International Journal of Clinical Case Reports 2025, Vol.15 http://medscipublisher.com/index.php/ijccr © 2025 MedSci Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved.
International Journal of Clinical Case Reports 2025, Vol.15 http://medscipublisher.com/index.php/ijccr © 2025 MedSci Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved. MedSci Publisher is an international Open Access publisher specializing in clinical case, clinical medicine, new variations in disease processesregistered at the publishing platform that is operated by Sophia Publishing Group (SPG), founded in British Columbia of Canada. Publisher MedSci Publisher Editedby Editorial Team of International Journal of Clinical Case Reports Email: edit@ijccr.medscipublisher.com Website: http://medscipublisher.com/index.php/ijccr Address: 11388 Stevenston Hwy, PO Box 96016, Richmond, V7A 5J5, British Columbia Canada International Journal of Clinical Case Reports (ISSN 1927-579X) is an open access, peer reviewed journal published online by MedSci Publisher. The journal is considering all the latest and outstanding research articles, letters and reviews in all aspects of clinical case, containing clinical medicine which advance general medical knowledge; the event in the course of observing or treating a patient; new variations in disease processes; as well as the expands the field of clinical relating to case reports. All the articles published in International Journal of Clinical Case Reports are Open Access, and are distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. MedSci Publisher uses CrossCheck service to identify academic plagiarism through the world’s leading plagiarism prevention tool, iParadigms, and to protect the original authors’ copyrights.
International Journal of Clinical Case Reports (online), 2025, Vol. 15, No.2 ISSN 1927-579X http://medscipublisher.com/index.php/ijccr © 2025 MedSci Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved. Latest Content Effect of Compliance with Electrical Stimulation Combined with Biofeedback Therapy on Pelvic Floor Electrophysiology in Primiparous Women Undergoing Natural Delivery Fengxia Xu, Xi Chen , Fangfang Ai International Journal of Clinical Case Reports, 2025, Vol. 15, No. 2, 52-58 A Study on the Application Effect of a Smart Platform-Based Remote Rehabilitation Nursing Model in Postoperative Patients Xiuli Ma, Lingling Qin, Chunyue He, Yeli Huang International Journal of Clinical Case Reports, 2025, Vol. 15, No. 2, 59-67 A Study on the Impact of Community Home-based Care on the Mental Health of Elderly Individuals Living Alone Mingzi Huang, Leiming Shen, Wei Shi, Yeli Huang International Journal of Clinical Case Reports, 2025, Vol. 15, No. 2, 68-78 Comprehensive Nursing Strategies for Stroke Patients ManmanLi International Journal of Clinical Case Reports, 2025, Vol. 15, No. 2, 79-89 Study on Application Effect of Rapid Assessment Tool in Nursing of Patients with Acute Cerebrovascular Accident Zonghong Zhu, Xiaolei Qi, Ranran Wu, Xiaoyan Wang, Hongxia Zhang, Yeli Huang International Journal of Clinical Case Reports, 2025, Vol. 15, No. 2, 90-97
International Journal of Clinical Case Reports, 2025, Vol.15, No.2, 52-58 http://medscipublisher.com/index.php/ijccr 52 Research Report Open Access Effect of Compliance with Electrical Stimulation Combined with Biofeedback Therapy on Pelvic Floor Electrophysiology in Primiparous Women Undergoing Natural Delivery Fengxia Xu, Xi Chen , Fangfang Ai Department of Obstetrics and Gynecology, Xuanwu Hospital, Capital Medical University, Xicheng, 100053, Beijing, China Corresponding author: 343745314@qq.com International Journal of Clinical Case Reports 2025, Vol.15, No.2 doi: 10.5376/ijccr.2025.15.0006 Received: 07 Jan., 2024 Accepted: 19 Feb., 2025 Published: 10 Mar., 2025 Copyright © 2025 Xu et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Xu F.X., Chen X., and Ai F.F., 2025, Effect of compliance with electrical stimulation combined with biofeedback therapy on pelvic floor electrophysiology in primiparous women undergoing natural delivery, International Journal of Clinical Case Reports, 15(2): 52-58 (doi: 10.5376/ijccr.2025.15.0006) Abstract To investigate the effect of electrical stimulation combined with biofeedback treatment compliance on the electrophysiology of pelvic floor muscle in parturients with natural delivery, the data of 184 patients were collected by retrospective case analysis, and the relationship between variables was explored by multiple linear hierarchical regression analysis. There was a significant negative correlation between pregnancy weight gain and pelvic floor electrophysiological (r=-0.367, P=0.000), and there was a significant positive correlation between compliance with electrical stimulation combined with biofeedback treatment and pelvic floor electrophysiological score (r=0.337, P=0.000). Weight gain during pregnancy and compliance of electrical stimulation combined with biofeedback therapy were included in the equation model of influencing factors, and the proportion of variation explanation for the equation model of influencing factors of pelvic floor muscle electrophysiological increased after the addition of compliance as an independent variable. The compliance of electrical stimulation combined with biofeedback therapy can affect the electrophysiological score of pelvic floor muscle of patients. It is suggested to improve the compliance of patients through multiple ways to delay the occurrence and development of pelvic floor dysfunction. Keywords