Clinical trial NCT04967872: Perioperative Management of Risk Factors in the Elderly Patients
Official title: Risk Management and Technical Measures and Evaluation Criteria for the Elderly During Perioperative Period
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Perioperative Cardiavascular Complication
Peroperative Complication
Perioperative Pulmonary Complication
Perioperative Neurological Complication
Keywords: the elderly population
frailty
perioperative visualization
perioperative ultrasound
perioperative monitoring
risk evaluation and prediction
sarcopenia
delirium
acute kidney injury
pneumonia
acute myocardial injury
Lead sponsor: Tongji Hospital
Sponsor class: OTHER
Collaborators: name: Renmin Hospital of Wuhan University
name: Beijing Hospital
name: Chinese Academy of Medical Sciences, Fuwai Hospital
First posted: 2021-07-20
Enrollment: 4782
Sex: ALL
Minimum age (years): 65
Standard ages: OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NON_RANDOMIZED
Intervention model: PARALLEL
Primary purpose: PREVENTION

Brief summary: In 2017, the number of operations on hospitalized patients in China was more than 57 million, of which more than 20 million were performed on elderly patients (≥65 years of age). As of the end of 2017, there were 143 million elderly people over 65 years old in China, of which 26 million people were 80 years old and over, accounting for 1.8% of the country's total population, and this proportion is increasing. More and more elderly patients need surgery. A study showed that compared with the 65-79-year-old population, the probability of myocardial infarction after orthopedic surgery in patients over 80 years of age increased by 2.7 times, the probability of lung infection increased by 3.5 times, and the mortality rate increased by 3.4 times. The inherent risks of surgery and increased postoperative complications in elderly patients are closely related to factors such as senile syndrome.

Geriatric syndrome refers to the deterioration of the function of various organ systems as the age increases, and a series of non-specific symptoms and signs appear in the elderly, including weakness, comorbidities, cognitive dysfunction and so on. These symptoms increase with age, seriously impairing the quality of life of the elderly and increasing their perioperative risk. Taking frailty as an example, the incidence of frailty among the 65-70 years old population is 3.2%, 71-74 years old is 5.3%, 75-79 years old is 9.5%, 80-84 years old is 16.3%, and\> 85 years old is 25.1. %. On the other hand, the physical functions of the elderly are constantly degrading with age. Take skeletal muscle as an example. After the age of 50, the skeletal muscle mass decreases by 1%-2% every year with the increase of age. The chronic muscle loss of people over 60 years old is estimated to be 30%, and the elderly people over 80 years old lose up to 50%. It can be seen that the elderly patients are a special group of elderly patients, which have their particularity compared with the low-age elderly groups. Therefore, the establishment of a perioperative risk warning and control system and technical system for elderly patients to deal with the unpredictable perioperative risks caused by their weakness, comorbidities, and physical hypofunction, and to provide safety guarantees for elderly surgical patients has become an urgent problem for geriatrics.

Detailed description: Enhanced recovery after surgery (ERAS) is based on evidence-based medicine and optimizes the clinical path of perioperative management through the collaboration of multiple departments. The core is patient-centered promotion of rehabilitation. This concept is deeply rooted in the hearts of the people. In this context, the center intends to use the high incidence of hip fractures and lung cancer in elderly patients as a breakthrough, and combine the center's domestic leading visualization technology and artificial intelligence (AI) technology to create a complete perioperative evaluation system for elderly patients to reduce the perioperative risk of elderly patients.

