Applying Object Detection and Large Language Model to Establish a Smart Telemedicine Diagnosis System with Chatbot: A Case Study of Pressure Injuries Diagnosis System.

Background: The scarcity of medical resources and personnel has worsened due to COVID-19. Telemedicine faces challenges in assessing wounds without physical examination. Evaluating pressure injuries is time consuming, energy intensive, and inconsistent. Most of today's telemedicine platforms utilize graphical user interfaces with complex operational procedures and limited channels for information dissemination. The study aims to establish a smart telemedicine diagnosis system based on YOLOv7 and large language model. Methods: The YOLOv7 model is trained using a clinical data set, with data augmentation techniques employed to enhance the data set to identify six types of pressure injury images. The established system features a front-end interface that includes responsive web design and a chatbot with ChatGPT, and it is integrated with a database for personal information management. Results: This research provides a practical pressure injury staging classification model with an average F1 score of 0.9238. The system remotely provides real-time accurate diagnoses and prescriptions, guiding patients to seek various medical help levels based on symptom severity. Conclusions: This study establishes a smart telemedicine auxiliary diagnosis system based on the YOLOv7 model, which possesses capabilities for classification and real-time detection. During teleconsultations, it provides immediate and accurate diagnostic information and prescription recommendations and seeks various medical assistance based on the severity of symptoms. Through the setup of a chatbot with ChatGPT, different users can quickly achieve their respective objectives.

Risk Prediction Model for Chronic Kidney Disease in Thailand Using Artificial Intelligence and SHAP.

Chronic kidney disease (CKD) is a multifactorial, complex condition that requires proper management to slow its progression. In Thailand, 11.6 million people (17.5%) have CKD, with 5.7 million (8.6%) in the advanced stages and >100,000 requiring hemodialysis (2020 report). This study aimed to develop a risk prediction model for CKD in Thailand. Data from 17,100 patients were collected to screen for 14 independent variables selected as risk factors, using the IBK, Random Tree, Decision Table, J48, and Random Forest models to train the predictive models. In addition, we address the unbalanced category issue using the synthetic minority oversampling technique (SMOTE). The indicators of performance include classification accuracy, sensitivity, specificity, and precision. This study achieved an accuracy rate of 92.1% with the top-performing Random Forest model. Moreover, our empirical findings substantiate previous research through highlighting the significance of serum albumin, blood urea nitrogen, age, direct bilirubin, and glucose. Furthermore, this study used the SHapley Additive exPlanations approach to analyze the attributes of the top six critical factors and then extended the comparison to include dual-attribute factors. Finally, our proposed machine learning technique can be used to evaluate the effectiveness of these risk factors and assist in the development of future personalized treatment.

A novel therapeutic approach for endometriosis using adipose-derived stem cell-derived conditioned medium- A new hope for endometriotic patients in improving fertility.