Compliance; Electrical stimulation combined with biofeedback; Parturient primipara; Pelvic floor muscle; Electrophysiology 1 Introduction In the early postpartum period, the sensitivity changes in pelvic floor tissue damage are primarily manifested as alterations in pelvic floor electrophysiology. With the persistence of injury and the lack of timely recovery, typical symptoms of pelvic floor dysfunction (PFD) gradually emerge (Sangsawang, 2014). According to the literature, the incidence of postpartum pelvic floor electrophysiological abnormalities ranges from 47% to 95% (Huang et al., 2018; Sun et al., 2015; Yang et al., 2019). Moreover, changes in postpartum pelvic floor electrophysiology are closely associated with the onset of PFD symptoms such as stress urinary incontinence and pelvic organ prolapse (Zhang et al., 2014). Affected patients are prone to negative emotions and feelings of shame (Wang et al., 2020), experience lower psychological resilience (Dai et al., 2018), and face an increased risk of postpartum depression, significantly impacting their quality of life. Non-surgical interventions, including manual therapy and stimulation or relaxation techniques (Sigurdardottir et al., 2021), are the primary treatment options for early-stage patients. Among these, pelvic floor electrical stimulation combined with biofeedback therapy has been strongly recommended in multiple guidelines as an essential method for postpartum pelvic floor rehabilitation (Okeahialam et al., 2022; Chinese Urological Association Female Urology Group, 2023). This approach facilitates passive contraction of the pelvic floor muscles through electrical stimulation while using sensors to convert muscle activity into visual or auditory signals, making the treatment process more engaging and interactive. Patients can also personalize the electrical stimulation intensity, frequency, and biofeedback training modes based on their pelvic floor muscle condition (e.g., muscle strength and contraction response). Compliance is a key factor in the success of non-surgical pelvic floor muscle therapy (Venegas et al., 2018; Araujo et al., 2020; Reed et al., 2020; Woodburn et al., 2021; Harper et al., 2023). However, no studies to date
International Journal of Clinical Case Reports, 2025, Vol.15, No.2, 52-58 http://medscipublisher.com/index.php/ijccr 53 have specifically examined patient compliance with pelvic floor electrical stimulation combined with biofeedback therapy or its impact on pelvic floor electrophysiology. Therefore, this study employs a retrospective cohort design to investigate patient compliance with this therapy and its effects on pelvic floor electrophysiology. 2 Subjects and Methods 2.1 Study Subjects Patients who visited the Pelvic Floor Rehabilitation Center of a tertiary hospital in Beijing between January 2024 and December 2024 were included in this study. The inclusion criteria were as follows: (1) primiparous women who had undergone natural delivery; (2) full-term singleton pregnancy; (3) age >20 years; (4) within 6 weeks to 6 months postpartum; (5) complete postpartum lochia discharge; and (6) informed consent and voluntary participation in the study. The exclusion criteria included: (1) postpartum hemorrhage; (2) chronic conditions causing sustained intra-abdominal pressure increases, such as chronic cough or constipation; (3) a history of pelvic surgery; and (4) vaginal bleeding. A retrospective analysis was conducted on the basic and clinical information of patients who met the inclusion and exclusion criteria. Initially, 213 primiparous women with natural delivery were identified, and after excluding those with missing data, a total of 184 patients were included in the final analysis. In terms of quality control, training of collection personnel, implementation of two-person check, integrity check, at least 10% of the data every week. When reviewing the records, the records of patients undergoing pelvic floor rehabilitation therapy in the system were first comprehensively searched, and then screened according to the inclusion and exclusion criteria, and the records of serious information missing, non-diagnosis and treatment in our hospital and participation in other clinical trials were excluded to ensure the accuracy and integrity of the data.This study has been approved by the Ethics Committee of Xuanwu Hospital, Capital Medical University (No. [2023] 055). 2.2 Assessment tools 2.2.1 Compliance assessment scale for pelvic floor electrical stimulation combined with biofeedback therapy Based on the definition of compliance proposed by the World Health Organization (WHO) (Burkhart and Sabaté, 2003) and previous research on pelvic floor muscle therapy (Wang and Wu, 2023), this study defined compliance with pelvic floor electrical stimulation combined with biofeedback therapy as the degree to which the frequency, sessions, and execution quality of the therapy aligned with the treatment plan jointly established by the healthcare provider and the patient. Accordingly, a compliance assessment scale for pelvic floor electrical stimulation combined with biofeedback therapy was developed and evaluated by responsible nurses based on patients' actual performance. The scale included the following criteria: Treatment sessions completed according to the agreed plan (fully completed=1 point, not completed=0 points). Treatment frequency according to the agreed plan (fully completed=1 point, not completed=0 points). Execution quality of movements, assessed based on abdominal muscle involvement (<10% involvement=2 points, 10%~30% involvement=1 point, 30% involvement=0 points). Adherence to treatment duration (typically 30 minutes; completed=1 point, not completed=0 points). The total score ranged from 0 to 5, with higher scores indicating better compliance with pelvic floor electrical stimulation combined with biofeedback therapy. To ensure the scientific validity, practicality, and effectiveness of the scale, six experts experienced in pelvic floor rehabilitation reviewed its content completeness, item rationality, scoring criteria, and clinical applicability using a four-point Likert scale (1=completely irrelevant, 5=highly relevant). The average score for all items was 3.833, indicating high content validity. 