Tag: pubmed

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

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

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

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

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

Oral Oncol. 2021 Aug 14;121:105480. doi: 10.1016/j.oraloncology.2021.105480. Online ahead of print.

ABSTRACT

OBJECTIVES: The prognostic impact of circulating tumor cells (CTCs) or circulating tumor microemboli (CTM) in locally advanced head and neck squamous cell carcinoma (LA-HNSCC) is yet to be determined, with conflicting results in previous trials. The role of induction chemotherapy (ICT) in the management of LA-HNSCC is controversial with no predictive biomarkers to guide treatment strategy in this scenario. The aim of this trial is to determine the prognostic impact of CTCs and CTM, their biomarkers expression by immunocytochemistry (ICC), and its potential role as predictors of ICT benefit in LA-HNSCC.

MATERIALS AND METHODS: Prospective study, with newly diagnosed stage III/IV non-metastatic LA-HNSCC patients treated with curative intent. Blood samples analyzed for CTCs and CTM before treatment using the ISET method.

RESULTS: A total of 83 patients were included. CTCs counts were an independent prognostic factor for overall survival (OS; HR: 1.17; 95 %CI: 1.05-1.31; p = 0.005) and progression free survival (PFS; HR:1.14; 95 %CI: 1.03-1.26; p = 0.007). Using the Lausen and Schumacher technique, 2.8 CTCs/mL for OS and 3.8 CTCs/mL for PFS were defined as the best cut-offs. CTM were detected in 27.7% of patients, correlating with worse PFS (HR = 2.70; IC95%: 1.30-5.58; p = 0.007). MRP-7 expression in CTM correlated with worse OS (HR = 3.49; 95 %CI: 1.01-12.04; p = 0.047) and PFS (HR = 3.62; 95 %CI: 1.08-12.13; p = 0.037). CTCs counts were predictive of complete response to treatment (OR = 0.74; 95 %CI: 0.58-0.95; p = 0.022) and high counts (cut-off 3.8/mL) and CTM were potential predictors of ICT benefit.

CONCLUSION: CTCs/CTM had significant prognostic impact and potential role as predictors of ICT benefit in LA-HNSCC.

PMID:34403888 | DOI:10.1016/j.oraloncology.2021.105480

Anaesth Crit Care Pain Med. 2021 Aug 14:100939. doi: 10.1016/j.accpm.2021.100939. Online ahead of print.

ABSTRACT

PURPOSE: Neuraxial analgesia is effective and widely used during labour, but little is known about maternal satisfaction with its use. Our objectives were to assess the frequency of incomplete maternal satisfaction with neuraxial labour analgesia and its predictors.

METHODS: We extracted data from the 2016 National Perinatal Survey, a cross-sectional population-based study including all births during one week in all French maternity units. This analysis included all women who attempted vaginal delivery with neuraxial analgesia. Maternal satisfaction with analgesia was assessed by a 4-point Likert scale during a postpartum interview. Incomplete satisfaction grouped together women who were fairly, not sufficiently and not at all satisfied. We performed generalised estimating equations analyses adjusted for sociodemographic, obstetric, anaesthetic, and organisational characteristics to compare women with incomplete satisfaction to those completely satisfied.

RESULTS: Among the 8538 women included, 35.2% were incompletely satisfied with their neuraxial analgesia. The odds of incomplete satisfaction were higher among women who reported a prenatal preference not to use neuraxial analgesia but subsequently did (adjusted odds ratio 1.21; 95% confidence interval 1.05-1.39) and among those who did not use patient-controlled neuraxial analgesia (1.20; 1.07-1.34); the odds were lower among women who used combined spinal epidural analgesia (0.53; 0.28-0.99) than among those with epidural analgesia.

CONCLUSION: Incomplete maternal satisfaction with neuraxial analgesia is a frequent concern in France. Increasing the use of patient-controlled neuraxial analgesia and combined spinal-epidural analgesia, as well as consistency between prenatal preference and actual use of neuraxial analgesia may improve maternal satisfaction.

PMID:34403793 | DOI:10.1016/j.accpm.2021.100939

J Acad Nutr Diet. 2021 Aug 14:S2212-2672(21)01201-6. doi: 10.1016/j.jand.2021.08.105. Online ahead of print.

ABSTRACT

BACKGROUND: Cost is one of the main drivers of food selection, thus it is important to monitor food prices. Evidence from low- and middle-income countries such as Mexico is limited.

OBJECTIVE: The aim of this study was to evaluate the price and price trend of healthy and less healthy food/beverage groups in Mexico from 2011 to 2018.

DESIGN: This study used time series of the prices of foods and beverages classified by 1) healthiness, 2) processing level, and 3) pairs of healthy/less healthy substitutes.

