Analysis of the Influence of Network Continuous Care on the Quality of Life of Patients with Coronary Artery Disease (CAD) after PIC.

Studies have shown that most patients after PCI cannot adhere to the cardiac rehabilitation program. The survey found that due to the lack of secondary prevention of cardiac rehabilitation, the phenomenon of drug reduction and withdrawal after PCI is very common after discharge, leading to recurrence of the patient's disease or worsen and repeated hospitalizations, so continuity of care is very important. In this paper, in addition to proposing a network care continuum with artificial intelligence handler in order to improve the healthcare system and provide new ideas for improving the postoperative recovery of CHD patients, we analyze the impact of PCI on the coronary heart disease patients' PCI postoperative quality of life. In the method part, this article introduces the concepts of continuation care and PCI after surgery, introduces the marker delivery algorithm in the field of artificial intelligence, and introduces the SF-36 scale for patient quality of life analysis. This article designs an experiment combining artificial intelligence processors to carry out network continuity care for patients and divides 100 eligible patients into an experimental group and a control group. In the analysis part, the two groups of patients were analyzed in terms of general data comparison, physical function, biochemical indicators, quality of life, and dependence. It can be seen from the experimental analysis that the anxiety and depression of the two groups of subjects have different degrees of decline. The HAMA value of the experimental group is 9.06 ± 0.77, and the HAMD value is 9.18 ± 1.20, which is significantly lower than that of the control group, P < 0.05. It can be seen that the use of network continuation care can reduce the negative emotions of patients more than general care. Through psychological counseling and postoperative follow-up, it can improve the optimism and positive emotions of the patients, reduce the negative emotions of the patients, and improve it to a certain extent.

1. Introduction

Artificial intelligence is an important branch of computer science. It is a fringe subject. It is the intersection of natural science and social science. It is also considered to be one of the three cutting-edge technologies in the 21st century. In the past few years, some computer systems with artificial intelligence have been established. For example, in the medical field, nursing systems and treatment systems using artificial intelligence processors have been developed. People use programs to enable computers to perform some thinking and reasoning, so that they have certain high-level human intelligence such as environmental adaptation, automatic learning, and automatic decision-making. In addition to the application of artificial intelligence to sensory simulation, a more important application is to simulate the thinking and analysis process of the human brain, that is, the application of game and logical reasoning, the sensing and processing of information, and so on [1].

The development of cardiac rehabilitation in Western developed countries has a history of nearly 50 years. After long-term practice, it has fully explained the important role and significance of cardiac rehabilitation after PCI for patients with coronary heart disease. Its main significance is it can greatly reduce the heart rate. Vascular accidents can improve long-term curative effects, reduce medical expenses, reduce the psychological burden of patients, significantly improve the quality of life of patients, improve patients' mobility, achieve the best mental state, and ultimately return to society. All in all, cardiac rehabilitation therapy can effectively help patients with coronary heart disease to recover more effectively after revascularization.

