The use of individual-based FDG-PET volume of interest in predicting conversion from mild cognitive impairment to dementia.

BACKGROUND: Based on a longitudinal cohort design, the aim of this study was to investigate whether individual-based 18F fluorodeoxyglucose positron emission tomography (18F-FDG-PET) regional signals can predict dementia conversion in patients with mild cognitive impairment (MCI). METHODS: We included 44 MCI converters (MCI-C), 38 non-converters (MCI-NC), 42 patients with Alzheimer's disease with dementia, and 40 cognitively normal controls. Data from annual cognitive measurements, 3D T1 magnetic resonance imaging (MRI) scans, and 18F-FDG-PET scans were used for outcome analysis. An individual-based FDG-PET approach was applied using seven volumes of interest (VOIs), Z transformed using a normal FDG-PET template. Hypometabolism was defined as a Z score < -2 of regional standard uptake value ratio. For the longitudinal cognitive test scores, generalized estimating equations were used. A linear mixed-effects model was used to compare the temporal impact of cortical hypometabolism and cortical thickness degeneration. RESULTS: The clinical follow-up period was 6.6 ± 3.8 years (range 3.1 to 16.0 years). The trend of cognitive decline could differentiate MCI-C from MCI-NC after 3 years of follow-up. In the baseline 18F-FDG-PET scan of the patients with MCI, medial temporal lobe (MTL; 94.7% sensitivity, 80.5% specificity) and posterior cingulate cortex (PCC; 89.5% sensitivity, 73.1% specificity) hypometabolism predicted conversion with high accuracy. 18F-FDG-PET hypometabolism preceded dementia conversion at an interval of 3.70 ± 1.68 years and was earlier than volumetric changes, with the exception of the MTL. CONCLUSIONS: Our finding supports the use of individual-based 18F-FDG-PET analysis to predict MCI conversion to dementia. Reduced FDG-PET metabolism in the MTL and PCC were strongly associated with future cognitive decline in the MCI-C group. Changes in 18F-FDG-PET occurred 1 to 8 years prior to conversion to dementia. Progressive hypometabolism in the PCC, precuneus and lateral temporal lobe, but not MTL, preceded MRI findings at the MCI stage.

Diet Pattern Analysis in Alzheimer's Disease Implicates Gender Differences in Folate-B12-Homocysteine Axis on Cognitive Outcomes.

BACKGROUND & AIMS: Low plasma B12 and folate levels or hyperhomocysteinemia are related to cognitive impairment. This study explores the relationships among diet pattern, blood folate-B12-homocysteine levels, and cognition measurement in Alzheimer's disease (AD) while exploring whether a gender effect may exist. METHODS: This cross-sectional study enrolled 592 AD patients (246 males, 346 females) and the demographic data, blood biochemical profiles, Mini-Mental State Examination (MMSE), and a Food Frequency Questionnaire (FFQ) for quantitative assessment of dietary frequency were collected. Structural Equation Modeling (SEM) was employed to explore the associations among dietary patterns, blood profiles, and cognition. A least absolute shrinkage and selection operator regression model, stratified by gender, was constructed to analyze the weighting of possible confounders. RESULTS: Higher MMSE scores were related to higher frequencies of coffee/tea and higher educational levels, body mass index, and younger age. The SEM model revealed a direct influence of dietary frequencies (skimmed milk, thin pork, coffee/tea) and blood profiles (homocysteine, B12, and folate) on cognitive outcomes. At the same time, the influence of dietary pattern on cognition was not mediated by folate-B12-homocysteine levels. In males, a direct influence on the MMSE is attributed to B12, while in females, homocysteine is considered a more critical factor. CONCLUSIONS: Dietary patterns and blood profiles are both associated with cognitive domains in AD, and there are gender differences in the associations of dietary patterns and the levels of B12 and homocysteine. To enhance the quality of dietary care and nutritional status for individuals with dementia, our study results still require future validations with multi-center and longitudinal studies.

Comparative Study of Heavy Metal Blood Serum Level Between Organic and Conventional Farmers in Eastern Taiwan.

