OBJECTIVE: The current review was aimed to present a comprehensive overview and critical appraisal of majorly employed neuroimaging techniques for rational diagnosis and effective monitoring of effectiveness of employed therapeutic intervention for NPH. Moreover, a critical overview of recent developments and utilization of pharmacological agents for treatment of hydrocephalus has also been appraised.
RESULTS: Considering the complications associated with the shunt-based surgical operations, consistent monitoring of shunting via neuroimaging techniques hold greater clinical significance. Despite having extensive applicability of MRI and CT scan, these conventional neuroimaging techniques are associated with misdiagnosis or several health risks to patients. Recent advances in MRI (i.e., Sagittal-MRI, coronal-MRI, Time-SLIP (time-spatial-labeling-inversion-pulse), PC-MRI and diffusion-tensor-imaging (DTI)) have shown promising applicability in diagnosis of NPH. Having associated with several adverse effects with surgical interventions, non-invasive approaches (pharmacological agents) have earned greater interest of scientists, medical professional, and healthcare providers. Amongst pharmacological agents, diuretics, isosorbide, osmotic agents, carbonic anhydrase inhibitors, glucocorticoids, NSAIDs, digoxin, and gold-198 have been employed for management of NPH and prevention of secondary sensory/intellectual complications.
CONCLUSION: Employment of rational diagnostic tool and therapeutic modalities avoids misleading diagnosis and sophisticated management of hydrocephalus by efficient reduction of cerebrospinal fluid (CSF) production, reduction of fibrotic and inflammatory cascades secondary to meningitis and hemorrhage, and protection of brain from further deterioration.
OBJECTIVES: This paper discusses activity detection and analysis (ADA) using security robots in workplaces. The application scenario of this method relies on processing image and sensor data for event and activity detection. The events that are detected are classified for its abnormality based on the analysis performed using the sensor and image data operated using a convolution neural network. This method aims to improve the accuracy of detection by mitigating the deviations that are classified in different levels of the convolution process.
RESULTS: The differences are identified based on independent data correlation and information processing. The performance of the proposed method is verified for the three human activities, such as standing, walking, and running, as detected using the images and sensor dataset.
CONCLUSION: The results are compared with the existing method for metrics accuracy, classification time, and recall.
Methods: This cross-sectional study was conducted with 202 independently mobile OP (males 32%) in seven LTC homes in the Klang Valley of Malaysia. Trained personnel measured their anthropometrics, body composition, gait speed, hand grip strength and timed up-and-go (TUG) duration. Criteria of the European Working Group on Sarcopenia in Older People (EWGSOP) and of the Asian Working Group for Sarcopenia were used to identify the presence of sarcopenia. The mini-nutritional assessment (MNA) was used to determine their nutritional status. Additionally, logistic regression analysis was performed to identify significant risk factors associated with pre-sarcopenia/sarcopenia.
Results: Pre-sarcopenia/sarcopenia was detected in 103 (51%) OP. The significant risk factors were body mass index (BMI, weight/height2; adjusted odds ratio [AOR] = 0.44, P < 0.001), percentage of body fat (PBF; AOR = 1.26, P < 0.001), age group (≥ 80 years; AOR = 3.63, P = 0.025) and 'at risk of malnutrition' status (AOR = 2.63, P = 0.049).
Conclusion: Sarcopenia is common among OP in LCT homes. The risk increases with decreasing BMI, increasing PBF, age ≥ 80 years and suboptimal nutrition status.
Materials and Methods: Sixty-three diabetic foot patients admitted from June 15, 2019 to February 15, 2020. Methods included one-on-one interview for clinico-demographic data, physical examination to determine the classification. Patients were followed-up and outcomes were determined. Pearson Chi-square or Fisher's Exact determined association between clinico-demographic data, the classifications, and outcomes. The receiver operating characteristic (ROC) curve determined predictive abilities of classification systems and paired analysis compared the curves. Area Under the Receiver Operating Characteristic Curve (AUC) values used to compare the prediction accuracy. Analysis was set at 95% CI.
Results: Results showed hypertension, duration of diabetes, and ambulation status were significantly associated with major amputation. WIFi showed the highest AUC of 0.899 (p = 0.000). However, paired analysis showed AUC differences between WIFi, Wagner, and University of Texas classifications by grade were not significantly different from each other.
Conclusion: The WIFi, Wagner, and University of Texas classification systems are good predictors of major amputation with WIFi as the most predictive.
Methods: Forty stroke survivors were recruited (20 with DPN and 20 without DPN) in this cross-sectional study design. Instrumented timed up and go (iTUG) tests were conducted in three different tasking conditions (single task, dual motor and dual cognitive). APDM® Mobility Lab system was used to capture the gait parameters during the iTUG tests. A two-way mixed analysis of variance was used to determine the main effects of gait performance on three taskings during the iTUG test.
Results: Spatiotemporal gait parameters and turning performance (turning time and turning step times) were more affected by the tasking conditions in stroke survivors with DPN compared to those without DPN (P < 0.05).
Conclusion: Stroke survivors with DPN had difficulty walking while turning and performing a secondary task simultaneously.
Methods: Fifty-five primary knee OA (median age 69.0, interquartile range [IQR] 11.0) participated in the cross-sectional study. Three performance-based tests were performed in two sessions with a 1-week interval; 30-s chair stand test, 40-m fast-paced walk test and 9-step stair climb test. Relative reliability included intra-class correlation and Spearman's correlation coefficient (SPC). Absolute reliability included standard error of measurement, minimum detectable change, coefficient of variance, limit of agreement (LOA) and ratio LOA. Knee Injury and Osteoarthritis Outcome Score-Physical Function Short Form (KOOS-PS), knee extensor strength and pain scale were analysed for convergent validity using Pearson's correlation coefficient and SPC. Analysis of Covariance was utilised for known-groups validity.
Results: Relative and absolute reliability were all acceptable. LOA showed small systematic bias. Acceptable construct validity was only found with knee extensor strength. All tests demonstrated known-groups validity with medium to large effect size.
Conclusion: The OARSI minimum core set of performance-based tests demonstrated acceptable relative and absolute reliability and good known-groups validity but poor convergent validity.