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Nevin Manimala Statistics

Working modes and evaluation of perceived stress during the Covid-19 pandemic

G Ital Med Lav Ergon. 2021 Dec;43(4):341-351.

ABSTRACT

Introduction. The global sanitary crisis due to covid 19 has had an unprecedent impact on human health and on the global economy creating unexpected challenges on work life. In Italy in order to limit the velocity of virus transmission, measures aimed towards social distancing were adopted by suspending all non essential working activities, with the recommendation of the maximum use of smart working (DPCM 01 MARCH 2020). Literature regarding precedent experiences worldwide on the impact of epidemic or pandemic flu viruses on the working enviroment report of a strong presence of correlated work stress. Objectives. The study is focalized in identifying the individual stress level correlated to work percieved in workers in the context of the unexpected scenario in adapting to work in a short time period relative to the emergency context. Materials and Methods. An epidemiological observational survey was conducted on the web during the months of May and June. The workers were invited in answering a questionnaire using a dedicated link. The questionnaire consisted in a introductive scheme(card) built ad hoc for the study containing information for the socio-demographic variables and work experience. The Evaluation Rapid Stress scale (VRS) was used for the rating of the subjective stress. The t Student test was used for the independant samples in the assay for the average scores of the VRS for sex and age. The ANOVA test was used in order to compare the various scores of the VRS in the three different working modes investigated (work on site, smart working or for both the modalities). A p0.05 was considered as level of significance. The statistical assay was conducted with the STATA software packet. Results. 337 workers answered the questionnaire. The rating of the VRS scores for sex highlighted significative differences between men and women in the levels of anxiety, depression, somatization and aggression showing higher values in women. The highest total scores of the VRS questionnaire and those related to the anxiety and somatization dimensions express higher levels of stress levels in response to the emergency situation in workers who carry out their activity in a on-site mode over the age of 40 and in parents. The comparison with the scores reported between the different working modes was resulted statistically significant. Conclusions. The results of our investigation are an expression of the perception of a widespread danger, linked to the threat of contracting the COVID-19 virus, whose mode and speed of transmission is surprising and for which therapy and in definitive treatment is not yet available. This leads to a series of emotional reactions in which stress is the main condition. The timely exploration aimed at the individuation of a stress problem in the working environment is extremely important especially in emergency situations in order to implement appropriate strategies of prevention.

PMID:35049158

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Optimization of 99m Tc whole-body SPECT/CT image quality: A phantom study

J Appl Clin Med Phys. 2022 Jan 20:e13528. doi: 10.1002/acm2.13528. Online ahead of print.

ABSTRACT

Investigate the impact of acquisition time and reconstruction parameters on single-photon emission computed tomography/computed tomography (SPECT/CT) image quality with the ultimate aim of finding the shortest possible acquisition time for clinical whole-body SPECT/CT (WB-SPECT/CT) while maintaining image quality METHODS: The National Electrical Manufacturers Association (NEMA) image quality measurements were performed on a SPECT/CT imaging system using a NEMA International Electrotechnical Commission (IEC) phantom with spherical inserts of varying diameter (10-37 mm), filled with 99m Tc in activity sphere-to-background concentration ratio of 8.5:1. A gated acquisition was acquired and binned data were summed to simulate acquisitions of 15, 8, and 3 s per projection angle. Images were reconstructed on a Hermes (HERMES Medical Solutions AB, Stockholm, Sweden) workstation using eight subsets and between 4 and 24 iterations of the three-dimensional (3D) ordered subset expectation maximization (OSEM) algorithm. Reconstructed images were post-smoothed with 3D Gaussian filter ranging from 0 to 12 mm full-width at half maximum (FWHM). Contrast recovery, background variability, and contrast-to-noise ratio were evaluated RESULTS: As expected, the spheres were more clearly defined as acquisition time and count statistics improved. The optimal iteration number and Gaussian filter were determined from the contrast recovery convergence and level of noise. Convergence of contrast recovery was observed at eight iterations while 12 iterations yielded stabilized values at all acquisition times. In addition, it was observed that applying 3D Gaussian filter of 8-12 mm FWHM suppressed the noise and mitigated Gibbs artifacts. Background variability was larger for small spheres than larger spheres and the noise decreased when acquisition time became longer. A contrast-to-noise ratio >5 was reached for the two smallest spheres of 10 and 13 mm at acquisition times of 8 s CONCLUSION: Optimized reconstruction parameters preserved image quality with reduce acquisition time in present study. This study suggests an optimal protocol for clinical 99m Tc SPECT/CT can be reached at 8 s per projection angle, with data reconstructed using 12 iterations and eight subset of the 3D OSEM algorithm and 8 mm Gaussian post-filter.