Numerous studies have indicated that organic fertilizers (OFer) might contain heavy metals (HMs) that present health risks to organic farmers (OFar). This study compared the concentrations of six HMs (Zn, Ni, Cd, Cu, Pb, Cr) in the blood of two distinct groups of farmers: 30 OFar from a designated organic area in eastern Taiwan, and 74 conventional farmers (CFar) from neighboring non-organic designated regions. The findings revealed that the OFar exhibited higher levels of Zn (1202.70 ± 188.74 µg/L), Cr (0.20 ± 0.09 µg/L), and Ni (2.14 ± 1.48 µg/L) in their blood compared to the CFar (988.40 ± 163.16 µg/L, 0.18 ± 0.15 µg/L, and 0.77 ± 1.23 µg/L), respectively. The disparities in Zn, Cr, and Ni levels were measured at 214.3 µg/L, 0.02 µg/L, and 1.37 µg/L, respectively. Furthermore, among the OFar, those who utilized green manures (GM) displayed significantly elevated blood levels of Zn (1279.93 ± 156.30 µg/L), Cr (0.24 ± 0.11 µg/L), and Ni (1.94 ± 1.38 µg/L) compared to individuals who exclusively employed chemical fertilizers (CFer) (975.42 ± 165.35 µg/L, 0.19 ± 0.16 µg/L, and 0.74 ± 1.20 µg/L), respectively. The differences in Zn, Cr, and Ni levels were measured at 304.51 µg/L, 0.05 µg/L, and 1.20 µg/L, respectively. As a result, OFar should be careful in choosing OFer and avoid those that may have heavy metal contamination.

Therapeutic Decision Making in Prevascular Mediastinal Tumors Using CT Radiomics and Clinical Features: Upfront Surgery or Pretreatment Needle Biopsy?

The study aimed to develop machine learning (ML) classification models for differentiating patients who needed direct surgery from patients who needed core needle biopsy among patients with prevascular mediastinal tumor (PMT). Patients with PMT who received a contrast-enhanced computed tomography (CECT) scan and initial management for PMT between January 2010 and December 2020 were included in this retrospective study. Fourteen ML algorithms were used to construct candidate classification models via the voting ensemble approach, based on preoperative clinical data and radiomic features extracted from the CECT. The classification accuracy of clinical diagnosis was 86.1%. The first ensemble learning model was built by randomly choosing seven ML models from a set of fourteen ML models and had a classification accuracy of 88.0% (95% CI = 85.8 to 90.3%). The second ensemble learning model was the combination of five ML models, including NeuralNetFastAI, NeuralNetTorch, RandomForest with Entropy, RandomForest with Gini, and XGBoost, and had a classification accuracy of 90.4% (95% CI = 87.9 to 93.0%), which significantly outperformed clinical diagnosis (p < 0.05). Due to the superior performance, the voting ensemble learning clinical-radiomic classification model may be used as a clinical decision support system to facilitate the selection of the initial management of PMT.

Comparison of Outpatient Department-Referred and Self-Referred Patients in the Emergency Department.

BACKGROUND: Patients present to emergency departments (EDs) from a variety of backgrounds, which may help inform decision making. OBJECTIVE: This study investigated the clinical characteristics and outcomes of outpatient department (OPD)-referred patients and self-referred patients in the ED. METHODS: We selected nontrauma ED adult patients from a tertiary teaching hospital in Taiwan between August 1, 2020, and October 31, 2020. The acuity levels were determined by dichotomizing the triage classification scores. After propensity score matching, we compared the hospitalization, mortality, and length of ED stay of OPD-referred and self-referred patients. We categorized the patients into "emergency" or "urgent" subgroups according to their triage information and then analyzed the effects of different severity levels. Statistical significance was set at p < 0.05. RESULTS: A total of 564 OPD-referred and 11,959 self-referred patients were included. After propensity score matching, the OPD-referred patients (n = 564), compared with self-referred patients (n = 564), had a higher admission rate (49.8% vs. 28.9%; p < 0.001; odds ratio [OR] 2.44). Among the emergency subgroup patients, there was no significant difference between OPD-referred patients (n = 131) and self-referred patients (n = 138) regarding the admission rate (p = 0.257) or the mortality rate (p = 0.253). Among the urgent subgroup patients, OPD-referred patients (n = 433), compared with self-referred patients (n = 426), had a significantly higher admission rate (46.0% vs. 20.2%; p < 0.001; OR 3.36), but not mortality rate (2.1% vs. 0.5%; p = 0.064). Regarding the length of ED stay, OPD-referred and self-referred patients had a significant difference only in the "urgent and discharged" subgroup (5.8 vs. 2.3 h; p < 0.001). CONCLUSIONS: OPD-referred ED patients might have more severe and complex conditions and need comprehensive care management.

