To Explore the Application Effect and Value of Evidence-Based Nursing in Patients with Pregnancy-Induced Hypertension Syndrome.

Objective: The objective is to explore the nursing methods of evidence-based nursing in preventing serious complications in patients with pregnancy-induced hypertension.
Methods: A total of 80 patients with pregnancy-induced hypertension from April 2020 to April 2022 were selected and randomly divided into a control group and a research group, with 40 cases in each group. The blood pressure, Self-Efficacy Scale score, Disease Uncertainty Scale score, the incidence of maternal and infant complications, the improvement of mental state, and the patients' satisfaction with the nursing program were observed and compared between the two groups.
Results: Compared with before the intervention, the self-efficacy scores of the two groups were significantly improved, and the blood pressure, disease uncertainty score, SAS, and SDS scores were significantly decreased, and the indicators in the study group were better than those before the intervention. In the control group, the difference was statistically significant (P < 0.05). After the intervention, among the 40 patients in the study group, 10 cases (25.00%) of cesarean section were significantly lower than 19 cases (47.50%) in the control group, and the nursing work satisfaction in the study group was significantly higher than that in the control group (P < 0.05).
Conclusion: The application of evidence-based nursing interventions and smart medical nursing interventions to patients with pregnancy-induced hypertension syndrome has significant effect and can effectively improve the blood pressure control effect of patients during pregnancy.

1. Introduction

Pregnancy-induced hypertension syndrome (pregnancy-induced hypertension for short) is a common pregnancy complication, which is mainly characterized by hypertension, edema, proteinuria, etc. Pregnancy-induced hypertension is a major cause of maternal and perinatal morbidity and mortality and endangers the lives of pregnant women and newborns [1-3]. The reasons for the onset of hypertensive disorders in pregnancy are still unclear. Studies have found that the occurrence of hypertensive disorders in pregnancy is related to prepregnancy body mass, increase in body mass index during pregnancy, pickles in dietary factors, calcium deficiency during pregnancy, parity, age, twin or multiple births, economic status, and other factors which were significantly correlated [4-6]. The severity of hypertensive disorders in pregnancy varies, and it can involve the kidneys and cause renal damage; it can also involve the decidua basalis and cause placental abruption; some patients have HELLP syndrome due to involvement of the liver, and the mortality rate can reach 24%. Headache and convulsions were the first symptoms of involvement of the nervous system and were admitted to hospital; severe patients could involve the heart and induce hypertensive heart disease during pregnancy [7, 8]. Domestic and foreign studies have found that the occurrence of long-term hypertension and cardiovascular disease is closely related to gestational hypertension. In view of the possible short-term and long-term adverse effects of hypertensive disorders during pregnancy, the 2013 edition of the American College of Obstetricians and Gynecologists guidelines pointed out that health education for patients about preeclampsia can help patients seek medical treatment in time when some symptoms and signs appear and improve pregnancy outcomes. Domestic scholars have also devoted themselves to the study of patients' disease cognitive state and health education, hoping that, through these methods, patients can gain more disease-related knowledge and better cooperate with treatment and care.