PMID:35049129 | DOI:10.1002/acm2.13528

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Combining a Pharmacological Network Model with a Bayesian Signal Detection Algorithm to Improve the Detection of Adverse Drug Events

Front Pharmacol. 2022 Jan 3;12:773135. doi: 10.3389/fphar.2021.773135. eCollection 2021.

ABSTRACT

Introduction: Improving adverse drug event (ADE) detection is important for post-marketing drug safety surveillance. Existing statistical approaches can be further optimized owing to their high efficiency and low cost. Objective: The objective of this study was to evaluate the proposed approach for use in pharmacovigilance, the early detection of potential ADEs, and the improvement of drug safety. Methods: We developed a novel integrated approach, the Bayesian signal detection algorithm, based on the pharmacological network model (ICPNM) using the FDA Adverse Event Reporting System (FAERS) data published from 2004 to 2009 and from 2014 to 2019Q2, PubChem, and DrugBank database. First, we used a pharmacological network model to generate the probabilities for drug-ADE associations, which comprised the proper prior information component (IC). We then defined the probability of the propensity score adjustment based on a logistic regression model to control for the confounding bias. Finally, we chose the Side Effect Resource (SIDER) and the Observational Medical Outcomes Partnership (OMOP) data to evaluate the detection performance and robustness of the ICPNM compared with the statistical approaches [disproportionality analysis (DPA)] by using the area under the receiver operator characteristics curve (AUC) and Youden’s index. Results: Of the statistical approaches implemented, the ICPNM showed the best performance (AUC, 0.8291; Youden’s index, 0.5836). Meanwhile, the AUCs of the IC, EBGM, ROR, and PRR were 0.7343, 0.7231, 0.6828, and 0.6721, respectively. Conclusion: The proposed ICPNM combined the strengths of the pharmacological network model and the Bayesian signal detection algorithm and performed better in detecting true drug-ADE associations. It also detected newer ADE signals than a DPA and may be complementary to the existing statistical approaches.

PMID:35046809 | PMC:PMC8762263 | DOI:10.3389/fphar.2021.773135

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Impact of a Collaborative Pharmaceutical Care Service for Patients With Parkinson’s Disease

Front Pharmacol. 2022 Jan 3;12:793361. doi: 10.3389/fphar.2021.793361. eCollection 2021.

ABSTRACT

Objective: To identify the impact of a collaborative pharmaceutical care service (CPCS) on medication safety and establish the impact of the CPCS on patient reported outcomes for Parkinson’s disease (PD) patients. Methods: Initially, PD outpatients receiving the CPCS between March 2017 and March 2019 were compared with PD patients receiving standard of care to identify differences in management. Pharmacist interventions data were coded and patients with PD receiving the CPCS were compared with those receiving standard of care to determine differences in medicines prescribed and dosage associated with these. Following this, data of patients receiving CPCS at baseline and 3-months follow-up were collected using a questionnaire consisting of validated measures of two patient-reported outcomes [adherence and quality of life (QoL)]. Mean scores for continuous variables were calculated, with descriptive analysis of categorical variables consisting of frequency counts and percentages. Change in adherence score before and after CPCS was investigated using a Wilcoxon sign rank sum test, spearman correlation analysis was used to correlate the changes in QoL before and after CPCS with the number of interventions, and p < 0.05 indicates that the difference is statistically significant. Results: A total of 331 PD outpatients received CPCS over 490 outpatient visits with an average age of 71.83 (±12.54). Five hundred and forty-five drug related problems were recorded as pharmacist interventions, of which most involved change to dosage (n = 226, 41.47%), adverse drug reactions (n = 135, 24.77%), and change in a medication (n = 102, 18.72%). Compared with those receiving standard of care, patients receiving CPCS were significantly less likely to have been prescribed pramipexole (18.52 versus 23.77%, p < 0.001) and more likely to have been prescribed amantadine (5.40 versus 3.70%, p = 0.02) and selegiline (17.36 versus 11.64%, p < 0.001). Lower dosages of levodopa/benserazide (0.51 ± 0.31 g versus 0.84 ± 0.37 g, p < 0.001), levodopa/carbidopa (0.33 ± 0.23 g versus 0.66 ± 0.47 g, p < 0.001), pramipexole (1.14 ± 1.63 mg versus 1.27 ± 0.69 mg, p = 0.01), and entacapone (130.00 ± 79.76 mg versus 173.09 ± 97.86 mg, p < 0.001) were also recorded. At baseline 119 PD outpatients with an average age of 69.98 (±9.90) were recruited for the longitudinal study. At 3-month follow-up, participants reported improvement in bodily pain subscale (baseline versus 3-months follow-up, 30.04 ± 22.21 versus 23.01 ± 20.98, p = 0.037) and medication adherence (6.19 ± 1.50 versus 6.72 ± 1.73, p = 0.014). Frequency of CPCS use was related to activity of daily living subscale (p = 0.047), the bodily pain subscale (p = 0.026), and medication adherence (p = 0.011). Total score of PDQ-39 was associated with patient education (p = 0.005) and usage and dosage combined with patient education (p = 0.006), while medication adherence score was associated with usage and dosage (p = 0.005). Conclusion: The CPCS was effective in resolving drug-related problems and in improving patients’ medication regimens, medication adherence, and QoL through patient education and dosage adjustments. This is the first step in the development and feasibility testing of pharmacy services for PD patients in China.

