Search Results (10)

This study presents an integrated analysis of climate-driven phenology and infestation dynamics of the invasive oak lace bug (Corythucha arcuata) in foothill oak ecosystems of Rășinari, Romania. Using reconstructed microclimatic data for 2024–2025, systematic field monitoring, degree-day (GDD) modeling, and the De Martonne aridity index, we assessed the combined effects of thermal accumulation and hydric stress on multigenerational development. Results indicate that warm springs and sustained summer temperatures enabled the completion of two full generations (G₁–G₂) in both years, while recurrent late-summer aridity intensified foliar vulnerability and accelerated nymphal development. A third generation (G₃) was initiated but remained incomplete due to declining autumn temperatures and photoperiod constraints. Strong habitat-specific differences were observed: exposed forest-edge stands exhibited the highest damage levels (up to 90%), whereas closed-canopy stands benefited from microclimatic buffering. The combined GDD–aridity framework showed close agreement with observed phenological transitions, providing a robust tool for identifying high-risk infestation periods. Climatic projections for 2026 suggest further advancement of generational timing under continued warming and increasing aridity. These findings highlight the growing climatic suitability of foothill oak ecosystems for C. arcuata and support the development of early-warning systems and adaptive strategies for sustainable oak forest management. Full article

Background/Objectives: Hospital readmissions are a key quality metric impacting both patient outcomes and healthcare costs. Traditional logistic regression models, including the LACE index (Length of stay, Admission type, Comorbidity index, and recent Emergency department visits), are commonly used for readmission risk stratification, though their accuracy may be limited by non-linear interactions with other clinical variables. This study compared the predictive performance of non-linear machine learning (ML) models with stepwise logistic regression (LR) and the LACE index for predicting 30-day general medicine readmissions. Methods: We retrospectively analysed adult general medical admissions at a tertiary hospital in Australia from 1 July 2022 to 30 June 2023. Thirty-two variables were extracted from electronic medical records, including demographics, comorbidities, prior healthcare use, socioeconomic status (SES), laboratory data, and frailty (measured by the Hospital Frailty Risk Score). Predictive models included stepwise LR and four ML algorithms: Least Absolute Shrinkage and Selection Operator (LASSO), random forest, Extreme Gradient Boosting (XGBoost), and artificial neural networks (ANNs). Performance was assessed using the area under the curve (AUC), with comparisons made using DeLong’s test. Results: Of 5371 admissions, 1024 (19.1%) resulted in 30-day readmissions. Readmitted patients were older and frailer and had more comorbidities and lower SES. Logistic regression (LR) identified the key predictors of outcomes, including heart failure, alcoholism, nursing home residency, and prior admissions, achieving an AUC of 0.62. LR’s performance was comparable to that of the LACE index (AUC = 0.61) and machine learning models: LASSO (AUC = 0.63), random forest (AUC = 0.60), and artificial neural networks (ANNs) (AUC = 0.60) (p > 0.05). However, LR significantly outperformed XGBoost (AUC = 0.55) (p < 0.05). Conclusions: About one in five general medicine patients are readmitted within 30 days. Traditional LR performed as well as or better than ML models for readmission risk prediction. Full article

The Miboshan Formation in the Middle Ordovician plays a crucial role in the sedimentary evolution of the western margin of the Ordos Basin as it represents the transition from a carbonate platform to a deep-water slope-basin environment. This study focuses on the paleoenvironment of claystone in the Middle Ordovician Miboshan Formation, located in the Ningxia Hui Autonomous Region of the Ordos Basin. The study aims to analyze the influence of sea level and salinity on rare earth elements, investigate terrigenous input and redox conditions through trace element analysis, and exemplify the coupling relationship between depositional and tectonic environments. The Miboshan Formation profile consists of thick- to thin-bedded limestones, mainly composed of lenticular calcirudite with erosion surfaces and horizontal laminae. Grayish black claystone have deformation structures and graptolite fossils. Based on the total number of rare earth elements and the trace element indexes, the seawater properties, redox degree, and terrigenous input are located in two data sets in different parts of the profile (i.e., sample 6-1 to 6-5: Concentrated in lower part, and samples 6-6 to 6-8: Concentrated in upper part), implying that they were deposited at different subaqueous uplifts. Negative Ce anomalies, La/Ce, V/Cr, and Fe³⁺/Fe²⁺ ratios indicate an anoxic condition with stratified redox structure, whereas characteristic La_N/Nd_N, Y/Ho, and Sr/Ba suggest deep-water affected by fresh water. The ∑REEs and Th/U ratios indicated that the study area was mainly deposited from terrigenous materials in the stable tectonic area. According to the ages of deposition, lithologic analyses, and chemical parameters, the Miboshan Formation is related to the deep water environment in a ponded basin influenced by subaqueous uplift resulting from plate subduction in an active continental margin. This study provides valuable insights into paleoenvironment and paleotectonic environments of the Miboshan Formation in the Middle Ordovician. Full article