The concept of smart healthcare originates from the “smart planet” strategy proposed by International Business Machines Corporation (IBM) in 2009, which includes six areas including smart cities and smart healthcare. In 2009, my country summarized smart medical care for the first time; in 2015, Qiu first proposed the concept of smart medical care in my country, and the research of many scholars has provided theoretical guidance for the development of smart medical care “+Artificial Intelligence,” with artificial intelligence as the core and big data as the foundation; applies artificial intelligence technology to make the digital human body and digital medical treatment highly intelligent; builds from the bottom-level gene and middle-level disease data based on big data to the upper-level diagnosis and surgery. It is a new medical system in which people and machines are interconnected, collaborated, and progressed together [9]. Mobile health is a new service model for the development of smart medical care, which includes user self-health management, vital sign monitoring, medical care, etc. In China, “Good Doctor Online” focuses on providing users with an online platform for direct communication with famous doctors and attending doctors and provides users with services such as registration and surgery appointments. “Chunyu Doctor” helps users to realize self-diagnosis and view similar consultation records through the self-examination function. “Dr Clove” is committed to providing users with professional drug information query and auxiliary drug functions and provides a large number of professional medical and health information. “WeDoctor” brings together the number sources of major hospitals and provides users with functions such as online registration and appointment registration. Abroad, Schreier et al. [10] designed a drug management system related to mobile medical, using RFID radio frequency tags and barcode records to identify drug intake. Turner-McGrievy et al. [11] studied the potential benefits of mobile medical applications for self-monitoring of physical activity and diet, and the results showed that mobile medical applications significantly increased users' exercise frequency, users' body mass index decreased, and self-monitoring of weight loss behaviors there are certain benefits. Beratarrechea et al. [12] explored the impact of voice- and text-message mobile medical interventions on chronic disease outcomes. The results suggest that mHealth interventions are cost-effective in improving clinic visits, clinical outcomes, and health-related quality of life. Ding et al. [13] designed an integration scheme of mobile health care and clinical chronic disease management network. The health data recorded in the user's smart device can be shared with multiple medical care teams understanding of both physicians and patients. Tozzi et al. [14] studied the attitudes of family members of patients with genetic diseases towards the use of mobile medical technology, and the results showed that the family members of patients had a positive attitude towards mobile medical technology. Evidence-based nursing (EBN) refers to a nursing team composed of doctors and nurses. By searching related literature and combining practical experience in clinical practice, the problems that need nursing care are determined. Finally, according to the actual condition of the patient, formulate the whole process of developing a highly targeted and optimal nursing plan [15, 16]. Its essence requires nursing staff to carefully and clearly combine patients' wishes and clinical experience with scientific research conclusions in the nursing process, so as to obtain the best nursing plan. Pather [17] and others carried out evidence-based nursing practice of IAD according to the IAD guidelines, which effectively improved the ability of nurses to identify IAD and stage 1 PI and improved the standardization of skin damage assessment and nursing operation of nurses. This study combines evidence-based nursing and smart medical care in patients with pregnancy-induced hypertension. The report is as follows.

2. Materials and Methods

2.1. General Information

A total of 80 patients with pregnancy-induced hypertension from April 2020 to April 2022 were selected and randomly divided into two groups, a control group and a research group, with 40 cases in each. There were 40 cases in the control group, aged 22–36 years, with an average of (28.18 ± 3.44) years; 24–35 gestational weeks, with an average of (28.15 ± 3.39) weeks. The study group consisted of 40 patients, aged 22–37 years, with an average of (28.85 ± 3.62) years; 23–35 gestational weeks, with an average of (28.25 ± 3.31) weeks. Inclusion criteria were the following:

Those who were diagnosed with reference to the “Guidelines for the Diagnosis and Treatment of Hypertensive Diseases in Pregnancy” (2015)

Those who had a singleton pregnancy

Those who had a body mass index between 18.5 and 24

Those with education level above primary school who can cooperate with completing the relevant scale survey

Informed consent research and cooperation with the signatories

Exclusion criteria were the following:

Those with other pregnancy complications or serious diseases of other organs and systems

Those with recent symptoms such as fever and infection

Those with cognitive, communication, and mental disorders

With poor compliance and inability to cooperate with the researcher

3. Method

The control group adopted smart medical care and routine nursing plan: the channels of smart medical platform in symptom management of patients with pregnancy-induced hypertension syndrome are divided into

Follow-up function modules in Internet hospitals based on physical hospitals

For medical staff special applications for interacting with patients, such as Chunyu Doctor, Ping An Good Doctor, and Good Doctor

Establishing WeChat group, QQ group, and other methods to communicate with patients, establish good communication to understand the patient's condition, monitor blood pressure changes, and conduct regular health education

Combined with routine nursing plan, after admission, provide relevant health education and psychological counseling, and timely eliminate the bad state of psychological irritability and depression for patients; explain the precautions and related basic knowledge of pregnancy-induced hypertension to patients in a timely manner; encourage patients to be active with their families in a timely manner. Communicate, let family members understand the severity of PIH in detail as early as possible, and obtain their support; nursing staff should give detailed guidance on the patient's diet, use more light food, and avoid spicy food, so as to ensure that patients eat sufficient amount of protein and fiber-rich foods are added to the body to supplement iron and calcium; nursing staff advise patients to pay more attention to rest to ensure that patients have adequate sleep and promote the recovery of the body.

