One-year Data Research Articles

The associations between caregivers’ psychosocial characteristics and caregivers’ depressive symptoms in stroke settings: a cohort study

BackgroundStudies have found that caregivers can influence stroke survivors’ outcomes, such as mortality. It is thus pertinent to identify significant factors associated with caregivers’ outcomes. The study objective was to examine the associations between caregivers’ psychosocial characteristics and caregivers’ depressive symptoms.MethodsThe analysis obtained three-month and one-year post-stroke data from the Singapore Stroke Study, which was collected from hospital settings. Caregivers’ depressive symptoms were assessed via the Center for Epidemiologic Studies Depression instrument. Psychosocial characteristics of caregivers included subjective burden (Zarit Burden Interview), quality of care-relationship (a modified 3-item scale from the University of Southern California Longitudinal Study of Three-Generation Families) and expressive social support (an 8-item scale from Pearlin et al.). Mixed effect Tobit regressions were used to examine the associations between these study variables.ResultsA total of 214 caregivers of stroke patients hospitalized were included in the final analysis. Most caregivers were Chinese women with secondary school education, unemployed and married to the patients. Caregivers' subjective burden was positively associated with their depressive symptoms (Partial regression coefficient: 0.18, 95% CI 0.11–0.24). Quality of care-relationship (Partial regression coefficient: − 0.35, 95% CI − 0.63 to − 0.06) and expressive social support (partial regression coefficient: − 0.28, 95% CI − 0.37 to − 0.19) were negatively associated with caregivers’ depressive symptoms. Caregivers’ depressive symptoms were higher at three-month post-stroke than one-year post-stroke (Partial regression coefficient: − 1.00, 95% CI − 1.80 to − 0.20).ConclusionThe study identified subjective burden, quality of care-relationship and expressive social support as significantly associated with caregivers’ depressive symptoms. Caregivers’ communication skills may also play a role in reducing caregivers’ depressive symptoms.

Infiltration Assessments on Top of Yungang Grottoes by Time-Lapse Electrical Resistivity Tomography

Water plays a vital role in the weathering process of grottoes. Precipitation is a main water source in the grotto hosting mountain rock. In this study, time-lapse electrical resistivity tomography was adopted to track the movement of infiltrated water in a profile in the Yungang Grottoes. Our one-year monitoring data indicated a good resistivity response to rainfall in the shallow unconsolidated soil layers. There were only resistivity decreases in the near surface 5 m across the whole monitoring profile, and resistivity values quickly returned to a neutral state after the rain stopped. Based on the analysis of a typical rainfall event during the rainy season, we found that the infiltrated water cannot continuously move downwards to recharge local groundwater. It moves horizontally to a nearby gully due to the existence of a hydraulic conductive fine sand layer and low permeable mudstone and sandstone base rocks. An artificial infiltration experiment was carried out to further verify the fate of infiltrated water. Based on mass balance analysis, with 10 m3 of infiltrated water, it only saturated dry soil in the top 1.36 m soil layer on average and this was roughly consistent with our field borehole wetting front verifications at 1.2 and 1.3 m. There were limited horizontal expansions from the infiltrated water. Therefore, based on our monitoring data and analysis, infiltrated water was not the main source of the water involved in the weathering process of the Yungang Grottoes.

Optimum storage sizing in a hybrid wind-battery energy system considering power fluctuation characteristics

Power dispatching is one of the important requirements for wind power systems. Using energy storage systems, especially the battery energy storage system (BESS) is one of the more effective solutions for overcoming this problem. The required battery capacity depends on the fluctuation level of the output power, which is affected by several factors. In this paper, the object is to estimate the required battery capacity based on wind speed data and turbines position in the design phase of a wind farm. An analytical method is presented to estimate the short-term fluctuation of wind farm power considering wake effect, turbulence, and spatial smoothing. Then, a method for estimating the optimum battery capacity, based on the statistical characteristics of wind farm power including average value and standard deviation over a long-term period, is presented. In addition, a new model is presented to estimate the battery lifetime in the case of non-uniform charge/discharge cycles. The numerical results for a case study, over one-year wind speed data, are presented and the results show the effectiveness of the proposed approach in determining the optimum battery capacity.

The Impact of Total Automaton on the Clinical Laboratory Workforce: A Case Study.