In this regard, scholars at home and abroad have conducted in-depth studies on postoperative recovery and the quality of life of patients. Waltzman and Kelsall introduced that the current cochlear implant (CI) technology has developed and progressed, but programming has not changed to the same degree, and there is still a lack of standardized technology. The purpose of the study is to compare the performance of subjects using experienced clinicians (EC) standard programming methods and FOX-based artificial intelligence algorithms for cochlear implantation subjects. The experiment selected 55 adult patients with more than 3 months of experience using Nucleus 5, 6, Kanso, or 7 series sound processors to perform the CNC words and AzBio sentences in the noise (+10dBSNR) test in a soundproof room and then use the EC program Connect the psychoacoustic battery directly. One month later, the test was repeated using the optimized FOX program, and subjective indicators of patient satisfaction were also measured. The group average results showed that the two programming methods have the same performance (Kruskal-Wallis ANOVA P = 0.934). Although some patients perform better with the FOX method, and some patients perform worse, most patients have the same performance and therefore prefer to use the FOX system. On average, FOX results are the same as those using traditional programming techniques. In addition, the FOX programming method can achieve cross-center standardization and increase the access rights of many beneficiaries. This experiment uses the FOX algorithm to put the cochlear implant into use, but the model design for this algorithm in the experiment is not perfect [2]. Liu et al. believe that patients with multiple traumas can benefit a lot from specialized care. Recognizing the value of bringing this expertise to patients after arriving at the hospital, the role of the trauma response nurse (TRN) was developed. The TRN role aims to provide a full-time nurse for SICU to care for trauma patients who arrive at the emergency department (ED) through treatment. The purpose of integrating the TRN role into the trauma team is to improve quality and safety, as well as communication and collaboration, and to improve the continuity of care. The main responsibility of TRN is to assist clinical interventions, transfer patients from ED to tests and procedures, and receive care through treatment. TRN's other responsibilities include education, community outreach, and performance improvement. TRN now responds to all trauma activations that occur during shifts during workdays. This role improves collaboration between nursing disciplines, improves the overall functions of the trauma team, and improves the safety of trauma patients during transportation. TRN makes a valuable contribution to the educational and publicity mission of the trauma program and ensures that patients receive the highest level of trauma care. In this experiment, the author made a detailed analysis of the prospects of TRN, but lacked a certain theoretical support [3]. MNAAl-Qezweny believes that patients treated with percutaneous coronary intervention (PCI) may be related to type D personality and depression. However, it is not yet clear whether this relationship exists for a long time. The purpose of this study was to investigate the relationship between type D personality at 6 months (baseline) after PCI and depression at 10-year follow-up and to test the relationship between type D personality and anxiety at baseline at 10-year follow-up. The patient completed the type D personality scale (DS14), which measures type D personality at baseline, and the Hospital Anxiety and Depression Scale (HADS), which measures anxiety and depression at baseline. At baseline, the prevalence of type D personality was 25% (135/534). Patients with type D personality are more prone to depression (42%) than those with nontype D personality (9%). The response rate of the 10-year anxiety and depression questionnaire was 75%. During the 10-year follow-up, 31% of patients with type D personality were depressed, while 13% of patients with non-D personality were depressed. After adjustment, the baseline type D personality was still independently associated with depression at 10 years (OR = 3.69; 95% CI [1.89-7.19]). Type D showed a similar association with anxiety at 10 years, although it was reduced (OR = 2.72; 95% CI [1.31-5.63]). During the 10-year follow-up, PCI patients with type D personality increased the risk of depression by 3.69 times and the risk of anxiety by 2.72 times. In this study, the author did a detailed data analysis on the quality of life of patients after surgery, but did not provide corresponding solutions, such as the application of postoperative care [4]. Nieuwenhuijsen et al. and Anderson et al. study the relationship between high need for rehabilitation (NFR) and higher likelihood of depression and draw valuable conclusions [5, 6].

This article combines continuous care with artificial intelligence processors to study the quality of life of patients with coronary heart disease after PCI. First of all, the literature of domestic and foreign scholars on patient quality of life, postoperative recovery, and postoperative care of patients were studied. In the method section, the concepts of continuation care, PCI postoperative, and artificial intelligence processor are introduced. A continuous nursing experiment combining the experimental group and the control group was designed; and the general data comparison, physical function, biochemical indicators, quality of life, and dependence were analyzed. This paper is as groundbreaking as the use of artificial intelligence to the healthcare field, with very long-term implications on patients' postoperative survival.

2. Method of the Influence of Network Continuity Nursing Combined with Artificial Intelligence Processor on the Quality of Life of Patients with Coronary Heart Disease after PCI

2.1. Continuing Care

Nursing continuity model started late in our country. Through literature research, it can be seen that the implementation of follow-up care in my country mainly includes the following three categories: hospital-based care continuity model, community-based care continuity model, and family interaction between hospital and community-continuous care collaboration model.