Introduction: Endometriosis is defined as the growth of endometrial glands and stromal cells in a heterotopic location with immune dysregulation. It usually leads to chronic pelvic pain and subfertility. Although various treatments are available, the recurrence rate remains high. Adipose tissue is an abundant source of multipotent mesenchymal adipose-derived stem cells (ADSCs). ADSCs display effects on not only tissue regeneration, but also immune regulation. Thus, the current study aims to test the effects of ADSCs on the growth of endometriosis. Methods: ADSCs isolated from lipoaspiration-generated adipose tissue and their conditioned medium (ADSC-CM) were subjected to quality validation, including karyotyping as well as growth promotion and sterility tests for microbial contamination under Good Tissue Practice and Good Manufacturing Practice regulations. An autologous endometriosis mouse model was established by suturing endometrial tissue to peritoneal wall followed by treating with DMEM/F12 medium, ADSC-CM, ADSCs or ADSC-CM+ADSCs for 28 days. The area of endometriotic cysts and the degree of pelvic adhesion were measured. ICAM-1, VEGF and caspase 3 expression was assessed by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and immunohistochemistry. Moreover, the mice were allowed to mate and deliver. The pregnancy outcomes were recorded. The ADSC-CM was subjected to proteomics analysis with further data mining with Ingenuity Pathway Analysis (IPA). Results: Both ADSC-CM and ADSCs passed quality validation. ADSC-CM reduced the area of endometriotic cysts. The inhibition by ADSC-CM was obliterated by adding ADSCs. The presence of ADSCs with or without ADSC-CM increased the peritoneal adhesion. ADSC-CM inhibited ICAM-1 and VEGF mRNA and protein expression, whereas the addition of ADSCs not only did not inhibit by itself, but also blocked the inhibition by ADSC-CM. The resorption rate was reduced by ADSC-CM. The number of live birth/dam and the survival rate of pup at 1 week-old were both increased by ADSC-CM in mice with endometriosis. IPA demonstrated that PTX3 was potentially critical for the inhibition of endometriosis by ADSC-CM due to its anti-inflammatory and antiangiogenic properties as well as its importance in implantation. Conclusion: ADSC-CM inhibited endometriosis development and improved pregnancy outcomes in mice. Potential translation to clinical treatment for human endometriosis is expected.

Plasma levels and tissue expression of liver-type fatty acid-binding protein in patients with breast cancer.

BACKGROUND: Liver-type fatty acid-binding protein (L-FABP) is widely expressed in hepatocytes and plays a role in lipid metabolism. It has been demonstrated to be overexpressed in different types of cancer; however, few studies have investigated the association between L-FABP and breast cancer. The aim of this study was to assess the association between plasma concentrations of L-FABP in breast cancer patients and the expression of L-FABP in breast cancer tissue. METHOD: A total of 196 patients with breast cancer and 57 age-matched control subjects were studied. Plasma L-FABP concentrations were measured using ELISA in both groups. The expression of L-FABP in breast cancer tissue was examined using immunohistochemistry. RESULT: The patients had higher plasma L-FABP levels than the controls (7.6 ng/mL (interquartile range 5.2-12.1) vs. 6.3 ng/mL (interquartile range 5.3-8.5), p = 0.008). Multiple logistic regression analysis showed an independent association between L-FABP and breast cancer, even after adjusting for known biomarkers. Moreover, the rates of pathologic stage T2+T3+T4, clinical stage III, positive HER-2 receptor status, and negative estrogen receptor status were significantly higher in the patients with an L-FABP level greater than the median. Furthermore, the L-FABP level gradually increased with the increasing stage. In addition, L-FABP was detected in the cytoplasm, nuclear, or both cytoplasm and nuclear of all breast cancer tissue examined, not in the normal tissue. CONCLUSIONS: Plasma L-FABP levels were significantly higher in the patients with breast cancer than in the controls. In addition, L-FABP was expressed in breast cancer tissue, which suggests that L-FABP may be involved in the pathogenesis of breast cancer.

Neuroprotective Effect of Abelmoschus manihot Flower Extracts against the H2O2-Induced Cytotoxicity, Oxidative Stress and Inflammation in PC12 Cells.

