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Nevin Manimala Statistics

The Treatment of Cancer Cachexia

Gan To Kagaku Ryoho. 2021 Aug;48(8):987-991.

ABSTRACT

Cancer cachexia is defined as a multifactorial syndrome that causes anorexia and an ongoing loss of skeletal muscle mass (with or without loss of fat mass). When patients got cachexia, the effectiveness and tolerance for anti-cancer therapy is reduced, leading to their poor prognosis. Although known as such disease, there had been no effective cure for cancer cachexia. Ghrelin is a peptide hormone that promotes appetite and improve cachexia. However, there is a limitation as a drug because its half-life is short and must be intravenous injected. Anamorelin is a first novel drug, an orally active, non- peptidic ghrelin mimetic and growth hormone secretagogue approved in Japan in January 2021. Like ghrelin, anamorelin also increases the appetite and lean body mass of patients with cancer cachexia. On the other hand, in clinical trials, there was no statistical significance for increasing the 6-minute walk test distance and recovering non-dominant hand grip strength. As for the functional recovery, a new program has been developed for non-pharmacotherapy with nutritional and exercise interventions. These 2 kinds of interventions will become effective anti-cachexia therapy. Research is also underway to produce anti-cachexia drugs other than anamorelin. Somes are already in their clinical trials. Anti-cachexia therapy will be a new option for treating advanced cancer.

PMID:34404062

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Nevin Manimala Statistics

Prevalence and correlates of bone and joint diseases and its association with falls among older adults in India: Evidence from LASI, 2017-18

Geriatr Nurs. 2021 Aug 14;42(5):1143-1150. doi: 10.1016/j.gerinurse.2021.07.007. Online ahead of print.

ABSTRACT

This study explores the prevalence and correlates of bone and joint diseases and its association with falls among older adults in India. Data from the Longitudinal Aging Study in India (2017-18) were utilized for analysis (n = 31,464). Bivariate and logistic regression was used to fulfill the study objectives. The findings revealed that 19.71% of older adults had bone and joint disease, which was higher among women (22.79%) than men (16.25%). The strongest predictors of such diseases included being currently employed, physically inactive, having difficulties in performing functional activities and higher economic status. The fall in the last two years was reported by 12.63% of older adults, and bone and joints diseases were significantly associated with falls (AOR = 1.287; 95% CI: 1.117-1.483) after adjusting for several socio-demographic and health covariates. These findings imply that policymakers and providers must implement interventions designed to reduce the risk of those diseases and associated falls.

PMID:34404017 | DOI:10.1016/j.gerinurse.2021.07.007

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Nevin Manimala Statistics

Neuromuscular Performance and Training Workload Over an In-Season Mesocycle in Elite Young Soccer Players

Int J Sports Physiol Perform. 2021 Aug 17:1-7. doi: 10.1123/ijspp.2020-0834. Online ahead of print.

ABSTRACT

PURPOSE: The purpose of this study was to assess neuromuscular performance capabilities over an in-season mesocycle in early-career professional soccer players and examine the relationship with training workload.

METHODS: Neuromuscular performance capabilities (isometric knee extensor: peak force, rate of force development, and peak twitch force) of 12 professional soccer players were assessed weekly over a 6-week period. Training and match workload were also recorded over the same period for each player (high-intensity running distance). Changes in neuromuscular performance and workload variables were analyzed.

RESULTS: There was evidence of fluctuations in neuromuscular performance capability over the mesocycle that reached statistical (P < .05) and practical (13.3% [peak-to-peak]) significance alongside interweek heterogeneity in training and match workload (∼17.5% [coefficient of variation], P < .05). Congruence among fluctuating patterns of intramesocycle training load and concomitant neuromuscular performance responses was noted over time for acute training load and acute:chronic workload ratio with peak force and rate of force development.

CONCLUSION: Neuromuscular performance capabilities fluctuate over an in-season mesocycle and are influenced by high-intensity running workload, emphasizing the need for acute monitoring in elite soccer players.

PMID:34404025 | DOI:10.1123/ijspp.2020-0834

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Depression in pregnancy “strongly predicts” depression postpartum: Are we inadvertently misleading clinicians and researchers?

J Affect Disord. 2021 Jul 21;295:50-55. doi: 10.1016/j.jad.2021.07.041. Online ahead of print.