1.2.2 Pelvic floor electrophysiology assessment scores Before the onset of symptomatic PFD, the primary manifestation of pelvic floor dysfunction is abnormal electromyographic (EMG) signals. Surface electromyography (sEMG) is a widely used clinical method for assessing pelvic floor muscle function, evaluating muscle strength, tone, activation speed, and coordination under
International Journal of Clinical Case Reports, 2025, Vol.15, No.2, 52-58 http://medscipublisher.com/index.php/ijccr 54 different movement patterns. The International Continence Society (ICS) recognizes sEMG as an important indicator for the early diagnosis and prediction of PFD (Halski et al., 2017; Li et al., 2022). This study used the MLDB2 pelvic floor rehabilitation device produced by the Medlander company. The device incorporates the internationally recognized Glazer assessment protocol, which records pelvic floor muscle electrical activity in different fiber groups during pre-resting, fast-twitch, slow-twitch, and post-resting phases using electromyography. It then quantifies the surface EMG values of different pelvic floor muscle fibers to generate a composite score. All patients underwent a surface EMG assessment before and after treatment, with no statistically significant differences in baseline pre-treatment pelvic floor EMG scores. 2.3 Data collection methods Two researchers extracted data from the hospital information system for primiparous women who met the inclusion and exclusion criteria. The collected information included patient age, pregnancy weight gain (kg), perineal tear status, neonatal birth weight (kg), and pelvic floor electrophysiology assessment scores at 6 weeks to 6 months postpartum (both pre-treatment and post-treatment). 2.4 Statistical analysis Statistical analyses were performed using SPSS 22.0 software. Normal continuous variables were expressed as mean ± standard deviation (±s) and analyzed using descriptive statistics. Both compliance scores for pelvic floor therapy and electrophysiology scores were continuous variables that followed a normal distribution, allowing Pearson correlation analysis to be used for correlation assessment. Multivariate linear hierarchical regression analysis was performed to control for confounding factors and accurately determine the independent impact of compliance with pelvic floor electrical stimulation combined with biofeedback therapy on electrophysiology scores. 3 Results and Analysis 3.1 Basic characteristics of the study subjects A total of 184 primiparous women who underwent natural delivery were included in this study. The mean age ranged from 23 to 49 years, with an average of (33.40 ± 4.512) years. The average pregnancy weight gain was (11.522 ± 3.721) kg, and the mean neonatal birth weight was (3.263 ± 0.428) kg. Perineal wound conditions were classified as follows: no perineal tears in 16 cases (8.7%), first-degree perineal tears in 95 cases (51.6%), second-degree perineal tears in 42 cases (22.8%), third-degree perineal tears in 10 cases (5.4%), and episiotomy in 21 cases (11.4%). The mean compliance score for pelvic floor electrical stimulation combined with biofeedback therapy was (2.37 ± 1.377). Among the participants, 13 cases (7.1%) showed complete non-compliance (score=0), 42 cases (22.8%) scored 1 point, 45 cases (24.5%) scored 2 points, 51 cases (27.7%) scored 3 points, 14 cases (7.6%) scored 4 points, and only 19 cases (10.3%) fully adhered to the prescribed therapy. There was no statistically significant difference in baseline pelvic floor electrophysiology scores before treatment among all patients (P>0.05). 3.2 Analysis of differences in pelvic floor electrophysiology scores Since age, pregnancy weight gain, neonatal birth weight, and compliance were continuous variables, Pearson correlation analysis was used to determine their relationship with pelvic floor electrophysiology scores. The results indicated a significant negative correlation between pregnancy weight gain and pelvic floor electrophysiology scores (r=-0.367, P=0.000) and a significant positive correlation between compliance scores and pelvic floor electrophysiology scores (r=0.337, P=0.000). Other variables showed no statistically significant correlation with pelvic floor electrophysiology scores (P > 0.05). A one-way ANOVA was performed to analyze the association between perineal wound conditions and pelvic floor electrophysiology scores, showing no statistically significant difference (F=1.173, P=0.324). 3.3 Multivariate hierarchical linear regression analysis of pelvic floor electrophysiology To evaluate additional potential risk factors, all variables from the univariate analysis were included in a multivariate linear regression model. The pelvic floor electrophysiology score was set as the dependent variable.
