DESIGN: A cross-sectional study.
METHODS: The study was conducted in a healthcare clinic in Malaysia, using multistage random sampling from November 2021 to January 2022. Three hundred seventy-five older adults aged 55 and older were included in the final analysis. There were 31 items in the final PMT scale. The analysis was performed within the whole population and grouped into 'faller' and 'non-faller', employing IBM SPSS version 26.0 for descriptive, independent t-test, chi-square, bivariate correlation and linear regressions.
RESULTS: A total of 375 older participants were included in the study. Fallers (n = 82) and non-fallers (n = 293) show statistically significant differences in the characteristics of ethnicity, assistive device users, self-rating of intention and participation in previous fall prevention programmes. The multiple linear regression model revealed fear, coping appraisal and an interaction effect of fear with coping appraisal predicting fall protection motivation among older adults in rural communities.
CONCLUSION: Findings from this study demonstrated that coping appraisal and fear predict the protection motivation of older adults in rural communities. Older adults without a history of falls and attaining higher education had better responses in coping appraisal, contributing to a reduction in perceived rewards and improving protection motivation. Conversely, older adults from lower education backgrounds tend to have higher non-preventive behaviours, leading to a decline in fall protection motivation.
IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: These results contribute important information to nurses working with older adults with inadequate health literacy in rural communities, especially when planning and designing fall prevention interventions. The findings would benefit all nurses, healthcare providers, researchers and academicians who provide care for older adults.
PATIENT OR PUBLIC CONTRIBUTION: Participants were briefed about the study, and their consent was obtained. They were only required to answer the questionnaire through interviews. Older individuals aged fifty-five and above in rural communities at the healthcare clinic who could read, write or understand Malay or English were included. Those who were suffering from mental health problems and refused to participate in the study were excluded from the study. Their personal information remained classified and not recorded in the database during the data entry or analysis.
MATERIALS AND METHODS: A 56-item questionnaire survey on NOA diagnosis and management was conducted globally from July to September 2022. This paper focuses on part 1, evaluating NOA diagnosis. Data from 367 participants across 49 countries were analyzed descriptively, with a Delphi process used for expert recommendations.
RESULTS: Of 336 eligible responses, most participants were experienced attending physicians (70.93%). To diagnose azoospermia definitively, 81.7% requested two semen samples. Commonly ordered hormone tests included serum follicle-stimulating hormone (FSH) (97.0%), total testosterone (92.9%), and luteinizing hormone (86.9%). Genetic testing was requested by 66.6%, with karyotype analysis (86.2%) and Y chromosome microdeletions (88.3%) prevalent. Diagnostic testicular biopsy, distinguishing obstructive azoospermia (OA) from NOA, was not performed by 45.1%, while 34.6% did it selectively. Differentiation relied on physical examination (76.1%), serum hormone profiles (69.6%), and semen tests (68.1%). Expectations of finding sperm surgically were higher in men with normal FSH, larger testes, and a history of sperm in ejaculate.
CONCLUSIONS: This expert survey, encompassing 367 participants from 49 countries, unveils congruence with recommended guidelines in NOA diagnosis. However, noteworthy disparities in practices suggest a need for evidence-based, international consensus guidelines to standardize NOA evaluation, addressing existing gaps in professional recommendations.
METHODS: A randomized controlled trial design was used, with pre-and post-intervention evaluations. Participants (n = 40), including children with ASD and their parents, were divided into three groups: (a) a family-school group (FSG-A, n = 14), (b) a school group (SG-B, n = 13), and (c) a control group (CG-C, n = 13).
