Findings in Chinese Patients With Parkinson's Disease: A Content Analysis From the SML Study

Psychosomatic and medical experiences of menopause in Chinese women: a social media study

OBJECTIVE

Menopause has a significant effect on a woman's quality of life, which leads to physical illnesses and mental stresses. Social media listening (SML) studies reveal the experiences of users, sources of information on disease experiences and health dynamics in populations. The aim of this study was to assess the overview of portraits, complaints, symptom distribution and treatment methods of menopausal women through SML.

METHODS

An info-surveillance study was conducted wherein the search was performed in the question and answer (Q&A) search and online consultation forums. Using the Python + Scrapy crawl technology tool, the search involved single or combined keywords related to menopause, including population, diagnosis, symptom, treatment and treatment comparison.

RESULTS

Data were extracted from three menopause-related Q&A search platforms and 15 online consultation forums. Menstrual disorders, menopausal symptoms, and menopausal examination and treatment were the high-frequency keywords while irritability, insomnia and hot flashes were the most commonly mentioned symptoms. A total of 76.62% of menopausal women had a willingness for tier 3 hospitals, with gynecology being the most preferred department chosen by the majority. Among the 359 women reporting hormone treatment to be effective, 90.96% women showed an improvement in symptoms, and the rest had improvement in emotions, various improvements and overall improvement.

CONCLUSION

The results of this SML study indicate that menopausal women in China have a strong urge for menopause-related knowledge but are not well informed. Thus, there is a need for science popularization to sensitize menopausal women to choose the right department, and explore the long-term management of menopause and menopausal hormone therapy.

Analysis of factors affecting hospitalization costs in Parkinson disease patients: A retrospective study based on 848 cases

This retrospective study aimed to examine hospitalization costs and associated factors for Parkinson disease (PD) patients. A total of 848 PD patients were extracted from the National Neurological and Brain Center in Xinjiang, and basic demographic information, medical insurance payment, and hospital expenses were collected. SPSS 26.0 was used and univariate analysis was performed on the number of days of hospitalization, times of hospitalizations, gender, payment method, and total hospitalization costs. Correlation analysis was performed using multiple linear regression to explore the influencing factors of hospitalization expenses. The average hospitalization cost of PD patients was 15,515.78 ± 29,667.49 yuan. Diagnosis fees accounted for the highest proportion (29.50%), followed by material costs (25.50%) and drug costs (21.20%). PD patients with less than 5 hospitalizations were the main source of disease, but 2.83% of them had more than 10 hospitalizations (P = .025). Female patients were significantly more than male patients, but the total hospitalization costs of male patients were much higher than those of female patients (P < .001). The number of PD patients increased significantly when they were over 60 years old, but the hospitalization costs were much lower than those of patients under 60 years old (P = .007). The effect of the payment method on total hospitalization cost did not show a statistical difference (P = .213). There was a positive correlation between hospitalization days and total hospitalization cost (P < .001). In conclusion, the results of the regression model suggested that age, length of hospital stay, gender, and number of hospitalizations could be used as predictive variables for hospitalization costs in PD patients.

Comparison of the quality of Nurse-Led palliative care with standard medical care during six months in 405 patients with Parkinson's disease and burdens of their Caregivers: A retrospective study at a single center in China

BACKGROUND

Palliative care is mainly used to improve the quality of life of patients with chronic diseases by addressing their medical conditions and psychological problems. End-stage Parkinson's disease (PD) is also a progressive disease like cancer and could be managed by palliative care. This study was conducted at a single center in China and aimed to compare the quality of nurse-led palliative care with standard medical care during six months in 405 patients with Parkinson's disease (PPD) and their caregivers using the Chinese version of the 39-item Parkinson's Disease Questionnaire (PDQ-39) and the Chinese Zarit Burden Interview (ZBI) scale.

METHODS

PPD (stage 2-5) received nurse-led palliative care (NP cohort, 103 patients; 103 caregivers) or neurologist-led standard care (NS cohort, 134 patients; 134 caregivers), or primary care practitioner-led usual care (PS cohort, 168 patients; 168 caregivers) for six months.

RESULTS

Before the health professional-led care (BN), the PDQ-39 score of PPD was 68 (71-64) and their caregivers had 54.86 ± 7.64 a ZBI scale. After 6-months of the health professional-led care (AN), the PDQ-39 score of PPD and a ZBI scale of their caregivers decreased for the NP cohort as compared to those of BN condition and those of patients in the NS and PS cohorts at AN condition (p < 0.001 for all).

CONCLUSIONS

The quality of life of PPD must be improved and the burden on their caregivers must be relieved. Nurse-led palliative care successfully improved the quality of life of PPD and reduced their caregiver burden.

Evaluation of the Needs and Experiences of Patients with Hypertriglyceridemia: Social Media Listening Infosurveillance Study

BACKGROUND

Hypertriglyceridemia is a risk factor for cardiovascular diseases. Internet usage in China is increasing, giving rise to large-scale data sources, especially to access, disseminate, and discuss medical information. Social media listening (SML) is a new approach to analyze and monitor online discussions related to various health-related topics in diverse diseases, which can generate insights into users' experiences and expectations. However, to date, no studies have evaluated the utility of SML to understand patients' cognizance and expectations pertaining to the management of hypertriglyceridemia.