Corrigendum: Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan.

[This corrects the article DOI: 10.3389/fonc.2023.1105100.].

Untargeted metabolomics analysis assisted by signal selection for comprehensively identifying metabolites of new psychoactive substances: 4-MeO-α-PVP as an example.

New psychoactive substances (NPS) have been rapidly emerged as legal alternatives to controlled drugs, which raised severe public health issue. The detection and monitoring of its intake by complete metabolic profiling is an urgent and vital task. Untargeted metabolomics approach has been applied for several NPS metabolites studies. Although the number of such works is relatively limited but with a rapidly growing need. The present study aimed to propose a procedure that includes liquid chromatography high-resolution mass spectrometry (LC-HRMS) analysis and a signal selection software, MetaboFinder, programed as a web tool. The comprehensive metabolites profile of one kind of NPS, 4-methoxy-α-pyrrolidinovalerophenone (4-MeO-α-PVP), was studied by using this workflow. In this study, two different concentrations of 4-MeO-α-PVP along with as blank sample were incubated with human liver S9 fraction for the conversion to their metabolites and followed by LC-MS analysis. After retention time alignment and feature identification, 4640 features were obtained and submitted to statistical analysis for signal selection by using MetaboFinder. A total of 50 features were considered as 4-MeO-α-PVP metabolite candidates showing significant changes (p < 0.00001 and fold change >2) between the two investigated groups. Targeted LC-MS/MS analysis was conducted focusing on these significantly expressed features. Assisted by chemical formula determination according to high mass accuracy and in silico MS2 fragmentation prediction, 19 chemical structure identifications were achieved. Among which, 8 metabolites have been reported derived from 4-MeO-α-PVP in a previous literature while 11 novel 4-MeO-α-PVP metabolites were identified by using our strategy. Further in vivo animal experiment confirmed that 18 compounds were 4-MeO-α-PVP metabolites, which demonstrated the feasibility of our strategy for screening the 4-MeO-α-PVP metabolites. We anticipate that this procedure may support and facilitate traditional metabolism studies and potentially being applied for routine NPS metabolites screening.

Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan.

Purpose: To compare the diagnostic performance of radiomic analysis with machine learning (ML) model with a convolutional neural network (CNN) in differentiating thymic epithelial tumors (TETs) from other prevascular mediastinal tumors (PMTs). Methods: A retrospective study was performed in patients with PMTs and undergoing surgical resection or biopsy in National Cheng Kung University Hospital, Tainan, Taiwan, E-Da Hospital, Kaohsiung, Taiwan, and Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan between January 2010 and December 2019. Clinical data including age, sex, myasthenia gravis (MG) symptoms and pathologic diagnosis were collected. The datasets were divided into UECT (unenhanced computed tomography) and CECT (enhanced computed tomography) for analysis and modelling. Radiomics model and 3D CNN model were used to differentiate TETs from non-TET PMTs (including cyst, malignant germ cell tumor, lymphoma and teratoma). The macro F1-score and receiver operating characteristic (ROC) analysis were performed to evaluate the prediction models. Result: In the UECT dataset, there were 297 patients with TETs and 79 patients with other PMTs. The performance of radiomic analysis with machine learning model using LightGBM with Extra Tree (macro F1-Score = 83.95%, ROC-AUC = 0.9117) had better performance than the 3D CNN model (macro F1-score = 75.54%, ROC-AUC = 0.9015). In the CECT dataset, there were 296 patients with TETs and 77 patients with other PMTs. The performance of radiomic analysis with machine learning model using LightGBM with Extra Tree (macro F1-Score = 85.65%, ROC-AUC = 0.9464) had better performance than the 3D CNN model (macro F1-score = 81.01%, ROC-AUC = 0.9275). Conclusion: Our study revealed that the individualized prediction model integrating clinical information and radiomic features using machine learning demonstrated better predictive performance in the differentiation of TETs from other PMTs at chest CT scan than 3D CNN model.

