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Clarifications and enhancements for cardiovascular risk study in metabolic dysfunction-associated steatotic liver disease

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EUROPEAN JOURNAL OF INTERNAL MEDICINE 2025年 132卷 158-159页

作者： Wu, Yinfang Xu, Weixing Shaoxing Second Hosp Dept Gastrointestinal & Minimally Invas Surg Yanan Rd 123 Shaoxing 312000 Zhejiang Peoples R China Shaoxing Univ Sch Med Dept Clin Med Shaoxing Zhejiang Peoples R China

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Agronomic assessment of the yield variability and yield gap of maize in Bhutan

CROP AND ENVIRONMENT

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CROP AND ENVIRONMENT 2024年第1期3卷 25-32页

作者： Wangmo, Passang Thinley, Kinzang Nakashima, Taiken Kato, Yoichiro Agr Res & Dev Ctr Wengkhar 43001 Bhutan Hokkaido Univ Grad Sch Agr Sapporo Hokkaido 0600808 Japan Univ Tokyo Grad Sch Agr & Life Sci Bunkyo ku Tokyo 1138654 Japan

Maize is the staple food crop in Bhutan, which has not achieved national food self-sufficiency. On-farm assessment of yield variability would provide insights into the priorities for Bhutan's maize development program. Here, we conducted three studies in Bhutan: a household survey, on-station experiment, and on-farm monitoring. First, we interviewed 100 households and collected information on maize crop management options and farming characteristics. Second, we evaluated maize growth at two research stations in different elevation zones (640 and 1,700 m a.s.l.). Third, we harvested maize from 25 farm fields at low and high elevations. The gaps between potential yield (with the best management practices at the research stations) and average farm yield and between the best and average farm yields were 53% and 23%, respectively, at the low elevation, and 23% and 20%, respectively, at the high elevation. The classification and regression tree (CART) model showed that field location (distance from the farmer's home), seed source (certified vs. self-produced), and the number of household members involved in farming were the key farming characteristics that affected yield variability, and the manure application regime, urea application, sowing method, and weeding frequency were key management practices. Our results suggest that future research should clarify the most suitable sowing methods and nutrient and weed management regimes, and identify optimal cultivars for each elevation zone, with the goal of developing crop management guidelines for smallholder farmers in Bhutan.

关键词： Bhutan classification and regression tree model Maize Management practice Yield gap Yield variability

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Prediction model for bleeding after endoscopic submucosal dissection of gastric neoplasms from a high-volume center

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JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY 2021年第8期36卷 2217-2223页

作者： Choe, Yeon Hwa Jung, Da Hyun Park, Jun Chul Kim, Ha Yan Shin, Sung Kwan Lee, Sang Kil Lee, Yong Chan Yonsei Univ Coll Med Div Gastroenterol Dept Internal MedSeverance Hosp 50-1 Yonsei Ro Seoul 03722 South Korea Yonsei Univ Coll Med Dept Biomed Syst Informat Biostat Collaborat Unit Seoul South Korea

Background and Aim Bleeding after endoscopic submucosal dissection (ESD) is a main adverse event. To date, although there have been several studies about risk factors for post-ESD bleeding, there has been few predictive model for post-ESD bleeding with large volume cases. We aimed to design a prediction model for post-ESD bleeding using a classification tree model. Methods We analyzed a prospectively established cohort of patients with gastric neoplasms treated with ESD from 2007 to 2016. Baseline characteristics were collected for a total of 5080 patients, and the bleeding risk was estimated using variable statistical methods such as logistic regression, AdaBoost, and random forest. To investigate how bleeding was affected by independent predictors, the classification and regression tree (CART) method was used. The prediction tree developed for the cohort was internally validated. Results Post-ESD bleeding occurred in 262 of 5080 patients (5.1%). In multivariate logistic regression, ongoing antithrombotic use during the procedure, cancer pathology, and piecemeal resection were significant risk factors for post-ESD bleeding. In the CART model, the decisive variables were ongoing antithrombotic agent use, resected specimen size >= 49 mm, and patient age <62 years. The CART model accuracy was 94.9%, and the cross-validation accuracy was 94.8%. Conclusions We developed a simple and easy-to-apply predictive tree model based on three risk factors that could help endoscopists identify patients at a high risk of bleeding. This model will enable clinicians to establish precise management strategies for patients at a high risk of bleeding and to prevent post-ESD bleeding.