At present, my country has the most research on the follow-up nursing model initiated by the hospital, the most widely used, and the most complete development of the nursing model. The intervention goals of this model mainly include acute hospitalization and discharge after a period of time, but still have a high level of care. Patients in need are usually divided into two stages, predischarge and postdischarge. Interventions before rejection include providing patients with basic health education, such as medication guidance, nutrition guidance, psychological guidance, and sports rehabilitation. Do a good job in evaluating side effects and risk of readmission, and provide targeted discharge training based on the evaluation results. A continuous care team composed of multidisciplinary professional medical staff will jointly develop personalized professional discharge rehabilitation services for patients according to the actual situation of the patient plan. This program includes regular home monitoring by nurses, telephone monitoring, and communication with other devices to understand and record the patient's physical condition and to provide patient assessment and medical advice; maintaining effective communication with community medical staff, providing professional technical guidance and ongoing collaboration for patients, and conducting technical guidance and risk assessment for community workers, correctly handle emergencies and formulate various emergency plans. The follow-up team conducts patient health education through personalized guidance, WeChat supervision, and questionnaire survey guidance, so that patients with coronary heart disease can obtain professional medical knowledge, determine the correct posture, and conduct medication. Improve medication compliance, develop healthy behaviors, and improve quality of life [7, 8].

2.2. After PCI

PCI, also known as percutaneous coronary intervention (PCI), is a technique that uses percutaneous puncture technology to insert a balloon catheter or use other related devices to relieve coronary artery stenosis or obstruction and rebuild coronary blood flow [9]. The main items include percutaneous transluminal coronary angioplasty, coronary stent implantation, percutaneous transluminal coronary atherectomy, directional atherectomy, atherectomy, atherectomy, and laser angioplasty. Among them, percutaneous coronary stent implantation, as the most important and commonly used method for the treatment of coronary heart disease, can effectively relieve stenosis and blockage in the blood vessels, promote smooth coronary blood circulation, and restore normal blood supply to the myocardium [10].

PCI, as a minimally invasive treatment that can dilate and recanalize the narrowed or blocked lesions, thereby improving myocardial ischemia and hypoxia, has now entered a stage of maturity, stability, and rapid development. This technique has become an important treatment for CHD due to its reliability, definite efficacy, minimally invasive nature, low bleeding, and quick recovery [11]. With the breakthrough of PCI technology, new problems that come with it are inevitable: such as perioperative myocardial injury, ischemia-reperfusion injury, TIMI blood flow < grade 3, stent thrombosis and restenosis, postoperative anxiety, depression, and low quality of life. Anxiety-based psychological disorders caused by psychological stress after PCI are widespread, which affect the quality of life of patients. Figure 1 shows the changes in the state of blood vessels before and after PCI surgery. It can be seen that the operation has dredged the occluded coronary artery lumen. This operation can relieve the patient's angina symptoms, improve the patient's heart function, and prolong their survival [12, 13].

Figure 1

Diagram of blood vessel status before and after PCI (picture from case patient picture).

2.3. Artificial Intelligence Processor

Artificial intelligence is an emerging technological science. It relies on the latest outstanding achievements of natural science and social science to form a new system with intelligence as the core and its own characteristics. Its research and application involve a wide range of fields, such as knowledge representation, search technology, and machine learning [14]. In the medical field, the most commonly used artificial intelligence is an expert system, also known as a knowledge-based system [15]. It is a type of domain knowledge and experience with expert level, the problem-solving ability of human experts, and the use of the rich experience and knowledge of human experts. An intelligent computer program system that simulates complex problems can usually be solved by experts. Expert systems emphasize knowledge rather than methods. When designing, separate knowledge, and other parts from the system, develop knowledge base and reasoning engine based on knowledge representation and knowledge reasoning technology. At present, the existing expert system development tools include EMYCIN, CLIPS, KEE, and OKPS [16]. As shown in Figure 2, it is a framework for artificial intelligence to be used on the network to continue nursing home users.

Figure 2

Home user terminal structure block diagram.

Mark delivery algorithm

The following introduces a label propagation algorithm (Label Propagation algorithm); the training sample is defined as a limited number of labeled samples K the corresponding label class B, unlabeled samples S, and S > >K [17, 18]. The purpose of the tag transfer algorithm is to construct a fully connected graph, where the edge weights represent the similarity between the data y and y:

β stands for the background super parameter, and [Q] represents the pattern of sample resemblance matrix, while the fringe weights will determine the transmission of the stickers.

