ABSTRACT
BACKGROUND: The first step towards creating a sound educational environment and healthcare in a medical institute is employing medical teachers who maintain ethical behavior in their professional practice. A method where bias and subjectivity can be minimized is by making the recruitment process objective. MATERIAL AND METHODS: The recruitment started as an offline process and was soon converted into an online form incorporating parameters for scoring. A total of 1,151 medical teachers had submitted their applications for posts in various departments, and 778 candidates were shortlisted and called for an interview. After the interview process, a unique symposium on the selection of medical teachers was organized. The feedback was incorporated into the online application that was released for the subsequent phases of recruitment. RESULTS: The response rate of the study was 96.55%. Analysis of the feedback by the applicants showed that 47.59% of the applicants were of the opinion that the prevailing selection process in the country needs a change; 84.14% felt that the inclusion of objective criteria would make the selection process more transparent; and 91.03% were happy with the stratification of marks; 82.75% of the applicants and experts felt that knowledge of statistics for quality research and publications in indexed and institutional journals may be considered for the selection process; and 52.41% thought that all authors of an article should be given equal weightage. Adopting a fairly new concept of workplace-based assessment (WPBA) in India was acceptable to 83.45%. CONCLUSIONS: Parameter-based, objective selection reduces bias, and merit alone is recognized.
ABSTRACT
Background: Hypertension is a modifiable risk factor for cardiovascular disease and is responsible for major deaths due to stroke and coronary heart disease. Several pharmacological and non-pharmacological interventions for reducing blood pressure have been tried earlier. Modulating brain regions such as prefrontal cortex (PFC) to channelize activities is an effective tool to target blood pressure. Purpose: Prefrontal cortex (PFC) exerts inhibitory control over sympathoexcitatory circuits, which was explored using a novel reaction time paradigm. Methods: Thirty participants of both genders in the age group 40-70 years with established hypertension were included. A structured reaction time paradigm was designed to include psychomotor and visuomotor elements with integrated sensory attention and motor performance tasks. Blood pressure, Lead II ECG, and EEG from F3 and F4 were recorded. A paired t-test was used to examine the variations in these parameters across tasks. Results: A significant reduction in mean arterial pressure by 4.04 mmHg (p = .0232) during the visuomotor task and a reduction of 3.38 mmHg during the auditory cue task (p = .0446) were observed. Analysis of the difference in heart rate has shown a profound decrease after passive listening tasks by 3.7 beats (p < .0001*). Spectral analysis from F3 and F4 shows high power in low-frequency zone of EEG indicating a relaxed state during auditory cues and passive listening. Conclusion: The reaction time paradigm, when applied to hypertensives, helped decrease blood pressure and heart rate and improved the high frequency (HF) component of heart rate variability, indicating parasympathetic dominance. Such reward-oriented paradigms may act as biofeedback modules that cause hyperactivity of the PFC to suppress the sympathoexcitatory circuit with increased parasympathetic activity beneficial to hypertensive individuals.
ABSTRACT
Background: COVID-19 pandemic has affected mankind globally. After the three waves since March 2020, the threat continues instilling fear in the minds. Vital parameter monitoring through remote health monitoring system (RHMS) becomes critical for effective disease management and manpower safety and confidence. In a low resource setting like India, a comprehensive, wearable, and remotely operable device that is economical was required to be introduced for COVID-19 care. Present study validated the remote health monitoring device named COVIDBEEP with gold standard equipment. Materials and Methods: Six parameters, namely heart rate, SpO2, respiratory rate, temperature, blood pressure, and ECG were acquired in the supine position using the devices. Result: Analysis was performed using Graph Pad Prism. Intraclass correlation coefficients were used to measure concurrent validity. Bland-Altman graphs were plotted to know the agreement for each vital parameter. Confidence limits were set at 95%. All the parameters recorded from the devices showed a significant correlation with an "r" value between 0.5 and 0.9 with P value between 0.001 and 0.0002. Bland-Altman plots showed a minimum bias of 0.033 for heart rate and maximum of 3.5 for systolic blood pressure and respiratory rate. Conclusion: The association between the parameters recorded by the devices strengthened as the time of collection of data increased. Agreement between the two methods in 95% confidence interval was also proven to be significant for the parameters. Therefore, the indigenously developed COVIDBEEP has shown good validity in comparison to standard monitoring device.
ABSTRACT
In the context of the recent pandemic, the necessity of inexpensive and easily accessible rapid-test kits is well understood and need not be stressed further. In light of this, we report a multi-nucleotide probe-based diagnosis of SARS-CoV-2 using a bioelectronics platform, comprising low-cost chemiresistive biochips, a portable electronic readout, and an Android application for data acquisition with machine-learning-based decision making. The platform performs the desired diagnosis from standard nasopharyngeal and/or oral swabs (both on extracted and non-extracted RNA samples) without amplifying the viral load. Being a reverse transcription polymerase chain reaction-free hybridization assay, the proposed approach offers inexpensive, fast (time-to-result: ≤ 30 min), and early diagnosis, as opposed to most of the existing SARS-CoV-2 diagnosis protocols recommended by the WHO. For the extracted RNA samples, the assay accounts for 87 and 95.2% test accuracies, using a heuristic approach and a machine-learning-based classification method, respectively. In case of the non-extracted RNA samples, 95.6% decision accuracy is achieved using the heuristic approach, with the machine-learning-based best-fit model producing 100% accuracy. Furthermore, the availability of the handheld readout and the Android application-based simple user interface facilitates easy accessibility and portable applications. Besides, by eliminating viral RNA extraction from samples as a pre-requisite for specific detection, the proposed approach presents itself as an ideal candidate for point-of-care SARS-CoV-2 diagnosis.
