Machine learning model based on RCA-PDCA nursing methods and differentiating factors to predict hypotension during cesarean section surgery.

BACKGROUND: Intraoperative hypotension during cesarean section has become a serious complication for maternal and fetal healthy. It is commonly encountered by subarachnoid anesthesia. However, currently used control methods have varying degrees of side effects, such as drugs. The Root Cause Analysis (RCA) - Plan, Do, Check, Act (PDCA) is a new model of care that identifies the root causes of problems. The study aimed to demonstrate the usefulness of RCA-PDCA nursing methods in preventing intraoperative hypotension during cesarean section and to predict the occurrence of intraoperative hypotension through a machine learning model. METHODS: Patients who underwent cesarean section at Traditional Chinese Medicine of Southwest Medical University from January 2023 to December 2023 were retrospectively screened, and the data of their gestational times, age, height, weight, history of allergies, intraoperative vital signs, fetal condition, operative time, fluid out and in, adverse effects, use of vasopressor drugs, anxiety-depression-pain scores, and satisfaction were collected and analyzed. The statistically different features were screened and five machine learning models were used as predictive models to assess the usefulness of the RCA-PDCA model of care. RESULTS: (1) Compared with the general nursing model, the RCA-PDCA nursing model significantly reduces the incidence of intraoperative hypotension and postoperative complications in cesarean delivery, and the patient experience is comfortable and satisfactory. (2) Among the five machine learning models, the RF model has the best predictive performance, and the accuracy of the random forest model in preventing intraoperative hypotension is as high as 90%. CONCLUSION: Through computer machine learning model analysis, we prove the importance of the RCA-PDCA nursing method in the prevention of intraoperative hypotension during cesarean section, especially the Random Forest model which performed well and promoted the application of artificial intelligence computer learning methods in the field of medical analysis.

In Silico Insights into Micro-Mechanism Understanding of Extracts of Taxus Chinensis Fruits Against Alzheimer's Disease.

BACKGROUND: The taxus chinensis fruit (TCF) shows promises in treatment of aging-related diseases such as Alzheimer's disease (AD). However, its related constituents and targets against AD have not been deciphered. OBJECTIVE: This study was to uncover constituents and targets of TCF extracts against AD. METHODS: An integrated approach including ultrasound extractions and constituent identification of TCF by UPLC-QE-MS/MS, target identification of constituents and AD by R data-mining from Pubchem, Drugbank and GEO databases, network construction, molecular docking and the ROC curve analysis was carried out. RESULTS: We identified 250 compounds in TCF extracts, and obtained 3,231 known constituent targets and 5,326 differential expression genes of AD, and 988 intersection genes. Through the network construction and KEGG pathway analysis, 19 chemicals, 31 targets, and 11 biological pathways were obtained as core compounds, targets and pathways of TCF extracts against AD. Among these constituents, luteolin, oleic acid, gallic acid, baicalein, naringenin, lovastatin and rutin had obvious anti-AD effect. Molecular docking results further confirmed above results. The ROC AUC values of about 87% of these core targets of TCF extracts was greater than 0.5 in the two GEO chips of AD, especially 10 targets with ROC AUC values greater than 0.7, such as BCL2, CASP7, NFKBIA, HMOX1, CDK2, LDLR, RELA, and CCL2, which mainly referred to neuron apoptosis, response to oxidative stress and inflammation, fibroblast proliferation, etc.Conclusions:The TCF extracts have diverse active compounds that can act on the diagnostic genes of AD, which deserve further in-depth study.

Geographical origin discriminatory analysis of onions: Chemometrics methods applied to ICP-OES and ICP-MS analysis.

Geographical origin is an important determinant of agricultural product quality and safety. Herein, inductively coupled plasma (ICP) analysis was applied to determine the inorganic elemental content of onions and identify their geographical origin (Korean or Chinese). Chemometric, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least square discriminant analysis (OPLS-DA) were applied to the ICP results. OPLS-DA distinguished each group, and 17 elements with variable importance in projection (VIP) values of ≥ 1 were selected. The receiver operating characteristic (ROC) curve had an area under the curve (AUC) of 1, indicating excellent discriminatory power. Differences in elemental content between groups were visually observed in a heatmap, and the country of origin was determined with 100% accuracy using canonical discriminant analysis (CDA). This method accurately distinguishes between Korean and Chinese onions and is expected to be beneficial for identifying agricultural products.