ABSTRACT

BACKGROUND: Many perinatal mental health risk factor studies report that antenatal depression is a signifcant risk factor for women being depressed postnatally. They often describe the strength of the risk as being ‘strong’ or ‘strongly predictive’ (or similar phrases), though usually without explaining why these terms are used. It is possible that readers of such research may misunderstand these qualitative descriptors.

METHOD: As part of routine teaching regarding risk analyses, we explored participants’ understanding of the conclusion stated in one specific perinatal risk study, which was that antenatal depression “strongly predicts” postnatal depression. Participants were groups of mental health professionals and postgraduate students, in Italy (N = 56) and Australia (N = 34).They completed an Estimate Survey, in which they indicated the actual number of antenatally depressed women they expected would have been depressed postpartum, given the study’s conclusion.

RESULTS: The majority of survey respondents (~80%) expected that “strongly predicts” meant that a much higher proportion of women with the risk then became depressed than was actually the case. Some participants expressed major concern at the study’s conclusion.

LIMITATION: Participants comprised two small convenience samples of health professionals and postgraduate students, and thus may not be representative of the population.

CONCLUSION: Studies that rely on the statistical significance of their analyses to conclude whether antenatal depression is a strong predictor or risk for postnatal depression may not accord with how health professionals interpret the data, once the absolute risk information is clearly provided. Recommendations for improving the reporting of results in such studies are made.

PMID:34403934 | DOI:10.1016/j.jad.2021.07.041

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Is there a self-positivity bias for destination memory? Behavioral and ERP evidence

Acta Psychol (Amst). 2021 Aug 14;219:103396. doi: 10.1016/j.actpsy.2021.103396. Online ahead of print.

ABSTRACT

Despite extensive existing research concerning source memory (i.e., memory for what has been said, given, or done to us by whom) during social interaction, destination memory (i.e., memory for what we have said, given, or done to whom) remains to be explored. Furthermore, although destination memory is believed to involve a self-reference process, it remains unclear whether such a process is sufficient to trigger a self-positivity bias. To address these issues, we combined the destination memory paradigm with the social dilemma game to compare destination memory for cooperation and cheating. Both behavioral performance and the neural index of successful encoding, the Dm (difference due to memory) effect, were concerned. Behaviorally, destination memory for cooperative, cheating, and neutral behaviors decreased successively. For neural activities, the pre-400 ms Dm effects during 200-400 ms were non-significant under any condition. In the latency windows of 400-800 ms and 800-1000 ms, the post-400 ms Dm effects were reliably observed for both cooperative and cheating behaviors and were statistically comparable between the two behavior types, but the effect was not obtained for neutral behaviors. These data suggest a self-positivity bias in the behavioral performance but not in the encoding-related Dm effects of destination memory.

PMID:34403980 | DOI:10.1016/j.actpsy.2021.103396

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Macroplastic accumulation in roadside ditches of New York State’s Finger Lakes region (USA) across land uses and the COVID-19 pandemic

J Environ Manage. 2021 Aug 14;298:113524. doi: 10.1016/j.jenvman.2021.113524. Online ahead of print.

ABSTRACT

Macroplastics are a ubiquitous and growing environmental contaminant with impacts in both marine and terrestrial systems. Marine sampling has dominated research in this field, despite the terrestrial origins of most plastic debris. Due to the high surface water connectivity facilitated by roadside ditches, these landscape features provide a unique sampling location linking terrestrial and surface water systems. We collected and analyzed macroplastic accumulation by number of pieces, mass, and polymer type in roadside ditches across four land uses, before and during the COVID-19 pandemic in the Finger Lakes Region of New York State. Commercial land use plastic accumulation rate was highest, while forested land use accumulation rates were lowest on a piece basis. Pre-COVID-19 piece accumulation rates were significantly higher than COVID-19 piece accumulation rates across all land uses. Mass accumulation rates followed similar patterns observed in piece accumulation, but the patterns were not always statistically significant. Plastic type 4 (i.e. thin plastic films), especially plastic bags and wrappers, was the most frequently collected type of macroplastic by piece across all land uses within the 1-7 Resin Identification Codes. By mass, the data were distributed less consistently across land uses. Cigarette filters, containing the polymer cellulose acetate, were the most frequently found roadside plastic, but are not within the 1-7 classification system. Our results suggest that policies in place limiting plastic bag usage could substantially reduce roadside plastics but other plastics, such as food wrappers and other single use plastic films, which comprised a large proportion of the plastic debris collected, should also be regulated to further decrease macroplastic pollution.