International Journal of Clinical Case Reports, 2025, Vol.15, No.2, 52-58 http://medscipublisher.com/index.php/ijccr 55 In the first layer, independent variables included age, pregnancy weight gain, neonatal birth weight, and perineal wound condition. To specifically examine the impact of compliance with pelvic floor electrical stimulation combined with biofeedback therapy, compliance was included as a second-layer independent variable in the regression model. The results showed that pregnancy weight gain and compliance were ultimately included in the regression model as significant influencing factors. After adding compliance as an independent variable, the adjusted R² value of the model increased from 0.099 to 0.193, indicating that the newly added variable (compliance) explained an additional 9.4% of the variance in the dependent variable. The results are presented in Table 1. Table 1 Impact of compliance with electrical stimulation and biofeedback therapy on pelvic floor electrophysiology (n=184) Variable Unstandardized coefficient (B) Standard error Standardized coefficient (β) t-value P-value First Layer Constant 57.121 12.879 - 4.435 0.000 Age 0.169 0.266 0.046 0.636 0.526 Pregnancy Weight Gain 3.984 0.870 0.328 4.578 0.000 Perineal Condition 0.213 1.186 0.014 0.180 0.857 Neonatal Birth Weight -3.030 3.426 -0.071 -0.884 0.378 Second Layer 2) Constant 63.042 12.249 - 5.147 0.000 Age 0.229 0.252 0.062 0.908 0.365 Pregnancy Weight Gain 3.412 0.832 0.281 4.099 0.000 Perineal Condition -0.388 1.129 -0.026 -0.344 0.732 Neonatal Birth Weight 0.480 3.327 0.011 0.144 0.885 Compliance -1.467 0.313 -0.326 -4.690 0.000 Note: First Layer Adjusted R2=0.099, F=6.020, P=0.000; Second Layer Adjusted R2=0.193, F=9.779, P=0.000 4 Discussion 4.1 Poor compliance with pelvic floor electrical stimulation combined with biofeedback therapy The study results showed that the compliance score for pelvic floor electrical stimulation combined with biofeedback therapy ranged from 0 to 5, with a mean score of 2.37 ± 1.377. Only 19 patients (10.3%) fully adhered to the prescribed therapy, indicating poor compliance, which is consistent with previous studies (Zheng, 2023). Possible reasons for this include discomfort during treatment. Electrical stimulation may cause sensations such as soreness and tingling in the pelvic floor muscles, which some patients find intolerable for extended periods, reducing their willingness to continue treatment. Additionally, this therapy requires patients to visit the hospital or rehabilitation center regularly, which may be difficult for those with demanding work schedules or heavy family responsibilities. Another possible reason for poor compliance is a lack of awareness regarding pelvic floor electrophysiological abnormalities (Wu et al., 2019; Sawettikamporn et al., 2022). Some patients may believe that rest and simple self-exercises are sufficient for recovery, neglecting professional treatment and further reducing compliance. The recovery of pelvic floor muscle function requires consistent stimulation and training, and incomplete treatment may lead to inadequate muscle strength improvement and poor muscle coordination. Consequently, symptoms associated with pelvic floor dysfunction, such as urinary incontinence and pelvic organ prolapse, may progress, increasing the complexity and cost of subsequent treatments. To address this issue, it is essential to enhance patient education on pelvic floor electrophysiological abnormalities. Additionally, personalized adjustments to electrical stimulation parameters (e.g., current intensity, frequency, and pulse width) should be made based on individual differences such as pelvic floor electrophysiological status and pain tolerance. This approach can ensure treatment efficacy while reducing discomfort and improving patient tolerance. Furthermore, treatment schedules should be adapted to patients' work and lifestyle commitments. Strategies such as extending treatment hours (e.g., adding morning and evening sessions), offering
International Journal of Clinical Case Reports, 2025, Vol.15, No.2, 52-58 http://medscipublisher.com/index.php/ijccr 56 appointment-based services, and providing online treatment guidance (for applicable home-based training programs) could facilitate patient adherence (Dou et al., 2025; Ren et al., 2024). 4.2 Pregnancy weight gain as a risk factor for pelvic floor electrophysiology scores The study findings indicated that increased pregnancy weight gain was associated with lower pelvic floor electrophysiology scores, which aligns with previous research (Huang et al., 2022). This association may be explained by the sustained pressure exerted on the pelvic floor muscles due to excessive weight gain, leading to prolonged overstretching. Such prolonged overstretching disrupts the structural integrity and elasticity of pelvic floor muscle fibers, impairing muscle contraction function and causing abnormal electrophysiological activity, ultimately reflected as lower scores in electrophysiological assessments. Additionally, hormonal changes during pregnancy influence pelvic floor muscle remodeling. For instance, increased relaxin secretion facilitates pelvic joint relaxation to aid fetal delivery. However, these hormonal changes also impact the metabolic and remodeling processes of pelvic floor tissues (Wang et al., 2022). Under excessive weight gain, pelvic floor muscles not only endure mechanical stress but also undergo structural changes mediated by hormonal fluctuations, further compromising their functional integrity and altering electrophysiological properties, thereby negatively affecting electrophysiology scores. Excessive pregnancy weight gain is also linked to complications such as gestational diabetes and hypertension. These conditions can impact maternal metabolism and blood circulation, indirectly affecting pelvic floor muscle nutrition and neuromuscular regulation. For example, diabetes-related neuropathy may impair nerve innervation of the pelvic floor muscles, disrupting electrical signal conduction and leading to decreased electrophysiological scores. Similarly, hypertension-induced vascular dysfunction may reduce blood perfusion to the pelvic floor muscles, impairing their physiological function and electrical activity. The U.S. Preventive Services Task Force (2021) recommends effective behavioral counseling and interventions for pregnant women, including personalized diet and exercise plans, regular follow-up and monitoring, and multidisciplinary collaboration. Implementing comprehensive pregnancy weight management strategies is crucial for promoting maternal and infant health. 