The concentration of arsenic (As), considered a toxic and carcinogenic metalloid, in agricultural soils has become a global challenge. Sources of arsenic in soils can be both anthropogenic and natural. Contaminated water is used for the irrigation of crops and vegetables, and therefore it is the main pathway for arsenic to enter the human food chain, creating a potential health risk. This study evaluated the concentrations of arsenic in agricultural soils in the rural parish of Papallacta, located 67 km east of the city of Quito, Northeastern Ecuador, and constitutes an analysis of the problem of arsenic in agricultural soils. Shallow groundwater and geothermal water discharges laced with arsenic are frequently used for irrigation and have raised the level of arsenic in agricultural soils. This work is focused on evaluating the environmental quality and contamination of agricultural soils through environmental quality indices such as geo-accumulation index, enrichment, and contamination factor. The average arsenic levels in the agricultural soils of the four studied areas fluctuate between 20.4 and 43.0 mg kg⁻¹, while in the sediments of the Papallacta Lake, higher values were found in the range between 16.8 and 102.4 mg kg⁻¹; all of which exceed the permissible limit by the Ecuadorian Environmental Legislation for agricultural use (12 mg kg⁻¹). The results of the study in the five studied sites of the Papallacta civil parish indicate low to moderate levels of arsenic enrichment, soils enriched by bedrock, and moderate to considerable contamination. Full article

(1) Background: Elders have higher rates of rehospitalization, especially those with functional decline. We aimed to investigate potential predictors of 30-day readmission risk by comprehensive geriatric assessment (CGA) in hospitalized patients aged 65 years or older and to examine the predictive ability of the LACE index and HOSPITAL score in older patients with a combination of malnutrition and physical dysfunction. (2) Methods: We included patients admitted to a geriatric ward in a tertiary hospital from July 2012 to August 2018. CGA components including cognitive, functional, nutritional, and social parameters were assessed at admission and recorded, as well as clinical information. The association factors with 30-day hospital readmission were analyzed by multivariate logistic regression analysis. The predictive ability of the LACE and HOSPITAL score was assessed using receiver operator characteristic curve analysis. (3) Results: During the study period, 1509 patients admitted to a ward were recorded. Of these patients, 233 (15.4%) were readmitted within 30 days. Those who were readmitted presented with higher comorbidity numbers and poorer performance of CGA, including gait ability, activities of daily living (ADL), and nutritional status. Multivariate regression analysis showed that male gender and moderately impaired gait ability were independently correlated with 30-day hospital readmissions, while other components such as functional impairment (as ADL) and nutritional status were not associated with 30-day rehospitalization. The receiver operating characteristics for the LACE index and HOSPITAL score showed that both predicting scores performed poorly at predicting 30-day hospital readmission (C-statistic = 0.59) and did not perform better in any of the subgroups. (4) Conclusions: Our study showed that only some components of CGA, mobile disability, and gender were independently associated with increased risk of readmission. However, the LACE index and HOSPITAL score had a poor discriminating ability for predicting 30-day hospitalization in all and subgroup patients. Further identifiers are required to better estimate the 30-day readmission rates in this patient population. Full article

Aims: This study aimed to utilize the existing LACE index (length of stay, acuity of admission, comorbidity index and emergency room visit in the past six months) to predict the risk of 30-day readmission and to find the associated factors in patients with AMI. Methods: This was a retrospective study and LACE index scores were calculated for patients admitted with AMI between 2015 and 2019. Data were utilized from the hospital’s electronic medical record. Multivariate logistic regression was performed to find the association between covariates and 30-day readmission. The risk prediction ability of the LACE index for 30-day readmission was analyzed by receiver operating characteristic curves with the C statistic. Results: A total of 205 (5.7%) patients were readmitted within 30 days. The odds ratio of older age group (OR = 1.78, 95% CI: 1.54–2.05), admission via emergency ward (OR = 1.45; 95% CI: 1.42–1.54) and LACE score ≥10 (OR = 2.71; 95% CI: 1.03–4.37) were highly associated with 30-day readmissions and statistically significant. The receiver operating characteristic curve C statistic of the LACE index for AMI patients was 0.78 (95% CI: 0.75–0.80) and showed favorable discrimination in the prediction of 30-day readmission. Conclusion: The LACE index showed a good discrimination to predict the risk of 30-day readmission for hospitalized patients with AMI. Further study would be recommended to focus on additional factors that can be used to predict the risk of 30-day readmission; this should be considered to improve the model performance of the LACE index for other acute conditions by using the national-based administrative data. Full article

