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Neck anastomosis esophagus cancer resection surgery part infection risk predicting scoring and system

A risk prediction, esophageal cancer technology, applied in prediction, complex mathematical operations, medical data mining and other directions, can solve the problem of impact, can not predict infection in advance, achieve high predictive value, easy clinical operation and use, simple calculation Effect

Inactive Publication Date: 2019-05-07
CANCER INST & HOSPITAL CHINESE ACADEMY OF MEDICAL SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

In this study, anastomotic leakage was mostly associated with infection, and more than 80% of patients with surgical site infection were accompanied by anastomotic leakage. Therefore, as a risk factor, it can neither play a role in predicting infection in advance, and it is possible to incorporate this factor into the model. Will affect the analysis of the role of other factors on infection

Method used

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  • Neck anastomosis esophagus cancer resection surgery part infection risk predicting scoring and system
  • Neck anastomosis esophagus cancer resection surgery part infection risk predicting scoring and system
  • Neck anastomosis esophagus cancer resection surgery part infection risk predicting scoring and system

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Experimental program
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Effect test

Embodiment 1

[0031] Clinical data were collected. From January 2010 to May 2015, a total of 711 patients underwent cervical anastomosis esophagectomy in the Department of Thoracic Surgery, Cancer Hospital, Chinese Academy of Medical Sciences, including 569 males and 142 females; the average age was 59 years old. All patients were identified as primary esophageal cancer by two independent case experts, and the TNM staging was based on the 7th edition of the International Classification of Tumor Diseases. This study was approved by the Ethics Committee of the Cancer Hospital. Using the retrospective survey method, fill in the questionnaire item by item according to the patient's electronic medical records, inspection records, inspection records, anesthesia operation records, etc., establish and enter the EPIDATA database, including the patient's age, gender, medical history (with or without underlying diseases) , ASA score, preoperative and postoperative nutritional status, operation time, o...

Embodiment 2

[0035] Effect of surgical site infection on postoperative hospital stay and perioperative mortality

[0036] Among 711 patients undergoing neck anastomosis for esophagectomy, 146 cases had surgical site infection, the incidence rate was 20.53%. Patients with surgical site infection had an average postoperative hospital stay of 31.28 days, while those without infection had an average postoperative hospital stay of 13.32 days (P<0.0001). The postoperative 30-day mortality rate was 4.11% for infected patients and 0.35% for non-infected patients (p=0.0010).

Embodiment 3

[0038]Demographic and clinical characteristics associated with the surgical site

[0039] Among the 711 patients, 569 were male (80.03%), with an average age of 59 years, and the group ≥70 years old had the highest risk of infection (p<0.05). The results of univariate analysis showed that the higher the ASA score, the greater the risk of infection; History, hypertension, and peripheral vascular disease have an increased risk of infection (p<0.05). Since fewer patients (11.25%) received preoperative chemoradiotherapy, the current results do not show that preoperative chemoradiotherapy increases the risk of infection. (Table 2)

[0040] Table 2 Comparison of demographic and clinical characteristics of patients in the two groups

[0041]

[0042]

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Abstract

The invention belongs to the technical field of a surgery part infection risk predicating scoring and a system based on independent danger factors. Particularly the invention relates to a risk predicting evaluation scoring method for neck anastomosis esophagus cancer resection surgery part infection and a system thereof. According to the independent danger factors which are firstly screened, an infection predicting model is established. According to an assignment score which is generated by a formula, the influence of the danger factors to a final result-surgery part infection can be more visually presented, thereby facilitating clinical early prediction and evaluation to possibility of surgery part infection after the surgery. Individualized infection risk evaluation supplies a basis forkey disposition of an infection preventing measure. The content of the invention is not reported in China and other countries. Through data statistics analysis, the independent predicting factors forneck anastomosis esophagus cancer resection surgery part infection are screened. A mathematical model is used for establishing the predicting scoring system for the surgery infection risks, thereby laying a certain basis for individually predicting the surgery part infection, and supplying guidance for clinical early intervention measure application.

Description

technical field [0001] The present application belongs to the technical field of risk prediction score and system for surgical site infection based on multiple factors. In particular, it relates to a prediction score and system for surgical site infection in neck anastomosis for esophagectomy. Background technique [0002] The incidence of esophageal cancer ranks eighth among common malignant tumors, and my country is one of the countries with high incidence and mortality of esophageal cancer. The treatment of esophageal cancer is a comprehensive treatment based on surgery. Surgical site infection is one of the serious complications after esophageal cancer surgery. The occurrence of surgical site infection can prolong the hospital stay of patients, delay the later treatment, and severe organ / space infection , can also lead to organ failure and death. Cervical anastomosis for esophagectomy is the most difficult operation with the highest incidence of complications in esopha...

Claims

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Application Information

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IPC IPC(8): G16H50/70G06Q10/06G06Q10/04G06F17/18
Inventor 尹丽霞陈宝敏薛奇袁启峰许轲高婷
Owner CANCER INST & HOSPITAL CHINESE ACADEMY OF MEDICAL SCI
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