At the same time, the transition probability matrix P of w × w is defined:

This formula expresses the probability that y gets the mark from y. Define a k × b matrix and s × b matrix, and the nth element of the sum is

Then use a w × b matrix to represent the category matrix of all samples:

From the above formula, it can be seen that the class label of the sample is passed from its neighbors, which means

It can be seen from the above algorithm that the unlabeled sample labeling process starts from the labeled sample and is passed to the adjacent unlabeled samples. The class label of the unlabeled sample is continuously updated in this process. When the class vector no longer changes, the iteration termination condition is reached [19, 20]. In addition, there is a quick way to implement it. First, divide the transition matrix P into 4 submatrices:

This can be rewritten as

For the category matrix of unlabeled samples, each iteration is

When the number of iterations w approaches infinity:

For the transition matrix, from the above formula:

From the matrix multiplication recursive formula:

Therefore, when w⟶∞, (R)f0⟶0. This shows that the initial category f0 of unlabeled samples will not affect the final discrimination result of the algorithm [21]. Reuse the terms and formulas of the infinite geometric sequence to get:

2.4. Evaluation Indicators of Patients' Quality of Life

Quality of life refers to the evaluation of the health status of patients from three aspects: physiological, mental function status, and social function. The world's healthcare service industry has regarded quality of life together with survival rate and other clinical indicators as key indicators for evaluating the effectiveness of treatment [22]. In the history of human medical treatment, with the development of medical technology and medical theory, the medical model is constantly optimized and progressed. From the initial single experience and technology to system science, human beings have organized a set of diseases from disease prevention to disease treatment and then to the complete system of cause summary and treatment evaluation [23]. People continue to eliminate and choose in this system to find the best way to solve human diseases [24]. With the widespread development of percutaneous coronary intervention, the lack of long-term efficacy has attracted the attention of cardiovascular physicians. However, like different medical methods for many diseases, interventional therapy is not the perfect ultimate therapy. While improving the quality of life of patients, there are also potential postoperative risks such as postoperative restenosis, postoperative angina, and postoperative depression [25]. To effectively improve the quality of life of patients after PCI, a more scientific and complete quality of life evaluation system must be established. In the actual clinical treatment process, many simple and easy-to-implement rehabilitation evaluation scales have been widely used by medical workers [26, 27]. Two evaluation scales are introduced here.

As a simple and easy-to-operate health questionnaire, SF-36 comprehensively summarizes the health concepts of body pain, intelligence, energy, and social function. It can be carried out through simple dialogues, making it easy for patients to understand and operate and reflect. Now domestically, the focus of the complex assessment form has been transformed into a simple and easy-to-understand scale, which has been widely accepted by patients, reflecting the characteristics of humanistic care. It is widely used in various aspects of life quality and efficacy evaluation. At present, the quality of life evaluation has been used by medical workers in the rehabilitation treatment of coronary heart disease after PCI [28, 29].

In addition to the SF-36 scale, the Seattle Angina Pectoris Scale (SAQ) is often used in nursing to evaluate the functional status and quality of life of patients before and after treatment. This scale covers five aspects of physical activity limitation, angina stability, frequency of angina pectoris, evaluation of treatment quality, and subjective feelings of disease. There are 19 items in total, with a total score of 100. The higher the score, the patient's life, the better the quality [30].

3. Experiment of Network Continuity Nursing Combined with Artificial Intelligence Processor on the Quality of Life of Patients with Coronary Heart Disease after PCI

3.1. Subjects

A total of 100 patients with coronary heart disease who underwent PCI in the Third Affiliated Hospital of Qiqihar Medical University from May 2020 to May 2021 were selected as the research objects.

3.2. Inclusion Criteria

Patients who were diagnosed with coronary heart disease by coronary angiography and received PCI for the first time

Secondary prevention drugs for coronary heart disease should be used after surgery

Normal thinking, a certain degree of understanding, able to communicate well, and can complete the assessment questionnaire independently or with assistance

Informed consent and voluntary participation in this research

Be able to follow up at any time

3.3. Exclusion Criteria

Heart function III and above

Hemorrhage tendency, severe liver and kidney insufficiency or cirrhosis, untreated or uncontrolled hypertension, diabetes, and other major diseases

Accompanied by neurological or mental illness

Severe infections and malignant tumors

Patients with systemic immune system diseases and connective tissue diseases

3.4. Experimental Method

Grouping method

The coronary heart disease patients were sorted according to the order of admission, and the patients meeting the inclusion criteria were enrolled into the group and were divided into a control group and an intervention group, with 50 people in each group.