关键词： Bleeding classification and regression tree model Endoscopic submucosal dissection Prediction

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Unusual Localization of Blood-Borne Loa loa Microfilariae in the Skin Depends on Microfilarial Density in the Blood: Implications for Onchocerciasis Diagnosis in Coendemic Areas

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CLINICAL INFECTIOUS DISEASES 2021年第Sup3期72卷 S158-S164页

作者： Niamsi-Emalio, Yannick Nana-Djeunga, Hugues C. Chesnais, Cedric B. Pion, Sebastien D. S. Tchatchueng-Mbougua, Jules B. Boussinesq, Michel Basanez, Maria-Gloria Kamgno, Joseph Ctr Res Filariasis & Other Trop Dis CRFilMT Yaounde Cameroon Univ Montpellier Inst Rech Dev IRD UMI233 INSERM U1175 Montpellier France Membre Reseau Int Inst Pasteur Ctr Pasteur Cameroun Serv Epidemiol Yaounde Cameroon Imperial Coll London MRC Ctr Global Infect Dis Anal Sch Publ Hlth Norfolk Pl London W2 1PG England Imperial Coll London Sch Publ Hlth Dept Infect Dis Epidemiol London Ctr Neglected Trop Dis Res Norfolk Pl London W2 1PG England Univ Yaounde I Fac Med & Biomed Sci Yaounde Cameroon

Background. The diagnostic gold standard for onchocerciasis relies on identification and enumeration of (skin-dwelling) Onchocerca volvulus microfilariae (mf) using the skin snip technique (SST). In a recent study, blood-borne Loa loa mf were found by SST in individuals heavily infected with L. loa, and microscopically misidentified as O. volvulus due to their superficially similar morphology. This study investigates the relationship between L. loa microfilarial density (Loa MFD) and the probability of testing SST positive. Methods. A total of 1053 participants from the (onchocerciasis and loiasis coendemic) East Region in Cameroon were tested for (1) Loa MFD in blood samples, (2) O. volvulus presence by SST, and (3) Immunoglobulin (Ig) G4 antibody positivity to Ov16 by rapid diagnostic test (RDT). A classification and regression tree (CART) model was used to perform a supervised classification of SST status and identify a Loa MFD threshold above which it is highly likely to find L. loa mf in skin snips. Results. Of 1011 Ov16-negative individuals, 28 (2.8%) tested SST positive and 150 (14.8%) were L. loa positive. The range of Loa MFD was 0-85 200 mf/mL. The CART model subdivided the sample into 2 Loa MFD classes with a discrimination threshold of 4080 (95% CI, 2180-12 240) mf/mL. The probability of being SST positive exceeded 27% when Loa MFD was >4080 mf/mL. Conclusions. The probability of finding L. loa mf by SST increases significantly with Loa MFD. Skin-snip polymerase chain reaction would be useful when monitoring onchocerciasis prevalence by SST in onchocerciasis-loiasis coendemic areas.

关键词： Onchocerca volvulus Loa loa diagnosis classification and regression tree model skin snip technique

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A hybrid CART-GAMs model to evaluate benthic macroinvertebrate habitat suitability in the Pearl River Estuary, China

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ECOLOGICAL INDICATORS 2022年第0期143卷

作者： Shen, Zhoubao Yang, Ying Ai, Lisha Yu, Chunxue Su, Meirong Dongguan Univ Technol Res Ctr Ecoenvironm Engn Dongguan 523808 Peoples R China