PMID:35046815 | PMC:PMC8762333 | DOI:10.3389/fphar.2021.793361

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Toward a Multimodal Computer-Aided Diagnostic Tool for Alzheimer’s Disease Conversion

Front Neurosci. 2022 Jan 3;15:744190. doi: 10.3389/fnins.2021.744190. eCollection 2021.

ABSTRACT

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder. It is one of the leading sources of morbidity and mortality in the aging population AD cardinal symptoms include memory and executive function impairment that profoundly alters a patient’s ability to perform activities of daily living. People with mild cognitive impairment (MCI) exhibit many of the early clinical symptoms of patients with AD and have a high chance of converting to AD in their lifetime. Diagnostic criteria rely on clinical assessment and brain magnetic resonance imaging (MRI). Many groups are working to help automate this process to improve the clinical workflow. Current computational approaches are focused on predicting whether or not a subject with MCI will convert to AD in the future. To our knowledge, limited attention has been given to the development of automated computer-assisted diagnosis (CAD) systems able to provide an AD conversion diagnosis in MCI patient cohorts followed longitudinally. This is important as these CAD systems could be used by primary care providers to monitor patients with MCI. The method outlined in this paper addresses this gap and presents a computationally efficient pre-processing and prediction pipeline, and is designed for recognizing patterns associated with AD conversion. We propose a new approach that leverages longitudinal data that can be easily acquired in a clinical setting (e.g., T1-weighted magnetic resonance images, cognitive tests, and demographic information) to identify the AD conversion point in MCI subjects with AUC = 84.7. In contrast, cognitive tests and demographics alone achieved AUC = 80.6, a statistically significant difference (n = 669, p < 0.05). We designed a convolutional neural network that is computationally efficient and requires only linear registration between imaging time points. The model architecture combines Attention and Inception architectures while utilizing both cross-sectional and longitudinal imaging and clinical information. Additionally, the top brain regions and clinical features that drove the model’s decision were investigated. These included the thalamus, caudate, planum temporale, and the Rey Auditory Verbal Learning Test. We believe our method could be easily translated into the healthcare setting as an objective AD diagnostic tool for patients with MCI.

PMID:35046766 | PMC:PMC8761739 | DOI:10.3389/fnins.2021.744190

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Factors Contributing to the Severity and Laterality of Pisa Syndrome in Parkinson’s Disease

Front Aging Neurosci. 2022 Jan 3;13:716990. doi: 10.3389/fnagi.2021.716990. eCollection 2021.

