METHOD: A multicenter cross-sectional observational study was conducted in 388 diabetes patients attending daily diabetes clinics and teaching hospitals in Pakistan's twin city between August 2019 and February 2020. The chi-square test and linear regression were used to detect RLS-related factors in type 2 diabetes mellitus.
RESULTS: The prevalence of RLS found was; 3.1% patients with diabetes were suffering from very severe RLS, 23.5% from severe RLS, 34% from moderate RLS, 21.1% from mild RLS and 18.3% from non-RLS. Gender, age, education, blood glucose fasting (BSF), blood glucose random (BSR) and HBA1c were found to be significant predictors of RLS in patients with diabetes.
CONCLUSION: Policy makers can develop local interventions to curb the growing RLS prevalence by keeping in control the risk factors of RLS in people living with type 2 diabetes.
OBJECTIVES: In this manuscript, the Interaction Modeling and Classification Scheme (IMCS) is introduced to improve the accuracy of HRI. This scheme consists of two phases, namely error classification and input mapping. In the error classification process, the input is analyzed for its events and conditional discrepancies to assign appropriate responses in the input mapping phase. The joint process is aided by a linear learning model to analyze the different conditions in the event and input detection.
RESULTS: The performance of the proposed scheme shows that it is capable of improving the interaction accuracy by reducing the ratio of errors and interaction response by leveraging the information extraction from the discrete and successive human inputs.
CONCLUSION: The fetched data are analyzed by classifying the errors at the initial stage to achieve reliable responses.
Materials and Methods: This research introduced a dual probe detection system involving aptamers and antibodies to identify Aβ. Aptamers and antibodies were attached to the gold (Au) urchin and hybrid on the carbon nanohorn-modified surface. The nanohorn was immobilized on the sensor surface by using an amine linker, and then a Au urchin dual probe was immobilized.
Results: This dual probe-modified surface enhanced the current flow during Aβ detection compared with the surface with antibody as the probe. This dual probe interacted with higher numbers of Aβ peptides and reached the detection limit at 10 fM with R2=0.992. Furthermore, control experiments with nonimmune antibodies, complementary aptamer sequences and control proteins did not display the current responses, indicating the specific detection of Aβ.
Conclusion: Aβ-spiked artificial cerebrospinal fluid showed a similar response to current changes, confirming the selective identification of Aβ.
Objective: To determine the additional relationship between factors discovered by searching for sociodemographic and metastasis factors, as well as treatment outcomes, which could help improve the prediction of the survival rate in cancer patients. Material and Methods. A total of 56 patients were recruited from the ambulatory clinic at the Hospital Universiti Sains Malaysia (USM). In this retrospective study, advanced computational statistical modeling techniques were used to evaluate data descriptions of several variables such as treatment, age, and distant metastasis. The R-Studio software and syntax were used to implement and test the hazard ratio. The statistics for each sample were calculated using a combination model that included methods such as bootstrap and multiple linear regression (MLR).
Results: The statistical strategy showed R demonstrates that regression modeling outperforms an R-squared. It demonstrated that when data is partitioned into a training and testing dataset, the hybrid model technique performs better at predicting the outcome. The variable validation was determined using the well-established bootstrap-integrated MLR technique. In this case, three variables are considered: age, treatment, and distant metastases. It is important to note that three things affect the hazard ratio: age (β 1: -0.006423; p < 2e - 16), treatment (β 2: -0.355389; p < 2e - 16), and distant metastasis (β 3: -0.355389; p < 2e - 16). There is a 0.003469102 MSE for the linear model in this scenario.
Conclusion: In this study, a hybrid approach combining bootstrapping and multiple linear regression will be developed and extensively tested. The R syntax for this methodology was designed to ensure that the researcher completely understood the illustration. In this case, a hybrid model demonstrates how this critical conclusion enables us to better understand the utility and relative contribution of the hybrid method to the outcome. The statistical technique used in this study, R, demonstrates that regression modeling outperforms R-squared values of 0.9014 and 0.00882 for the predicted mean squared error, respectively. The conclusion of the study establishes the superiority of the hybrid model technique used in the study.
METHODS: We used the 11-item Duke Social Support Index to assess perceived social support through a face-to-face interview. Higher scores indicate better social support. Linear regression analysis was carried out to determine the factors that influence perceived social support by adapting the conceptual model of social support determinants and its impact on health.
RESULTS: A total of 3959 respondents aged ≥60 years completed the Duke Social Support Index. The estimated mean Duke Social Support Index score was 27.65 (95% CI 27.36-27.95). Adjusted for confounders, the factors found to be significantly associated with social support among older adults were monthly income below RM1000 (-0.8502, 95% CI -1.3523, -0.3481), being single (-0.5360, 95% CI -0.8430, -0.2290), no depression/normal (2.2801, 95% CI 1.6666-2.8937), absence of activities of daily living (0.9854, 95% CI 0.5599-1.4109) and dependency in instrumental activities of daily living (-0.3655, 95% CI -0.9811, -0.3259).
CONCLUSION: This study found that low income, being single, no depression, absence of activities of daily living and dependency in instrumental activities of daily living were important factors related to perceived social support among Malaysian older adults. Geriatr Gerontol Int 2020; 20: 63-67.
MATERIALS AND METHODS: We retrospectively assessed 107 cadavers that had undergone conventional autopsy and PMCT. We made 5 measurements from the PMCT that included cervical length (CL), thoracic length (TL), lumbosacral length (LS), total column length of the spine, excluding the sacrum and coccyx (TCL), and ellipse line measurement of the whole spine, excluding the sacrum and coccyx (EL). We compared these anthropometric PMCT measurements with AL and correlated them using linear regression analysis.