Gray matter reserve determines glymphatic system function in young-onset Alzheimer's disease: Evidenced by DTI-ALPS and compared with age-matched controls.

BACKGROUND: The diffusion tensor imaging analysis along the perivascular space (ALPS)-index can be used to model the glymphatic system in vivo. AIM: This study explores putative mechanisms between prediction of ALPS-index and cognitive outcomes in young-onset Alzheimer's disease (YOAD) and age-matched controls (CTLs) and analyzes whether the link was mediated by the integrity of ALPS-index-anchored cerebral gray matter (GM). METHODS: We enrolled 130 patients with YOAD and 137 CTLs. All participants underwent three-dimensional T1 -weighted MRI, diffusion tensor imaging and cognitive tests. We constructed GM regions correlated with the ALPS-index in the YOAD and CTL groups. For the GM regions significantly correlated with the ALPS-index and cognitive measures, we extracted a 4-mm radius sphere. In the YOAD and CTL groups, we used mediator analysis to explore the ALPS-index as predictor, GM partitions as mediators, and significant cognitive test scores as outcomes. RESULTS: Patient group had significantly lower ALPS-index. The ALPS-index was associated with GM volume in the cerebellar gray, dorsolateral prefrontal, thalamus, superior frontal, amygdala and hippocampus, and these coherent regions coincided with those showing GM atrophy in the YOAD group. Mediation analysis of the YOAD group suggested that the relationships between the ALPS-index and cognitive performance were fully mediated by the integrity of ALPS-index coherent GM areas. DISCUSSION: Reserved GM mediates the link between the glymphatic system and cognition. Our findings suggest that GM integrity rather than the glymphatic system could serve as a direct cognitive test scores predictor in patients with YOAD.

Sexuality and Quality of Life in Eastern Taiwan People With Schizophrenia.

OBJECTIVE: Patients with schizophrenia are living at the border of society and their sexuality is often neglected. The aim of the study is to explore the association among The Brief Psychiatric Rating Scale (BPRS), quality of life (QoL), Taiwanese Depression Questionnaire, and Sexual Desire Inventory in people with schizophrenia (PwS). METHODS: This study used a cross-sectional design with 277 psychiatric inpatients. A descriptive analysis, difference analysis, and logistic regression model were presented to identify relevant variables that may affect the probability of good QoL. RESULTS: The study showed that male PwS had higher scores of standard deviation (SD) than females in PwS. The study also showed that smoking, early illness onset age, and shorter illness duration demonstrated a significantly higher SD. The logistic regression analysis showed that BPRS, depression, and SD significantly affected the probability of QoL. By structural equation model, SD would be positively correlated with mental status and SD would indirectly influence QoL. CONCLUSION: Our results showed psychological and sociological factors interactions may contribute to the QoL and SD for PwS. This study also demonstrated a close relationship between SD, depression, and BPRS. These factors may predict the probability of good life quality for the PwS.

Cognitive Decline Related to Diet Pattern and Nutritional Adequacy in Alzheimer's Disease Using Surface-Based Morphometry.