ABSTRACT

Objective: Pisa syndrome (PS) is a disabling postural deformity in Parkinson’s disease (PD). We aimed to elucidate clinical factors determining the severity and laterality of PS in PD. Methods: In 54 PD patients with PS, we measured the clinical factors that are previously known to contribute to the occurrence of PS as follows: asymmetry of motor symptoms for the evaluation of asymmetric basal ganglia dysfunction, the degree and direction of subjective visual vertical (SVV) tilt for the misperception of body verticality, the canal paresis for unilateral peripheral vestibulopathy, and the tonic electromyographic (EMG) hyperactivity of paraspinal muscles for dystonia. Multivariable linear and logistic regression analyses were conducted to identify the clinical factors associated with the degree of truncal tilt, for the quantification of the severity of PS, and PS tilting to the less affected side, respectively. Results: The multivariable linear regression analyses revealed that the larger degree of SVV tilt (β = 0.29, SE = 0.10, p = 0.005), right-sided SVV tilt (β = 2.32, SE = 0.82, p = 0.007), and higher Hoehn and Yahr (HY) stage (β = 4.01, SE = 1.29, p = 0.003) significantly increased the severity of PS. In the multivariable logistic regression analyses, greater asymmetry of motor symptoms [odds ratio (OR) = 2.01, 95% CI = 1.34-3.49] was significantly associated with PS tilting to the less affected side, while right-sided SVV tilt (OR = 0.02, 95% CI = 0.001-0.21), unilateral canal paresis (OR = 0.06, 95% CI = 0.003-0.79), and higher HY stage (OR = 0.04, 95% CI = 0.002-0.46) were associated with PS tilting to the more affected side. Conclusion: Misperception of verticality, asymmetric basal ganglia dysfunction, unilateral peripheral vestibulopathy, and motor disability are the clinical factors associated with the severity and laterality of PS in patients with PD.

PMID:35046790 | PMC:PMC8761952 | DOI:10.3389/fnagi.2021.716990

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Impact of a Novel Strategy for Critical Values Communication for the Management of Patients Treated with Clozapine

EJIFCC. 2021 Dec 7;32(4):458-466. eCollection 2021 Dec.

ABSTRACT

INTRODUCTION: Clozapine is an antipsychotic drug used to treat resistant schizophrenia and other disorders. Based on the actual Spanish legislation, patients treated with clozapine must undergo periodical haematological examinations and treatment should be reviewed when the haemogram shows either a leukocyte count of ≤ 3500/mm3 or neutrophil count < 2000/mm3. An automatic notification system has been developed to optimize patient management and it’s utility was assessed following the implementation of the new system.

MATERIAL AND METHODS: When clozapine (CLO) laboratory test request was made, a reflex complete blood count test was also done. An automatic e-mail was sent by the laboratory information system to the physician when a CLO was ordered and low leukocyte or neutrophil counts were detected, or when a patient with an ordered CLO test did not attend the laboratory for blood drawing.

RESULTS: For patients with haemogram alterations, the time to take clinical action was significantly decreased from 23 to 7 days (p = 0.02). Moreover, the adherence to Spanish Agency of Drugs and Sanitary Devices recommendations significantly increased from 45% to 76% (p = 0.02). For not attending patients, the days out of control decreased from 29 to 12 days, although it was not statistically significant (p = 0.06).

CONCLUSIONS: This strategy has allowed the compliance of legal requirements, the improvement of patient safety, and the optimisation of clinical and laboratory procedures.

PMID:35046764 | PMC:PMC8751398

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Ups and Downs of COVID-19: Can We Predict the Future? Local Analysis with Google Trends for Forecasting the Burden of COVID-19 in Pakistan

EJIFCC. 2021 Dec 7;32(4):421-431. eCollection 2021 Dec.

ABSTRACT

BACKGROUND: We aim to study the utility of Google Trends search history data for demonstrating if a correlation may exist between web-based information and actual coronavirus disease 2019 (COVID-19) cases, as well as if such data can be used to forecast patterns of disease spikes.

PATIENTS & METHODS: Weekly data of COVID-19 cases in Pakistan was retrieved from online COVID-19 data banks for a period of 60 weeks. Search history related to COVID-19, coronavirus and the most common symptoms of disease was retrieved from Google Trends during the same period. Statistical analysis was performed to analyze the correlation between the two data sets. Search terms were adjusted for time-lag over weeks, to find the highest cross-correlation for each of the search terms.

RESULTS: Search terms of ‘fever’ and ‘cough’ were the most commonly searched online, followed by coronavirus and COVID. The highest peak correlations with the weekly case series, with a 1-week backlog, was noted for loss of smell and loss of taste. The combined model yielded a modest performance for forecasting positive cases. The linear regression model revealed loss of smell (adjusted R2 of 0.7) with significant 1-week, 2-week and 3-week lagged time series, as the best predictor of weekly positive case counts.

