference for other peers who wish to build a colorectal cancer database.
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.
ObjectiveTo analyze the tumor characteristics of colorectal cancer in the current version of Database from Colorectal Cancer (DACCA).MethodsThe DACCA version was the updated version on April 16, 2020. The data items including: procedure of anastomosis, shape of anastomosis, enhanced suture for anastomosis, stuffing, drainage, coverage of major omentum, anti-adhesion material, reconstruction of pelvic peritoneum, contaminate, and drug implants were analyzed for the characteristics of each selected data item.ResultsA total of 6 338 analyzable data rows were obtained by screening the DACCA database. Among the 6 338 pieces of data, the most common one was the double staple technique (58.1%), end-to-end anastomosis (69.4%), one-total-circle of enhancement (33.2%), and without stuffing (54.1%) in the items of procedure of anastomosis, shape of anastomosis, enhanced suture for anastomosis, stuffing, respectively; the ratio with drainage was higher (79.2%) in the term of drainage, the drainage time was (3.74±2.89) d and median drainage time was 3.00 d; the ratio with covering part of major omentum, without anti-adhesion material, with unilateral partial closure, without contaminate, and without drug implants were more higher, which was 41.1%, 79.8%, 58.7%, 73.9%, and 53.9% in the items of coverage of major omentum, anti-adhesion material, reconstruction of pelvic peritoneum, contaminate, and drug implants, respectively.ConclusionIt might better explain the outcome of surgery associated with intraoperative operation by studying the features of surgery of DACCA and guide the operation in the future for better outcomes.
“Patient profile” is a specific application of user profile technology in the field of healthcare. As an emerging means of integrating health information, it provides personalized and precise health management for patients by analyzing multidimensional health data, improving health management effectiveness, reducing medical costs, and increasing their satisfaction and participation. It has broad application prospects in the field of nursing, but the current research status of its application in the field of nursing is not clear. This article reviews the application progress of patient profile based on big data in the field of nursing at home and abroad, systematically analyzes its construction methods, application scenarios, implementation effects and challenges, and puts forward relevant suggestions, aiming to provide references for the precise and intelligent development of nursing services.
ObjectiveTo analyze the tumor characteristics of colorectal cancer in the current version of Database from Colorectal Cancer (DACCA).MethodsThe DACCA version was the updated version on September 26, 2019. The data items included: date of surgery, precancerous lesions, cancer family, tumor site, distance to the dentate line, morphology of tumor, size, position, happening and origination, differentiation, pathology of tumor, Ki-67 of protein, complications (included obstruction, intussusception, perforation, pain, edema, and hemorrhage) were analyzed for the characteristics of each selected data item.ResultsA total of 11 898 analyzable data rows were obtained by screening the DACCA database. Among the 11 898 pieces of data, the effective data of precancerous lesions was 1 275, including 541 (42.4%) with precancerous lesions, and 734 (57.6%) without precancerous lesions. There were 1 116 valid data on cancer families, and 761 (6.4%) had a family history of cancer. The Ki-67 index had a total of 1 893 valid data, which ranged form 0 to 95% [(59.0±20.1) %]. According to the classification of tumor occurrence, the primary colorectal cancer accounted for the vast majority (92.8%), and the metastatic colorectal cancer was the least (0.3%). According to the primary and multiple primary, respectively analysis of tumor site, distance to the dentate line, morphology of tumor, size, position, differentiation, and pathology of tumor showed that, most tumor’s position were in the rectum (76.9%, 41.9%), the most common morphology was ulcers (42.4%, 51.5%), the most tumors were located around the wall of intestine (44.6%, 35.0%), the degree of differentiation was mostly moderate (65.4%, 61.3%), most of the tumor pathologies were adenocarcinoma (77.8%, 64.0%).ConclusionA more accurate and detailed analysis of colorectal cancer tumor characteristics by the DACCA database is helpful for determining the diagnosis and treatment plan in clinical work, judging the prognosis, and so on.