BackgroundThere has been a significant concern that total automation can decrease the need for laboratory personnel at all levels. The objective of this study was to investigate the impact of total laboratory automation on the clinical laboratory workforce.MethodsA one-year data including the demographical features of laboratory workforce and technical productivity of laboratory tests were provided by two medical laboratory departments of similar profile and different equipment setup; one adopting a total automation system and the other utilizing discrete analysis system. The technical productivities of the two laboratories were compared and statistically tested.ResultsA similar technical productivity per single laboratory worker was noted in the hematology section in each of the two sites with no significant difference (average odd radio = 0.9, p = 0.79). However, with total automation, the number of tests performed per single worker has increased to an average of 1.4 and 3.7 times with total automation in the clinical chemistry and serology sections, respectively (p ≤ 0.001).ConclusionTotal laboratory automation improves the productivity of the laboratory, leading to a decreased laboratory workforce. The laboratory workload has increased steadily therefore, the existing laboratory workforce, in the absence of automation, could not have been able to maintain the current volume of service. Adoption of automation reduces repetitive manual labor, thereby allowing the redefinition of the job roles of the laboratory workforce. TLA is ideal for laboratories that suffer from workforce shortages or managing high volume testing with less staff.

Economic Loss, Amount of Beef Discarded, Natural Resources Wastage, and Environmental Impact Due to Beef Discoloration

Any deviation from a bright-red color leads to a discounted price or beef is discarded. Limited data are currently available on the economic losses due to retail beef discoloration. Therefore, the objective of the study was to estimate economic losses, the amount of beef discarded, natural resource wastage, and environmental impact due to beef discoloration. One-year data of total beef sales, total beef discarded, and discounted sale values were collected from 2 national retail chains and 1 regional retail chain located in the Southern United States, representing data from 5,034 stores and 44 states. The US beef system life cycle parameters from published literature were used to calculate the impact of discarded meat on water and energy use and greenhouse gas emissions. The study noted that approximately 2.55% of beef is discarded because of discoloration. The results indicate that the US beef industry loses $3.73 billion annually owing to discoloration. The total amount of beef discarded per year in the US corresponds to 194.70 million kg, which represents wasting 780,000 animals and the associated natural resources used in their production. A 1% decrease in discolored beef in the US could reduce natural resource waste and environmental impact by 23.95 billion L of water, 96.88 billion MJ of energy consumed, and 0.40 million tons of carbon dioxide equivalent emission along the beef upstream value chain. Therefore, improving the color stability of meat could increase the sustainability of beef production and limit the waste of nutritious beef, so the application of novel technologies to mitigate color deterioration should be imperative.

One-year changes in fruit and vegetable variety intake and cardiometabolic risk factors changes in a middle-aged Mediterranean population at high cardiovascular risk.

Previous studies have shown beneficial associations between fruit and vegetable (FV) consumption and cardiometabolic risk factors. However, variety in FV, which may play an important role on cardiovascular health due to the different nutrient and phytochemical content among the different groups and subgroups of FV has been poorly investigated. We longitudinally investigated associations between 1-year changes in variety and quantity of FV and concurrent changes in cardiometabolic risk factors in elderly subjects with overweight/obesity and metabolic syndrome. a one-year data longitudinal analysis of 6647 PREDIMED-plus study participants (48% women) was conducted. Data were collected at baseline, six months and 1-year of follow-up. Variety and quantity of FV were estimated using a food frequency questionnaire and continuous scores for variety were created based on items/month of FV. Linear mixed-models adjusted for potential confounders were performed to estimate associations (β-coefficients and 95% confidence interval) between 1-year changes in FV variety and/or quantity and concurrent changes in cardiometabolic risk factors. Two points increment in the FV variety score over one year was associated with a concurrent decrease in glucose (-0.33 mg/dL (0.58, -0.07)), body weight (-0.07 kg (-0.13, -0.02)) and waist circumference (WC) (-0.08 cm (-0.16, -10.01)). An increment of 100 g/d of FV over one year was associated with a concurrent decrease in triglycerides (-0.50 mg/dL (-0.93, -0.08)), glucose (-0.21 mg/dL (-0.32, -0.11)), body weight (-0.11 kg (-0.15, -0.07)) and WC (-0.10 cm (-0.14, -0.06)) over 1-year. Changes in FV consumption which led to higher quantity and variety over one year were associated with downward changes in glucose (-1.26 mg/dL (-2.09, -0.43)), body weight (-0.40 kg (-0.58, -0.23)) and WC (-0.50 cm (-0.73, -0.28)). Greater variety, in combination with higher quantity of FV was significantly associated with a decrease in several cardiometabolic risk factors among elderly subjects at high cardiovascular risk.