PMID:34403916 | DOI:10.1016/j.jenvman.2021.113524

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The carbon dioxide neutralizing effect of energy innovation on international tourism in EU-5 countries under the prism of the EKC hypothesis

J Environ Manage. 2021 Aug 14;298:113513. doi: 10.1016/j.jenvman.2021.113513. Online ahead of print.

ABSTRACT

Mitigation of carbon dioxide emissions has become an utmost important global agenda, keeping into consideration the associated environmental hardships. As a result, it is important to unearth the factors which can neutralize carbon emissions to transform the world economy into a low-carbon one. Against this backdrop, this study explores the carbon dioxide neutralizing effects of economic growth, international tourism, clean energy promotion, and technological innovation in the context of five European Union (EU-5) nations during the 1990-2015 period. This study’s main contribution is in terms of its approach to test the interaction effect between foreign direct investment (FDI) inflows and energy innovation on carbon dioxide emissions. The econometric analysis chronologically involves the employment of unit root, cointegration, causality, and regression methods. Overall, the findings support the inverted-U-shaped economic growth-carbon dioxide emissions nexus to verify the Environmental Kuznets Curve (EKC) hypothesis. Besides, the Pollution Haven Hypothesis in the context of the selected panel is also verified as higher FDI inflows are seen to boost the carbon dioxide emission levels. The results also confirm that energy innovation moderates the harmful effect of air transport (a proxy for international tourism) on carbon dioxide emissions during the developing stage of the tourism industry. On the other hand, renewable energy promotion is found to curb carbon dioxide emissions. These findings suggest that the European governments need to enhance investments in their respective renewable energy sectors and simultaneously ensure the development of clean industries, which can collectively help these nations become carbon-neutral in the future.

PMID:34403918 | DOI:10.1016/j.jenvman.2021.113513

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The effect of Shiatsu massage on agitation in mechanically ventilated patients: A randomized controlled trial

Heart Lung. 2021 Aug 14;50(6):893-897. doi: 10.1016/j.hrtlng.2021.07.013. Online ahead of print.

ABSTRACT

BACKGROUND: Patients admitted to the intensive care units encounter many complications due to the nature of the disease and invasive medical procedures such as intubation and mechanical ventilation. Among these complications, agitation is a frequently-observed and serious problem.

OBJECTIVES: This study aimed to investigate the effect of Shiatsu massage on agitation in mechanically ventilated patients.

METHODS: In this randomized controlled trial, a total of 68 mechanically ventilated patients were selected and then randomly assigned to two groups of intervention and control. Patients in the intervention group received three 5-minute periods of Shiatsu massage with a 2-minute break between them, while patients in the control group only received a touch on the area considered for the message. Data were collected before and after the intervention using the Richmond Agitation-Sedation Scale (RASS) and then analyzed using IBM SPSS Statistics for Windows, version 25.0 (IBM Corp., Armonk, N.Y., USA).

RESULTS: The results showed that the level of agitation significantly decreased in the intervention group compared to the control group (p=.001).

CONCLUSION: Application of shiatsu massage seems to be effective in managing agitation in mechanically ventilated patients. Further studies with greater sample size and longer follow-up period are needed to confirm the current findings.

PMID:34403892 | DOI:10.1016/j.hrtlng.2021.07.013

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Simulated driving performance among daily and occasional cannabis users

Accid Anal Prev. 2021 Aug 14;160:106326. doi: 10.1016/j.aap.2021.106326. Online ahead of print.

ABSTRACT

OBJECTIVE: Daily cannabis users develop tolerance to some drug effects, but the extent to which this diminishes driving impairment is uncertain. This study compared the impact of acute cannabis use on driving performance in occasional and daily cannabis users using a driving simulator.

