BACKGROUND AND OBJECTIVES

data-mce-style="text-align: justify;">The Philippines faces challenges in the screening of tuberculosis (TB), one of them being the shortage in the health workforce who are skilled and allowed to screen TB. Deep learning neural networks (DLNNs) have shown potential in the TB screening process utilizing chest radiographs (CXRs). However, local studies on AIbased TB screening are limited. This study evaluated qXR3.0 technology's diagnostic performance for TB screening in Filipino adults aged 15 and older. Specifically, we evaluated the specificity and sensitivity of qXR3.0 compared to radiologists' impressions and determined whether it meets the World Health Organization (WHO) standards.

data-mce-style="text-align: justify;">A prospective cohort design was used to perform a study on comparing screening and diagnostic accuracies of qXR3.0 and two radiologist gradings in accordance with the Standards for Reporting Diagnostic Accuracy (STARD). Subjects from two clinics in Metro Manila which had qXR 3.0 seeking consultation at the time of study were invited to participate to have CXRs and sputum collected. Radiologists' and qXR3.0 readings and impressions were compared with respect to the reference standard Xpert MTB/RiF assay. Diagnostic accuracy measures were calculated.

data-mce-style="text-align: justify;">With 82 participants, qXR3.0 demonstrated 100% sensitivity and 72.7% specificity with respect to the reference standard. There was a strong agreement between qXR3.0 and radiologists' readings as exhibited by the 0.7895 (between qXR 3.0 and CXRs read by at least one radiologist), 0.9362 (qXR 3.0 and CXRs read by both radiologists), and 0.9403 (qXR 3.0 and CXRs read as not suggestive of TB by at least one radiologist) concordance indices.

data-mce-style="text-align: justify;">qXR3.0 demonstrated high sensitivity to identify presence of TB among patients, and meets the WHO standard of at least 70% specificity for detecting true TB infection. This shows an immense potential for the tool to supplement the shortage of radiologists for TB screening in the country. Future research directions may consider larger sample sizes to confirm these findings and explore the economic value of mainstream adoption of qXR 3.0 for TB screening.

BACKGROUND

data-mce-style="text-align: justify;">Six-pyruvoyl-tetrahydrobiopterin synthase (6-PTPS) deficiency is an inherited metabolic disorder which results in tetrahydrobiopterin (BH4) deficiency causing hyperphenylalaninemia.

data-mce-style="text-align: justify;">This study aimed to describe the clinical, biochemical, and radiologic profiles, and neurologic and developmental outcomes of patients diagnosed with 6-pyruvoyl tetrahydrobiopterin (PTPS) deficiency through newborn screening and confirmed by BH4 loading test, pterin analysis, and gene sequencing who were following-up with the metabolic team.

data-mce-style="text-align: justify;">The research was a single-center descriptive case series study design that was done at the Philippine General Hospital, a tertiary government hospital. The clinical, biochemical, radiologic profiles and neurodevelopmental evaluation of each patient were described.

data-mce-style="text-align: justify;">Nine patients from 1 year 2 months to 14 years 5 months of age were enrolled in the study. Clinical manifestations before treatment were hypotonia, poor suck, and seizure. The most common clinical manifestation even after treatment initiation was seizure. The mean phenylalanine level on newborn screening was 990.68 umol/L, but after treatment was started, mean levels ranged from 75.69 to 385.09 umol/L. Two of the patients had focal atrophy of the posterior lobe on brain imaging. Pathogenic variants on molecular analysis were all missense, with two predominant variants, c.155A>G and c.58T>C. Eight of the nine patients had varying degrees of developmental delay or intellectual disability, while the remaining patient had signs of a learning disorder.

data-mce-style="text-align: justify;">Newborn screening has played a crucial role in the early identification and management of patients with hyperphenylalaninemia due to 6-PTPS deficiency. Confirmation of diagnosis through determination of DHPR activity, urine pterins and/or molecular analysis is necessary for appropriate management. However, despite early initiation of treatment, neurodevelopmental findings of patients with 6-PTPS deficiency were still unsatisfactory.