Diagnostic characteristics of refractometry cut-off points for the estimation of immunoglobulin G concentration in mare colostrum.

BACKGROUND: Feeding foals with poor quality colostrum predisposes them to failure of passive transfer (FPT). FPT is a major risk factor for neonatal infections. OBJECTIVES: To assess the optimal cut-offs for the optical (OR) and digital (DR) refractometer and determine their accuracy for poor quality colostrum diagnosis. STUDY DESIGN: A diagnostic validation study. METHODS: Eighty-one colostrum samples and sera were collected from broodmares and their neonatal foals, respectively. Colostral and serum IgG concentrations were measured by radial immunodiffusion (RID), DR and OR. Correlation coefficients were calculated. ROC curves were generated to identify optimal cut-offs for the refractometers and their diagnostic characteristics were evaluated. RESULTS: The optimal cut-offs for DR and OR were ≤23.75% and 23.9%, respectively. The sensitivity and specificity of the DR were 93.3% (95% CI: 66.0-99.7) and 87.9% (95% CI: 77.0-94.3) to detect colostral IgG <60 g/L, respectively. The sensitivity and specificity of the OR were 93.3% (95% CI: 66.0-99.7) and 81.8% (95% CI: 70.0-89.9), respectively. DR and OR had negative predictive values of 98.3% (95% CI: 89.7-99.9) and 98.2% (95% CI: 89.0-99.9), respectively, whilst positive predictive values were lower. No maternal variable, including breed, significantly influenced colostral IgG concentrations. Fifteen out of 81 colostrum samples had IgG <60 g/L. FPT and PFPT were diagnosed in 4/81 and 10/81 foals, respectively. Nine out of 14 animals with FPT/PFPT suckled colostrum with IgG <60 g/L. A moderate correlation (rs 0.542; P = .01) was observed between IgG concentrations measured by RID in sera and colostrum. MAIN LIMITATIONS: A smaller number of samples than the size requirement based on a priori estimate of specificity and the low prevalence of poor quality colostrum. CONCLUSIONS: The method has the potential to reliably differentiate between good and poor quality colostrum. Assessing colostrum quality by refractometry may be an indicator of passive transfer of immunity.

INTRODUCTION/CONTEXTE: Nourrir les poulains avec du colostrum de mauvaise qualité prédispose à l'échec du transfert d'immunité passive (FPT). FPT constitue un risque majeur pour les infections néonatales. OBJECTIFS: Évaluer les valeurs limites optimales au réfractomètre optique (RO) et digital (RD) et déterminer leur précision pour le diagnostic du colostrum de pauvre qualité. TYPE D'ÉTUDE: Étude de validation diagnostique. MÉTHODES: Quatre-vingt-un colostrums et sérums ont été recueillis à partir de juments de reproduction et de leur poulains nouveaux-nés respectivement. Les concentrations d'IgG dans le sérum et le colostrum ont été mesurées par immunodiffusion radiale (IDR), RO et RD. Les coefficients de corrélation ont été calculés. Des graphes d'air sous la courbe (ASC) ont été générés afin d'identifier les valeurs limites optimales aux différents réfractomètres et leurs caractéristiques diagnostiques ont été évaluées. RÉSULTATS: Les valeurs limites optimales pour les RD et RO étaient ≤23.75% et 23.9% respectivement. La sensibilité et la spécificité du RD étaient 93.3% (95% IC: 66.0-99.7) et 87.9% (95% IC: 77.0-94.3) pour la détection des IgG colostraux <6000 mg/dl, respectivement. La sensibilité et spécificité du RO étaient de 93.3% (95% IC: 66.0-99.7) et 81.8% (95% IC: 70.0-89.9), respectivement. Les RD et RO avaient une valeur prédictive négative de 98.3% (95% IC: 89.7-99.9) et 98.2% (95% IC: 89.0-99.9) respectivement, alors que les valeurs prédictives positives étaient plus basses. Aucune variable maternelle, incluant la race, n'a influencé significativement les concentrations colostrales en IgG. Quinze des 81 échantillons colostraux avaient une valeur d'IgG <6000 mg/dl. FPT et PFPT ont été diagnostiqué chez 4/81 et 10/81 poulains respectivement. Neuf des 14 animaux avec FPT/PFPT ont reçu du colostrum ayant des valeurs d'IgG <6000 mg/dl. Une corrélation modérée (rs 0.542; p= 0.01) a été observée entre les concentrations d'IgG mesurées par IDR dans le sérum et le colostrum. LIMITES PRINCIPALES: Le nombre d'échantillon est inférieur à celui recommandé basé sur unestimé a priori de la spécificité et considérant la faible prévalence de colostrum de pauvre qualité. CONCLUSIONS: La méthodologie utilisée pourrait différencier de façon fiable les colostrums de pauvre et bonne qualité. L'évaluation de la qualité du colostrum par réfractométrie pourrait représenter un indice du transfert d'immunité passive.

Iron quantitative analysis of motor combined with bulbar region in M1 cortex may improve diagnosis performance in ALS.

OBJECTIVES: To explore whether the combined analysis of motor and bulbar region of M1 on susceptibility-weighted imaging (SWI) can be a valid biomarker for amyotrophic lateral sclerosis (ALS). METHODS: Thirty-two non-demented ALS patients and 35 age- and gender-matched healthy controls (HC) were retrospectively recruited. SWI and 3D-T1-MPRAGE images were obtained from all individuals using a 3.0-T MRI scan. The bilateral posterior band of M1 was manually delineated by three neuroradiologists on phase images and subdivided into the motor and bulbar regions. We compared the phase values in two groups and performed a stratification analysis (ALSFRS-R score, duration, disease progression rate, and onset). Receiver operating characteristic (ROC) curves were also constructed. RESULTS: ALS group showed significantly increased phase values in M1 and the two subregions than the HC group, on the all and elderly level (p < 0.001, respectively). On all-age level comparison, negative correlations were found between phase values of M1 and clinical score and duration (p < 0.05, respectively). Similar associations were found in the motor region (p < 0.05, respectively). On both the total (p < 0.01) and elderly (p < 0.05) levels, there were positive relationships between disease progression rate and M1 phase values. In comparing ROC curves, the entire M1 showed the best diagnostic performance. CONCLUSIONS: Combining motor and bulbar analyses as an integral M1 region on SWI can improve ALS diagnosis performance, especially in the elderly. The phase value could be a valuable biomarker for ALS evaluation. KEY POINTS: • Integrated analysis of the motor and bulbar as an entire M1 region on SWI can improve the diagnosis performance in ALS. • Quantitative analysis of iron deposition by SWI measurement helps the clinical evaluation, especially for the elderly patients. • Phase value, when combined with the disease progression rate, could be a valuable biomarker for ALS.

Computed tomography enterography predicts surgical-free survival in symptomatic stricturing Crohn's disease.

OBJECTIVES: The study aimed to predict surgical risks for patients with symptomatic stricturing Crohn's disease (CD) using computed tomography enterography (CTE) and to assess the association between CTE findings and pathological changes. METHODS: Crohn's disease patients with symptomatic stricture(s) were included. Exclusion criteria were concomitant penetrating disease, intra-abdominal abscess, previous bowel resection, or asymptomatic. Patients from January 2016 to December 2019 were identified as the primary cohort and those from January 2020 to June 2020 were identified as the validation cohort. Two independent experienced radiologists evaluated CTE variables including mucosal enhancement, mural stratification, wall enhancement, comb sign, lymphadenopathy, thick non-enhancing wall, bowel wall thickness, luminal diameter, and upstream lumen. Receiver operating characteristic, logistic regression, and nomogram were performed to identify the independent predictors of surgical-free survival. Histopathological scores of surgical specimens were also evaluated. RESULTS: 198 patients (primary cohort, 123 with surgery and 75 under non-surgical intervention, and 41 patients (validation cohort) were analyzed. Bowel wall thickness < 5.9 mm, luminal stenosis > 3.35 mm, and upstream lumen < 27.5 mm were predictors of surgical-free survival for symptomatic stricturing CD patients. Logistic analysis showed the three CTE variables were the independent predictors of surgical-free survival (p < 0.001). A nomogram was developed with the concordance indexes of 0.905 and 0.892 in the primary and validation cohorts. Histopathological analysis showed bowel wall muscular hyperplasia/hypertrophy significantly correlated with luminal stenosis (r = - 0.655, p = 0.008) and combined CTE variable (r = - 0.683, p = 0.005). CONCLUSIONS: CTE is highly predictive of disease course and surgical-free survival for patients with symptomatic stricturing CD, suggesting the important role of CTE in decision-making of treatment.