In the context of perioperative risk control, our primary goal is to comprehensively identify potential risk factors through systematic analysis of their relationships with postoperative complications. We meticulously document patients' underlying conditions, comorbidities, laboratory test results, and imaging findings, while also using a variety of scales to perform a preoperative evaluation. These scales include the Activities of Daily Living (Barthel Index), Insomnia Severity Index (ISI), Stop-Bang score, FRAIL scale, Mini Nutritional Assessment (MNA), Mini-Cog for cognitive performance, as well as the Amsterdam Preoperative Anxiety and Information Scale (APAIS) for anxiety assessment and the Geriatric Depression Scale (GDS). Additionally, we employ the ARISCAT (Catalonian Surgical Patients' Pulmonary Risk Assessment) and the Revised Cardiac Risk Index (RCRI) to further delineate surgical risk. During the surgical process, we meticulously record details of the operation and anesthesia, including anesthetic drugs, intraoperative monitoring, and vital signs; postoperatively, we identify cardiovascular, pulmonary, and neurological complications based on established standards. Through this comprehensive approach, we can identify the relevant risk factors present in both the preoperative and intraoperative phases, thereby enabling effective control and management of perioperative risks.

Visualization techniques include visualization of airway tools, ultrasound visualization, and visualization of brain function monitoring, etc., which are widely used in preoperative risk assessment, bedside rapid assessment, airway management, auxiliary vascular puncture, guided regional block anesthesia, postoperative analgesia, etc. Links, and achieved good clinical results. These technologies have their own advantages, but lack systematic integration and targeted optimization. Organically integrate various visualization technologies suitable for elderly patients to create a complete perioperative evaluation system for elderly patients, comprehensive and real-time dynamic evaluation of patients, and realize the perioperative mental, neurological, respiratory, and circulatory functions of elderly patients Precise management reduces the stress and damage of important organs (such as heart, lung, brain, kidney, etc.), achieves the holistic management of elderly patients during the perioperative period, and reduces the risk of elderly patients during the perioperative period.

Artificial intelligence technology can deeply mine medical big data, integrate a large amount of complex data and have powerful comprehensive analysis functions. It is suitable for assisting elderly patients with complex preoperative evaluation, perioperative medical decision-making, and real-time warning of unpredictable adverse events. This technology has been widely used in various medical fields, including tumor imaging diagnosis, skin disease diagnosis, diabetes diagnosis, etc. At present, foreign scholars have combined the relevant clinical characteristics of patients and used artificial intelligence technology to develop an early warning system for intraoperative hypotension, a real-time early warning system for monitoring the death risk of inpatients, and an in-hospital cardiac arrest prediction system. Artificial intelligence is used to comprehensively assess and predict perioperative risks and real-time early warning, which will cover the entire perioperative period of elderly patients and implement effective risk control.

The inherent risks of surgery and postoperative complications of elderly patients increase. To deal with the unpredictable perioperative risks caused by their weakness, comorbidities, and hypofunction, providing safety guarantees for elderly surgical patients has become a major issue in geriatrics. This project uses visualization technology for preoperative evaluation, anesthesia management, bedside real-time monitoring and intervention, etc., to achieve accurate perioperative management of elderly patients and whole-process whole-person management. AI technology is applied to perioperative risk prediction of elderly patients and real-time follow-up risk warning to guide the control of the depth of anesthesia and the maintenance of organ function. The above technologies are organically integrated around the various situations that increase the perioperative risk of elderly patients, and embedded in the closed loop of evaluation-diagnosis-intervention-re-evaluation to create a complete perioperative evaluation system for elderly patients. And through a multi-disciplinary team to optimize the clinical path of perioperative management, to demonstrate the whole-person risk management system for elderly patients during the perioperative period for further promotion.

Eligibility criteria: Inclusion Criteria:

1. selective surgery
2. aged over 65-years-old.

Exclusion Criteria:

1. Participating in other clinical trials within 6 months
2. Patients receiving local anesthesia
3. Cases with unknown outcomes

Primary outcomes:
measure: The incidence of perioperative adverse events in elderly patients
timeFrame: From the beginning of anesthesia induction to 30 days after surgery or discharged of hospital
Secondary outcomes:
Other outcomes:
Locations:
city: Wuhan
country: China
facility: TongjiHospital
Study officials:
References: