A quick method to customize pictorial blood assessment tools towards better measurement: Method development and validation.

OBJECTIVE: Identification of heavy menstrual bleeding (HMB) cases in primary care settings is often done by using pictorial blood assessment charts (PBAC). The study aims to highlight the challenge of assessing blood loss, to develop a standardized method to efficiently customize a patient-reported pictorial chart, to validate the tool produced with our proposed method, and to demonstrate the feasibility of using PBACs in settings where resources are scarce. MATERIALS AND METHODS: Using blood samples and feedback from 21 women aged 30-51 years, we followed guidelines suggested in the literature, developed a method to produce PBACs for regular, long and night sizes, and had 9 participants testuse them. Linear regression analysis was performed to determine the correlation between participants' scores and menstrual blood weight. RESULTS: The study demonstrated the feasibility of customizing product-sensitive and size-specific pictorial charts by adopting essential steps including collecting menstrual blood with menstrual cups, employing fluid application techniques, and using sanitary pads as icons for easy identification. Linear regression analyses of score versus blood weight showed that the recorded blood weight was around 95% of the scored values (R2 = 0.9428, 0.947, and 0.9508, respectively; p < 0.001). CONCLUSION: Valid patient-reported PBACs created by the proposed method provides an innovative women's healthcare solution to assist HMB identification and reduce health expenditure by preventing risks for HMB related complications in varying economic and technological contexts. Women's participation in tracking menstrual abnormalities may improve health literacy.

Prey group defense and hunting cooperation among generalist-predators induce complex dynamics: a mathematical study.

Group defense in prey and hunting cooperation in predators are two important ecological phenomena and can occur concurrently. In this article, we consider cooperative hunting in generalist predators and group defense in prey under a mathematical framework to comprehend the enormous diversity the model could capture. To do so, we consider a modified Holling-Tanner model where we implement Holling type IV functional response to characterize grazing pattern of predators where prey species exhibit group defense. Additionally, we allow a modification in the attack rate of predators to quantify the hunting cooperation among them. The model admits three boundary equilibria and up to three coexistence equilibrium points. The geometry of the nontrivial prey and predator nullclines and thus the number of coexistence equilibria primarily depends on a specific threshold of the availability of alternative food for predators. We use linear stability analysis to determine the types of hyperbolic equilibrium points and characterize the non-hyperbolic equilibrium points through normal form and center manifold theory. Change in the model parameters leading to the occurrences of a series of local bifurcations from non-hyperbolic equilibrium points, namely, transcritical, saddle-node, Hopf, cusp and Bogdanov-Takens bifurcation; there are also occurrences of global bifurcations such as homoclinic bifurcation and saddle-node bifurcation of limit cycles. We observe two interesting closed 'bubble' form induced by global bifurcations due to change in the strength of hunting cooperation and the availability of alternative food for predators. A three dimensional bifurcation diagram, concerning the original system parameters, captures how the alternation in model formulation induces gradual changes in the bifurcation scenarios. Our model highlights the stabilizing effects of group or gregarious behaviour in both prey and predator, hence supporting the predator-herbivore regulation hypothesis. Additionally, our model highlights the occurrence of "saltatory equilibria" in ecological systems and capture the dynamics observed for lion-herbivore interactions.

Association Between Urinary Phthalate Metabolites and Chronic Obstructive Pulmonary Disease: A Cross-Sectional Study.

Objective: To determine the association of urinary phthalate metabolites with chronic obstructive pulmonary disease (COPD), airflow obstruction, lung function and respiratory symptoms. Methods: Our study included a total of 2023 individuals aged ≥ 40 years old in the National Health and Nutrition Examination Survey (NHANES). Multivariate logistic regression was conducted to explore the correlation of eleven urinary phthalate metabolites (MCNP, MCOP, MECPP, MnBP, MCPP, MEP, MEHHP, MEHP, MiBP, MEOHP, and MBzP) with COPD, airflow obstruction and respiratory symptoms. Linear regression analyses were used to evaluate the relationship between urinary phthalate metabolites and lung function. Results: When compared to the first tertile, the third tertile of MEHHP was associated with the risk of COPD [OR: 2.779; 95% confidence interval (CI): 1.129-6.840; P = 0.026]. Stratified analysis showed that MEHHP increased the risk of COPD by 7.080 times in male participants. Both MCPP and MBzP were positively correlated with the risk of airflow obstruction. The third tertile of MBzP increased the risk of cough by 1.545 (95% CI: 1.030-2.317; P = 0.035) times. Both FEV1 and FVC were negatively associated with MEHHP, MECPP, MnBP, MEP, MiBP and MEOHP. Conclusion: Higher levels of MEHHP are associated with increased risk of COPD, and lower measures of FEV1 and FVC. MBzP is positively related to airflow obstruction and cough.

Bayesian inference for multivariate probit model with latent envelope.