Dietary pattern (DP) results in nutrition adequacy and may influence cognitive decline and cortical atrophy in Alzheimer's disease (AD). The study explored DP in 248 patients with AD. Two neurobehavioral assessments (intervals 13.4 months) and two cortical thickness measurements derived from magnetic resonance images (intervals 26.5 months) were collected as outcome measures. Reduced rank regression was used to assess the groups of DPs and a linear mixed-effect model to explore the cortical neurodegenerative patterns. At screening, underweight body mass index (BMI) was related to significant higher lipid profile, impaired cognitive function, smaller cortical thickness, lower protein DP factor loading scores and the non-spouse caregiver status. Higher mini-mental state examination (MMSE) scores were related to the DP of coffee/tea, compared to the lipid/sugar or protein DP group. The underweighted-BMI group had faster cortical thickness atrophy in the pregenual and lateral temporal cortex, while the correlations between cortical thickness degeneration and high HbA1C or low B12 and folate levels were localized in the medial and lateral prefrontal cortex. The predictive model suggested that factors related to MMSE score were related to the caregiver status. In conclusion, normal or overweight BMI, coffee/tea DP group and living with a spouse were considered as protective factors for better cognitive outcomes in patients with AD. The influence of glucose, B12 and folate on the cortical degeneration was spatially distinct from the pattern of AD degeneration.

Predicting Bacteremia among Septic Patients Based on ED Information by Machine Learning Methods: A Comparative Study.

INTRODUCTION: Bacteremia is a common but life-threatening infectious disease. However, a well-defined rule to assess patient risk of bacteremia and the urgency of blood culture is lacking. The aim of this study is to establish a predictive model for bacteremia in septic patients using available big data in the emergency department (ED) through logistic regression and other machine learning (ML) methods. MATERIAL AND METHODS: We conducted a retrospective cohort study at the ED of National Cheng Kung University Hospital in Taiwan from January 2015 to December 2019. ED adults (≥18 years old) with systemic inflammatory response syndrome and receiving blood cultures during the ED stay were included. Models I and II were established based on logistic regression, both of which were derived from support vector machine (SVM) and random forest (RF). Net reclassification index was used to determine which model was superior. RESULTS: During the study period, 437,969 patients visited the study ED, and 40,395 patients were enrolled. Patients diagnosed with bacteremia accounted for 7.7% of the cohort. The area under the receiver operating curve (AUROC) in models I and II was 0.729 (95% CI, 0.718-0.740) and 0.731 (95% CI, 0.721-0.742), with Akaike information criterion (AIC) of 16,840 and 16,803, respectively. The performance of model II was superior to that of model I. The AUROC values of models III and IV in the validation dataset were 0.730 (95% CI, 0.713-0.747) and 0.705 (0.688-0.722), respectively. There is no statistical evidence to support that the performance of the model created with logistic regression is superior to those created by SVM and RF. DISCUSSION: The advantage of the SVM or RF model is that the prediction model is more elastic and not limited to a linear relationship. The advantage of the LR model is that it is easy to explain the influence of the independent variable on the response variable. These models could help medical staff identify high-risk patients and prevent unnecessary antibiotic use. The performance of SVM and RF was not inferior to that of logistic regression. CONCLUSIONS: We established models that provide discrimination in predicting bacteremia among patients with sepsis. The reported results could inspire researchers to adopt ML in their development of prediction algorithms.

Gene expression analysis of combined RNA-seq experiments using a receiver operating characteristic calibrated procedure.

Because of rapid advancements in sequencing technology, the experimental platforms of RNA-seq are updated frequently. It is quite common to combine data sets from several experimental platforms for analysis in order to increase the sample size and achieve more powerful tests for detecting the presence of differential gene expression. The data sets combined from different experimental platforms will have a complex data distribution, which causes a major problem in statistical modeling as well as in multiple testing. Although plenty of research have studied this problem by modeling the batch effects, there are no general and robust data-driven procedures for RNA-seq analysis. In this paper we propose a new robust procedure which combines the use of popular methods (packages) with a data-driven simulation (DDS). We construct the average receiver operating characteristic curve through the DDS to provide the calibrated levels of significance for multiple testing. Instead of further modifying the adjusted p-values, we calibrated the levels of significance for each specific method and mean effect model. The procedure was demonstrated with several popular RNA-seq analysis methods (edgeR, DEseq2, limma+voom). The proposed procedure relaxes the stringent assumptions of data distributions for RNA-seq analysis methods and is illustrated using colorectal cancer studies from The Cancer Genome Atlas database.

