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 April 16th, 2020. The data items included timing of operation, types of operative procedure, radical resection level of operation, patient’s wish of anus-reserving, types of stomy, date of stoma closure, surgical approaches, extended resection, and type of intersphincteric resection (ISR). The data item interval of stoma closure was added, and the selected data items were statistically analyzed.ResultsThe total number of medical records (data rows) that met the criteria was 11 757, including 2 729 valid data on the timing of operation (23.2%), 11 389 valid data on the types of operative procedure (96.9%), 4 255 valid data on the radical resection level of operation (36.2%), 3 803 valid data on patient’s wish of anus-reserving (32.3%), 4 377 valid data on types of stomy (37.2%), 989 valid data on date of stoma closure (8.4%), 4 418 valid data on surgical approaches (37.6%), 3 941 valid data on extended resection (33.5%), and 1 156 valid data on type of ISR (9.8%). In the timing of operation, the most cases were performed immediately after discovery or neoadjuvant completion (915, 33.5%). In types of operative procedure, ultra low anterior resection (ULAR), right hemicolectomy (RHC), and low anterior resection (LAR) were the most, including 1 986 (17.4%), 1 412 (12.4%), and 1 041 (9.1%) lines. Respectively in the colon and rectal cancer surgery, the proportion of RHC (50.0%) and ULAR (26.0%) was the highest, with 172 (26.1%) and 815 (27.9%) extended resection. In ISR surgery the majority was ISR-2 (741, 64.1%). In radical resection level of operation, the number of R0 was the largest with 2 575 (60.5%) lines. In patient’s wish of anus-reserving, positive and rational were the most with 1 811 (47.6%) and 1 440 (37.9%) lines, respectively. And in types of stomy, there were 2 628 lines (60.0%) without stoma and 1 749 cases (40.0%) with stoma, among which the most lines were right lower ileum stoma (612, 35.0%). The minimum value, maximum value, and median value of interval of stoma closure were 0 d, 2 678 d and 112 d. The linear regression prediction of date of stoma closure by year was \begin{document}${\hat {y}} $\end{document}=9.234 3x+22.394 (R2=0.2928, P=0.07). In the surgical approaches, the majority was standard with 3 182 (72.0%) lines.ConclusionsIn the DACCA, rectal cancer surgery is still the majority, and ULAR is the most type. The application of extended resection in both colon and rectal cancer has important significance. The data related to stoma are diversified and need to be further studied.
ObjectiveTo elaborate constitute, definition, and interpretation of tumor characteristics module of colorectal cancer in the Database from Colorectal Cancer (DACCA) in the West China Hospital.MethodThe article was described in the words.ResultsThe tumor features module of colorectal cancer in the DACCA included the precancerous lesion, cancer family, location of tumor, distance to the dentate line, morphology of tumor, size, position, happening and origination, differentiation, pathology of tumor, Ki-67 protein, obstruction, intussusception, perforation, pain, edema, and hemorrhage. The exact definitions of morphology of tumor, size, position, differentiation, pathology of tumor, Ki-67 protein and complication (included obstruction, intussusception, perforation, pain, edema, and hemorrhage), tag and structure, corrective precautions and update of these columns, and how to use these tumor characteristics in the DACCA when analysis was carried out were described in detail.ConclusionThrough detailed description and specification of current tumor characteristics module of colorectal cancer in DACCA in West China Hospital, it can provide a reference for standardized treatment of colorectal cancer and also provide experiences for the peers who wish to build a colorectal cancer database.
ObjectiveTo explain surgical and medical comorbidities and preoperative physical status of colorectal cancer in detail as well as their tags and structures of Database from Colorectal Cancer (DACCA) in West China Hospital.MethodThe article was described in words.ResultsThe definition to the surgical comorbidities with its related content module, the medical comorbidity with its related content modules, and the preoperative physical status and characteristics of the DACCA in West China Hospital were given. The data label corresponding to each item in the database and the structured way 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 medical and surgical comorbidities and the preoperative physical status 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.
ObjectiveBased on recently update Database from Colorectal Cancer (DACCA), we aimed to analyze the characteristics of in-hospital process management from reginal medical center’s colorectal cancer patients.MethodsWe used Version January 29th, 2019 of DACAA being the analyzing source. The items were included date of first out-patient meeting, admitted date, operative date, discharged date, waiting-time, preoperative staying days, postoperative staying days, hospital staying days, and manage protocol, whose characteristics would be analyzed.ResultsWe left 8 913 lines to be analyzed by filtering DACCA. Useful data lines of first out-patient meeting had 3 915, admitted date had 8 144, operative date had 8 049, and discharged date had 7 958. The average of waiting-time were (9.41±0.43) days, and based on timeline trend for line prediction analyzing, which showed R2=0.101 257, P<0.001. The average of preoperative staying days were (5.41±0.04) days, and based on timeline trend for line prediction analyzing, which showed R2=0.023 671, P<0.001. The average of postoperative staying days were (8.99±0.07) days, and based on timeline trend for line prediction analyzing, which showed R2=0.086 177, P<0.001. The average of hospital staying days were (14.43±0.08) days, and based one timeline trend of line prediction analyzing, which showed R2=0.098 44, P<0.001. Analyzable ERAS data were 2 368 lines in DACCA. Total EARS data in 2 368 lines, there were 108 lines (5%) completed and 2 260 lines (95%) incomplete. Pre/post ERAS data in 2 260 lines, there were 150 lines (7%) completed and 2 110 lines (93%) incomplete. Post ERAS data in 2 110 lines, there were 170 lines (8%) completed and 1 940 lines (92%) incomplete.ConclusionsIn recent 20 years, the regional medical center served in-hospital colorectal cancer patients with decreased preoperative staying days, postoperative staying days, and in-hospital staying days from DACCA analyzing, which could prove the service ability had been in improved. Utilization rate of EARS was increased, and also being the main in-hospital process management.