Benthic macminvertebrates are an important part of the aquatic food chain in estuaries. Therefore, understanding their associated habitat requirements is critical in maintaining estuarine ecosystem stability, which has until now been evaluated using habitat suitability evaluations. Although most habitat suitability index (HSI)-based methods can determine the target species preferences for a few specific habitat factors, benthic macroinvertebrates are influenced by multiple habitat factors in estuaries. However, applying too many habitat factors can result in data redundancy, thereby reducing model efficiency. Additionally, nonlinear relationships between species and habitat factors and interactions between different habitat factors are often difficult to evaluate. Previous studies have not focused on methods that can simultaneously address these two issues. Accordingly, this study introduced CART-GAMs, a classification and regression tree model (CART) and a generalized additive model (GAM) hybrid, which can evaluate the suitability of multiple habitat factors relevant to benthic macroinvertebrates in estuaries. First, to remove irrelevant variables (i.e., data redundancy), CART was used to identify critical habitat factors that have significant impacts on benthic macminvertebrates. GAMs were then used to quantify the nonlinear relationships between critical habitat factors and species. Finally, response curves fitted by GAMs were used to determine species habitat preferences (i.e., suitable critical habitat factor ranges). This study applied the CART-GAMs model to the Pearl River Estuary (PRE) to test its effectiveness. The results showed that CART identified four critical water quality factors, that is, salinity (SAL), total phosphorus (TP), pH, and ammonia nitrogen (NH3-N) from the 12 measured factors, subsequently reducing data redundancy by 66.7%. Using critical water quality factors, GAMs explained 66.2% of the variance in Margate s diversity index (dM) of bent

关键词： Benthic macroinvertebrates Habitat suitability evaluations Pearl River Estuary classification and regression tree model Generalized additive models

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Establishing Nutrient Criteria in Nine Typical Lakes in China: A Conceptual model

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CLEAN-SOIL AIR WATER 2016年第10期44卷 1335-1344页

作者： Zhang, Yali Huo, Shouliang Xi, Beidou Ma, Chunzi He, Zhuoshi Beijing Normal Univ Sch Environm State Key Lab Water Environm Simulat Beijing Peoples R China Chinese Res Inst Environm Sci State Key Lab Environm Criteria & Risk Assessment 8 Anwai Dayangfang St Beijing 100012 Peoples R China

Nutrient criteria can provide technical support and management decisions information for avoiding over-and under-protection of lakes. Integrating a conceptual model with multiple nutrient changepoints by three non-linear statistical methods (classification and regression tree model, deviance reduction method, and Bayesian changepoint method) was used to determine the nutrient criteria for nine typical lakes in China differing by specific disturbance degrees and trophic status. Based on the similar impairment levels of nutrient changepoints, the studied lakes were classified into three types roughly including clean lakes, slightly altered lakes, and degraded lakes. For clean lakes, the changepoints were directly used as nutrient criteria (0.005-0.100 mg/L total phosphorus and 0.570-0.600 mg/L total nitrogen). For slightly altered and degraded lakes, due to ecological resilience, the target nutrient criteria should be lower than that of reference lakes inferring from the rationale of "space-for-time substitution." The percentages of decline at changepoints (5, 10, and 20%) are suggested in light of chlorophyll a response criterion limits (2, 5, and 10 mu g/L) for ensuring the safety of drinking water. The conceptual model used to address ecological succession along the gradient of disturbance degrees, is applicable to establish nutrient criteria in other lake ecosystems.

关键词： Bayesian changepoint method classification and regression tree model Deviance reduction method Nutrient criteria

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Comparison of conventional risk factors in middle-aged versus elderly diabetic and nondiabetic patients with myocardial infarction: prediction with decision-analytic model

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THERAPEUTIC ADVANCES IN ENDOCRINOLOGY AND METABOLISM 2015年第6期6卷 258-266页

作者： Mahmoodi, Mohammad Reza Baneshi, Mohammad Reza Rastegari, Azam Kerman Univ Med Sci Sch Hlth Cardiovasc Res Ctr Kerman Iran Kerman Univ Med Sci Sch Hlth Dept Nutr Kerman Iran Kerman Univ Med Sci Res Ctr Modeling Hlth Inst Futures Studies Hlth Kerman Iran