3.1. Research Group

The smart medical treatment and evidence-based nursing program were adopted, and the smart medical treatment method was the same as that of the control group. Evidence-based nursing program includes the following:

The establishment of evidence-based nursing team: composed of physicians, head nurses, and responsible nurses, all team members have received evidence-based nursing training to deepen their understanding of the purpose and meaning of evidence-based nursing. According to the actual situation of the patient, the scientific theory, research literature, and clinical practice experience are combined to formulate the corresponding nursing intervention plan.

Establishment of evidence-based questions: after the patient is admitted to the hospital, a comprehensive evaluation is carried out, and the patient's situation is investigated through the relevant questionnaire, communication and exchanges with the patient are strengthened, and the individual needs of the patient are understood, so as to establish the corresponding clinical problems to be solved.

Evidence-based support and literature analysis: according to the various evidence-based questions listed, data retrieval was conducted in domestic scientific and technological periodicals such as CNKI, Wanfang, VIP, and other foreign literature databases such as PubMed, Cochrane Library, and other online resources to collect the latest nursing literature. All literature is screened, and evidence-based evidence is graded and studied to support nursing decision making

Evidence-based practice and application:

① Health education: due to the lack of disease-related knowledge, patients have poor awareness of personal health care. Therefore, it is necessary to carry out health education for patients and their families after hospitalization, use plain language to explain the clinical manifestations and related knowledge of pregnancy-induced hypertension syndrome, understand the risk factors and countermeasures of postpartum hemorrhage, and improve pregnancy-induced hypertension syndrome, in addition to cognitive ability of patients with postpartum hemorrhage.

② Psychological care: pregnant women are prone to fear, anxiety, and tension because they are in a special period, especially high-risk pregnant women. Excessive mental stress in patients will produce a series of physiological reactions, interfere with the function of the central nervous system, affect the normal contraction of the uterus, and increase the risk of postpartum hemorrhage. Therefore, nurses should pay attention to the patient's psychological status, patiently listen to the patient's complaints and needs, ease their negative emotions, establish production confidence, and actively seek the cooperation and support of the patient's family, so that the patient can face production with a peaceful mind.

③ Preparation of emergency supplies: postpartum hemorrhage can lead to a rapid decrease in the patient's circulating blood volume, resulting in tissue or cell hypoxia and hemorrhagic shock. If not rescued in time, the patient's life will be endangered. Therefore, nurses need to prepare first aid materials in advance based on the requirements of evidence-based nursing, quickly establish venous access after bleeding is found, keep the airway open and inhale oxygen, use indwelling needles for infusion, and strive for more rescue work for postpartum hemorrhage, along with timely, symptomatic hemostatic treatment for the cause of bleeding.

④ Labor care: closely monitor the patient's vital signs and pay attention to the progress of labor, prevent prolonged labor, pay attention to the timing of episiotomy, assist the mother to deliver the fetus according to the actual situation, and properly dispose of the retained placenta.

⑤ Postpartum care: closely observe the vital signs of patients with postpartum hemorrhage within 2 days after delivery, pay attention to the postpartum hemorrhage, including the color, flow, and coagulation of the bleeding, and regularly check the involution of the uterus. Formulate a reasonable diet plan, strengthen nutritional supplements, and instruct patients to pay attention to genital hygiene to avoid puerperal infection.

3.2. Observation Indicator

Self-efficacy and disease uncertainty: before and after the intervention, two groups of General Self-Efficacy Scale (GSES) [18] and Chinese version of Mishel's uncertainty in illness scale (MUIS) were administered [19]. Evaluation GSES has a total of 10 items, and each item is evaluated on a 0–4-point scale, with a total score of 40 points. The higher the score, the higher the self-efficacy; the MUIS has a total of 25 items, which are evaluated on a 5-point scale, ranging from 25 to 125 points. The higher the level, the more severe the disease uncertainty.