The progression of neurodegenerative diseases is associated with oxidative stress and inflammatory responses. Abelmoschus manihot L. flower (AMf) has been shown to possess excellent antioxidant and anti-inflammatory activities. This study investigated the protective effect of ethanolic extract (AME), water extract (AMW) and supercritical extract (AMS) of AMf on PC12 neuronal cells under hydrogen peroxide (H2O2) stimulation. This study also explored the molecular mechanism underlying the protective effect of AME, which was the best among the three extracts. The experimental results showed that even at a concentration of 500 µg/mL, neither AME nor AMW showed toxic effects on PC12 cells, while AMS caused about 10% cell death. AME has the most protective effect on apoptosis of PC12 cells stimulated with 0.5 mM H2O2. This is evident by the finding when PC12 cells were treated with 500 µg/mL AME; the viability was restored from 58.7% to 80.6% in the Treatment mode (p < 0.001) and from 59.1% to 98.1% in the Prevention mode (p < 0.001). Under the stimulation of H2O2, AME significantly up-regulated the expression of antioxidant enzymes, such as catalase, glutathione peroxidase and superoxide dismutase; promoted the production of the intracellular antioxidant; reduced glutathione; and reduced ROS generation in PC12 cells. When the acute inflammation was induced under the H2O2 stimulation, AME significantly down-regulated the pro-inflammatory cytokines and mediators (e.g., TNF-α, IL-1ß, IL-6, COX-2 and iNOS). AME pretreatment could also greatly promote the production of nucleotide excision repair (NER)-related proteins, which were down-regulated by H2O2. This finding indicates that AME could repair DNA damage caused by oxidative stress. Results from this study demonstrate that AME has the potential to delay the onset and progression of oxidative stress-induced neurodegenerative diseases.

Enhanced Authenticated Key Agreement for Surgical Applications in a Tactile Internet Environment.

The Tactile Internet enables physical touch to be transmitted over the Internet. In the context of electronic medicine, an authenticated key agreement for the Tactile Internet allows surgeons to perform operations via robotic systems and receive tactile feedback from remote patients. The fifth generation of networks has completely changed the network space and has increased the efficiency of the Tactile Internet with its ultra-low latency, high data rates, and reliable connectivity. However, inappropriate and insecure authentication key agreements for the Tactile Internet may cause misjudgment and improper operation by medical staff, endangering the life of patients. In 2021, Kamil et al. developed a novel and lightweight authenticated key agreement scheme that is suitable for remote surgery applications in the Tactile Internet environment. However, their scheme directly encrypts communication messages with constant secret keys and directly stores secret keys in the verifier table, making the scheme vulnerable to possible attacks. Therefore, in this investigation, we discuss the limitations of the scheme proposed by Kamil scheme and present an enhanced scheme. The enhanced scheme is developed using a one-time key to protect communication messages, whereas the verifier table is protected with a secret gateway key to mitigate the mentioned limitations. The enhanced scheme is proven secure against possible attacks, providing more security functionalities than similar schemes and retaining a lightweight computational cost.

Big Data, Decision Models, and Public Health.

As the digital era unfolds, the volume and velocity of environmental, population, and public health data are rapidly increasing [...].

Suppressive Effects of Siegesbeckia orientalis Ethanolic Extract on Proliferation and Migration of Hepatocellular Carcinoma Cells through Promoting Oxidative Stress, Apoptosis and Inflammatory Responses.

Previous studies have demonstrated that Siegesbeckia orientalis (SO) has a suppressive effect on the growth and migration of endometrial and cervical cancer cells. The present study examined the effect of SO ethanolic extract (SOE) on the proliferation and migration of hepatocellular carcinoma (HCC) and examined the effects of SOE on non-cancerous cells using HaCaT keratinocytes as a model. The SOE effectively inhibited the proliferation of Hepa1-6 (IC50 = 282.4 µg/mL) and HepG2 (IC50 = 344.3 µg/mL) hepatoma cells, whereas it has less cytotoxic effect on HaCaT cells (IC50 = 892.4 µg/mL). The SOE treatment increased the generation of ROS in HCC, but decreased the expression of antioxidant enzymes such as superoxide dismutase, glutathione peroxidase and catalase. In contrast, it reduced intracellular ROS formation and upregulated the expression of the related antioxidant enzymes in the H2O2-stimulated HaCaT cells. The SOE intervention also down-regulated the anti-apoptotic Bcl-2 and the migration-related proteins including matrix metalloproteinases (MMPs) and ß-catenin in the HCC, suggesting that SOE could promote HCC apoptosis and inhibit HCC migration. On the contrary, it reduced apoptosis and promoted the migration of the keratinocytes. Additionally, the SOE treatment significantly up-regulated the pro-inflammatory cytokines, including TNF-α, IL-6 and IL-1ß, in Hepa1-6 and HepG2 cells. Conversely, it significantly decreased the expression of these cytokines in the H2O2-induced HaCaT cells. These findings indicated that SOE treatment can delay the progression of HCC by increasing oxidative stress, promoting inflammatory response, inducing cancer cell apoptosis and inhibiting their migration. It also has protective effects from pro-oxidant H2O2 in non-cancerous cells. Therefore, SOE may provide a potential treatment for liver cancer.