OBJECTIVE

The aim of this study was to utilize SML to explore the disease cognition level of patients with hypertriglyceridemia, choice of intervention measures, and the status quo of online consultations and question-and-answer (Q&A) search platforms.

METHODS

An infosurveillance study was conducted wherein a disease-specific comprehensive search was performed between 2004 and 2020 in Q&A search and online consultation platforms. Predefined single and combined keywords related to hypertriglyceridemia were used in the search, including disease, symptoms, diagnosis, and treatment indicators; lifestyle interventions; and therapeutic agents. The search output was aggregated using an aggregator tool and evaluated.

RESULTS

Disease-specific consultation data (n=69,845) and corresponding response data (n=111,763) were analyzed from 20 data sources (6 Q&A search platforms and 14 online consultation platforms). Doctors from inland areas had relatively high voice volumes and appear to exert a substantial influence on these platforms. Patients with hypertriglyceridemia engaging on the internet have an average level of cognition about the disease and its intervention measures. However, a strong demand for the concept of the disease and "how to treat it" was observed. More emphasis on the persistence of the disease and the safety of medications was observed. Young patients have a lower willingness for drug interventions, whereas patients with severe hypertriglyceridemia have a clearer intention to use drug intervention and few patients have a strong willingness for the use of traditional Chinese medicine.

CONCLUSIONS

Findings from this disease-specific SML study revealed that patients with hypertriglyceridemia in China actively seek information from both online Q&A search and consultation platforms. However, the integrity of internet doctors' suggestions on lifestyle interventions and the accuracy of drug intervention recommendations still need to be improved. Further, a combined prospective qualitative study with SML is required for added rigor and confirmation of the relevance of the findings.

Radiomics for Parkinson's disease classification using advanced texture-based biomarkers

Parkinson's disease (PD) is one of the neurodegenerative diseases and its manual diagnosis leads to time-consuming process. MRI-based computer-aided diagnosis helps medical experts to diagnose PD more precisely and fast. Texture-based radiomic analysis is carried out on 3D MRI scans of T1 weighted and resting-state modalities. 43 subjects from Neurocon and 40 subjects from Tao-Wu dataset were examined, which consisted of 36 scans of healthy controls and 47 scans of Parkinson's patients. Total 360 2D MRI images are selected among around 17000 slices of T1-weighted and resting scans of selected 72 subjects. Local binary pattern (LBP) method was applied with custom variants to acquire advanced textural biomarkers from MRI images. LBP histogram helped to learn discriminative local patterns to detect and classify Parkinson's disease. Using recursive feature elimination, data dimensions of around 150-300 LBP histogram features were reduced to 13-21 most significant features based on score, and important features were analysed using SVM and random forest algorithms. Variant-I of LBP has performed well with highest test accuracy of 83.33%, precision of 84.62%, recall of 91.67%, and f1-score of 88%. Classification accuracies were obtained from 61.11% to 83.33% and AUC-ROC values range from 0.43 to 0.86 using four variants of LBP.•Parkinson's classification is carried out using an advanced biomedical texture feature. Texture extraction using four variants of uniform, rotation invariant LBP method is performed for radiomic analysis of Parkinson's disorder.•Proposed method with support vector machine classifier is experimented and an accuracy of 83.33% is achieved with 10-fold cross validation for detection of Parkinson's patients from MRI-based radiomic analysis.•The proposed predictive model has proved the potential of textures of extended version of LBP, which have demonstrated subtle variations in local appearance for Parkinson's detection.

Patient Journey Toward a Diagnosis of Light Chain Amyloidosis in a National Sample: Cross-Sectional Web-Based Study

BACKGROUND

Systemic light chain (AL) amyloidosis is a rare and multisystem disease associated with increased morbidity and a poor prognosis. Delayed diagnoses are common due to the heterogeneity of the symptoms. However, real-world insights from Chinese patients with AL amyloidosis have not been investigated.

OBJECTIVE

This study aimed to describe the journey to an AL amyloidosis diagnosis and to build an in-depth understanding of the diagnostic process from the perspective of both clinicians and patients to obtain a correct and timely diagnosis.

METHODS

Publicly available disease-related content from social media platforms between January 2008 and April 2021 was searched. After performing data collection steps with a machine model, a series of disease-related posts were extracted. Natural language processing was used to identify the relevance of variables, followed by further manual evaluation and analysis.

RESULTS

A total of 2204 valid posts related to AL amyloidosis were included in this study, of which 1968 were posted on haodf.com. Of these posts, 1284 were posted by men (median age 57, IQR 46-67 years); 1459 posts mentioned renal-related symptoms, followed by heart (n=833), liver (n=491), and stomach (n=368) symptoms. Furthermore, 1502 posts mentioned symptoms related to 2 or more organs. Symptoms for AL amyloidosis most frequently mentioned by suspected patients were nonspecific weakness (n=252), edema (n=196), hypertrophy (n=168), and swelling (n=140). Multiple physician visits were common, and nephrologists (n=265) and hematologists (n=214) were the most frequently visited specialists by suspected patients for initial consultation. Additionally, interhospital referrals were also commonly seen, centralizing in tertiary hospitals.

CONCLUSIONS

Chinese patients with AL amyloidosis experienced referrals during their journey toward accurate diagnosis. Increasing awareness of the disease and early referral to a specialized center with expertise may reduce delayed diagnosis and improve patient management.