Acute responses of bone specific and related markers to maximal eccentric exercise of the knee extensors and flexors in young men.

OBJECTIVES: The present study determined time-course changes in plasma bone-specific and -related markers following a bout of maximal eccentric contractions (MaxEC) of bilateral knee extensors (KE) and flexors (KF). METHODS: Sedentary young men (n=30) performed a bout of 10 sets of 10 MaxEC (30°/s) of KE and KF with each leg, respectively. Maximal voluntary isometric contraction (MVC) torque, muscle soreness (SOR), plasma creatine kinase (CK) activity, insulin, leptin, tumor necrosis factor-α (TNF-α), undercarboxylated-osteocalcin (ucOCN), carboxy-terminal crosslinking telopeptide of type I collagen (CTX-1) and procollagen type I N-terminal propeptide (P1NP) concentrations were measured from before to 7 days after MaxEC. RESULTS: Significant changes in MVC (KE: -28%, KF: -38%), SOR and plasma CK activity (peak: 39,163 IU/L) following MaxEC were evident (P<0.05) compared to baseline. Plasma leptin (17%) concentrations decreased at 1 day after MaxEC. In bone related markers, plasma ucOCN concentrations (20%) increased at 7 days after MaxEC, and plasma CTX-1 concentrations decreased at 2, 4 and 7 days after MaxEC (6~7%; P<0.05). CONCLUSION: These results demonstrate that a lean effect of bone generation and an enhanced energy anabolism can be induced by a single bout of MaxEC.

Assessment of Serological Early Biomarker Candidates for Lung Adenocarcinoma by using Multiple Reaction Monitoring-Mass Spectrometry.

PURPOSE: Plasma markers that enable diagnosis in the early stage of lung cancer is not discovered. A liquid chromatography multiple reaction monitoring-mass spectrometry (LC-MRM-MS) assay for identifying potential early marker proteins for lung adenocarcinoma is developed. EXPERIMENTAL DESIGN: LC-MRM-MS assay is used for measuring the level of 35 candidate peptides in plasma from 102 lung adenocarcinoma patients (including n = 50, 16, 24, and 12 in stage I, II, III, and IV, respectively.) and 84 healthy controls. Stable isotope labeled standard peptides are synthesized to accurately measure the amount of these proteins. RESULTS: Seven proteins are able to distinguish stage I patients from controls. These proteins are combined in to a protein marker panel which improve the sensitivity to discriminate stage I patients from controls with cross-validated area under the curve = 0.76. Besides, it is found that low expression of eukaryotic initiation factor 4A-I and high expression of lumican show significantly poor prognosis in overall survival (p = 0.012 and 0.0074, respectively), which may be used as prognostic biomarkers for lung cancer. CONCLUSIONS AND CLINICAL RELEVANCE: Proteins highlighted here may be used for early detection of lung adenocarcinoma or therapeutics development after validation in a larger cohort.

Assessing the Similarity between Random Copolymer Drug Glatiramer Acetate by Using LC-MS Data Coupling with Hypothesis Testing.

The full characterization of nonbiological complex drugs (NBCDs) is not possible, but analytical approaches are of urgent need to evaluate the similarity between different lots and compare with their follow-up versions. Here, we propose a hypothesis testing-based approach to assess the similarity/difference between random amino acid copolymer drugs using liquid chromatography mass spectrometry (LC-MS) analysis. Two glatiramer acetate (GA) drugs, commercially available Copaxone and in-house synthesized SPT, and a negative control were digested by Lys-C and followed by HILIC-MS analysis. After retention time alignment and feature identification, 1627 features matched to m/z values in an elemental composition database were considered as derived from active drug ingredients. A hypothesis testing approach, the sum of squared deviations test, was developed to process high-dimensional data derived from LC-MS spectra. The feasibility of this approach was first demonstrated by testing 5 versus 5 lots of Copaxone and Copaxone versus SPT, which suggested a significant similarity by obtaining the estimated 95th percentile of the distribution of the estimator (ρ̂(95%)) at 0.0056 (p-value = 0.0026) and 0.0026 (p-value < 0.0001), respectively. In contrast, the ρ̂ was 0.036 (p-value = 1.00), while comparing Copaxone and the negative control, implying a lack of similarity. We further synthesized nine stable isotope-labeled peptides to validate the proposed amino acid sequences in the database, demonstrating the correctness in sequence identification. The quantitation variations in our analytical procedures were determined to be 6.8-7.7%. This approach was found to have a great potential for evaluating the similarity between generic NBCDs and listed reference drugs, as well as to monitor the lot-to-lot variation.