BACKGROUND AND OBJECTIVES

data-mce-style="text-align: justify;">One of the effects of the COVID-19 pandemic on medical education is an increased awareness and use of social media (SocMed) to facilitate learning. However, literature on the use of SocMed in medical education has focused primarily on educator-led teaching activities. Our study aimed to describe SocMed initiatives that were student-led, particularly for information dissemination and peer collaborative learning, and to elicit perceptions of medical students towards such activities.

data-mce-style="text-align: justify;">An online survey on SocMed usage in medical education was sent to all first- and second-year medical students at the University of the Philippines Manila College of Medicine from October to December 2021. The questionnaire collected data on demographics, SocMed habits and preferences, and perceived advantages and disadvantages of SocMed. Descriptive statistics were calculated while the free-text responses were grouped into prominent themes and summarized.

data-mce-style="text-align: justify;">We received a total of 258 responses (71%) out of 361 eligible participants. Overall, 74% found SocMed platforms to be very and extremely helpful; 88% recommended its continued use. The most popular SocMed platforms for different tasks were as follows: Discord for independent study groups and for conducting peer tutoring sessions; Facebook Messenger for reading reminders; Telegram for reading announcements related to academics and administrative requirements, and for accessing material provided by classmates and professors.

data-mce-style="text-align: justify;">The high uptake of SocMed among medical students may be attributed to its accessibility and costefficiency. The use of a particular SocMed platform was dependent on the students’ needs and the platform's features. Students tended to use multiple SocMed platforms that complemented one another. SocMed also had disadvantages, such as the potential to distract from academic work and to become a source of fatigue. Educators must engage with students to understand how SocMed platforms can be integrated into medical education, whether in the physical or virtual learning environment.

BACKGROUND

data-mce-style="text-align: justify;">Community Health Workers (CHWs) play a vital role in addressing community healthcare needs, yet little is known about their psychosocial status and job satisfaction. This study aimed to describe the psychosocial status and job satisfaction of CHWs, and examine the factors associated with their job satisfaction.

data-mce-style="text-align: justify;">A cross-sectional study was conducted among 440 CHWs aged 25-60 years working in urban and rural areas of Batangas, Philippines. Linear regression models were used to examine the association between psychosocial factors and job satisfaction. Other factors associated with job satisfaction were also examined.

data-mce-style="text-align: justify;">Despite 90.0% of CHWs reporting high perceived stress and 52.1% experiencing high depressive symptoms, they demonstrated relatively high job satisfaction (mean [standard deviation]= 80.05 [17.56]; range= 0-100) and high perceived social support (mean [standard deviation]= 25.09 [2.93]; range= 10-30). Among psychosocial factors, only perceived social support was associated with job satisfaction (unstandardized beta [B] 0.93; 95% confidence interval [CI] 0.44, 1.41). Other factors associated with job satisfaction include fixed working hours (B 4.71; 95% CI 0.49, 8.94), work amenities (B 7.37; 95% Cl 0.03, 14.72), ≥21 years of work experience (B 5.64; 95% CI 0.35, 10.93), and working in rural areas (B 5.88; 95% CI 2.77, 8.99).

data-mce-style="text-align: justify;">Psychological factors such as perceived stress and depressive symptoms were not found to be associated with job satisfaction among CHWs. However, factors such as greater perceived social support, fixed working hours, work amenities, longer work experience, and working in rural areas were identified as contributors to higher levels of job satisfaction among CHWs.

data-mce-style="text-align: justify;">This reflective paper explored the philosophical foundations of lifelong learning and impactful research in the field of nursing. Anchored in personal experience and supported by scholarly literature, it illustrated the transformative power of continuous learning, the cultivation of research competence, and the moral responsibility of contributing meaningfully to society. A nurse researcher's journey is not defined by awards or accomplishment but by an unwavering dedication to knowledge creation, community involvement, and evidence-based practice. The "emptying one's cup" metaphor embodies intellectual humility, a mindset that keeps the mind open to learning, self-improvement, and meaningful service throughout one's career.