[Evaluation of diagnostic efficacy of artery elasticity and endothelial function indexes for coronary heart disease with blood stasis syndrome in postmenopausal women by Logistic regression combined with ROC curve model].

The present study explored the correlation of coronary heart disease(CHD) with blood stasis syndrome in postmenopausal women with artery elasticity and endothelial function indexes and evaluated the diagnostic efficacy of the prediction model via logistic regression and receiver operating characteristic(ROC) curve model. A retrospective comparison was made between 366 postmenopausal CHD patients from August 1, 2020, to September 30, 2021, in the Department of Cardiology of Integrated Traditional Chinese and Western Medicine of China-Japan Friendship Hospital, who were divided into the blood stasis syndrome group(n=196) and the non-blood stasis syndrome group(n=170). General clinical characteristics of the two groups were compared. Multivariate logistic regression analysis was used to probe the correlation of CHD with blood stasis syndrome in postmenopausal women with brachial-ankle pulse wave velocity(baPWV), ankle-brachial index(ABI), and flow-mediated dilatation(FMD), and the ROC curve was drawn to evaluate the diagnostic efficiency of the prediction model. Multivariate logistic regression analysis showed that the correlation coefficients of CHD with blood stasis syndrome in postmenopausal women with baPWV, ABI, and FMD were 1.123, 0.109, and 0.719, respectively(P=0.004, P=0.005, P<0.001),and the regression equation for predicting probability P was P=1/[1+e~(-(3.131+0.116×baPWV-2.217×ABI-0.330×FMD))]. ROC curve analysis suggested that in the context of baPWV≥19.19 m·s~(-1) or ABI≤1.22 or FMD≤9.7%, it was of great significance to predict the diagnosis of CHD with blood stasis syndrome in postmenopausal women. The AUC of baPWV, ABI, FMD, and prediction probability P was 0.763, 0.607, 0.705, and 0.836, respectively. The AUC of prediction probability P was higher than that of each index alone(P<0.001), and the sensitivity and specificity were 0.888 and 0.647, respectively. The results demonstrate that baPWV, ABI, and FMD are independently correlated with CHD with blood stasis syndrome in postmenopausal women, and show certain independent predictive abilities(P<0.05). The combined evaluation of the three possesses the best diagnostic efficiency.

Breast cancer-related lymphoedema: Risk factors and prediction model.

AIMS: To identify the risk factors for lymphoedema following axillary lymph node dissection (ALND) in a European sample and to propose a lymphoedema prediction model for this population. DESIGN: Predictive retrospective cohort study comparing women who developed lymphoedema in 2 years of undergoing ALND with those who did not developed lymphoedema. METHODS: We reviewed the clinical records of 504 women who, between January 2008 and May 2018, underwent surgery for breast cancer that involved ALND. Logistic regression was used to identify significant risk factors for lymphoedema. The prediction accuracy of the model was assessed by calculating the area under the receiver operating characteristic curve. RESULTS: Of the 504 women whose records were analysed, 156 developed lymphoedema. Significant predictors identified in the regression model were level of lymph node dissection, lymph node status, post-operative complications, body mass index (BMI) and number of lymph nodes extracted. The prediction model showed good sensitivity (80%) in the study population. CONCLUSIONS: The factor contributing most to the risk of lymphoedema was the level of lymph node dissection, and the only patient-related factor in the prediction model was BMI. The model offers good predictive capacity in this population and it is a simple tool that breast care units could use to assess the risk of lymphoedema following ALND. Nurses with specialist knowledge of lymphoedema have a key role to play in ensuring that women receive holistic and individualized care. IMPACT: What problem did the study address? Secondary lymphoedema is one of the main complications in the treatment of breast cancer. What were the main findings? The prediction model included five factors associated with the risk of lymphoedema following ALND. The strongest predictor was the level of lymph node dissection, and the only patient-related factor was BMI. Where and on whom will the research have an impact? The prediction model offers breast care units a tool for assessing the risk of lymphoedema in women undergoing surgery involving ALND. The results highlight the importance of weight reduction as a preventive measure and support a more conservative surgical approach.

Nuevo índice de desempeño global de una prueba diagnóstica: el índice T / New global performance index of a diagnostic test: the T index

Introducción. En el presente artículo se propone un nuevo índice de desempeño global de una prueba diagnóstica: el índice T, que corresponde a la proporción de aciertos (Pa) menos la proporción de error (Pe) dividido entre la proporción de aciertos (Pa). Métodos. Describir los fundamentos teóricos y prácticos del índice T. Comparar el índice T frente al índice de Youden para poder establecer si dos o más modalidades diagnósticas difieren en su capacidad de discriminar, correctamente, entre los individuos verdaderamente enfermos de los sanos. Comparar el índice T frente al índice de Youden para poder establecer si el índice T puede ser utilizado para escoger "el mejor punto de corte" cuando la prueba diagnóstica de interés expresa sus resultados en forma cuantitativa continua.Resultados. Comparado frente al índice de Youden, el índice T permite distinguir entre las pruebas diagnósticas con alto desempeño diagnóstico de aquellas con pobre desempeño diagnóstico. Además, el índice T, de manera confiable, permite escoger "el mejor punto de corte" cuando una prueba diagnóstica utiliza una variable cuantitativa continua para expresar sus resultados.Conclusiones. Al contrastar los resultados del índice T versusel índice de Youden y los resultados del índice T versus la curva COR, podemos afirmar que el índice T es un índice exacto y eficiente.

Introduction. In this article, a new global performance index of a diagnostic test is proposed: the T Index, which corresponds to the proportion of the hit ratio (Hr) minus the error ratio (Er) divided by the hit ratio (Hr).Methods. To describe the theoretical and practical foundations of the T index; to compare the T index against the Youden index in order to establish whether two or more diagnostic modalities differ in their ability to correctly discriminate between truly ill and healthy individuals; and to compare the T index with the Youden index in order to establish whether the T index can be used to choose the "best cut-off point" when the diagnostic test of interest expresses its results in a continuous quantitative way.Results. Compared with the Youden index, the T index allows us to differentiate between diagnostic tests with high diagnostic performance and those with poor diagnostic performance. In addition, the T index, reliably, allows choosing "the best cut-off point" when a diagnostic test uses a continuous quantitative variable to express its results.Conclusions. By contrasting the results of the T index versus the Youden index and the results of the T index versus the COR curve, we can affirm that the T index is an accurate and efficient index.

A Comparison of Multiple Allergen Simultaneous Tests Using Allergen-Specific IgE Concentration and Intradermal Skin Tests in Atopic Horses With Pollen Allergy.

Intradermal tests (IDTs) and measurement of specific immunoglobulin E class (sIgE) levels in sera are the most common and reliable methods used in allergological clinical practice. The purpose of this study was to explore the sensitization of pollen allergy in atopic horses with pollinosis and to assess the diagnostic value of the multiple allergen simultaneous tests (MASTs) compared with that of the IDT. Twenty-one Malopolski horses with typical skin hypersensitivity symptoms during pollen seasons were enrolled. Intradermal tests were performed, and allergen-specific IgE concentrations in sera were measured using a monoclonal anti-IgE antibody to pollens of grass, weeds, trees, and cultivated plants. The highest sensitization rate was for Secale cereale (IDT, 76%; MAST, 66.7%), grass (IDT, 71%; MAST, 57%), and Brassica napus (IDT, 52.4%; MAST, 57%). Receiver operating characteristic (ROC) curve analysis and the area under the ROC curve (AUC) showed that Betula spp., Alnus spp., and Corylus spp. had the highest AUC at 0.854, followed by Secale cereale (AUC = 0.796), Plantago lanceolata (AUC = 0.726), Brassica napus (AUC = 0.704), and a grass allergen mixture (AUC = 0.695). The mean AUC for all allergens was 0.712 (0.604-0.867). The overall sensitivity of the sIgE plant horse panel was 78% (range, 68%-90%), the specificity was 86.3% (range, 64%-100%), and the accuracy was 79% (range, 64%-87%). Statistical kappa (κ) agreement between the MAST and IDT was reached for tree (κ = 0.767), rye (κ = 0.687), colza (κ = 0.671), and grass (κ = 0.664) pollen. The MAST showed a favorable agreement with the IDT and can be used for the detection of sIgE in atopic horses with pollinosis.

Identifying early postoperative serum parathyroid hormone levels as predictors of hypocalcaemia after total thyroidectomy: A prospective non-randomized study.

OBJECTIVE: There is no clear cut-off value of serum parathyroid hormone (PTH) or calcium in which patients are at risk for hypocalcemia after total thyroidectomy. We evaluated the usefulness of serum calcium and PTH concentration measurements after total thyroidectomy in predicting late-occurring hypocalcemia. DESIGN: A prospective, single-center, non-randomized longitudinal cohort study of 143 patients undergoing thyroidectomy between August 2019 and December 2019 with serum calcium and PTH levels sampled 1 h after surgery and on the first and fifth postoperative day. Hypocalcemia was defined as serum calcium levels < 2.14 mmol/L regardless of clinical symptoms. Normal PTH range was 1.6-6.9 pmol/L. MEASUREMENTS: The primary outcome measure was presence of hypocalcemia on the first and fifth postoperative day, analyzed by a logistic regression model. The PTH cut-off value for prediction of hypocalcemia was identified using a ROC curve comparing all three time points using the Youden J index. RESULTS: Out of 143 patients, 52 (36.4%) had hypocalcemia on the fifth postoperative day. Advanced age, concomitant neck dissection and serum PTH levels < 2.9 pmol/L 1 h after surgery and on the first postoperative surgery day were associated with a high risk of hypocalcemia on the first and fifth postoperative day and need for higher doses of calcium supplements (P < 0.0001, AUC 0.748, 95% CI 0.669-0.817, with 76.92% sensitivity and 71.43% specificity). CONCLUSION: Serum PTH level measured immediately postoperatively and on the first postoperative day is a reliable predictor of postoperative hypocalcemia with important clinical implications.

Establishment and verification of preeclampsia risk assessment model / 中华疾病控制杂志

Objective To analyze the risk factors affecting pre-eclampsia, to establish a pre-eclampsia risk assessment model, and to assess the risk of pre-eclampsia early. Methods A face-to-face questionnaire survey was conducted for all women who gave birth in the Department of Obstetrics, the First Hospital of Shanxi Medical University from March 2012 to September 2016. A total of 10 319 qualified questionnaires were collected to exclude 9 623 cases of other hypertensive diseases related to pregnancy. A total of 70% of the subjects were randomly selected as training samples to analyze the influencing factors of pre-eclampsia, and a Logistic regression model was established. The remaining 30% of the objects are used as test samples to verify the effect of the model. Results Logistic regression model was established with training samples. Logit P=-2.517-0.696×Pre-pregnancy lean +0.200 ×Pre-pregnancy overweight +0.944×Pre-pregnancy obesity -1.995×Residential in city -0.409×Folic acid supplemented before pregnancy +1.323×Twin and multiple pregnancy +1.708× History of previous pregnancy hypertension. Homer-Lemeshow test P=0.377. Model AUC=0.767 (95%CI:0.747-0.786, P<0.001). Using the test sample to verify the model, the model sensitivity was 81.68%, the specificity was 75.05%, the positive likelihood ratio was 3.27, and the negative likelihood ratio was 0.24. The test sample model AUC = 0.771 (95%CI=0.763-0.790,P<0.001). Conclusion This study establishes a simple and effective pre-eclampsia risk assessment model with controllable factors. The model has good fit and sensitivity and specificity.