RESULTS: After 12 weeks of intervention, the within-group comparison revealed that the FSG-A performed better than the SG-B and CG-C for all variables. The among-group comparison further revealed that the FSG-A had greater fundamental motor skill scores than the SG-B (p = 0.021) and CG-C (p
METHODS: This study applies radiomics and deep learning in the diagnosis of lung cancer to help clinicians accurately analyze the images and thereby provide the appropriate treatment planning. 86 patients were recruited from Bach Mai Hospital, and 1012 patients were collected from an open-source database. First, deep learning has been applied in the process of segmentation by U-NET and cancer classification via the use of the DenseNet model. Second, the radiomics were applied for measuring and calculating diameter, surface area, and volume. Finally, the hardware also was designed by connecting between Arduino Nano and MFRC522 module for reading data from the tag. In addition, the displayed interface was created on a web platform using Python through Streamlit.
RESULTS: The applied segmentation model yielded a validation loss of 0.498, a train loss of 0.27, a cancer classification validation loss of 0.78, and a training accuracy of 0.98. The outcomes of the diagnostic capabilities of lung cancer (recognition and classification of lung cancer from chest CT scans) were quite successful.
CONCLUSIONS: The model provided means for storing and updating patients' data directly on the interface which allowed the results to be readily available for the health care providers. The developed system will improve clinical communication and information exchange. Moreover, it can manage efforts by generating correlated and coherent summaries of cancer diagnoses.
METHODS: Information regarding the consumption of coffee, tea, and alcohol was collected from the UK Biobank, with sample sizes of 428,860, 447,485, and 462,346 individuals, respectively. Data on 41 inflammatory cytokines were obtained from summary statistics of 8293 healthy participants from Finnish cohorts.
RESULTS: The consumption of coffee was found to be potentially associated with decreased levels of Macrophage colony-stimulating factor (β = -0.57, 95% CI -1.06 ~ -0.08; p = 0.022) and Stem cell growth factor beta (β = -0.64, 95% CI -1.16 ~ -0.12; p = 0.016), as well as an increase in TNF-related apoptosis-inducing ligand (β = 0.43, 95% CI 0.06 ~ 0.8; p = 0.023) levels. Conversely, tea intake was potentially correlated with a reduction in Interleukin-8 (β = -0.45, 95% CI -0.9 ~ 0; p = 0.045) levels. Moreover, our results indicated an association between alcohol consumption and decreased levels of Regulated on Activation, Normal T Cell Expressed and Secreted (β = -0.24, 95% CI -0.48 ~ 0; p = 0.047), as well as an increase in Stem cell factor (β = 0.17, 95% CI 0.02 ~ 0.31; p = 0.023) and Stromal cell-derived factor-1 alpha (β = 0.20, 95% CI 0.04 ~ 0.36; p = 0.013).
CONCLUSION: Revealing the interactions between beverage consumption and various inflammatory cytokines may lead to the discovery of novel therapeutic targets, thereby facilitating dietary interventions to complement clinical disease treatments.
METHODS: This was an observational study conducted among sepsis patients presented to ED of a tertiary university hospital from 18th January 2021 until 28th February 2021. ED overcrowding status was determined using the National Emergency Department Overcrowding Score (NEDOCS) scoring system. Sepsis patients were identified using Sequential Organ Failure Assessment (SOFA) scores and their door-to-antibiotic time (DTA) were recorded. Patient outcomes were hospital length of stay (LOS) and in-hospital mortality. Statistical analysis was done using Statistical Package for Social Sciences (SPSS) version 26. P-value of less than 0.05 for a two-sided test was considered statistically significant.
RESULTS: Total of 170 patients were recruited. Among them, 33 patients presented with septic shock and only 15% (n = 5) received antibiotics within one hour. Of 137 sepsis patients without shock, 58.4% (n = 80) received antibiotics within three hours. We found no significant association between ED overcrowding with DTA time (p = 0.989) and LOS (p = 0.403). However, in-hospital mortality increased two times during overcrowded ED (95% CI 1-4; p = 0.041).
CONCLUSION: ED overcrowding has no significant impact on DTA and LOS which are crucial indicators of sepsis care quality but it increases overall mortality outcome. Further research is needed to explore other factors such as lack of resources, delay in initiating fluid resuscitation or vasopressor so as to improve sepsis patient care during ED overcrowding.