METHODS: in this study, a fixed retrospective cohort design has been conducted by using data from the Indonesia Family Life Survey (IFLS) in 2007 and 2014. A total of 6,863 respondents who were not diagnosed with NCD by medical personnel in 2007 were successfully traced. After being controlled for covariates, the association between NCD type and poor physical function was measured by using the Adjusted Risk Ratio (ARR) and Population Attributable Risk (PAR).
RESULTS: respondents with poor physical function were at a significantly increased of being diagnosed with stroke (ARR: 6.9, 95%CI: 4.3-10.9), diabetes (ARR: 3.1, 95%CI: 2.4-4.1), or heart disease (ARR: 3.2, 95%CI: 2.4-4.5). The PAR score of respondents with diabetes was 0.006, meaning 0.6% of diabetes cases are attributed to poor physical function and can therefore be prevented if people maintain good physical function.
CONCLUSION: poor physical function can be assessed to identify risk of diabetes, heart disease, and stroke. Healthcare personnel should provide education programs that inform patients on the importance of maintaining a healthy physical ability.
METHODS: A retrospective study was conducted on 543 mammograms of 467 Malays, 48 Chinese, and 28 Indians in a middle-income nation. Three breast radiologists interpreted the examinations independently in two reading sessions (with and without AI support). Breast density and BI-RADS categories were assessed, comparing the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) results.
RESULTS: Of 543 mammograms, 69.2% had lesions detected. Biopsies were performed on 25%(n=136), with 66(48.5%) benign and 70(51.5%) malignant. Substantial agreement in density assessment between the radiologist and AI software (κ =0.606, p < 0.001) and the BI-RADS category with and without AI (κ =0.74, p < 0.001). The performance of the AI software was comparable to the traditional methods. The sensitivity, specificity, PPV, and NPV or radiologists alone, radiologist + AI, and AI alone were 81.9%,90.4%,56.0%, and 97.1%; 81.0%, 93.1%,55.5%, and 97.0%; and 90.0%,76.5%,36.2%, and 98.1%, respectively. AI software enhances the accuracy of lesion diagnosis and reduces unnecessary biopsies, particularly for BI-RADS 4 lesions. The AI software results for synthetic were almost similar to the original 2D mammography, with AUC of 0.925 and 0.871, respectively.
CONCLUSION: AI software may assist in the accurate diagnosis of breast lesions, enhancing the efficiency of breast lesion diagnosis in a mixed population of opportunistic screening and diagnostic patients.
KEY MESSAGES: • The use of artificial intelligence (AI) in mammography for population-based breast cancer screening has been validated in high-income nations, with reported improved diagnostic performance. Our study evaluated the usage of an AI tool in an opportunistic screening setting in a multi-ethnic and middle-income nation. • The application of AI in mammography enhances diagnostic accuracy, potentially leading to reduced unnecessary biopsies. • AI integration into the workflow did not disrupt the performance of trained breast radiologists, as there is a substantial inter-reader agreement for BI-RADS category assessment and breast density.
METHODS: A comparative cross-sectional study was conducted between August 2016 and May 2018 involving type 2 DM patients with no DR, non-proliferative DR (NPDR), and proliferative DR (PDR). Tear samples were collected using no.41 Whatman filter paper (Schirmer strips) and 5 mL blood samples were drawn by venous puncture. VEGF levels in tears and serum were measured by enzyme-linked immunosorbent assay.
RESULTS: A total of 88 type 2 DM patients (no DR: 30 patients, NPDR: 28 patients, PDR: 30 patients) were included in the study. Mean tear VEGF levels were significantly higher in the NPDR and PDR groups (114.4 SD 52.5 pg/mL and 150.8 SD 49.7 pg/mL, respectively) compared to the no DR group (40.4 SD 26.5 pg/mL, p < 0.001). There was no significant difference in the mean serum VEGF levels between the three groups. There was a fair correlation between serum and tear VEGF levels (p = 0.015, r = 0.263).
CONCLUSION: VEGF levels in tears were significantly higher amongst diabetic patients with DR compared to those without DR and were significantly associated with the severity of DR. There was a fair correlation between serum and tear VEGF levels. Detection of VEGF in tears is a good non-invasive predictor test for the severity of DR. A large cohort study is needed for further evaluation.
DISCUSSION: As surgery and radiotherapy alter the appearance of the breasts, distinguishing between recurrence and benign post-surgical changes can be challenging radiologically due to overlapping features. Despite this, differentiation between these two entities is usually possible by recognizing characteristic features of post-treatment sequelae and the evolution of the appearance of the conservatively treated breast by comparing interval findings on serial studies.
CONCLUSION: This pictorial review aims to describe the typical and unusual features of post-treated breasts in the multimodality imaging workup of an established breast care centre in a teaching hospital in Malaysia.
METHOD: This pilot study screened 60 patients who underwent ultrasound-guided supradiaphragmatic central venous catheter insertion. We compared the investigators' guidewire's J-tip detection, D50% rapid atrial swirl sign (RASS) findings on the RVI-PLAX view and the central venous catheter tip on chest radiograph. We also compared the mean capillary blood sugar level before and after the 5 ml D50% flush.
RESULTS: No guidewire J-tips were detected from the RVI-PLAX view. The first and second investigators' diagnosis of central venous catheter malposition detected on RVI-PLAX CEUS achieved an almost perfect agreement (κ = 1.0 (95% confidence interval (CI): 0.90 to 1.0), p