(2) Intervention methods

Comparison group was provided with conventional nursing care in the institution. To begin with, when patients are admitted to the hospital, the relevant caregiver will inform relevant kinds of information and provide them with assistance; during hospitalization, regular treatment includes fundamental nursing care, expert nursing care, and health instructions; after patients are discharged from the garden, they will be advised of cautions and followed up frequently; patients are followed up normally.

The experimental group received in-hospital routine nursing and information-based continuous nursing. First, set up a continuous care team after PCI. Before the patient is discharged from the hospital, the team members will teach the patient, including the concept of coronary heart disease, the causes and clinical manifestations, and the knowledge of medication for patients after PCI. Establish a file for the patient: continue the nursing team members to understand the general situation of the patient, the understanding and attitude of the disease and the drug through face-to-face communication with the patient, complete the collection of patient data, gain the trust of the patient, sign the consent form, establish the patient follow-up file, and formulate individualized interventions program. Conduct tele-education after patients are released from the hospital. For the occurrence of patient problems, team participants should timely choose telephone contact visits or home visits or employ an artificial smart processors based information acquisition platform to solve questions and ensure the sustainability and availability of therapeutic interventions. Conduct tele-education after patients are released from the hospital. For the occurrence of patient problems, team participants should timely choose telephone contact visits or home visits or employ an artificial smart processors based information acquisition platform to solve questions and ensure the sustainability and availability of therapeutic interventions.

3.5. Experimental Tools

This experiment uses the SF-36 scale for data analysis. The scale contains 36 items to assess the damage caused by mental or physical health, including 8 areas: the domains are social performance, physical functioning, physical pain, physical functioning, health in general, vitality, mood functioning, and mental health. The fields are graded from 0 to 100 (higher values reflect fewer health issues), and the data are divided into eight areas: physical and mental. The most commonly used questionnaire in the assessment of the health-related quality of life of patients with chronic arthritis is the universal 36-item concise health status questionnaire, which is considered to be the “gold standard” questionnaire. It is a general questionnaire for the assessment of patient health-related quality of life.

4. Impact of Network Continuity Nursing Combined with Artificial Intelligence Processor on the Quality of Life of Patients with Coronary Heart Disease after PCI

4.1. Comparison of the Data of the Two Groups of Patients with Coronary Heart Disease after PCI

This experiment is divided into a control group and an experimental group. The ages of the two groups of experimental subjects were between 30 and 60 years old. Among them, there are 50 cases in the experimental group, including 31 male patients and 19 female patients. There were 50 cases in the control group, 35 cases were male patients, and 15 cases were female patients. The general data comparison of the two groups of experiments is shown in Table 1.

Table 1

Comparison of information between two groups of patients with coronary heart disease.

Item		Test group	Control group	x 2/t	P
Age		41.86 ± 4.9	44 ± 3.2	1.762	0.168
Gender	Male	31 (70.84)	35 (63.58)	1.652	0.176
	Female	19 (27.43)	15 (33.72)
Marital status	Married	35 (82.43)	38 (86.35)	0.323	0.692
	Unmarried	15 (30.22)	12 (29.34)
Employment status	Employed	8 (18.54)	10 (19.86)	0.084	0.937
	Unemployed	42 (91.23)	40 (89.43)
Education level	Junior high school and below	6	9	-0.325	0.792
	High school or technical secondary school	18	23
	Junior college	19	14
	Bachelor degree and above	7	4

It can be seen from Table 1 that there is little difference in the ratio of males to females selected in the two groups of experiments, and most of the 100 patients are male, which conforms to the epidemiological characteristics of coronary heart disease. Among them, the experimental group and the control group accounted for 88% and 82%, respectively, a high school education or greater, showing that the more education, the better the patient's ability to understand and work together.