Objective To analyze the impact of body mass index (BMI) on tumor characteristics of colorectal patients served by West China Hospital as a regional center in the current version of Database from Colorectal Cancer (DACCA). MethodsThe data of DACCA was updated on October 16, 2021. All data items included BMI, precancerous lesions, cancer family, tumor site, tumor morphology, location, differentiation, pathological properties of tumor, obstruction, overlap, perforation, pain, edema, and bleeding. The patients were divided into lean (BMI<18.5 kg/m2), normal (BMI 18.5–23.9 kg/m2), overweight (BMI 24.0–27.9 kg/m2) and obesity (BMI≥28.0 kg/m2) by Chinese classification methods. ResultsAfter scanning, 5 761 data rows were analyzed. Chi-square test showed that there was significant difference in the type composition ratio of tumor location in colorectal cancer patients under different BMI groups (χ2=31.477, P<0.001). Rank sum test showed that there was significant difference in the degree of obstruction (H=42.490, P<0.001), intussusception (H=8.179, P=0.042), edema (H=14.795, P=0.002), and bleeding (H=9.884, P=0.020) among different BMI groups. ConclusionsThe BMI classification of colorectal cancer patients is related to the location of tumor and the occurrence of some tumor complications. Patients with tumor involving intestinal lumens for one week are more likely to have low BMI. The patients with low BMI are more likely to have severe bleeding, obstruction, intestinal intussusception, and severe intestinal wall edema.
Objective To analyze the data of external fixation instruments (including Ilizarov instruments) used by QIN Sihe orthopaedic surgical team in the treatment of limb deformities in the past 30 years, and to explore the indications for the application of modern external fixation techniques in the correction of limb deformities and individual device configuration selection strategy. Methods According to QIN Sihe orthopaedic surgical team, the use of external fixator between January 1988 and December 2017 was analyzed retrospectively. The total use of external fixation and the proportion of different external fixators were analyzed in gender, different operation time, different age, different parts, and different diseases. Results External fixators were used in 8 113 patients, 69 of them were used simultaneously in both lower extremity surgery, so 8 182 external fixators were used. Among them, there were 4 725 (57.74%) combined external fixators, 3 388 (41.41%) Ilizarov circle fixators, 64 (0.78%) single arm external fixators (including Orthofix), 5 (0.06%) Taylor space external fixators. There were 4 487 males (55.31%) and 3 626 females (44.69%). According to the analysis of different time periods, the number of external fixators increased year by year, and the number of applications increased after 2000. The main age of the patients was 11-30 years old, of which 1 819 sets (22.23%) were used at the age of 21-25 years. The use of the external fixator covered almost all parts of the limbs, with the ankle and toe areas being the most common, reaching 4 664 sets (57.00%), and the upper extremities the least, with 152 sets (1.86%). The 8 113 cases covered more than a dozen disciplines and more than 150 kinds of diseases. The top 5 diseases were poliomyelitis sequelae, cerebral palsy, deformity of lower extremity after spina bifida, traumatic sequelae, and congenital equinovarus foot. Conclusion Ilizarov technique has been widely used in extremity deformity, disability, and complicated orthopedic diseases caused by vascular, lymphoid, nerve, skin, endocrine, and other diseases. The indication of operation is far beyond the scope of orthopedics. The domestic external fixator and its mounting tools can basically meet the requirements of various treatments. The technique of external fixation has entered a new era of tension tissue regeneration under stress control, natural repair of tissue trauma and deformity, and reconstruction of limb function.
With the establishment and development of regional healthcare big data platforms, regional healthcare big data is playing an increasingly important role in health policy program evaluations. Regional healthcare big data is usually structured hierarchically. Traditional statistical models have limitations in analyzing hierarchical data, and multilevel models are powerful statistical analysis tools for processing hierarchical data. This method has frequently been used by healthcare researchers overseas, however, it lacks application in China. This paper aimed to introduce the multilevel model and several common application scenarios in medicine policy evaluations. We expected to provide a methodological framework for medicine policy evaluation using regional healthcare big data or hierarchical data.