INTRODUCTION: Medical errors commonly occur in medical imaging departments. These errors are frequently influenced by patient safety culture. This study aimed to develop a suitable patient safety culture assessment tool for medical imaging departments. METHODS: Staff members of a teaching hospital medical imaging department were invited to complete the generic short version of the Safety Attitude Questionnaire (SAQ). Internal consistency and reliability were evaluated using Cronbach's α. Confirmatory factor analysis (CFA) was conducted to examine model fit. A cut-off of 60% was used to define the percentage positive responses (PPR). PPR values were compared between occupational groups. RESULTS: A total of 300 complete responses were received and the response rate was 75.4%. In reliability analysis, the Cronbach's α for the original 32-item SAQ was 0.941. Six subscales did not demonstrate good fit with CFA. A modified five-subscale, 22-item model (SAQ-MI) showed better fit (goodness-to-fit index ≥0.9, comparative fit index ≥ 0.9, Tucker-Lewis index ≥0.9 and root mean square error of approximation ≤0.08). The Cronbach's α for the 22 items was 0.921. The final five subscales were safety and teamwork climate, job satisfaction, stress recognition, perception of management and working condition, with PPR of 62%, 68%, 57%, 61% and 60%, respectively. Statistically significant differences in PPR were observed between radiographers, doctors and others occupational groups. CONCLUSION The modified five-factor, 22-item SAQ-MI is a suitable tool for the evaluation of patient safety culture in a medical imaging department. Differences in patient safety culture exist between occupation groups, which will inform future intervention studies.
Humans ; Surveys and Questionnaires ; Patient Safety ; Attitude of Health Personnel ; Diagnostic Imaging ; Reproducibility of Results ; Male ; Female ; Adult ; Job Satisfaction ; Factor Analysis, Statistical ; Middle Aged ; Hospitals, Teaching ; Safety Management ; Organizational Culture ; Medical Errors/prevention & control*

INTRODUCTION: Obstructive sleep apnoea (OSA) is a serious but underdiagnosed condition. Demand for the gold standard diagnostic polysomnogram (PSG) far exceeds its availability. More efficient diagnostic methods are needed, even in tertiary settings. Machine learning (ML) models have strengths in disease prediction and early diagnosis. We explored the use of ML with oximetry, demographic and anthropometric data to diagnose OSA. METHODS: A total of 2,996 patients were included for modelling and divided into test and training sets. Seven commonly used supervised learning algorithms were trained with the data. Sensitivity (recall), specificity, positive predictive value (PPV) (precision), negative predictive value, area under the receiver operating characteristic curve (AUC) and F1 measure were reported for each model. RESULTS: In the best performing four-class model (neural network model predicting no, mild, moderate or severe OSA), a prediction of moderate and/or severe disease had a combined PPV of 94%; one out of 335 patients had no OSA and 19 had mild OSA. In the best performing two-class model (logistic regression model predicting no-mild vs. moderate-severe OSA), the PPV for moderate-severe OSA was 92%; two out of 350 patients had no OSA and 26 had mild OSA. CONCLUSION Our study showed that the prediction of moderate-severe OSA in a tertiary setting with an ML approach is a viable option to facilitate early identification of OSA. Prospective studies with home-based oximeters and analysis of other oximetry variables are the next steps towards formal implementation.
Humans ; Oximetry/methods* ; Sleep Apnea, Obstructive/diagnosis* ; Male ; Female ; Middle Aged ; Machine Learning ; Polysomnography ; Adult ; Anthropometry ; ROC Curve ; Aged ; Algorithms ; Predictive Value of Tests ; Sensitivity and Specificity ; Neural Networks, Computer ; Demography

INTRODUCTION: In this study, we aimed to compare the performance of a convolutional neural network (CNN)-based deep learning model that was trained on a dataset of normal and abnormal paediatric elbow radiographs with that of paediatric emergency department (ED) physicians on a binomial classification task. METHODS: A total of 1,314 paediatric elbow lateral radiographs (patient mean age 8.2 years) were retrospectively retrieved and classified based on annotation as normal or abnormal (with pathology). They were then randomly partitioned to a development set (993 images); first and second tuning (validation) sets (109 and 100 images, respectively); and a test set (112 images). An artificial intelligence (AI) model was trained on the development set using the EfficientNet B1 network architecture. Its performance on the test set was compared to that of five physicians (inter-rater agreement: fair). Performance of the AI model and the physician group was tested using McNemar test. RESULTS: The accuracy of the AI model on the test set was 80.4% (95% confidence interval [CI] 71.8%-87.3%), and the area under the receiver operating characteristic curve (AUROC) was 0.872 (95% CI 0.831-0.947). The performance of the AI model vs. the physician group on the test set was: sensitivity 79.0% (95% CI: 68.4%-89.5%) vs. 64.9% (95% CI: 52.5%-77.3%; P = 0.088); and specificity 81.8% (95% CI: 71.6%-92.0%) vs. 87.3% (95% CI: 78.5%-96.1%; P = 0.439). CONCLUSION The AI model showed good AUROC values and higher sensitivity, with the P-value at nominal significance when compared to the clinician group.
Humans ; Deep Learning ; Child ; Retrospective Studies ; Male ; Female ; Radiography/methods* ; ROC Curve ; Elbow/diagnostic imaging* ; Neural Networks, Computer ; Child, Preschool ; Elbow Joint/diagnostic imaging* ; Emergency Service, Hospital ; Adolescent ; Infant ; Artificial Intelligence