A modified developmental care bundle reduces pain and stress in preterm infants undergoing examinations for retinopathy of prematurity: A randomised controlled trial.

AIMS AND OBJECTIVES: To determine the comparative efficacy of developmental care versus standard care for reducing pain and stress in preterm infants during examinations for retinopathy of prematurity (ROP). BACKGROUND: ROP examinations are routinely performed in neonatal intensive care units to detect these lesions. Pain scores recorded during and after eye examinations have revealed physiological and behavioural manifestations of pain and stress. DESIGN: A randomised crossover trial was conducted. METHODS: Fourteen preterm infants were evaluated. The modified developmental care bundle included environmental modifications, positioning and containment, oxygen supplementation, interaction and approach and cue-based individual care, which were applied before, during and after the ROP examination. The primary outcomes were obtained from pain and stress scores using the premature infant pain profile-revised (PIPP-R) and a behavioural evaluation. The secondary outcomes were recovery time to the baseline of the vital signs and oxygen saturation. RESULTS: Statistical significances were found in the care type comparison (p = 0.013), time comparison (p < 0.001) and type-by-time interaction (p = 0.005) in the PIPP-R, and also in the care type comparison (p < 0.001), time comparison (p < 0.001) and type-by-time interaction (p = 0.001) in the behavioural evaluation scores using a generalised estimating equation (GEE) analysis. Recovery time for the developmental care (N = 13, mean = 8.6 ± 11.5 min, 95% CI = 1.68-15.57) was significantly shorter than for the standard care (N = 11, mean = 25.5 ± 20.8 min, 95% CI = 11.45-39.46), which was found to be statistically significant according to the Wilcoxon signed-rank test (N = 11, p = 0.003). CONCLUSIONS: A bundled developmental care intervention significantly reduced pain and stress responses and the time needed for infants to recover their physiological status following the procedure. RELEVANCE TO CLINICAL PRACTICE: Since the results show the benefits of developmental care in an ROP examination, it can be the practical evidence basis by which to develop a standard of procedure or guideline for clinical practice.

Psychometric evaluation of a Chinese version of Lymphoedema Functioning, Disability and Health Questionnaire for Lower Limb Lymphoedema in women with gynaecological cancer surgery.

The prevalence of lower limb lymphoedema and its impact in gynaecological cancer patients is underestimated. However, a valid and reliable scale to measure lower leg lymphoedema in Taiwan has not been available. The purpose of the study was to translate the English version of Lymphoedema Functioning, Disability and Health Questionnaire for Lower Limb Lymphoedema into a Chinese version (Lymph-ICF-LL-C), and evaluate the psychometric properties of the Lymph-ICF-LL-C in Taiwanese women with gynaecological cancer surgery. A total of 170 women with gynaecological cancer surgery were recruited to examine the Lymph-ICF-LL-C. The Lymph-ICF-LL-C shows satisfactory internal consistency (Cronbach's alphas ≥ 0.84) and stability test-retest reliability (Intraclass correlation coefficient ≥0.55-0.90) at a 2-week interval. Exploratory factor analysis showed that 68.53% of the total variance was explained by a five-factor solution. The concurrent validity of the Lymph-ICF-LL-C was evidenced by a significant correlation with a fatigue scale (r = 0.46, p < 0.01) and with the bilateral difference of lower limb circumference (r = 0.24-0.36, all p < 0.01). The Lymph-ICF-LL-C can be used for assessing the life impact of lower limb lymphoedema, allowing appropriate interventions to prevent further deterioration and complications.