A novel offshore wind farm typhoon wind speed prediction model based on PSO–Bi-LSTM improved by VMD

Accurate typhoon wind speed prediction is significant because it enables wind farms to take advantage of high wind speeds and to simultaneously protect wind turbines from damage. However, the wind characteristics of the typhoon are highly random, fluctuating, and nonlinear, which makes precise prediction difficult. One-year wind data collected from a wind farm on the southeast coast of China are employed in the study. The characteristics of the typhoon are analyzed, and a sensitivity study is carried out by comparing two groups of training datasets. This study proposes a hybrid approach that considers both the physical model and the artificial neural network (ANN) model to accurately predict the short-term typhoon wind speed. The variational mode decomposition (VMD) algorithm is selected to decompose wind speed, and the particle swarm optimization (PSO) method is employed to optimize the bidirectional, long short-term memory (Bi-LSTM) prediction model. The results show that the proposed PSO-VMD-Bi-LSTM has strong robustness for making uncertainty predictions and can be utilized to predict the wind speed of typhoons. This study demonstrates the potential of an innovative ANN method to predict wind speed during the typhoon period.

Patients with degenerative cervical myelopathy exhibit neurophysiological improvement upon extension and flexion: a retrospective cohort study with a minimum 1-year follow-up

BackgroundCervical extension and flexion are presumably harmful to patients with degenerative cervical myelopathy (DCM) because they worsen medullary compression visible on dynamic magnetic resonance imaging (MRI). Dynamic somatosensory evoked potentials (SSEPs) are an objective tool to measure the electrophysiological function of the spinal cord at different neck positions. In contrast to previous hypotheses, a considerable proportion of patients with DCM present improved SSEPs upon extension and flexion compared to a neutral position.MethodsPatients with DCM who underwent preoperative dynamic SSEP examinations and subsequent decompression surgeries between 2015 and 2019 were retrospectively evaluated. We compared extension and flexion SSEPs with neutral SSEPs in each patient and classified them into extension-improved (EI) or extension-nonimproved (EN) and flexion-improved (FI) or flexion-nonimproved (FN) groups. Preoperative clinical evaluations, decompression surgical methods and one-year follow-up clinical data were recorded. Cervical spondylolisthesis and cervical alignment types were evaluated on plain cervical lateral radiographs. The number of stenotic segments, Mühle stenosis grade and disc degeneration stage of the most severe segment, and presence of ligamentum flavum hypertrophy and intramedullary T2 weighted imaging (T2WI) hyperintensity were evaluated on lateral and axial MRI. Data were compared between the EN and EN groups or FI and FN groups with T-tests, chi-square tests or Kruskal-Wallis tests. Prediction criteria were determined with logistic regression analyses.ResultsForty-nine patients were included, and 9 (18.4%) and 11 (22.4%) showed improved extension and flexion SSEPs compared to their own neutral SSEPs, respectively. Interestingly, EI or FI patients had significantly better one-year postoperative mJOA recoveries than EN or FN patients (T-test, P < 0.001). Moreover, the disease duration (T-test, P = 0.024), involved segment number (Kruskal-Wallis test, P < 0.001), and cervical alignment type (chi-square test, P = 0.005) varied significantly between the EI and EN groups. The FI group presented a significantly higher Mühle stenosis grade than the FN group (Kruskal-Wallis test, P = 0.038). Furthermore, ≤ 2 involved segments and straight or sigmoid cervical alignment were significant criteria predicting improved extension SSEPs (probability: 85.7%), while Mühle stenosis Grade 3 and disease duration ≤6 months were significant criteria predicting improved flexion SSEPs (probability: 85.7%).ConclusionsOur findings provide evidence for neurophysiological improvement in patients with DCM at extension and flexion and its significance in predicting prognoses. Moreover, certain clinical and radiographic criteria may help predict neurophysiological improvement upon extension or flexion.Trial registration“[2020]151”. Retrospectively registered on April 30, 2020.