Before and after the intervention, the self-rating anxiety scale (SAS) was used to evaluate the anxiety level of the patients. This table was compiled by William [20] in 1971 to measure the anxiety status and severity of the respondents. The SAS has a total of 20 items, each item corresponds to a symptom, and each item is scored on a scale of 1 to 4 according to the actual feelings of the research subjects in the last month, of which 10 items are scored in reverse order, and the negative items are converted. Then, the cumulative score of each item is the total rough score of anxiety score. Standard score (SAS score) = total gross score × 1.25, and anxiety severity is divided into four grades according to SAS score: anxiety score less than 50 points as no anxiety symptoms, 50–59 points for mild anxiety, 60–69 points for moderate anxiety, and greater than or equal to 70 is classified as severe anxiety. Before the intervention, after the intervention, and 3 months after the intervention, the Self-rating Depression Scale (SDS) was used to evaluate the degree of depression in the patients. The SDS was compiled by William [21] in 1965 and used. Depression status and severity of survey respondents were measured. The scale has 20 items in total, each item corresponds to a symptom and is scored by 1, 2, 3, 4 according to the actual feelings of the research subjects in the last month, of which 10 items are scored in reverse order, and the negative items are scored after conversion. The cumulative score of each item is the total gross score of depression score. Standard score (SDS score) = total gross score × 1.25. The severity of depression is divided into four grades according to the SDS score: depression score less than 53 points as no depressive symptoms, 53–62 points as mild depression, 63–72 points as moderate depression, and greater than 72 was classified as severe depression.

Satisfaction questionnaire is used, including 25 questions covering all aspects from admission to hospital. Each question adopts a 5-point scoring system: very dissatisfied is 0 points, very satisfied is 5 points, the total score is 0–100 points, very satisfied is 85–100 points, satisfied is 70–84, dissatisfied is less than 70 points, and total satisfaction is the sum of very satisfied and satisfied.

The levels of systolic blood pressure and diastolic blood pressure before and after nursing intervention in the two groups were observed and recorded.

The pregnancy outcomes and complications of the two groups were observed.

3.3. Statistical Methods

SPSS 26.0 statistical software was used for data analysis, measurement data was expressed as (‾x ± s), comparison between groups was by t-test, count data was expressed by n, %, and χ2 test was used between groups. The difference was statistically significant at P < 0.05.

4. Results

4.1. Comparison of Blood Pressure between the Two Groups before and after Intervention

Before intervention, there was no significant difference in diastolic blood pressure and systolic blood pressure between the two groups (P > 0.05). After the intervention and before the intervention, the blood pressure of the two groups was significantly lower, and the blood pressure of the study group was significantly lower than that of the control group, and the difference was statistically significant (P < 0.05). See Table 1.

Table 1

Comparison of blood pressure between the two groups before and after intervention (‾x ± s , mmHg).

Item	Systolic blood pressure		Diastolic blood pressure
	Before intervention	After intervention	Before intervention	After intervention
Research group (n = 40)	153.70 ± 4.02	120.93 ± 2.37∗#	92.18 ± 1.63	76.60 ± 1.91#
Control group (n = 40)	152.10 ± 3.99	132.18 ± 2.29∗	92.25 ± 2.39	85.23 ± 2.01∗

Note. Compared with before treatment, ∗P < 0.05; compared with control group, #P < 0.05.

4.2. Comparison of Self-Efficacy and Disease Uncertainty Scores between the Two Groups

Before intervention, there was no significant difference in self-efficacy and disease uncertainty scores between the two groups (P > 0.05) After the intervention and before the intervention, the self-efficacy scores of the two groups were significantly improved, and the disease uncertainty scores were significantly decreased, and the indicators in the study group were better than those in the control group, and the differences were statistically significant (P < 0.05) See Table 2.

Table 2

Comparison of self-efficacy and disease uncertainty scores between the two groups (‾x ± s，score).

Item	GSES		MUIS
	Before intervention	After intervention	Before intervention	After intervention
Research group (n = 40)	17.43 ± 2.60	36.15 ± 2.38∗#	97.05 ± 4.80	56.43 ± 2.90∗#
Control group (n = 40)	18.45 ± 2.50	28.20 ± 2.66∗	98.40 ± 4.79	71.03 ± 2.53∗

Note. Compared with before treatment, ∗P < 0.05; compared with control group, #P < 0.05.