4.3 Compliance with pelvic floor electrical stimulation combined with biofeedback therapy as a protective factor for pelvic floor electrophysiology The multivariate linear regression analysis results demonstrated that compliance with pelvic floor electrical stimulation combined with biofeedback therapy is a significant influencing factor of pelvic floor electrophysiology, independently accounting for 9.4% of the variance. This finding is consistent with previous studies (Bayat et al., 2021; Corona-González et al., 2023), which reported that adherence to pelvic floor muscle training effectively improves pelvic floor function. Good compliance facilitates the repair and regeneration of pelvic floor tissues following injury. Electrical stimulation promotes the proliferation and differentiation of pelvic floor muscle cells, increasing muscle fiber quantity and cross-sectional area, thereby enhancing muscle structure and function. Concurrently, biofeedback training optimizes pelvic floor muscle movement patterns, reducing muscle fatigue and injury while creating a favorable mechanical and physiological environment for tissue repair and regeneration. These mechanisms ultimately improve pelvic floor electrophysiology, leading to higher electrophysiological scores (Jaffar et al., 2022). Pelvic floor training systems include mobile applications, wearable devices, and online health management platforms. However, these e-health systems often suffer from poor usability, unfriendly interfaces, lack of scientific and engaging content, low involvement of healthcare professionals, and the inability to provide timely feedback and guidance on patient-uploaded data, all of which contribute to poor compliance (Latorre et al., 2019). Therefore, there is an urgent need to analyze the strengths and limitations of existing e-health systems in enhancing compliance with pelvic floor training. A comparative assessment of different system types should be
International Journal of Clinical Case Reports, 2025, Vol.15, No.2, 52-58 http://medscipublisher.com/index.php/ijccr 57 conducted to explore ways to optimize these platforms. Potential improvements include integrating artificial intelligence for more precise training guidance, enhancing privacy protection to encourage patient use, and linking these systems with actual healthcare services. Better integration of e-health technologies into pelvic floor health management could significantly improve patient adherence and treatment outcomes. In this study, it was found that there was poor compliance of the combination of pelvic floor myoelectric stimulation and biofeedback therapy in parterients with natural delivery, and the compliance of the treatment was a protective factor of pelvic floor myoelectric physiology, and the pregnancy weight gain was identified as a risk factor of pelvic floor myoelectric physiology score. However, there are some limitations in this study, which did not consider potential confounding factors, such as BMI and previous diseases, etc., which may have an impact on the effect of pelvic floor electrical stimulation combined with biofeedback therapy. Follow-up studies can be further improved. Funding This research was funded by a grant from Beijing Municipal Hospital Research Incubation Program (PG202315). Conflict of Interest Disclosure The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. Reference Araujo C.C., Marques A.D.A., and Juliato C.R., 2020, The adherence of home pelvic floor muscles training using a mobile device application for women with urinary incontinence: a randomized controlled trial, Urogynecology, 26(11): 697-703. https://doi.org/10.1097/SPV.0000000000000670 Bayat M., Eshraghi N., Naeiji Z., and Fathi M., 2021, Evaluation of awareness, adherence, and barriers of pelvic floor muscle training in pregnant women: a cross-sectional study, Urogynecology, 27(1): e122-e126. https://doi.org/10.1097/SPV.0000000000000852 Burkhart P.V., and Sabaté E., 2003, Adherence to long-term therapies: evidence for action, Journal of Nursing Scholarship, 35(3): 207. https://doi.org/10.1111/j.1547-5069.2003.tb00001.x Chinese Urological Association Female Urology Group, 2023, Chinese expert consensus on the diagnosis and treatment of pelvic organ prolapse and stress urinary incontinence, Chinese Journal of Urology, 6: 401-404. Corona-González J.G., Valderrama-Santillán J.J., Sosa-Bustamante G.P., Luna-Anguiano J.L.F., Paque-Bautista C., and González A.P., 2023, Home therapeutic adherence of pelvic floor muscle exercises in urinary incontinence, Revista Medica del Instituto Mexicano del Seguro Social, 61(Suppl 2): S148-S154. Dai B.B., Qiao J.H., Sun F.F., Bo C.L., Ding K.W., Su W., and Xu C.P., 2018, Analysis of psychological resilience level and its influencing factors in patients of postpartum pelvic floor dysfunction, Chinese Journal of Practical Nursing, 34(8): 590-595. Dou L., Wang W., 2025, Effect of pelvic floor electrical stimulation biofeedback combined with proprioceptive training on postpartum pelvic floor dysfunction, Chinese Journal of Family Planning, 33(1): 130-133, 139. Halski T., Ptaszkowski K., Słupska L., Dymarek R., and Paprocka-Borowicz M., 2017, Relationship between lower limb position and pelvic floor muscle surface electromyography activity in menopausal women: a prospective observational study, Clinical Interventions in Aging, 2017: 75-83. https://doi.org/10.2147/CIA.S121467 Harper R.C., Sheppard S., Stewart C., and Clark C.J., 2023, Exploring