Determination of Content Limit of Isoflavone Glucoside of Hengshan Wild-simulated Astragali Radix by ROC Curve Method / 中国实验方剂学杂志

Objective: To explore the receiuer operating characteristic(ROC) curve mathematical statistics method to establish the content limit of isoflavones glucoside contents in Astragali Radix,in order to distinguish the difference in isoflavones glucoside content between Hengshan wild-simulated Astragali Radix in Shanxi and cultivated Astragali Radix in Gansu. Method: A total of 225 samples of 45 batches of wild-simulated Astragali Radix in Hengshan and 210 samples of 42 batches of cultivated Astragali Radix in Gansu were selected as research objects,and isoflavones glucoside contents of these samples were determined by using the method in the edition 2015 Chinese Pharmacopoeia. Data was statistically analyzed, and the ROC curve was used to determine the critical value of wild-simulated Astragali Radix in Hengshan and transplanted Astragali Radix in Gansu. Result: The average contents of isoflavones glucoside in imitative wild Astragali Radix in Henshan and cultivated Astragali Radix in Gansu were 0.107%and 0.039%respectively,with statistically significant differences(PConclusion: ROC curve can be used to distinguish the critical value of the wild-simulated Astragali Radix in Hengshan and cultivated Astragali Radix in Gansu. The results reflected the regularity of "high quality and good price" in the market. The research provided a theoretical basis for the establishment of standard of high-quality Chinese herbal medicines.

Urbanization and climate change impacts on surface water quality: Enhancing the resilience by reducing impervious surfaces.

Climate change and urbanization are key factors affecting the future of water quality in urbanized catchments. The work reported in this paper is an evaluation of the combined and relative impact of climate change and urbanization on the water quality of receiving water bodies in the context of a highly urbanized watershed served by a combined sewer system (CSS) in northern Italy. The impact is determined by an integrated modelling study involving two years of field campaigns. The results obtained from the case study show that impervious urban surfaces and rainfall intensity are significant predictors of combined sewer overflows (CSOs) and consequently of the water quality of the receiving water body. Scenarios for the year 2100 demonstrate that climate change combined with increasing urbanization is likely to lead to severe worsening of river water quality due to a doubling of the total phosphorus load from CSOs compared to the current load. Reduction in imperviousness was found to be a suitable strategy to adapt to these scenarios by limiting the construction of new impervious areas and decreasing the existing areas by only 15%. This information can be further utilized to develop future designs, which in turn should make these systems more resilient to future changes in climate and urbanization.

Development of a clinical prediction algorithm for knee osteoarthritis structural progression in a cohort study: value of adding measurement of subchondral bone density.

BACKGROUND: Risk prediction algorithms increase understanding of which patients are at greatest risk of a harmful outcome. Our goal was to create a clinically useful prediction algorithm for structural progression of knee osteoarthritis (OA), using medial joint space loss as a proxy; and to quantify the benefit of including periarticular bone mineral density (BMD) in the algorithm. METHODS: Participants were from the Osteoarthritis Initiative (OAI) Progression Cohort, with X-ray readings of medial joint space at 36- and 48-month visits, and a 30- or 36-month medial-to-lateral tibial BMD ratio (M:L BMD ratio) value. Loss of medial joint space was the outcome and clinically available factors associated with OA progression were employed in the base prediction algorithm, with M:L BMD ratio added to an enhanced prediction algorithm. The benefit of adding M:L BMD ratio was evaluated by change in area under the ROC curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI). RESULTS: Five hundred thirty-three participants were included; 51 (14%) had medial joint space loss; 47% were female; the mean (SD) age was 64.6 (9.2) years and BMI was 29.6 (4.8) kg/m2. The base algorithm model included age, BMI, gender, recent injury, knee pain, and hand OA as predictors and had an AUC value of 0.65. The algorithm adding M:L BMD ratio had an AUC value of 0.73, and the AUC, NRI and IDI were all significantly improved (p ≤ 0.002). CONCLUSIONS: This clinical prediction algorithm predicts structural progression in individuals with OA using only clinically available predictors supplemented by the M:L BMD ratio, a biomarker that could be made available at clinical sites.

Finding an appropriate equation to measure similarity between binary vectors: case studies on Indonesian and Japanese herbal medicines.