4.3. Comparison of SAS and SDS Scores between the Two Groups

Before intervention, there was no significant difference in SAS and SDS scores between the two groups (P > 0.05). After the intervention and before the intervention, the SAS and SDS scores of the patients in the two groups were significantly decreased, and the indicators in the study group were better than those in the control group, with a statistically significant difference (P < 0.05). See Table 3.

Table 3

Comparison of SAS and SDS scores between the two groups (‾x ± s , score).

Item	SAS		SDS
	Before intervention	After intervention	Before intervention	After intervention
Research group (n = 40)	60.48 ± 5.42	47.70 ± 4.08∗#	58.15 ± 4.03	47.10 ± 4.19∗#
Control group (n = 40)	59.68 ± 5.12	51.73 ± 3.93∗	57.30 ± 4.45	51.05 ± 5.14∗

Note. Compared with before treatment, ∗P < 0.05; compared with control group, #P < 0.05.

4.4. Comparison of Pregnancy Outcomes and Complications between the Two Groups

After intervention, among the 40 patients in the study group, 10 (25.00%) who underwent Cesarean section were significantly lower than 19 (47.50%) in the control group, and the difference was statistically significant (P < 0.05). See Table 4.

Table 4

Comparison of pregnancy outcomes and complications between the two groups (n, %).

Item	Pregnancy outcome		Complications
	Vaginal delivery	Cesarean section	Postpartum hemorrhage	Eclampsia	Neonatal asphyxia
Research group (n = 40)	30(75.00)#	10(25.00)#	1(2.50)	1(2.50)	0(0.00)
Control group (n = 40)	21(52.50)	19(47.50)	3(7.50)	2(5.00)	1(2.50)

Note. Compared with before treatment, ∗P < 0.05; compared with control group, #P < 0.05.

4.5. Comparison of Nursing Satisfaction between the Two Groups

After the intervention, the nursing satisfaction of the observation group (95.00%) was better than that of the control group (77.50%), and the difference was statistically significant (P < 0.05). See Table 5.

Table 5

Comparison of nursing satisfaction between the two groups (n, %).

Item	Dissatisfied	Satisfied	Very satisfied	Total satisfaction
Research group (n = 40)	2(5.00)	4(10.00)	34(85.00)	38(95.00)#
Control group (n = 40)	9(22.50)	10(25.00)	21(52.50)	31(77.50)

Note. Compared with the control group, #P < 0.05.

5. Discussion

Pregnancy-induced hypertension syndrome is a common disease of pregnant women. As the disease progresses, a series of complications can occur and lead to systemic organ failure, which has a great impact on the life safety of mothers and perinatal infants [22, 23]. Due to the pathophysiological characteristics of the disease itself, gestational hypertension has become a high-risk factor for maternal postpartum hemorrhage. Postpartum hemorrhage refers to the amount of vaginal hemorrhage exceeding 500 mL within 24 hours after the delivery of the fetus, which is the primary cause of maternal death [24]. Studies have shown that the causes of postpartum hemorrhage in patients with pregnancy-induced hypertension are closely related to emotional changes, uterine fatigue, and improper disposal of the placenta [25]. Therefore, how to effectively prevent postpartum hemorrhage in patients with pregnancy-induced hypertension syndrome and control work is a critical issue. On April 18, 2018, the state issued the Opinions on Promoting the Development of “Internet + Medical Health,” which effectively regulates the development of “Internet + medical and health” from three aspects: service system, support system, and strengthening industry supervision and security. To meet the growing medical and health needs of the people, many large hospitals are actively building their own smart medical services, providing users with services such as appointment registration, appointment inspections, and inspection results through APPs, WeChat public accounts, etc. and connecting to mobile payment platforms such as WeChat Pay and Alipay, which greatly facilitates users' medical needs. Romero et al. [26] pointed out that mobile health smart medicine has great potential in supporting hypertensive disorders in pregnancy and improving current clinical practice, reporting very positive results in terms of usability and improving maternal health. Jongsma et al. [27] studied the application of mobile medicine to patients with pregnancy-induced hypertension, and the results showed that mobile medical intervention was positively evaluated by patients in monitoring blood pressure during pregnancy. Evidence-based nursing is a new nursing model advocated in recent years. It is based on scientific theory, adopts retrospective analysis method to study clinical data and evidence, and combines the professional skills and clinical experience of medical staff to formulate a medical plan that meets the actual needs of patients. A series of nursing measures is used to solve the problem in time and improve the prognosis of patients [28, 29]. This study combined evidence-based nursing and smart medical care in patients with pregnancy-induced hypertension, aiming to provide data support for the clinical application of a new nursing program combining the two.