Sexual Activity, Sexual Dysfunction, and Sexual Life Quality Among Psychiatric Hospital Inpatients With Schizophrenia.

BACKGROUND: Sexual dysfunction occurs commonly in patients with psychiatric illness and may be related to the primary mental disorder, comorbidity with sexual disorders or medical illness, or medications used for mental disorders treatment, but the magnitude of this problem is unknown. AIM: To estimate the prevalence of current sexual activity, sexual dysfunction, and sexual attitude and influence of factors on patients with schizophrenia. METHODS: This study used a cross-sectional design with a total of 317 patients diagnosed with schizophrenia. The subjects completed a demographic questionnaire, sexual attitude scale, sexual dysfunction scale, and sexual behavior scale. Descriptive analysis, difference analysis, and logistic regression model were used to identify relevant variables that may affect sexual life quality. OUTCOMES: Age, sexual satisfaction, and patient symptoms may predict sexual life quality on patients with schizophrenia. RESULTS: The mean age of patients was 47.71 ± 9.54 years old. About the sexual activities, 53% of subjects had sexual intercourse experience, and 41.3% reported currently having sexual intercourse. The mean ± SD age for first sexual intercourse was 20.83 ± 5.95 years old (median was 20.0 years old). Moreover, women older than 50 years had significantly higher medians for the Brief Psychiatric Rating Scale (BPRS) score, higher proportions of sexual dysfunction, and lower proportions of feeling important to sexual life quality than men. For participants with age ≤50 years old, there was a significant relationship among BPRS group (mean score >2.5 vs ≤2.5), sexual dysfunction (P < .001), sexual life quality (P < .001), and sexual satisfaction (P = .006). Among the predictors of feeling important to sexual life quality, sexual satisfaction (odds ratio = 7.005, 95% CI = 4.126-11.892, P < .001) and BPRS score (odds ratio = 4.501, 95% CI = 2.042-9.923, P < .001) were significant independent factors after adding the interaction of age group and BPRS group. CLINICAL TRANSLATION: This study also reveals the close relationship between sexual satisfaction and BPRS score, which may predict sexual life quality of patients with schizophrenia. Limitations include the possibility of underreporting and bias associated with self-report measurement. CONCLUSION: Sexual life quality and sexual dysfunction on patients with schizophrenia are associated with interaction among psychological, sociological, and biochemical-pharmacological factors. Ma M-C, Chao J-K, Hung J-Y, et al. Sexual Activity, Sexual Dysfunction, and Sexual Life Quality Among Psychiatric Hospital Inpatients With Schizophrenia. J Sex Med 2018;15:324-333.

Parental intention regarding the administration of the HPV vaccine for adolescent daughters in Taiwan.

This study aimed to investigate parental intention regarding the human papilloma virus (HPV) vaccination for adolescent daughters. Parents or guardians of adolescent girls, aged 12-14 years, from junior high schools in Taiwan participated and completed a HPV vaccination intention survey based on the Theory of Planned Behavior. The survey was conducted from October to November, 2009. Most, 78%, of the respondents reported a high intention to vaccinate daughters against HPV. A high intention of vaccination was associated with a family history of gynecological tumors (adjusted odds ratio [OR]: 2.22, 95% confidence interval [CI]: 1.10-4.51) and HPV awareness (adjusted OR: 2.33, 95% CI: 1.45-3.76). Higher parental intention was reported by respondents with a positive attitude toward the HPV vaccine (adjusted OR: 6.83, 95% CI: 4.16-11.22), perceived greater influence of subjective norms (adjusted OR: 121.23, 95% CI: 42.69-344.21), greater perceived behavioral control (adjusted OR: 67.69, 95% CI: 16.40-279.41), and perceived that the vaccine had limited influence on adolescent sexual behavior (adjusted OR: 2.24, 95% CI: 1.41-3.78). Health-care professionals must be knowledgeable about the HPV and actively promote vaccination among adolescent girls. Improvements in vaccination can be achieved through recommendations by physicians and nurses.