ObjectiveTo explore the methods of data management and statistical analysis for longitudinal big data collected from mobile health management applications (APP). MethodsThe data management process and statistical analysis method were proposed by summarizing the characteristics of the data from mobile health management APPs. The methods would be clarified by a practical case: an APP recording female menstruation. ResultsThe data from health management APPs belong to longitudinal big data and the original record of the APP should be reprocessed or computed before conducting statistical analysis. A two-step data cleaning procedure was suggested for data management of the original records and reprocessed data, and longitudinal models such as mixed models was recommended for statistical analysis. ConclusionsThe data from health management APPs could be used for medical research via specific data management and statistical analysis after removing suspicious data. Cloud computing could be a viable method to improve efficiency of the big data analysis of health management APPs.
ObjectiveTo investigate the characteristics and corrective strategies of various limb deformities treated by QIN Sihe orthopaedic team in the past 40 years, so as to provide a large sample for understanding the causes, types, and treatment methods of limb deformity and disability in China.MethodsA clinical data of 35 075 cases who were treated by QIN Sihe orthopaedic team between May 1978 and December 2018 was summarized. The age, gender, deformity characteristics, etiological and pathological composition, regional distribution, and surgical methods of the patients were analyzed.ResultsThere were 20 458 males (58.33%) and 14 617 females (41.67%). The age ranged from 1 to 82 years (mean, 20.5 years). The majority people (19 363 cases, 55.20%) were 11-25 years old. Of which, 33 259 cases (94.82%) were operated on lower extremity. The geographical distribution of patients covered 33 regions in China and 12 foreign countries. There were 202 etiologies involved neurological, heredity, metabolism, traumatic sequelae, congenital, vascular, lymphoid, skin, endocrine, iatrogenic, and so on. The disease covered all subsubjects of orthopaedics. The top six deformities secondary to poliomyelitis sequelae, cerebral palsy, traumatic sequelae, spondylolysis sequelae, genu varum and genu valgum, and congenital talipes equinovarus. There were 280 kinds of surgical methods, the majority of which were Achilles tendon lengthening, supracondylar osteotomy, subtalar joint arthrodesis, tibiofibular osteotomy, metatarsal aponeurosis, and Achilles tendon replacement of peroneal longus muscle, etc. Orthopaedic surgery combined with external fixation were applied in 8 702 cases, including Ilizarov fixator in 3 696 cases and Hybrid fixator in 5 006 cases.ConclusionQIN Sihe orthopaedic database with 40 years is the largest one of limb deformity and disability in China. It reflects the etiology, type, population characteristics, surgical methods and strategy of limb disability and deformity which can be treated by orthopaedic surgery. The data needs to be further excavated and deeply studied in future because of its important academic value and historical significance.
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.
ObjectiveTo analyze the follow-up data of colorectal cancer in the Database from Colorectal Cancer (DACCA).MethodsThe information in the Dacca database was screened, and the one whose operative date and follow-up date were not blank in the total data was selected. The follow-up data were analyzed, including length of follow-up, survival outcomes, coping styles (doctors’ attitude and reaction for follow-up), follow-up path (whether to choose out-patient, Wechat, QQ tools, phone call, text message, mobile application, face-to-face), the number of follow-up (the number of out-patient follow-up, the number of telephone follow-up, and the number of follow-up within 5 years).ResultsA total of 6 437 data items were analyzed for colorectal cancer adjuvant follow-up. ① The follow-up period of five years (2004–2015) was 56.6% (3 642/6 437), and the follow-up time was 0–201, 67 (26, 97) months. ② The highest data composition ratio of survival outcomes was “Survival” (79.7%, 4 611/5 787), and in the data with five-year follow-up period (2004–2015), the highest data composition ratio of survival outcomes was “Survival” (75.0%, 2 550/3 401), and the survival rate of the five-year follow-up period in 2008 was the highest (91.4%, 235/257). ③ The highest data composition ratio of the coping styles was the doctors’ active follow-up (76.8%, 2 121/2 762). ④ The highest data composition ratio of the follow-up path was out-patient service (90.6%, 4 236/4 676). ⑤ The highest data composition ratio of the number of out-patient follow-up was conducted by the original surgical team (100%, 4 380/4 380), the specific number was 0–130、5 (2, 10) times. The data composition ratio of telephone follow-up was 86.9% (3 808/4 380) and the specific number was 0–68、0 (0, 1) times. The highest frequency of follow-up was in the first year (89.9%, 3 044/3 386) and the specific number was 0–73、5 (3, 9) times.ConclusionBy expounding the characteristics of the colorectal cancer follow-up from colorectal cancer in DACCA, it provides some references for using big data to determine prognosis.
ObjectiveTo describe the difficulties and quality evaluation of colorectal cancer surgical procedures in the West China Colorectal Cancer Database (DACCA).MethodWe used the form of text description.ResultsThe related content modules of DACCA operation in West China Hospital, included operator, 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, and quality of operation, were elaborated. Then the surgical characteristics were detailed for their definition, label, structure, error correction, and update.ConclusionThrough detailed description and specification of surgical difficulties and quality evaluation of colorectal cancer in DACCA in West China Hospital, it can provide a reference for standardized treatment of colorectal cancer and also provide experiences for the peers who wish to build a colorectal cancer database.