adherence to pelvic floor muscle training in women using mobile apps: scoping review, JMIR mHealth and uHealth, 11(1): e45947. https://doi.org/10.2196/45947 Huang J.L., Sun Y.F., and Liao L.M., 2022, Effects of body weight management during pregnancy and the main risk factors on postpartum pelvic floor function in overweight and obese women, Maternal and Child Health Care of China, 17: 3138-3141. Huang X.F., Xia H.W., and Wei H.W., 2018, Survey on pelvic floor dysfunction and risk factors analysis of pelvic floor muscle strength abnormalities among postpartum women from six cities in Guangxi, Guangxi Medical Journal, 40(19): 2261-2264, 2274. Jaffar A., Mohd-Sidik S., Foo C.N., Admodisastro N., Abdul Salam S.N., and Ismail N.D., 2022, Improving pelvic floor muscle training adherence among pregnant women: validation study, JMIR Human Factors, 9(1): e30989. https://doi.org/10.2196/30989 Latorre G.F., de Fraga R., Seleme M.R., Mueller C.V., and Berghmans B., 2019, An ideal e-health system for pelvic floor muscle training adherence: systematic review, Neurourology and Urodynamics, 38(1): 63-80. https://doi.org/10.1002/nau.23835
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International Journal of Clinical Case Reports, 2025, Vol.15, No.2, 59-67 http://medscipublisher.com/index.php/ijccr 59 Research Insight Open Access A Study on the Application Effect of a Smart Platform-Based Remote Rehabilitation Nursing Model in Postoperative Patients XiuliMa 1, Lingling Qin 1, Chunyue He 1, Yeli Huang2 1 Heart Center, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, Beijing, China 2 Nursing Department, The Sixth Medical Center, General Hospital of People’s Liberation Army, Beijing 100048, Beijing, China Corresponding author: huangyeli88@163.com International Journal of Clinical Case Reports 2025, Vol.15, No.2 doi: 10.5376/ijccr.2025.15.0007 Received: 17 Jan., 2025 Accepted: 23 Feb., 2025 Published: 20 Mar., 2025 Copyright © 2025 Ma et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Ma X.L., Qin L.L., He C.Y., and Huang Y.L., 2025, A study on the application effect of a smart platform-based remote rehabilitation nursing model in postoperative patients, International Journal of Clinical Case Reports, 15(2): 59-67 (doi: 10.5376/ijccr.2025.15.0007) Abstract With advancements in medical technology, the importance of postoperative rehabilitation nursing has become increasingly evident. Traditional nursing models face limitations, including spatial restrictions, lack of personalization, and low patient adherence, which constrain improvements in rehabilitation outcomes. The remote rehabilitation nursing model based on an intelligent platform offers an innovative solution for postoperative patients, enabling real-time monitoring of health data, personalized nursing guidance, and dynamic adjustments to rehabilitation plans. This study provides a detailed analysis of the current applications of intelligent platforms in rehabilitation nursing, exploring their key functional modules and practical applications in postoperative care. It systematically evaluates the value of intelligent platforms in enhancing patient engagement, improving adherence, and optimizing rehabilitation outcomes. The manuscript further highlights the role shift of healthcare professionals in utilizing intelligent platforms and their training needs to ensure effective implementation of remote rehabilitation nursing. Through case analysis, the study verifies the significant advantages of intelligent platforms in improving postoperative patient outcomes and addresses the challenges faced in promoting this model by proposing targeted solutions. This research provides comprehensive theoretical support and practical guidance for the application of intelligent platforms in postoperative rehabilitation nursing, which is significant for driving innovation and optimization in modern rehabilitation nursing models and contributes to improving the quality of rehabilitation and life for postoperative patients. Keywords Postoperative rehabilitation; Intelligent platform; Remote nursing; Personalized care; Patient adherence 1 Introduction Postoperative rehabilitation nursing is crucial for enhancing patient recovery, reducing complications, and improving overall quality of life after surgery. Traditional nursing models, however, often fall short in addressing the comprehensive needs of postoperative patients. These models typically involve in-person visits and manual monitoring, which can lead to inefficiencies and errors. For instance, traditional methods may result in incorrect patient connections, disorganized patient data, and medication errors, ultimately reducing nursing efficiency and patient outcomes (Duan and Lin, 2022). Additionally, traditional models may not provide the continuous support and personalized care necessary for optimal recovery, leading to prolonged hospital stays and higher rates of postoperative complications (Wang et al., 2023). The integration of intelligent platform technology in healthcare has shown promising results in enhancing the quality and efficiency of medical services. Technologies such as artificial intelligence (AI), big data, and the Internet of Things (IoT) are being increasingly utilized to support remote monitoring and smart assistance in various medical fields. For example, AI-based applications have been used for activity recognition, movement classification, and clinical status prediction, which are essential for remote rehabilitation services (Lv and Yang, 2021). Intelligent medical data analysis technology has also been employed to improve postoperative nursing care by streamlining data management and enhancing nursing efficiency (Zhou et al., 2020). Moreover, mobile phone-based programs and social media platforms like WeChat have been used to deliver multimodal nursing programs, demonstrating significant improvements in patient outcomes and satisfaction (Fan et al., 2023). Remote rehabilitation nursing offers several potential advantages over traditional models, particularly in the context of postoperative recovery. By leveraging intelligent platforms, remote rehabilitation can provide continuous,