4.2. Body Function

The functional areas of patients with coronary heart disease after PCI in the experimental group and the conventional nursing group using network continuation care are analyzed. Table 2 shows the results after scoring using the SF-36 scale. It can be seen from the table that compared with the control group, the experimental group has higher scores in terms of role function, cognitive function, social function, and health level than the control group, indicating that this nursing method can improve the patient's various physical functions.

Table 2

Comparison of functional area scores in patients with coronary heart disease.

Item	Test group	Control group	t	P
Physical function	43.78 ± 13.32	48.29 ± 13.87	-2.34	0.1434
Role function	57.85 ± 21.87	54.12 ± 16.34	1.20	0.3921
Emotional function	54.21 ± 12.89	56.72 ± 13.82	-1.39	0.7367
Cognitive function	60.31 ± 17.38	53.72 ± 15.59	2.31	0.0782
Social function	63.26 ± 16.33	53.87 ± 19.67	3.32	0.4628
General health	74.63 ± 13.53	67.29 ± 12.78	3.88	0.0827

In addition to the above body functions, this study also analyzed the heart function. As shown in Figure 3, it can be seen that the heart function of the control group and the experimental group during hospitalization and discharge is similar. In the 1-6 months after discharge, the cardiac function of the two groups of subjects gradually increased, but the upward trend was not parallel. The increase rate of the experimental group is higher than that of the control group, indicating that the continual nursing based on artificial intelligence processor is better than the control group in improving the recovery of heart function in the elderly.

Figure 3

Estimated marginal mean of cardiac function score.

4.3. Comparative Analysis of Biochemical Indicators

As shown in Table 3, before they were treated, there is no significant difference in blood pressure, blood lipids, and fasting glucose and heart rate between the laboratory group and the control group (P > 0.05), and they are comparable. After the PCI procedures, the comparison was not significant between the two experimental groups, and a period of time postoperative care was needed to make further differences.

Table 3

Comparison of biochemical indicators between the two groups before treatment.

Group	Blood pressure (mmHg)	Blood lipids (mmol/L)	Fasting blood glucose (mmol/L)	Heart rate (times/min)
Test group	137.32 ± 11.82	6.01 ± 0.34	7.59 ± 1.98	91.39 ± 9.14
Control group	137.30 ± 14.07	6.07 ± 0.41	7.57 ± 1.93	91.02 ± 8.45
t	-0.128	-0.721	0.014	0.139
P	0.822	0.463	0.918	0.873

It can be seen from Table 4 that 8 weeks after treatment, there were significant differences in heart rate, blood pressure, blood lipids, and fasting blood glucose between the experimental group and the control group (P < 0.05). The blood pressure of the experimental group dropped from 137.32 ± 11.82 to 118.32 ± 11.82, and the heart rate dropped from 91.39 ± 9.14 to 78.82 ± 7.31. The index change range of the control group was small, the blood pressure changed little, from 137.30 ± 14.07 to 129.91 ± 14.07, and the heart rate dropped from 91.02 ± 8.45 to 84.23 ± 8.18. It can be seen that after eight weeks of postoperative recovery, the effect of network continuity nursing combined with artificial intelligence technology is more obvious, which helps the patient's various physiological indicators to return to normal.

Table 4

Comparison of biochemical indicators between the two groups at 8 weeks after treatment.

Group	Blood pressure (mmHg)	Blood lipids (mmol/L)	Fasting blood glucose (mmol/L)	Heart rate (times/min)
Test group	118.32 ± 11.82	3.02 ± 0.34	4.99 ± 0.78	78.82 ± 7.31
Control group	129.91 ± 14.07	5.31 ± 0.37	6.37 ± 1.63	84.23 ± 8.18
t	-4.012	-16.945	-4.782	-3.940
P	0.002	0.021	0.005	0.003

4.4. Quality of Life Analysis

During this research, the Hamilton Anxiety Inventory (HAMA) and the Hamilton Depression Inventory (HAMD) were scored. Both scales reflect patients' negative emotions like nervousness, dejection, and anxiety at the time of the therapy.