The three-year evolution of overactive bladder syndrome in community-dwelling female residents aged 40 years and above.

OBJECTIVE: In this 3-year longitudinal cohort study, we aimed to evaluate the evolution of overactive bladder in female community residents aged 40 years and above in central Taiwan and identify its risk factors. MATERIALS AND METHODS: Female community residents aged 40 years and above were invited to participate in this study and fill out a yearly Overactive Bladder Symptom Score (OABSS) questionnaire over a 3-year period. A woman was defined to have OAB if the total OABSS was ≧4 and urgency score was ≧2. At the end of the third year, the incidence, remission, persistence, and relapse of OAB in these community residents were calculated. A novel statistical analysis technique, machine learning with data mining, was applied to examine its use in this field. Five machine learning models were used to predict the risk factors associated with persistent OAB and the results were compared with the conventional logistic regression model. RESULTS: In total, 1469 female residents were included in the first year and 1290 (87.8%) women completed the questionnaires for all 3 years. The prevalence of OAB was 20.2% (n = 260). The second- and third-year incidence rates of OAB were 13.5% and 7.1%. The remission rates were 39.6% and 44.3%. Twenty-two percent of the women reported relapse of OAB in the third year. The two-year OAB persistence rate was 43.8%. For the prediction of risk factors for persistent OAB, the multivariable logistic regression model had better predictive accuracy (AUC = 0.664) than the five machine learning models. Age â‰§ 60 was associated with persistent OAB (OR 2.8; 95% CI: 1.34-5.89, P = 0.002). CONCLUSION: The yearly incidence, remission, and persistence rates of OAB were high in female community residents aged 40 years and above in central Taiwan. Older women had a higher risk of persistent OAB symptoms in this 3-year longitudinal cohort study.

Effects of Abelmoschus manihot Flower Extract on Enhancing Sexual Arousal and Reproductive Performance in Zebrafish.

The flower of Abelmoschus manihot L. is mainly used for the treatment of chronic kidney diseases, and has been reported to have bioactivities such as antioxidant, anti-inflammatory, antiviral, and antidepressant activities. This study used wild-type adult zebrafish as an animal model to elucidate the potential bioactivity of A. manihot flower ethanol extract (AME) in enhancing their sexual and reproductive functions. Zebrafish were fed AME twice a day at doses of 0.2%, 1%, and 10% for 28 days, and were then given the normal feed for an additional 14 days. The hormone 17-ß estradiol was used as the positive control. Sexual behavioral parameters such as the number of times males chased female fish, the production of fertilized eggs, and the hatching rate of the fertilized eggs were recorded at days 0.33, 7, 14, 21, 28, and 42. The expression levels of sex-related genes­including lhcgr, ar, cyp19a1a, and cyp19a1b­were also examined. The results showed that the chasing number, fertilized egg production, and hatching rate were all increased with the increase in the AME treatment dose and treatment time. After feeding with 1% and 10% AME for 28 days, the chasing number in the treated group as compared to the control group increased by 1.52 times and 1.64 times, respectively; the yield of fertilized eggs increased by 1.59 times and 2.31 times, respectively; and the hatching rate increased by 1.26 times and 1.69 times, respectively. All three parameters exhibited strong linear correlations with one another (p < 0.001). The expression of all four genes was also upregulated with increasing AME dose and treatment duration. When feeding with 0.2%, 1%, and 10% AME for 28 days, the four sex-related genes were upregulated at ranges of 1.79−2.08-fold, 2.74−3.73-fold, and 3.30−4.66-fold, respectively. Furthermore, the effect of AME was persistent, as the promotion effect continued after the treatment was stopped for at least two weeks. The present findings suggest that AME can enhance the endocrine system and may improve libido and reproductive performance in zebrafish.