The LACE index accounts for: Length of stay (L), Acuity of admission (A), Comorbidities (C), and recent Emergency department use (E). This study aimed to explore the LACE index to predict the high risk of 30-day readmission in patients with diverse disease conditions by an updated systematic review. A systematic review carried out by electronic databases from 2011–2021. The studies included a LACE index score for 30-day of readmission and patients with all types of diseases and were published in the English language. The meta-analysis was performed by using a random-effects model with a 95% confidence interval. Of 3300 records, a total of 16 studies met the inclusion criteria. The country of publication was primarily the USA (n = 7) and study designs were retrospective and perspective cohorts. The average mean age was 64 years. The C-statistics was 0.55 to 0.81. The pooled random effects of relative risk readmission were overall (RR, 0.20; 95% CI, 0.12–0.34) and it was favorable. The subgroup analysis of the opted disease-based relative risk of readmissions of all causes, cardiovascular and pulmonary diseases, and neurological diseases were consistent and statistically significant at p < 0.001 level. Current evidence of this review suggested that incorporating a high-risk LACE index showed favorable to risk prediction and could be applied to predict 30-day readmission with chronic conditions. Future study would be planned to predict the high risk of 30-day readmission in acute clinical care for utility, and applicability of promising LACE index in South Korean hospitals. Full article

The consumption of microgreens has increased due to their having higher levels of bioactive compounds and mineral nutrients than mature plants. The lighting conditions during the cultivation of microgreens, if optimally selected, can have a positive effect by further increasing their nutritional value. Thus, our study aimed to determine the changes in mineral nutrients contents of Brassicaceae microgreens depending on different blue–red (B:R) light ratios in light-emitting diode (LED) lighting and to evaluate their growth and nutritional value according to different indexes. Experiments were performed in controlled environment growth chambers at IH LRCAF, 2020. Microgreens of mustard (Brassica juncea ‘Red Lace’) and kale (Brassica napus ‘Red Russian’) were grown hydroponically under different B:R light ratios: 0%B:100%R, 10%B:90%R, 25%B:75%R, 50%B:50%R, 75%B:25%R, and 100%B:0%R. A 220 μmol m⁻² s⁻¹ total photon flux density (TPFD), 18 h photoperiod, 21/17 ± 2 °C temperature and 60% ± 5% relative humidity in the growth chamber were maintained during cultivation. We observed that an increasing percentage of blue light in the LED illumination spectrum during growth was associated with reduced elongation in the microgreens of both species and had a positive effect on the accumulation of mostly macro- and micronutrients. However, different B:R light ratios indicate a species-dependent response to changes in growth parameters such as leaf area, fresh and dry mass, and optical leaf indexes such as for chlorophyll, flavonol, anthocyanin, and carotenoid reflectance. Full article

The LACE index and HOSPITAL score models are the two most commonly used prediction models identifying patients at high risk of readmission with limited information for home care patients. This study compares the effectiveness of these two models in predicting 30-day readmission following acute hospitalization of such patients in Taiwan. A cohort of 57 home care patients were enrolled and followed-up for one year. We compared calibration, discrimination (area under the receiver operating curve, AUC), and net reclassification improvement (NRI) to identify patients at risk of 30-day readmission for both models. Moreover, the cost-effectiveness of the models was evaluated using microsimulation analysis. A total of 22 readmissions occurred after 87 acute hospitalizations during the study period (readmission rate = 25.2%). While the LACE score had poor discrimination (AUC = 0.598, 95% confidence interval (CI) = 0.488–0.702), the HOSPITAL score achieved helpful discrimination (AUC = 0.691, 95% CI = 0.582–0.785). Moreover, the HOSPITAL score had improved the risk prediction in 38.3% of the patients, compared with the LACE index (NRI = 0.383, 95% CI = 0.068–0.697, p = 0.017). Both prediction models effectively reduced readmission rates compared to an attending physician’s model (readmission rate reduction: LACE, 39.2%; HOSPITAL, 43.4%; physician, 10.1%; p < 0.001). The HOSPITAL score provides a better prediction of readmission and has potential as a risk management tool for home care patients. Full article

Pharmacists in primary care settings have unique opportunities to address the causes of ineffective care transitions. The objective of this study is to describe the implementation of a multifaceted pharmacist transitions of care (TOC) intervention integrated into a primary care practice and evaluate the effectiveness of the program. This was a two-phase pilot study describing the development, testing, and evaluation of the TOC program. In Phase 1, the TOC intervention was implemented in a general patient population, while Phase 2 focused the intervention on high-risk patients. The two pilot phases were compared to each other (Phase 1 vs. Phase 2) and to a historical control group of patients who received usual care prior to the intervention (Phase 1 and Phase 2 vs. control). The study included 138 patients in the intervention group (Phase 1: 101 and Phase 2: 37) and 118 controls. At baseline, controls had a significantly lower LACE index, shorter length of stay, and a lower number of medications at discharge, indicating less medical complexity. A total of 344 recommendations were provided over both phases, approximately 80% of which were accepted. In adjusted models, there were no significant differences in 30-day all-cause readmissions between Phase 2 and controls (aOR 0.78; 95% CI 0.21–2.89; p = 0.71) or Phase 1 (aOR 0.99; 95% CI 0.30–3.37; p = 0.99). This study successfully implemented a pharmacist-led TOC intervention within a primary care setting using a two-phase pilot design. More robust studies are needed in order to identify TOC interventions that reduce healthcare utilization in a cost-effective manner. Full article