Geographical prevalence of SARS-CoV-2 variants, August 2020 to July 2021

We extracted one-year genomic data (August 2020–July 2021) from GISAID EpiCoV™ database and estimated monthly proportions of 11 SARS-CoV-2 variants in various geographical regions. From continental perspective, Delta VOC predominated in Africa, Asia, Europe, North America and Oceania, with proportions of 67.58–98.31% in July 2021. In South America, proportion of Delta VOC (23.24%) has been approaching the predominant yet diminishing Gamma VOC (56.86%). We further analyzed monthly data on new COVID-19 cases, new deaths, vaccination status and variant proportions of 6 countries. Delta VOC predominated in all countries except Brazil (Gamma VOC) in July 2021. In most occasions, rise and predominance of Alpha, Beta, Gamma, Delta and Zeta variants were accompanied with surges of new cases, especially after the time point of major lineage interchange. The ascending phases of new cases lasted for 1–5 months with 1.69- to 40.63-fold peak growth, whereas new death tolls varied with regional vaccination status. Our data suggested surges of COVID-19 cases might be predicted from variant surveillance data. Despite vaccine breakthroughs by Delta VOC, death tolls were more stable in countries with better immunization coverage. Another takeaway is the urgent need to improve vaccine efficacy against Delta and emerging variants.

Explaining the Association Between Urbanicity and Psychotic-Like Experiences in Pre-Adolescence: The Indirect Effect of Urban Exposures.

Urban living is a growing worldwide phenomenon with more than two-thirds of people expected to live in cities by 2050. Although there are many benefits to living in an urban environment, urbanicity has also been associated with deleterious health outcomes, including increased risk for psychotic outcomes particularly when the urban exposure occurs in pre-adolescence. However, the mechanisms underlying this association is unclear. Here, we utilize one-year follow-up data from a large (N=7,979), nationwide study of pre-adolescence in the United States to clarify why urbanicity (i.e., census-tract population density) might impact psychotic-like experiences (PLE) by looking at the indirect effect of eight candidate urbanicity-related physical (e.g., pollution) and social (e.g., poverty) exposures. Consistent with other work, we found that of the evaluated exposures related to urbanicity, several were also related to increased number of PLE: PM2.5, proximity to roads, census-level homes at-risk for exposure to lead paint, census-level poverty, and census-level income-disparity. These same urban-related exposures were also related to the persistence of PLE after 1 year, but not new onset of PLE. Mediation analysis revealed that a substantial proportion the urbanicity-PLE association (number and persistence) could be explained by PM2.5 (23–44%), families in poverty (68–93%), and income disparity (67–80%). Together, these findings suggest that specific urban-related exposures contribute to the existence and maintenance, but not onset of PLE, which might help to explain why those in urban environments are disproportionately at-risk for psychosis and point toward areas for public health intervention.

Evaluation of Demographic and Clinical Data of Herpes Zoster Patients Admitted To Tertiary Referral Dermatology Clinic During COVID-19 Pandemic

Background: Herpes zoster infection (shingles) occurs due to reactivation of the varicella zoster virus (VZV) usually contracted during childhood. Dermatomal involvement is characterized by vesicular rash. Symptoms such as pain and itching are usually present. Complications may be life-threatening and/or result with sequelae. Psychogenic factors and/or other underlying systemic diseases may provoke reactivation of VZV. Coronavirus disease (COVID-19) infection is one such factor.&#x0D; Objectives: The aim of this study is to evaluate the demographic and clinical data collected from patients admitted to our tertiary referral medical center and diagnosed with herpes zoster during the COVID-19 pandemic.&#x0D; Methods: Six hundred and sixty-one patients admitted to our hospital and diagnosed with herpes zoster between October 2020 and October 2021 were included in the cross-sectional retrospective study.&#x0D; Results: The age range was between 1 and 90, and the mean age was 50.4±19.9 years. Fifty percent were female and 50% were male. Complications were found in 62% of the patients, and 54% had postherpetic neuralgia. A history of an additional comorbidity was found in 79% of the patients. It was observed that 10% of the patients were hospitalized, and their mean age was 66.26±14.4 years. Three percent of the patients had an association with COVID-19 vaccine/infection.&#x0D; Conclusion: Our study is unique because it includes both pediatric and adult patients. Also significant for providing one-year demographic data for shingles during the COVID-19 era.