In this study, the SAS and SDS scores of the study group after nursing were significantly lower than those of the control group, suggesting that evidence-based nursing can significantly improve negative emotions such as depression and anxiety, which is consistent with the reports of Hirshler et al. [30] and Wasil et al. [31]. Due to the lack of understanding of the condition and the concerns about whether the fetus is developing normally and whether the pregnancy can be delivered smoothly, patients with pregnancy-induced hypertension often cause mood swings, and the blood pressure rises accordingly, which is easy to further aggravate the condition. In this study, the diastolic blood pressure and systolic blood pressure of the patients in the study group after nursing were significantly lower than those in the control group, indicating that, in the process of evidence-based nursing, taking effective communication means for health education and psychological counseling can effectively control blood pressure levels [32]. It can be attributed to the fact that evidence-based nursing can overcome the defects and deficiencies in routine nursing and traditional nursing and provide the best nursing care to patients with PIH in a timely and effective manner, resulting in treatment and optimal care [33]. For this reason, after adopting an evidence-based nursing program on the basis of smart medicine, the blood pressure of patients with PIH was recovered.

In 1981, American nursing scientist Mishell proposed the theory of disease uncertainty [34], pointing out that when patients have unclear diagnosis of disease or do not understand the process of treatment and nursing, they cannot fully understand the severity of disease and cannot fully predict disease progression. When prognosing, it will cause stress to the patient and cannot better promote recovery. In recent years, the uncertainty of disease has been widely used in the study of malignant tumors, perioperative patients, family members of patients, parents of children, and other people with chronic diseases. The uncertainty of disease is affected by many factors. The age, education level, family monthly income, medical payment, etc. may all have an impact on the patient's level of uncertainty about the disease [35]. In this study, after the intervention, the GSES of the study group was higher than that of the control group, and the MUIS score was lower than that of the control group (P < 0.05), suggesting that smart medical treatment combined with evidence-based nursing is more helpful than smart medical treatment combined with routine nursing to improve the prognosis of PIH patients' self-efficacy and reduce their illness uncertainty. After the occurrence of PIH and knowing that drug treatment is required, patients are more worried that the disease and drugs may have adverse effects on the fetus, their sense of self-efficacy decreases, they have a serious sense of uncertainty about the disease, and their cooperation with clinical interventions decreases [36]. In response to this, evidence-based nursing understands the psychological and emotional conditions of patients, conducts psychological interventions in advance, explains relevant health knowledge, comforts and encourages patients, and guides family members to accompany them, which can effectively reduce the psychological pressure of patients, thereby improving self-efficacy and disease. The effect of uncertainty Cesarean section is a commonly used method of termination of pregnancy for patients with pregnancy-induced hypertension syndrome. In this study, the vaginal delivery rate in the study group was significantly higher than that in the control group, indicating that evidence-based nursing interventions can significantly improve the rate of natural childbirth. In addition, this study pointed out that the nursing satisfaction in the research group was significantly higher than that in the control group, but there was no significant difference in the incidence of complications between the two groups (P > 0.05), which may be attributed to the insufficient sample size of this study. In the next stage, this study will expand the sample size, analyze the application effect of evidence-based nursing interventions and smart medical care in patients with pregnancy-induced hypertension syndrome, and provide more data support for their clinical application.

6. Conclusions

In conclusion, for patients with pregnancy-induced hypertension syndrome, the use of evidence-based nursing interventions and smart medical care can improve nursing job satisfaction, effectively improve patients' blood pressure and negative emotions, improve patients' self-efficacy, and reduce disease uncertainty for clinical reference application.