CONCLUSIONS: Our local analysis of Pakistan-based data seemingly confirms that Google trends can be used as an important tool for anticipating and predicting pandemic patterns and pre-hand preparedness in such unprecedented pandemic crisis.

PMID:35046760 | PMC:PMC8751396

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Profiling of Lactate Dehydrogenase Isoenzymes in COVID-19 Disease

EJIFCC. 2021 Dec 7;32(4):432-441. eCollection 2021 Dec.

ABSTRACT

INTRODUCTION: Serum total lactate dehydrogenase (LDH) activity was elevated and showed a positive correlation with disease severity and outcome in severe COVID-19 disease. However, it is still unknown whether the relative abundance or calculated activity of any LDH isoenzyme is predominately increased in COVID-19 subjects.

METHODS: Twenty-two consecutive patients suffered from moderate or severe COVID-19 pneumonia were recruited into this study who showed enhanced total LDH activity. The ratio of LDH isoenzyme activities was further investigated using gel electrophoresis (Hydragel®, Sebia) with densitometric evaluation. Calculated activity values of these isoenzymes were correlated with routine laboratory parameters, the degree of lung parenchymal affection based on chest CT and clinical outcome.

RESULTS: Total LDH activity was raised in the range of 272-2141 U/L and significantly correlated with calculated LDH-3 and LDH-4 activities (r=0.765, P=0.0001; and r=0.783, P=0.0001, respectively). In contrast, the relative abundance of neither LDH isoenzyme was exclusively abnormal in COVID-19 patients. Calculated activity of LDH-3 and LDH-4 demonstrated a modest but statistically significant association with serum ferritin (r=0.437, P=0.042; r=0.505, P=0.016, respectively). When the relationship between the severity of pulmonary affection by SARS-CoV-2 infection and relative abundance of LDH isoenzymes was studied, a larger ratio of mid-zone fractions was observed in the presence of ≥ 50% lung parenchymal involvement. Finally, regardless of LDH isoenzyme pattern, abnormal relative ratio of LDH-4 and higher calculated LDH-3 and LDH-4 activity values were detected in subjects with unfavorable outcome.

CONCLUSION: No characteristic profile of LDH isoenzymes can be detected in COVID-19 pneumonia, however, elevated activities of LDH-3 and LDH-4 are associated with worse clinical outcomes.

PMID:35046761 | PMC:PMC8751399

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The Benefits of Mindfulness Meditation on Trait Mindfulness, Perceived Stress, Cortisol, and C-Reactive Protein in Nursing Students: A Randomized Controlled Trial

Adv Med Educ Pract. 2022 Jan 13;13:47-58. doi: 10.2147/AMEP.S348062. eCollection 2022.

ABSTRACT

PURPOSE: Mindfulness meditation was used to reduce stress and its responses such as cortisol and C-reactive protein (CRP) among healthy and ill individuals in various cultures, but its effect has not yet been studied among nursing students, experiencing tremendous stress. The objective of this study was to examine the effects of mindfulness meditation on trait mindfulness, perceived stress, serum cortisol, and serum C-reactive proteins (CRP) in nursing students.

PATIENTS AND METHODS: Using a two-arm, randomized, parallel study (conducted in a large university in Jordan, 108 nursing students were randomly assigned to experimental group receiving five 30-minute weekly sessions of mindfulness meditation and control group sitting quiet during the experimental sessions. Trait mindfulness, perceived stress, serum cortisol, and CRP were measured at baseline and end of the intervention.

RESULTS: Using one-way MANOVA and post-hoc comparisons, the results showed that mindfulness meditation was significantly effective in decreasing serum cortisol levels and perceived stress. The mindfulness meditation also decreased CRP and increased trait mindfulness although the results did not reach statistically significant levels.

CONCLUSION: These findings underscore the need for serious consideration of mindfulness meditation in nursing colleges to improve stress and raise immunity in this vulnerable population.

TRIAL REGISTRATION: Mindfulness Meditation for Nursing Students: clinicaltrials.gov, identifier: NCT05099224.

PMID:35046747 | PMC:PMC8763207 | DOI:10.2147/AMEP.S348062