Persistence, effectiveness and safety of ustekinumab compared to TNF inhibitors in psoriatic arthritis within the Italian PsABio cohort.

To compare real-world persistence, effectiveness and tolerability of ustekinumab versus TNF inhibitors (TNFi) in psoriatic arthritis (PsA). One-year data from Italian subjects enrolled in the PsABio study (PsA patients receiving 1st- to 3rd-line treatment with ustekinumab or TNFi) were evaluated. Treatment persistence was analysed using Kaplan-Meier curves; hazard ratios (HR) of stopping treatment, and the corresponding 95% confidence intervals (CI), were computed through Cox regression models. Proportions of patients reaching clinical effectiveness endpoints were analysed using logistic regression, including propensity score (PS) adjustment for imbalanced baseline covariates, and non-response imputation if treatment was stopped/switched. Among 222 participants with follow-up data (effectiveness set), 101 received ustekinumab and 121 TNFi. In the ustekinumab group, 74.3% continued treatment up to 12±3 months compared to 63.6% in the TNFi group. Ustekinumab showed better persistence than TNFi, overall and in specific subgroups (females, monotherapy without methotrexate, BMI <25 or >30 kg/m2, patients receiving ustekinumab as 2nd-line treatment instead of a second TNFi). Overall, the PS-adjusted HR of treatment discontinuation was 0.46 (95% CI: 0.26-0.82) for ustekinumab vs. TNFi. cDAPSA LDA/remission was achieved in 43.5% of ustekinumab and 43.6% of TNFi-treated patients, while MDA was achieved in 24.2% and 28.0% of patients, respectively. After PS adjustment, odds ratios of clinical effectiveness did not differ significantly. Both treatments showed an acceptable safety profile. This prospective, real-life study found a better persistence of ustekinumab than TNFi in PsA patients. At 1 year, both treatments showed similar effectiveness.

Impacts of pollution heterogeneity on population exposure in dense urban areas using ultra-fine resolution air quality data

Traditional air quality data have a spatial resolution of 1 km or above, making it challenging to resolve detailed air pollution exposure in complex urban areas. Combining urban morphology, dynamic traffic emission, regional and local meteorology, physicochemical transformations in air quality models using big data fusion technology, an ultra-fine resolution modeling system was developed to provide air quality data down to street level. Based on one-year ultra-fine resolution data, this study investigated the effects of pollution heterogeneity on the individual and population exposure to particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and ozone (O3) in Hong Kong, one of the most densely populated and urbanized cities. Sharp fine-scale variabilities in air pollution were revealed within individual city blocks. Using traditional 1 km average to represent individual exposure resulted in a positively skewed deviation of up to 200% for high-end exposure individuals. Citizens were disproportionally affected by air pollution, with annual pollutant concentrations varied by factors of 2 to 5 among 452 District Council Constituency Areas (DCCAs) in Hong Kong, indicating great environmental inequities among the population. Unfavorable city planning resulted in a positive spatial coincidence between pollution and population, which increased public exposure to air pollutants by as large as 46% among districts in Hong Kong. Our results highlight the importance of ultra-fine pollutant data in quantifying the heterogeneity in pollution exposure in the dense urban area and the critical role of smart urban planning in reducing exposure inequities.

Delineating E. coli occurrence and transport in the sandy beach groundwater system by radon-222

Fecal pollution poses a global threat to environmental safety and ecosystem, but the mechanism of microbial transport and occurrence in the beach groundwater system is still poorly explored. Here, we leveraged one-year field data of Escherichia coli (E. coli) and radon-222 (222Rn) and found that E. coli occurrence and transport in the sandy beach groundwater system can be delineated by 222Rn. The underlying mechanism behind this phenomenon is due to similar half-lives of 222Rn and E. coli in the sandy beach groundwater system. Thus, the unique relationship between 222Rn and E. coli can provide additional critical context to the microbial water quality assessments and ecosystem resilience. Also, the beach aquifer in this study is found to be a vital compartment for E. coli removal. The net E. coli removal/production capacity is identified to be highly impacted by submarine groundwater discharge. Finally, a conceptual model is constructed for a better understanding of the occurrences and characteristics of E. coli and 222Rn at multiple spatial scales. These findings are constructive to mitigate the hazardous influences of microbe on water quality, especially in recreational sandy beaches and mariculture zones.