Combinatory effects of current regimens and Guizhi Fuling Wan on the development of endometriosis.

OBJECTIVE: Endometriosis, defined as the growth of endometrial glands and stromal cells in a heterotopic location under the cyclic influence of ovarian hormones, is a common gynecological disorder manifested by chronic pelvic pain and infertility. In traditional Chinese medicine, endometriosis is characterized by stagnation of vital energy (qi) and blood stasis. Guizhi Fuling Wan (GFW) was first described in Chinese canonical medicine to treat disorders associated with stagnation of qi and blood stasis, including endometriosis. Therefore, the current study aimed to test the effects of combining GFW with western medicine on the suppression of endometriosis. MATERIALS AND METHODS: Endometriosis was generated by suturing endometrial tissue on the peritoneal wall of C57BL/6JNarl mice. The mice were subsequently treated with either GFW or current hormonal therapies or in combination for 28 days. RESULTS: Endometriosis development was inhibited by GFW, Gestrinone, Visanne, GFW + Gestrinone or GFW + medroxyprogesterone acetate (MPA). The expression of intercellular adhesion molecule 1 (ICAM-1) was inhibited by GFW, Gestrinone, MPA, Visanne, GFW + Gestrinone, GFW + MPA and GFW + Visanne. Vascular endothelial growth factor (VEGF) expression was inhibited by GFW, Gestrinone, Visanne, GFW + Gestrinone and GFW + MPA. Both ICAM-1- and VEGF-reducing effects of GFW were attenuated by western medicines. Administration of GFW, MPA, Visanne, GFW + MPA and GFW + Visanne also correspondingly reduced macrophage population in peritoneal fluid. GFW, MPA, Visanne, GFW + MPA and GFW + Visanne enhanced B-cell population in peritoneal fluid. CONCLUSION: The current study reveals the therapeutic effects of GFW on endometriosis. However, the combination of GFW and current hormonal therapies potentially impedes the efficacy of each individual agent in treating endometriosis.

Associations between Sex and Risk Factors for Predicting Chronic Kidney Disease.

Gender is an important risk factor in predicting chronic kidney disease (CKD); however, it is under-researched. The purpose of this study was to examine whether gender differences affect the risk factors of early CKD prediction. This study used data from 19,270 adult health screenings, including 5101 with CKD, to screen for 11 independent variables selected as risk factors and to test for the significant effects of statistical Chi-square test variables, using seven machine learning techniques to train the predictive models. Performance indicators included classification accuracy, sensitivity, specificity, and precision. Unbalanced category issues were addressed using three extraction methods: manual sampling, the synthetic minority oversampling technique, and SpreadSubsample. The Chi-square test revealed statistically significant results (p < 0.001) for gender, age, red blood cell count in urine, urine protein (PRO) content, and the PRO-to-urinary creatinine ratio. In terms of classifier prediction performance, the manual extraction method, logistic regression, exhibited the highest average prediction accuracy rate (0.8053) for men, whereas the manual extraction method, linear discriminant analysis, demonstrated the highest average prediction accuracy rate (0.8485) for women. The clinical features of a normal or abnormal PRO-to-urinary creatinine ratio indicated that PRO ratio, age, and urine red blood cell count are the most important risk factors with which to predict CKD in both genders. As a result, this study proposes a prediction model with acceptable prediction accuracy. The model supports doctors in diagnosis and treatment and achieves the goal of early detection and treatment. Based on the evidence-based medicine, machine learning methods are used to develop predictive model in this study. The model has proven to support the prediction of early clinical risk of CKD as much as possible to improve the efficacy and quality of clinical decision making.