SETTING: Food and beverage prices used to estimate the Consumer Price Index were obtained. Prices were collected weekly from 46 cities (>20,000 habitants) distributed across the country.

MAIN OUTCOME MEASURES: Price trend (% change/year) from 2011-2018 for all food/beverage groups and price/100 g in 2018 for pairs of healthy/less healthy substitutes were obtained.

STATISTICAL ANALYSES: Linear regression models were used for each food/beverage group with the logarithm of deflated price as the dependent variable and time (years) as the independent variable.

RESULTS: On average, prices for less healthy foods and beverages increased more than prices of healthy foods and beverages (foods: 1.72% vs. 0.70% change/year; beverages: 1.61% vs. -0.19% change/year). The price change was similar for unprocessed/minimally processed foods and ultra-processed foods (1.95% vs. 1.85% change/year), yet, within each processing category, the price of less healthy foods increased more. By pairs of substitutes (within food/beverage groups), the healthier option for bread, sodas, and poultry was more expensive (price/100g) in 2018, whereas for red meat, cheese, mayonnaise, and milk the healthier option was cheaper.

CONCLUSIONS: Overall, the food prices of less healthy foods and beverages increased more than the food prices of healthy foods and beverages. However, by processing level there was no difference and for pairs of healthy/less healthy substitutes results were mixed. Continued monitoring of food prices is warranted and future research is needed to understand how these price changes affect dietary quality.

PMID:34403815 | DOI:10.1016/j.jand.2021.08.105

Comput Methods Programs Biomed. 2021 Aug 10;209:106336. doi: 10.1016/j.cmpb.2021.106336. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Rapid and precise diagnosis of COVID-19 is very critical in hotspot regions. The main aim of this proposed work is to investigate the baseline, laboratory and CT features of COVID-19 affected patients of two groups (Early and Critical stages). The detection model for COVID-19 is built depending upon the manifestations that define the severity of the disease.

METHODS: The CT scan images are fed into the various deep learning, machine learning and hybrid learning models to mine the necessary features and predict CT Score. The predicted CT score along with other clinical, laboratory and CT scan image features are then passed to train the various Regression models for predicting the COVID Criticality (CC) Score. These baseline, laboratory and CT features of COVID-19 are reduced using Statistical analysis and Univariate logistic regression analysis.

RESULTS: When analysing the prediction of CT scores using images alone, AlexNet+Lasso yields better outcome with regression score of 0.9643 and RMSE of 0.0023 when compared with Decision tree (RMSE of 0.0034; Regression score of 0.9578) and GRU (RMSE of 0.1253; regression score of 0.9323). When analysing the prediction of CC scores using CT scores and other baseline, laboratory and CT features, VGG-16+Linear Regression yields better results with regression score of 0.9911 and RMSE of 0.0002 when compared with Linear SVR (RMSE of 0.0006; Regression score of 0.9911) and LSTM (RMSE of 0.0005; Regression score of 0.9877). The correlation analysis is performed to identify the significance of utilizing other features in prediction of CC Score. The correlation coefficient of CT scores with actual value is 0.93 and 0.92 for Early stage group and Critical stage group respectively. The correlation coefficient of CC scores with actual value is 0.96 for Early stage group and 0.95 for Critical stage group.The classification of COVID-19 patients are carried out with the help of predicted CC Scores.

CONCLUSIONS: This proposed work is carried out in the motive of helping radiologists in faster categorization of COVID patients as Early or Severe staged using CC Scores. The automated prediction of COVID Criticality Score using our diagnostic model can help radiologists and physicians save time for carrying out further treatment and procedures.

PMID:34403841 | DOI:10.1016/j.cmpb.2021.106336

Int J Infect Dis. 2021 Aug 14:S1201-9712(21)00657-3. doi: 10.1016/j.ijid.2021.08.022. Online ahead of print.

ABSTRACT

In this single centre observational study, we demonstrated that lower cycle threshold (Ct) values (indicating higher viral loads) on admission to hospital, were associated with poorer outcomes in unvaccinated, hospitalised patients with Covid-19. We prospectively collected demographic and outcome data on all adult patients who tested positively for SARS-CoV-2 on admission to the University Hospitals North Midlands (UHNM) NHS Trust between 1^st February and 1^st July 2020. Nasopharyngeal swab samples were obtained, and a valid Ct value determined for all patients using the Public Health England (PHE) validated Viasure© reverse transcription PCR assay on admission to hospital. Multivariable logistic regression results based on data from 618 individuals demonstrated a statistically significant inverse relationship between the odds of death and Ct values (adjusted odds ratio (aOR) 0.95, 95% CI 0.92 to 0.98, p-value 0.001). The association remained highly statistically significant after adjusting for known clinical risk factors for the disease.

PMID:34403784 | DOI:10.1016/j.ijid.2021.08.022