RESULTS: The results showed a significant linear relationship existed between TL and LS with AL, which was higher in comparison with the other parameters than the rest of the spine parameters. The linear regression formula derived was: 48.163 + 2.458 (TL) + 2.246 (LS).
CONCLUSIONS: The linear regression formula derived from PMCT spine length parameters particularly thoracic and lumbar spine gave a finer correlation with autopsy body length and can be used for accurate estimation of cadaveric height. To the best of our knowledge, this is the first ever linear regression formula for cadaveric height assessment using only post mortem CT spine length measurements.
Methods: Cross-sectional data from 62 developing countries were used to run several multivariate linear regressions. R2 was used to compare the powers of MPI with income-poverties (income poverty gaps [IPG] at 1.9 and 3.1 USD) in explaining LE.
Results: Adjusting for controls, both MPI (β =-0.245, P<0.001) and IPG at 3.1 USD (β=-0.135, P=0.044) significantly correlates with LE, but not IPG at 1.9 USD (β=-0.147, P=0.135). MPI explains 12.1% of the variation in LE compared to only 3.2% explained by IPG at 3.1 USD. The effect of MPI on LE is higher on female (β=-0.210, P<0.001) than male (β=-0.177, P<0.001). The relative influence of the deprivation indictors on LE ranks as follows (most to least): Asset ownership, drinking water, cooking fuel, flooring, child school attendance, years of schooling, nutrition, mortality, improved sanitation, and electricity.
Conclusion: Interventions to reduce poverty and improve LE should be guided by MPI, not income poverty indices. Such policies should be female-oriented and prioritized based on the relative influence of the various poverty deprivation indicators on LE.
METHODS: Twenty-nine asymptomatic subjects were enrolled prospectively (age: mean 34.31, range 23-50; 14 men, 15 women) from August 2016 to April 2017. Qualitative analysis of muscles was done using Goutallier's system on CT and MRI. Quantitative analysis entailed cross sectional area (CSA) on CT and MRI, Hounsfield unit (HU) on CT, fat fraction using two-point Dixon technique on MRI. Three readers independently analyzed the images; intra- and inter-observer agreements were measured. Linear regression and Spearman's analyses were used for correlation with demographic data.
RESULTS: CSA values were significantly higher in men (p
METHODS/DESIGN: This open-labelled, randomised controlled trial (RCT) will randomly allocate patients into intervention and control groups. Ambulated Malaysian aged over 18 years and scheduled for elective surgery for (suspected) GC, will be included in this study. The intervention group will be given whey-protein-infused carbohydrate-loading drinks on the evening before their operation and 3 h before their operation as well as started on early oral feeding 4 h post-operatively. The control group will be fasted overnight pre-operation and only allowed plain water, and return to a normal diet is allowed when bowel sounds return post-operatively. The primary outcomes of study are length of post-operative hospital stay, length of clear-fluid tolerance, solid-food tolerance and bowel function. Additional outcome measures are changes in nutritional status, biochemical profile and functional status. Data will be analysed on an intention-to-treat basis.
TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT03667755. Retrospectively registered on 12 September 2018; Protocol version: version 3 dated 27 September 2017.
OBJECTIVE: To investigate the relationship between a +ve postoperative Upper Instrumented Vertebra (UIV) (≥0°) tilt angle and the risk of medial shoulder/neck and lateral shoulder imbalance among Lenke 1 and 2 Adolescent Idiopathic Scoliosis (AIS) patients following Posterior Spinal Fusion.
SUMMARY OF BACKGROUND DATA: Current UIV selection strategy has poor correlation with postoperative shoulder balance. The relationship between a +ve postoperative UIV tilt angle and the risk of postoperative shoulder and neck imbalance was unknown.
METHODS: One hundred thirty-six Lenke 1 and 2 AIS patients with minimum 2 years follow-up were recruited. For medial shoulder and neck balance, patients were categorized into positive (+ve) imbalance (≥+4°), balanced, or negative (-ve) imbalance (≤-4°) groups based on T1 tilt angle/Cervical Axis measurement. For lateral shoulder balance, patients were classified into +ve imbalance (≥+3°) balanced, and -ve imbalance (≤-3°) groups based on Clavicle Angle (Cla-A) measurement. Linear regression analysis identified the predictive factors for shoulder/neck imbalance. Logistic regression analysis calculated the odds ratio of shoulder/neck imbalance for patients with +ve postoperative UIV tilt angle.
RESULTS: Postoperative UIV tilt angle and preoperative T1 tilt angle were predictive of +ve medial shoulder imbalance. Postoperative UIV tilt angle and postoperative PT correction were predictive of +ve neck imbalance. Approximately 51.6% of patients with +ve medial shoulder imbalance had +ve postoperative UIV tilt angle. Patients with +ve postoperative UIV tilt angle had 14.9 times increased odds of developing +ve medial shoulder imbalance and 3.3 times increased odds of developing +ve neck imbalance. Postoperative UIV tilt angle did not predict lateral shoulder imbalance.
CONCLUSION: Patients with +ve postoperative UIV tilt angle had 14.9 times increased odds of developing +ve medial shoulder imbalance (T1 tilt angle ≥+4°) and 3.3 times increased odds of developing +ve neck imbalance (cervical axis ≥+4°).
LEVEL OF EVIDENCE: 4.