OBJECTIVE: To observe the effects of Huayu Tongluo (transforming stasis and unblocking collaterals) moxibustion on learning-memory ability and hippocampal mammalian sterile 20-like kinase 1 (Mst1)/nuclear factor κB (NF-κB) p65 pathway related to inflammatory response in rats with vascular dementia (VD). METHODS: A total of 60 male Wistar rats of SPF grade were randomly divided into a sham operation group (12 rats) and a modeling group (48 rats). VD model was established by the method of modified bilateral common carotid artery permanent ligation in the modeling group. Thirty-six rats with successful modeling were randomly divided into a model group, a moxibustion group and a western medication group, with 12 rats in each group. Huayu Tongluo moxibustion was applied at "Dazhui" (GV14), "Baihui" (GV20) and "Shenting" (GV24) in the moxibustion group, 20 min each time, once a day, 7 day-intervention was as one course, and 1 day-interval was taken between two courses, for a total of 3 courses. In the western medication group, piracetam was given 0.72 mg/kg by intragastric administration, twice a day, the course of intervention was same as that of the moxibustion group. The learning-memory ability was detected by Morris water maze test; the morphology of hippocampal CA1 region was observed by HE staining; the mRNA expression of Mst1, M1 microglia markers CD86, interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) was detected by real-time PCR; the levels of IL-6 and TNF-α in hippocampus were detected by ELISA; and the protein expression of Mst1 and NF-κB p65 in hippocampus was detected by Western blot in rats of each group. RESULTS: Compared with the sham operation group, the escape latency was prolonged in the model group (P<0.05); compared with the model group, the escape latency was shortened in the moxibustion group and the western medication group (P<0.05). The cells in the CA1 region of hippocampus were disordered, cell collapse and irregular nuclei could be observed in the model group; compared with the model group, the cell arrangement in the CA1 region of hippocampus was more regular, and the damage was improved in the moxibustion group and the western medication group. Compared with the sham operation group, the mRNA expression of Mst1, CD86, IL-6 and TNF-α, as well as the protein expression of Mst1, NF-κB p65 in hippocampus were increased in the model group (P<0.05). Compared with the model group, the mRNA expression of Mst1, CD86, IL-6 and TNF-α, as well as the protein expression of Mst1, NF-κB p65 in hippocampus were decreased in the moxibustion group and the western medication group (P<0.05). Compared with the sham operation group, the levels of IL-6 and TNF-α in hippocampus were increased in the model group (P<0.05). Compared with the model group, the levels of IL-6 and TNF-α in hippocampus were decreased in the moxibustion group and the western medication group (P<0.05). CONCLUSION Huayu Tongluo moxibustion can improve the learning-memory ability of VD rats, the mechanism may be related to regulating the activation of microglia through Mst1/NF-κB p65 pathway, reducing the release of pro-inflammatory factors i.e. IL-6 and TNF-α, so as to alleviating the damage of inflammatory factors in the hippocampus of VD rats.
Animals ; Male ; Rats ; Moxibustion ; Hippocampus/metabolism* ; Rats, Wistar ; Dementia, Vascular/genetics* ; Memory/drug effects* ; Humans ; Transcription Factor RelA/genetics* ; Learning ; Protein Serine-Threonine Kinases/genetics* ; Acupuncture Points ; Interleukin-6/genetics* ; Signal Transduction/drug effects* ; Drugs, Chinese Herbal

This study aims to develop an abdominal acupoint localization system based on computer vision and convolutional neural networks (CNNs). To address the challenge of abdominal acupoint localization, a multi-task CNNs architecture was constructed and trained to locate the Shenque (CV8) and human body boundaries. Based on the identified Shenque (CV8), the system further deduces key characteristics of four acupoints: Shangwan (CV13), Qugu (CV2), and bilateral Daheng (SP15). An affine transformation matrix is applied to accurately map image coordinates to an acupoint template space, achieving precise localization of abdominal acupoints. Testing has verified that this system can accurately identify and locate abdominal acupoints in images. The development of this localization system provides technical support for TCM remote education, diagnostic assistance, and advanced TCM equipment, such as intelligent acupuncture robots, facilitating the standardization and intelligent advancement of acupuncture.
Acupuncture Points ; Humans ; Deep Learning ; Abdomen/diagnostic imaging* ; Neural Networks, Computer ; Acupuncture Therapy ; Image Processing, Computer-Assisted