Urban Gardens’ Potential to Improve Stormwater Management: A Comparative Analysis among Urban Soils in Sorocaba, São Paulo, Brazil

Permeable surfaces are increasingly rare in urban centers, but they have the utmost importance for stormwater infiltration. In this context, green spaces are key to reducing problems caused by runoff. This work aimed to evaluate the physical characteristics of the soil used for agroecological gardening, in comparison with parks, wasteland, and riparian forest in Sorocaba, São Paulo, Brazil. During the one-year data collection, urban gardens were superior to other areas in hydraulic conductivity (35.8 mm h−1), humidity (25.8%), and soil penetration resistance (1.21 MPa). On the other hand, the riparian forest showed signs of soil degradation, with low water infiltration rates (121.9 mm h−1) and humidity (14.4%). These findings highlight the importance of better soil management solutions to avoid compaction, such as the protection and conservation of riparian forests. Furthermore, the encouragement of urban gardens and parks with multiple uses can be an option for the enhancement of stormwater management in cities, since this practice has the potential to improve the physical characteristics of urban soils and provide several ecosystem services.

Optimal planning of solar PV and battery storage with energy management systems for Time‐of‐Use and flat electricity tariffs

This paper determines the optimal capacity of solar photovoltaic (PV) and battery energy storage (BES) with novel rule-based energy management systems (EMSs) under flat and time-of-use (ToU) tariffs. Four schemes are investigated based on the combinations of flat and ToU tariffs for buying and selling the electricity: (1) Flat-Flat, (2) ToU-Flat, (3) Flat-ToU, and (4) ToU-ToU. For each scheme, two configurations are evaluated: (i) PV only, and (ii) PV-BES. The optimization of the grid-connected household is evaluated based on one-year realistic data. An uncertainty analysis is presented based on the variations of insolation, temperature, and load. Sensitivity analyses are implemented based on the average daily load, the grid constraint, and the costs of PV and BES. The operational analyses for 48 h in summer and winter are carried out to evaluate the dynamic performance of the systems for high and low solar insolation. The effectiveness of the proposed model is verified by comparing the results with that of common EMS based on the net metering scheme. It is found that the COE of the proposed EMS for a PV-BES house with ToU-Flat scheme (as the best option) is 2 ¢/kWh lower than that of the net metering scheme.

Emergency Department Visits Within 90 Days of Anterior Cruciate Ligament Reconstruction.

Background:Emergency department (ED) visits after orthopaedic surgery such as anterior cruciate ligament reconstruction (ACLR) affect patients and health care systems and should be better understood.Purpose:To determine the incidence, predictors, and reasons for ED visits within 90 days after ACLR.Study Design:Descriptive epidemiologic study.Methods:Patients who had undergone ACLR between 2010 and 2020 were identified in a national database, and 90-day ED visits, readmissions, risk factors, and primary diagnoses for visits were determined. One-year postoperative data were used to establish baseline weekly ED visits for the cohort. Patient age, sex, Elixhauser comorbidity index, region of the country (Northeast, Midwest, West, South), and insurance coverage (Medicare, Medicaid, and commercial) were extracted, and these variables were compared using univariate analysis and multivariate logistic regression.Results:Out of 81,179 patients, ED visits were identified for 6764 (8.3%), and readmissions were identified for 592 (0.7%). Overall, 5300 patients had 1 ED visit, 1020 patients had 2 visits, 275 patients had 3 visits, and 169 patients had ≥4 or more visits; visits occurred within 2 weeks of surgery 38% of the time. Notably, weekly visits returned to baseline at week 3. Independent predictors of ED utilization from multivariate analysis were insurance type (relative to commercial insurance: Medicaid [odds ratio [OR], 2.41; 95% CI, 2.23-2.60] and Medicare [OR, 1.38; 95% CI, 1.19-1.60]), higher Elixhauser comorbidity index (per 2-point increase: OR, 2.24; 95% CI, 2.18-2.29), younger age (per 10-year decrease: OR, 1.23; 95% CI, 1.21-1.24), female sex (OR, 1.05; 95% CI, 1.02-1.08), and region of the country (relative to the West: Midwest [OR, 1.33; 95% CI, 1.26-1.39], Northeast [OR, 1.24; 95% CI, 1.18-1.30], and South [OR, 1.17; 95% CI, 1.12-1.23]). In the first 2 weeks, 67.5% of ED visits were for issues involving the surgical site, most commonly surgical-site pain (29% of all visits). In the total 90-day period, 39.4% of visits involved the surgical site.Conclusion:Within 90 days of ACLR, >8% of patients visited the ED, while 0.7% were readmitted. ED visits increased in the first 2 postoperative weeks and returned to baseline rates around week 3. Within the first 2 weeks, two-thirds of visits involved the surgical site. Younger patients, patients with greater comorbidity burden, those in certain regions of the country, and those with Medicaid had greater odds of ED utilization.