Background: We sought to predict occurrence of myocardial infarction (MI) by means of a classification and regression tree (CART) model by conventional risk factors in middle-aged versus elderly (age >= 65years) diabetic and nondiabetic patients from the Modares Heart Study. Method: A total of 469 patients were randomly selected and categorized into two groups according to clinical diabetes status. Group I consisted of 238 diabetic patients and group II consisted of 231 nondiabetic patients. Our population was MI positive. The outcome investigated was diabetes mellitus. We used a decision-analytic model to predict the diagnosis of patients with suspected MI. Results: We constructed 4 predictive patterns using 12 input variables and 1 output variable in terms of their sensitivity, specificity and risk. The differences among patterns were due to inclusion of predictor variables. The CART model suggested different variables of hypertension, mean cell volume, fasting blood sugar, cholesterol, triglyceride and uric acid concentration based on middle-aged and elderly patients at high risk for MI. Levels of biochemical measurements identified as best risk cutoff points. In evaluating the precision of different patterns, sensitivity and specificity were 47.9-84.0% and 56.3-93.0%, respectively. Conclusions: The CART model is capable of symbolizing interpretable clinical data for confirming and better prediction of MI occurrence in clinic or in hospital. Therefore, predictor variables in pattern could affect the outcome based on age group variable. Hyperglycemia, hypertension, hyperlipidemia and hyperuricemia were serious predictors for occurrence of MI in diabetics.

关键词： classification and regression tree model diabetic elderly nondiabetic middle-aged myocardial infarction

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Factors Associated with Malnutrition among Tribal Children in India: A Non-Parametric Approach

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JOURNAL OF TROPICAL PEDIATRICS 2014年第3期60卷 211-215页

作者： Debnath, Avijit Bhattacharjee, Nairita Assam Univ Dept Econ Silchar 788011 Assam India

The purpose of this study is to identify the determinants of malnutrition among the tribal children in India. The investigation is based on secondary data compiled from the National Family Health Survey-3. We used a classification and regression tree model, a non-parametric approach, to address the objective. Our analysis shows that breastfeeding practice, economic status, antenatal care of mother and women's decision-making autonomy are negatively associated with malnutrition among tribal children. We identify maternal malnutrition and urban concentration of household as the two risk factors for child malnutrition. The identified associated factors may be used for designing and targeting preventive programmes for malnourished tribal children.

关键词： scheduled tribe child malnutrition classification and regression tree model India

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Climatic and topographic controls on patterns of fire in the southern and central Appalachian Mountains, USA

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LANDSCAPE ECOLOGY 2011年第2期26卷 195-209页

作者： Flatley, William T. Lafon, Charles W. Grissino-Mayer, Henri D. Texas A&M Univ Dept Geog College Stn TX 77843 USA Univ Tennessee Dept Geog Knoxville TN 37996 USA

Climate and topography are two important controls on spatial patterns of fire disturbance in forests globally, via their influence on fuel moisture and fuel production. To assess the influences of climate and topography on fire disturbance patterns in a temperate forest region, we analyzed the mapped perimeters of fires that burned during 1930-2003 in two national parks in the eastern United States. These were Great Smoky Mountains National Park (GSMNP) in the southern Appalachian Mountains and Shenandoah National Park (SNP) in the central Appalachian Mountains. We conducted GIS analyses to assess trends in area burned under differing climatic conditions and across topographic gradients (elevation, slope position, and aspect). We developed a classification and regression tree model in order to further explore the interactions between topography, climate, and fire. The results demonstrate that climate is a strong driver of both spatial and temporal patterns of wildfire. Fire was most prevalent in the drier SNP than the wetter GSMNP, and during drought years in both parks. Topography also influenced fire occurrence, with relatively dry south-facing aspects, ridges, and lower elevations burning most frequently. However, the strength of topographic trends varied according to the climatic context. Weaker topographic trends emerged in the drier SNP than GSMNP, and during low-PDSI (dry) years than high-PDSI (wet) years in both parks. The apparent influence of climate on the spatial patterning of fire suggests a more general concept, that disturbance-prone landscapes exhibit weaker fine-scale spatial patterning of disturbance than do less disturbance-prone landscapes.

关键词： Fire ecology Forest disturbance Climate Topography Fire perimeters Spatial pattern Great Smoky Mountains National Park Shenandoah National Park classification and regression tree model

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