International Journal of Clinical Case Reports, 2025, Vol.15, No.2, 59-67 http://medscipublisher.com/index.php/ijccr 60 personalized care that is accessible from the patient's home. This approach can significantly reduce hospital stays, lower the incidence of postoperative complications, and improve patient satisfaction. Remote rehabilitation also allows for better management of postoperative symptoms such as pain, fatigue, and sleep disturbances, thereby enhancing the overall quality of life for patients. Additionally, remote monitoring and smart assistance can ensure timely interventions and support, which are critical for successful recovery. This study evaluated the effectiveness of the intelligent platform-based telerehabilitation care model in postoperative patients. By asting this innovative approach with traditional models of care, to determine its effectiveness in improving patient outcomes, reducing complications and enhancing satisfaction with care. This study has the potential to revolutionize postoperative rehabilitation by providing a more efficient, effective and patient-centered care approach. The findings may pave the way for a wider application of smart platform technologies in healthcare, thereby ultimately improving patient outcomes and making more efficient use of healthcare resources. 2 Overview of the Application of Intelligent Platforms in Remote Rehabilitation Nursing 2.1 Definition of intelligent platforms and their functions in rehabilitation nursing Intelligent platforms in rehabilitation nursing refer to integrated systems that utilize advanced technologies such as artificial intelligence (AI), the Internet of Things (IoT), and machine learning to provide remote, personalized, and efficient rehabilitation services. These platforms are designed to support decentralized models of care, enabling therapeutic interventions to be delivered from a distance. They incorporate various functionalities, including remote monitoring, data analysis, and real-time feedback, to enhance patient outcomes and streamline the rehabilitation process (Mennella et al., 2023). 2.2 Key modules and implementation steps of intelligent platforms in rehabilitation nursing The implementation of intelligent platforms in rehabilitation nursing involves several key modules and steps. The system architecture typically includes wearable sensors and devices that capture real-time data on patient movements and physiological parameters. For instance, platforms like SKYRE use multi-sensor wearable garments to monitor knee rehabilitation exercises (Seibert et al., 2020). The data collected is transmitted to a central server or cloud platform where it is analyzed using machine learning algorithms to assess patient progress and predict optimal rehabilitation settings (Palagin et al., 2022). The platform provides interactive interfaces, such as mobile applications or web portals, for both patients and clinicians to access and manage rehabilitation programs. These interfaces often include features for virtual reality exercises, real-time feedback, and teleconsultations (Tedesco et al., 2022). 2.3 Potential application scenarios and advantages of these platforms in postoperative rehabilitation nursing Intelligent platforms offer numerous potential application scenarios in postoperative rehabilitation nursing. They can be used for remote monitoring of patients recovering from surgeries such as hip or knee replacements, where continuous assessment and timely interventions are crucial for optimal recovery (Gharaei et al., 2021). These platforms enable patients to perform rehabilitation exercises at home while being remotely supervised by healthcare professionals, thus reducing the need for frequent hospital visits and minimizing healthcare costs (Fan, 2022). Additionally, the use of AI and machine learning allows for personalized rehabilitation plans that adapt to the individual needs and progress of each patient, enhancing the effectiveness of the therapy. The integration of IoT and robotics further facilitates advanced rehabilitation techniques, such as the use of exoskeletons for limb rehabilitation, providing more comprehensive and targeted support (Zhao et al., 2020). Overall, intelligent platforms in remote rehabilitation nursing improve patient compliance, satisfaction, and outcomes by offering convenient, accessible, and high-quality care. 3 Role of Intelligent Platforms in Postoperative Rehabilitation Outcomes 3.1 The support and tracking of postoperative recovery progress through systematic health monitoring Intelligent platforms play a crucial role in supporting and tracking postoperative recovery progress through systematic health monitoring. These platforms utilize various technologies such as wearable devices, mobile
International Journal of Clinical Case Reports, 2025, Vol.15, No.2, 59-67 http://medscipublisher.com/index.php/ijccr 61 applications, and telehealth systems to monitor patients' physical activity, adherence to rehabilitation exercises, and overall health status. For instance, commercially available smartphone apps and wearable devices have been shown to effectively monitor physical activity and improve patient engagement following total knee arthroplasty (TKA) (McKeon et al., 2021). Similarly, telerehabilitation systems like ReHub® provide real-time performance feedback and ensure communication between patients and healthcare providers, leading to higher adherence to exercise plans and improved quadriceps strength (Figure 1) (Mennella et al., 2023; Nuevo et al., 2023). These technologies not only facilitate continuous monitoring but also enable healthcare providers to make timely interventions, thereby enhancing the overall recovery process. Figure 1 The patient wears the ReHub® sensor on the tibia in preparation for exercise (Adopted from Nuevo et al., 2023) 3.2 How personalized nursing guidance provided by the platform supports the development of patient