A Comparison between MLR, MARS, SVR and RF Techniques: Hydrological Time-series Modeling

Pan evaporation modeling is an essential part of water resources management and water budget governance. The study's objective was to examine the suitability of regression and tree-based techniques for estimating pan evaporation from climatic variables. Multiple linear regression (MLR), multivariate adaptive regression splines (MARS), support vector machine (SVM) and random forest (RF) techniques are employed for weekly pan evaporation modeling for the Ranichauri station situated in the Mid-Himalayan region of Uttarakhand, India. The determination of the most appropriate inputs among climatic variables to map evaporation was done by regression approaches. The data was divided into two parts: the first three years of data used for calibration and the remainder of the one-year data used for model validation. Statistical indices such as root mean square error (RMSE), Nash Sutcliffe coefficient of efficiency (NSE), and coefficient of determination (R2) were used to assess the performance of weekly pan evaporation estimating models. Based on scatter plots, the results are under-predicted and over-predicted for the weekly pan evaporation values. The results showed that the values of the RMSE values ranged from 0.542 to 0.689, the NSE values ranged from 0.953 to 0.974, and the highest R2value was found for the SVR model for the testing period. Therefore, the SVR model was found to be superior and can be applied to predict weekly pan evaporation values for the Ranichauri site. Doi: 10.28991/HEF-2022-03-01-07 Full Text: PDF

Assessment of Physico-chemical Characteristics of Vairtarna Estuary of Palghar, (M.S.) India

The study of estuarine water quality plays an important role in evaluating and determining the pollution status and health of the water. Vaitarna River estuary is one of the important water bodies in the Palghar district. Entire stretch of the estuary was arbitrarily divided into three zones. Physical and chemical variables of water were monitored season-wise in the year 2016. In the present study, the entire stretch of estuary showed high values of Temperature, pH, BOD, C.O.D. Acidity, Salinity, Hardness and Sulphate different physicochemical parameters were studied in 3 stations of the estuary. There was no previous data from the Vaitarna estuary. The study revealed that one-year data (January 2016 to December 2016) shows good environmental conditions to differences in physicochemical characteristics within the permissible limit. It concluded that the water quality is good, and it is the responsibility of our society the importance of such water bodies to keep free from pollution. Because of the fishery point of view the local fishermen depend on this area of water resources.

Long-Term Sequelae of COVID-19: A Systematic Review and Meta-Analysis of One-Year Follow-Up Studies on Post-COVID Symptoms.

Emerging evidence has shown that COVID-19 survivors could suffer from persistent symptoms. However, it remains unclear whether these symptoms persist over the longer term. This study aimed to systematically synthesise evidence on post-COVID symptoms persisting for at least 12 months. We searched PubMed and Embase for papers reporting at least one-year follow-up results of COVID-19 survivors published by 6 November 2021. Random-effects meta-analyses were conducted to estimate pooled prevalence of specific post-COVID symptoms. Eighteen papers that reported one-year follow-up data from 8591 COVID-19 survivors were included. Fatigue/weakness (28%, 95% CI: 18–39), dyspnoea (18%, 95% CI: 13–24), arthromyalgia (26%, 95% CI: 8–44), depression (23%, 95% CI: 12–34), anxiety (22%, 95% CI: 15–29), memory loss (19%, 95% CI: 7–31), concentration difficulties (18%, 95% CI: 2–35), and insomnia (12%, 95% CI: 7–17) were the most prevalent symptoms at one-year follow-up. Existing evidence suggested that female patients and those with more severe initial illness were more likely to suffer from the sequelae after one year. This study demonstrated that a sizeable proportion of COVID-19 survivors still experience residual symptoms involving various body systems one year later. There is an urgent need for elucidating the pathophysiologic mechanisms and developing and testing targeted interventions for long-COVID patients.