METHODS: We used a within-subjects design to observe driving performance in adults age 25 to 45 years with different cannabis use histories. Eighty-five participants (43 males, 42 females) were included in the final analysis: 24 occasional users (1 to 2 times per week), 31 daily users and 30 non-users. A car-based driving simulator (MiniSim™, National Advanced Driving Simulator) was used to obtain two measures of driving performance, standard deviation of lateral placement (SDLP) and speed relative to posted speed limit, in simulated urban driving scenarios at baseline and 30 min after a 15 min ad libitum cannabis smoking period. Participants smoked self-supplied cannabis flower product (15% to 30% tetrahydrocannabinol (THC). Blood samples were collected before and after smoking (30 min after the start of smoking). Non-users performed the same driving scenarios before and after an equivalent rest interval. Changes in driving performance were analyzed by repeated measures general linear models.

RESULTS: Mean whole blood THC cannabinoids concentrations post smoking were use THC = 6.4 ± 5.6 ng/ml, THC-COOH = 10.9 ± 8.79 ng/mL for occasional users and THC = 36.4 ± 37.4 ng/mL, THC-COOH = 98.1 ± 90.6 ng/mL for daily users. On a scale of 0 to 100, the mean post-use score of subjective high was similar in occasional users and daily users (52.4 and 47.2, respectively). In covariate-adjusted analysis, occasional users had a significant increase in SDLP in the straight road segment from pre to post compared to non-users; non-users decreased by a mean of 1.1 cm (25.5 cm to 24.4 cm) while occasional users increased by a mean of 1.9 cm (21.7 cm to 23.6 cm; p = 0.02). Daily users also increased adjusted SDLP in straight road segments from baseline to post-use (23.2 cm to 25.0 cm), but the change relative to non-users was not statistically significant (p = 0.08). The standardized mean difference in unadjusted SDLP from baseline to post-use in the straight road segments comparing occasional users to non-users was 0.64 (95% CI 0.09 – 1.19), a statistically significant moderate increase. When occasional users were contrasted with daily users, the baseline to post changes in SDLP were not statistically significant. Daily users exhibited a mean decrease in baseline to post-use adjusted speed in straight road segments of 1.16 mph; a significant change compared to slight speed increases in the non-users and occasional users (p = 0.02 and p = 0.01, respectively).

CONCLUSION: We observed a decrement in driving performance assessed by SDLP after acute cannabis smoking that was statistically significant only in the occasional users in comparison to the nonusers. Direct contrasts between the occasional users and daily users in SDLP were not statistically significant. Daily users drove slower after cannabis use as compared to the occasional use group and non-users. The study results do not conclusively establish that occasional users exhibit more driving impairment than daily users when both smoke cannabis ad libitum.

PMID:34403895 | DOI:10.1016/j.aap.2021.106326

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Large Vessel Occlusion Prediction in the Emergency Department with National Institutes of Health Stroke Scale Components: A Machine Learning Approach

J Stroke Cerebrovasc Dis. 2021 Aug 14;30(10):106030. doi: 10.1016/j.jstrokecerebrovasdis.2021.106030. Online ahead of print.

ABSTRACT

OBJECTIVE: To determine the feasibility of using a machine learning algorithm to screen for large vessel occlusions (LVO) in the Emergency Department (ED).

MATERIALS AND METHODS: A retrospective cohort of consecutive ED stroke alerts at a large comprehensive stroke center was analyzed. The primary outcome was diagnosis of LVO at discharge. Components of the National Institutes of Health Stroke Scale (NIHSS) were used in various clinical methods and machine learning algorithms to predict LVO, and the results were compared with the baseline method (aggregate NIHSS score with threshold of 6). The Area-Under-Curve (AUC) was used to measure the overall performance of the models. Bootstrapping (n = 1000) was applied for the statistical analysis.

RESULTS: Of 1133 total patients, 67 were diagnosed with LVO. A Gaussian Process (GP) algorithm significantly outperformed other methods including the baseline methods. AUC score for the GP algorithm was 0.874 ± 0.025, compared with the simple aggregate NIHSS score, which had an AUC score of 0.819 ± 0.024. A dual-stage GP algorithm is proposed, which offers flexible threshold settings for different patient populations, and achieved an overall sensitivity of 0.903 and specificity of 0.626, in which sensitivity of 0.99 was achieved for high-risk patients (defined as initial NIHSS score > 6).

CONCLUSION: Machine learning using a Gaussian Process algorithm outperformed a clinical cutoff using the aggregate NIHSS score for LVO diagnosis. Future studies would be beneficial in exploring prospective interventions developed using machine learning in screening for LVOs in the emergent setting.

PMID:34403842 | DOI:10.1016/j.jstrokecerebrovasdis.2021.106030