rehabilitation plans Personalized nursing guidance provided by intelligent platforms significantly supports the development of patient-specific rehabilitation plans. These platforms often incorporate machine learning algorithms and artificial intelligence to tailor rehabilitation programs based on individual patient data. For example, a nurse-led eHealth cardiac rehabilitation system demonstrated significant improvements in health behaviors, self-efficacy, and quality of life by providing individualized progress monitoring and feedback through a digital platform (Su and Yu, 2021). Additionally, smart web-based platforms can offer real-time assessments of exercise correctness, ensuring that patients perform therapeutic exercises accurately, which is crucial for effective rehabilitation (Constantinescu et al., 2022). The integration of personalized guidance helps in setting realistic goals, tracking progress, and making necessary adjustments to the rehabilitation plan, thereby optimizing patient outcomes (Figure 2) (Nuevo et al., 2023). 3.3 Strategies to enhance patient engagement and improve adherence to rehabilitation Enhancing patient engagement and improving adherence to rehabilitation programs are critical for successful postoperative recovery. Intelligent platforms employ various strategies to achieve these goals. One effective approach is the use of gamification and interactive features that make rehabilitation exercises more engaging and enjoyable for patients. For instance, the ReHub® platform uses interactive telerehabilitation to provide real-time feedback and motivate patients, resulting in higher adherence to exercise plans (Han et al., 2022). Another strategy involves the use of wearable devices paired with mobile applications to facilitate self-directed rehabilitation, which has been shown to be as effective as traditional physical therapy in maintaining postoperative outcomes. Additionally, incorporating social support elements, such as peer influence and group feedback sessions, can further enhance patient motivation and adherence, as demonstrated in a nurse-led eHealth cardiac rehabilitation program (Zhang, 2024). These strategies, combined with continuous monitoring and personalized feedback, create a supportive environment that encourages patients to stay committed to their rehabilitation plans.
International Journal of Clinical Case Reports, 2025, Vol.15, No.2, 59-67 http://medscipublisher.com/index.php/ijccr 62 Figure 2 Patients take exercise with the assistance of an intelligent platform (Adopted from Nuevo et al., 2023) 4 Role and Training of Healthcare Professionals Supported by Intelligent Platforms 4.1 Importance of increasing healthcare professionals' engagement in remote rehabilitation nursing Increasing the engagement of healthcare professionals in remote rehabilitation nursing is crucial for several reasons. Firstly, the growing aging population and the prevalence of non-communicable diseases necessitate innovative approaches to healthcare, including remote rehabilitation (Padilha et al., 2020). Engaging healthcare professionals in these models ensures that patients receive continuous and high-quality care, even outside traditional clinical settings. Additionally, remote rehabilitation models, such as the SMART-system, facilitate a patient-centered approach, which is essential for effective rehabilitation outcomes (Palagin et al., 2022). The integration of digital platforms in nursing education, such as MOOCs, has shown to enhance the self-management intervention skills of nurses, thereby improving patient care. Therefore, increasing engagement in remote rehabilitation nursing not only benefits patients but also enhances the professional development of healthcare providers (Wang and Huang, 2024). 4.2 How effective training and continuing education enhance healthcare professionals' skills Effective training and continuing education are pivotal in enhancing the skills of healthcare professionals, particularly in the context of remote rehabilitation nursing. Virtual reality (VR) technology, for instance, has emerged as a highly effective method for improving nursing professional skills, offering immersive and interactive training experiences (Hong and Wang, 2023). Continuing professional development (CPD) is essential for maintaining and acquiring the necessary knowledge and skills to provide person-centered, safe, and effective care. Factors that optimize the impact of CPD include self-motivation, relevance to practice, and a positive workplace culture (O'Connor et al., 2021). Moreover, the use of virtual patient simulation platforms has been shown to significantly improve the competency levels of healthcare providers, demonstrating the effectiveness of these training tools in real practice scenarios. Thus, ongoing education and training are critical for ensuring that healthcare professionals are well-equipped to deliver high-quality remote rehabilitation services. 4.3 Technical support and tools for healthcare personnel within the platform Technical support and tools are integral components of intelligent platforms that facilitate remote rehabilitation nursing. The SMART-system, for example, provides a comprehensive framework for remote support of rehabilitation activities, incorporating services like UkrVectōrēs and vHealth to support patient-centered care. The use of web-based platforms and social media has also been recognized as valuable tools for professional medical education, offering contemporary information in various formats and enabling rapid dissemination of knowledge (Iancu et al., 2023). Additionally, the integration of digital professionalism training helps healthcare professionals navigate online environments effectively, ensuring appropriate communication and information sharing (King et al., 2020). These technical tools and support systems not only enhance the efficiency of remote rehabilitation services but also contribute to the continuous professional development of healthcare providers.
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