It can be seen from Table 5 that before the intervention, there was no significant difference between the HAMA and HAMD values of the two groups of experiments, that is, P > 0.05; after the intervention, the anxiety and depression of the two groups of subjects decreased to varying degrees. The HAMA value of the experimental group was 9.06 ± 0.77, and the HAMD value was 9.18 ± 1.20, which was significantly lower than that of the control group, P < 0.05. It can be seen that the use of network continuation care can reduce the negative emotions of patients more than general care. Through psychological counseling and postoperative follow-up, it can improve the optimism and positive emotions of the patients, reduce the negative emotions of the patients, and improve it to a certain extent.

Table 5

Comparison of the psychological status of the two groups of subjects before and after intervention.

Group	HAMA		HAMD
	Before	After	Before	After
Test group	11.89 ± 1.92	9.06 ± 0.77	13.48 ± 1.65	9.18 ± 1.20
Control group	11.37 ± 2.43	10.78 ± 0.79	13.76 ± 1.87	12.09 ± 1.04
t	-0.298	15.927	-0.426	10.628
P	0.628	0.001	0.647	0.001

As can be seen in Figure 4, the quality of life of patients with coronary heart disease has improved significantly after receiving care. Among them, the patient's physical function, emotional function, and mental health have all improved. Just after the treatment, the effect of the experimental group was better than that of the control group. At three months after the operation, the experimental group, that is, the recovery effect of the continuous care of the network was significantly higher than that of the traditional nursing method, which was very helpful to the improvement of the patient's quality of life.

Figure 4

Before and after treatment for patients with coronary heart disease.

It can be seen from Figure 5 that after the PCI operation, the two groups of patients have significant differences in compliance with several aspects of postoperative recovery. In the experimental group, about 70 patients strictly follow the postoperative recovery program, such as 66% of patients who quit smoking and 52% of the control group. In the experimental group, patients who performed self-test and a balanced diet accounted for 76% and 78%, respectively, while those in the control group accounted for 58% and 62%, respectively. The number of patients followed in various recovery items in the experimental group was significantly higher than that in the control group. As can be shown, the adoption of web-based continuity of care has a clearer monitoring effect on this patient, which makes them and their families realize the significance of medication, balanced diet, regular rest and movement, and follow-up check-ups and appointments; mobilizes the patient's initiative fully; and helps them cultivate the habit of postoperative surgery recovery more, thus better enhancing the patient's living standard.

Figure 5

Comparison of rehabilitation compliance between two groups after intervention.

4.5. Dependency Analysis

As shown in Table 6, the two groups of experimental patients had little difference in their dependence on treatment when they were just discharged from the hospital. Three months after being discharged from the hospital, the degree of dependence of the experimental group decreased significantly, from 32% to 14%, indicating that the continuation of postoperative care can effectively help patients gradually get rid of their dependence on treatment, and rely more on their own activities and review for recovery. Although the dependence of the control group has also declined, the change of dependence before and after is not very obvious, from 34% to 30%.

Table 6

Comparison of the ability of daily living.

Group	n	On discharge		Three months after discharge
		No need to rely on	Need to rely on	No need to rely on	Need to rely on
Test group	50	34	16	43	7
Control group	50	33	17	35	15
x 2		0.083		3.786
P		>0.05		<0.05

5. Conclusion

Coronary heart disease is the disease with the highest fatality rate in my country, which seriously threatens people's health and social development. Although the development of a series of interventional methods has enabled some coronary heart diseases to be treated in a timely and effective manner, the disease still has a high incidence and characteristics of high mortality. This study shows that the implementation of continuous care for patients with coronary heart disease after PCI can improve the quality of life and ability of daily living of patients and control the stability of heart rate. The shortcoming of this article is that due to the limited time and manpower, only the effect of continuing nursing intervention programs and conventional health education is compared, and further comparisons with other intervention programs are needed to analyze the effects of continuous nursing intervention programs in depth; this research is based on the random sampling method and the implementation of intervention in a hospital have limited the promotion and application of the results of this study. It is also necessary to optimize stratified sampling for different levels of hospitals to further understand the network continuous nursing intervention based on artificial intelligence processors. The intervention's effect on post-PCI quality of life in coronary heart disease patients; in other words, this paper only simply evaluates the impacts on self-care and quality of life after sustained infection, and further research is necessary to achieve a more disciplined, sustained, and scientific flow of intervention options that can be applied widely to the discharged patients' treatment.