Predicting the Risk Factors of Second Primary Cancer in Patients with Hepatocellular Carcinoma.

Screening for cancer and improved treatments have not only improved treatment outcomes and patient survival but have also led to an increase in the number of second primary cancers (SPCs). Hepatocellular carcinoma has been a common occurrence in Taiwan over the past decade. The mortality rate is second only to malignant tumors of lung cancer, and it also represents the fourth highest cancer medical expenditure. This study aimed to use machine learning to identify the risk factors for Hepatocellular carcinoma survivors. Of 378,445 datasets, including 15,251 from patients with SPCs, were collected; 18 predictive variables were considered risk factors for SPCs based on the physician panel discussion. The machine learning techniques employed included support vector machine, C5 decision tree, and random forest. SMOTE (Synthetic Minority Oversampling Technique) sampling method was used to resolve the imbalance problem. The results showed that the top 5 risk factors for SPCs were tumor size, clinical stage, surgery, total bilirubin, and BCLC Stage. The support vector machine method had the highest predicted accuracy (0.7673). The risk factors extracted from the classification models and association rules will be used to provide valuable information for HCC therapy.

Developing a Stacked Ensemble-Based Classification Scheme to Predict Second Primary Cancers in Head and Neck Cancer Survivors.

Despite a considerable expansion in the present therapeutic repertoire for other malignancy managements, mortality from head and neck cancer (HNC) has not significantly improved in recent decades. Moreover, the second primary cancer (SPC) diagnoses increased in patients with HNC, but studies providing evidence to support SPCs prediction in HNC are lacking. Several base classifiers are integrated forming an ensemble meta-classifier using a stacked ensemble method to predict SPCs and find out relevant risk features in patients with HNC. The balanced accuracy and area under the curve (AUC) are over 0.761 and 0.847, with an approximately 2% and 3% increase, respectively, compared to the best individual base classifier. Our study found the top six ensemble risk features, such as body mass index, primary site of HNC, clinical nodal (N) status, primary site surgical margins, sex, and pathologic nodal (N) status. This will help clinicians screen HNC survivors before SPCs occur.

Development of a Longitudinal Diagnosis and Prognosis in Patients with Chronic Kidney Disease: Intelligent Clinical Decision-Making Scheme.

Previous studies on CKD patients have mostly been retrospective, cross-sectional studies. Few studies have assessed the longitudinal assessment of patients over an extended period. In consideration of the heterogeneity of CKD progression. It's critical to develop a longitudinal diagnosis and prognosis for CKD patients. We proposed an auto Machine Learning (ML) scheme in this study. It consists of four main parts: classification pipeline, cross-validation (CV), Taguchi method and improve strategies. This study includes datasets from 50,174 patients, data were collected from 32 chain clinics and three special physical examination centers, between 2015 and 2019. The proposed auto-ML scheme can auto-select the level of each strategy to associate with a classifier which finally shows an acceptable testing accuracy of 86.17%, balanced accuracy of 84.08%, sensitivity of 90.90% and specificity of 77.26%, precision of 88.27%, and F1 score of 89.57%. In addition, the experimental results showed that age, creatinine, high blood pressure, smoking are important risk factors, and has been proven in previous studies. Our auto-ML scheme light on the possibility of evaluation for the effectiveness of one or a combination of those risk factors. This methodology may provide essential information and longitudinal change for personalized treatment in the future.

Risk Prediction of Second Primary Endometrial Cancer in Obese Women: A Hospital-Based Cancer Registry Study.