BACKGROUND: The binary similarity and dissimilarity measures have critical roles in the processing of data consisting of binary vectors in various fields including bioinformatics and chemometrics. These metrics express the similarity and dissimilarity values between two binary vectors in terms of the positive matches, absence mismatches or negative matches. To our knowledge, there is no published work presenting a systematic way of finding an appropriate equation to measure binary similarity that performs well for certain data type or application. A proper method to select a suitable binary similarity or dissimilarity measure is needed to obtain better classification results. RESULTS: In this study, we proposed a novel approach to select binary similarity and dissimilarity measures. We collected 79 binary similarity and dissimilarity equations by extensive literature search and implemented those equations as an R package called bmeasures. We applied these metrics to quantify the similarity and dissimilarity between herbal medicine formulas belonging to the Indonesian Jamu and Japanese Kampo separately. We assessed the capability of binary equations to classify herbal medicine pairs into match and mismatch efficacies based on their similarity or dissimilarity coefficients using the Receiver Operating Characteristic (ROC) curve analysis. According to the area under the ROC curve results, we found Indonesian Jamu and Japanese Kampo datasets obtained different ranking of binary similarity and dissimilarity measures. Out of all the equations, the Forbes-2 similarity and the Variant of Correlation similarity measures are recommended for studying the relationship between Jamu formulas and Kampo formulas, respectively. CONCLUSIONS: The selection of binary similarity and dissimilarity measures for multivariate analysis is data dependent. The proposed method can be used to find the most suitable binary similarity and dissimilarity equation wisely for a particular data. Our finding suggests that all four types of matching quantities in the Operational Taxonomic Unit (OTU) table are important to calculate the similarity and dissimilarity coefficients between herbal medicine formulas. Also, the binary similarity and dissimilarity measures that include the negative match quantity d achieve better capability to separate herbal medicine pairs compared to equations that exclude d.

Anatomically related gray and white matter alterations in the brains of functional dyspepsia patients.

BACKGROUND: Previous studies summarized altered brain functional patterns in functional dyspepsia (FD) patients, but how the brain structural patterns are related to FD remains largely unclear. The objective of this study was to determine the brain structural characteristics in FD patients. METHODS: Optimized voxel-based morphometry and tract-based spatial statistics were employed to investigate the changes in gray matter (GM) and white matter (WM) respectively in 34 FD patients with postprandial distress syndrome and 33 healthy controls based on T1-weighted and diffusion-weighted imaging. The Pearson's correlation evaluated the link among GM alterations, WM abnormalities, and clinical variables in FD patients. The optimal brain structural parameters for identifying FD were explored using the receiver operating characteristic curve. KEY RESULTS: Compared to controls, FD patients exhibited a decrease in GM density (GMD) in the right posterior insula/temporal superior cortex (marked as pINS), right inferior frontal cortex (IFC), and left middle cingulate cortex, and an increase in fractional anisotropy (FA) in the posterior limb of the internal capsule, posterior thalamic radiation, and external capsule (EC). Interestingly, the GMD in the pINS was significantly associated with GMD in the IFC and FA in the EC. Moreover, the EC adjacent to the pINS provided the best performance for distinguishing FD patients from controls. CONCLUSIONS & INFERENCES: Our results showed pINS-related structural abnormalities in FD patients, indicating that GM and WM parameters were not affected independently. These findings would lay the foundation for probing an efficient target in the brain for treating FD.

A Comparative Study on the Validity of Fall Risk Assessment Scales in Korean Hospitals

PURPOSE: The purpose of this study was to compare the validity of three fall risk assessment scales including the Morse Fall Scale (MFS), the Bobath Memorial Hospital Fall Risk Assessment Scale (BMFRAS), and the Johns Hopkins Hospital Fall Risk Assessment Tool (JHFRAT). METHODS: This study was a prospective validation cohort study in five acute care hospitals in Seoul and Gyeonggi-Do, Korea. In total, 356 patients over the age of 18 years admitted from December 2009 to February 2010 participated. The three fall risk assessment scales listed above were tested for sensitivity, specificity, positive predictive and negative predictive values. A receiver-operating characteristic (ROC) curve was generated to show sensitivities and specificities for predicting falls based on different threshold scores for considering patients at high risk. RESULTS: Based on the mean scores of each scale for falls, the MFS at a cut-off score of 50 had a sensitivity of 78.9%, specificity of 55.8%, positive predictive value of 30.8%, and negative predictive value of 91.4%, which were the highest values among the three fall assessment scales. Areas under the curve of the ROC curves were .761 for the MFS, .715 for the BMFRAS, and .708 for the JHFRAT. CONCLUSIONS: Accordingly, of the three fall risk assessment scales, the highest predictive validity for identifying patients at high risk for falls was achieved by the MFS.