Due to the high effectiveness of cancer screening and therapies, the diagnosis of second primary cancers (SPCs) has increased in women with endometrial cancer (EC). However, previous studies providing adequate evidence to support screening for SPCs in endometrial cancer are lacking. This study aimed to develop effective risk prediction models of second primary endometrial cancer (SPEC) in women with obesity (body mass index (BMI) > 25) and included datasets on the incidence of SPEC and the other risks of SPEC in 4480 primary cancer survivors from a hospital-based cancer registry database. We found that obesity plays a key role in SPEC. We used 10 independent variables as predicting variables, which correlated to obesity, and so should be monitored for the early detection of SPEC in endometrial cancer. Our proposed scheme is promising for SPEC prediction and demonstrates the important influence of obesity and clinical data representation in all cases following primary treatments. Our results suggest that obesity is still a crucial risk factor for SPEC in endometrial cancer.

Glossogyne tenuifolia Extract Increases Nitric Oxide Production in Human Umbilical Vein Endothelial Cells.

The vascular nitric oxide (NO) system has a protective effect in atherosclerosis. NO is generated from the conversion of L-arginine to L-citrulline by the enzymatic action of endothelial NO synthase (eNOS). Compounds with the effect of enhancing eNOS expression are considered to be candidates for the prevention of atherosclerosis. In this study, extracts from the aerial, root, and whole plant of Glossogyne tenuifolia (GT) were obtained with ethanol, n-hexane, ethyl acetate (EA), and methanol extraction, respectively. The effects of these GT extracts on the synthesis of NO and the expression of eNOS in human umbilical vein endothelial cells (HUVECs) were investigated. NO production was determined as nitrite by colorimetry, following the Griess reaction. The treatment of HUVECs with EA extract from the root of GT and n-hexane, methanol, and ethanol extract from the aerial, root, and whole plant of GT increased NO production in a dose-dependent manner. When at a dose of 160 µg/mL, NO production increased from 0.9 to 18.4-fold. Among these extracts, the methanol extract from the root of GT (R/M GTE) exhibited the most potent effect on NO production (increased by 18.4-fold). Furthermore, using Western blot and RT-PCR analysis, treatment of HUVECs with the R/M GTE increased both eNOS protein and mRNA expression. In addition, Western blot analysis revealed that the R/M GTE increased eNOS phosphorylation at serine1177 as early as 15 min after treatment. The chemical composition for the main ingredients was also performed by HPLC analysis. In conclusion, the present study demonstrated that GT extracts increased NO production in HUVECs and that the R/M GTE increased NO production via increasing eNOS expression and activation by phosphorylation of eNOS at serine1177.

Postpartum HPV Vaccination Rate and Differences in Background Characteristics Between HPV Vaccinated and Unvaccinated Postpartum Women: Strict Monitoring and Follow-Up of Postpartum HPV Vaccination Program.

There is a need to increase the vaccine completion rates in women who have already received human papillomavirus (HPV) vaccines. With vaccines requiring multiple doses, designing a vaccination control program and increasing the proportion of women who complete vaccination are critical and remain as huge challenges. Currently, there are no published reports on the differences in the background characteristics between postpartum women who are vaccinated or unvaccinated against HPV. This study aimed to determine the vaccination rates of the second and third doses of HPV vaccination utilizing an achievable HPV vaccination program in postpartum women. In this retrospective study, 243 postpartum women attending Chiayi Chang Gung Memorial Hospital between March and September 2014 were enrolled. These women were classified into two groups: one group received the HPV vaccine under a practical, controlled postpartum HPV vaccination program, and the other group did not. The rates for the second and third rounds of HPV vaccination in postpartum women were calculated. The differences in the background characteristics between the two groups were determined using the Student's t test, chi-square test or Fisher's exact test, and the multiple logistic models, as appropriate. Under the controlled postpartum HPV vaccination program, the completion rate for the three doses of postpartum HPV vaccination was 97.2%. Significant differences were observed according to maternal age, gender of the newborn, and postpartum Pap smear results between the two groups in our study. In conclusion, the controlled postpartum HPV vaccination program is a reasonable method for achieving an excellent completion rate for the three doses of postpartum HPV vaccination and may be a good model for any multiple-dose vaccination protocol.