The response envelope model proposed by Cook et al. (2010) is an efficient method to estimate the regression coefficient under the context of the multivariate linear regression model. It improves estimation efficiency by identifying material and immaterial parts of responses and removing the immaterial variation. The response envelope model has been investigated only for continuous response variables. In this paper, we propose the multivariate probit model with latent envelope, in short, the probit envelope model, as a response envelope model for multivariate binary response variables. The probit envelope model takes into account relations between Gaussian latent variables of the multivariate probit model by using the idea of the response envelope model. We address the identifiability of the probit envelope model by employing the essential identifiability concept and suggest a Bayesian method for the parameter estimation. We illustrate the probit envelope model via simulation studies and real-data analysis. The simulation studies show that the probit envelope model has the potential to gain efficiency in estimation compared to the multivariate probit model. The real data analysis shows that the probit envelope model is useful for multi-label classification.

Improved high-performance liquid chromatography tandem mass spectrometry method for quantification of infliximab in pediatric plasma and its application in therapeutic drug monitoring.

RATIONALE: The application of infliximab (IFX) to immune-mediated disease is limited by the significant individual variability and associated clinical nonresponse, emphasizing the importance of therapeutic drug monitoring (TDM). Because of the cross-reactivity, limited linear range, and high costs, the clinical application of the previous reported methods was limited. Here, an improved high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) method was developed to address the issues. METHODS: This study developed an improved bioanalytical HPLC-MS/MS method coupling nanosurface and molecular-orientation limited proteolysis technology. The commercially available compound P14R was selected as the internal standard. This method was developed with fewer volume of reagents and was thoroughly validated. The validated method was applied to TDM in pediatric inflammatory bowel disease (IBD). RESULTS: Chromatography was performed using a Shim-pack GISS-HP C18 metal-free column (3 µm, 2.1 × 100 mm) with a gradient elution of 0.1% formic acid in water and acetonitrile at 0.4 mL/min. Detection and quantitation were performed using electrospray ionization (ESI) and multiple reaction monitoring in the positive ion mode. The method was validated to demonstrate its selectivity, linearity, accuracy, precision, recovery, matrix effect, and stability. The method exhibited a linear dynamic range of 0.3-100 µg/mL, with intra- and inter-day precision and relative errors below 15%. The recovery and matrix effect were measured as 87.28%-89.72% and 41.98%-67.17%, respectively, which were effectively compensated by the internal standard. A total of 32 samples collected from 24 pediatric patients with IBD were analyzed using the validated method, and only 46.9% achieved the reported targeted trough level. CONCLUSION: This study developed an improved HPLC-MS/MS method for the quantitative determination of IFX concentration in human plasma. The accurate, reliable, and cost-effective method was validated and utilized in the analysis of clinical samples. The results confirmed the importance of TDM on IFX and the clinical application prospects of the improved method.

Accuracy of prediction from multi-environment trials for new locations using pedigree information and environmental covariates: the case of sorghum (Sorghum bicolor (L.) Moench) breeding.

KEY MESSAGES: We investigate a method of extracting and fitting synthetic environmental covariates and pedigree information in multilocation trial data analysis to predict genotype performances in untested locations. Plant breeding trials are usually conducted across multiple testing locations to predict genotype performances in the targeted population of environments. The predictive accuracy can be increased by the use of adequate statistical models. We compared linear mixed models with and without synthetic covariates (SCs) and pedigree information under the identity, the diagonal and the factor-analytic variance-covariance structures of the genotype-by-location interactions. A comparison was made to evaluate the accuracy of different models in predicting genotype performances in untested locations using the mean squared error of predicted differences (MSEPD) and the Spearman rank correlation between predicted and adjusted means. A multi-environmental trial (MET) dataset evaluated for yield performance in the dry lowland sorghum (Sorghum bicolor (L.) Moench) breeding program of Ethiopia was used. For validating our models, we followed a leave-one-location-out cross-validation strategy. A total of 65 environmental covariates (ECs) obtained from the sorghum test locations were considered. The SCs were extracted from the ECs using multivariate partial least squares analysis and subsequently fitted in the linear mixed model. Then, the model was extended accounting for pedigree information. According to the MSEPD, models accounting for SC improve predictive accuracy of genotype performances in the three of the variance-covariance structures compared to others without SC. The rank correlation was also higher for the model with the SC. When the SC was fitted, the rank correlation was 0.58 for the factor analytic, 0.51 for the diagonal and 0.46 for the identity variance-covariance structures. Our approach indicates improvement in predictive accuracy with SC in the context of genotype-by-location interactions of a sorghum breeding in Ethiopia.

Independent variables of pH: Ten Knights of the Hydrogen Ion Kingdom-Part I. A prospective observational study.

CO2, HCO3, SID, and total weak acids have been defined as pH's independent variables. However, according to Gamble, HCO3 should be equal to the difference between the sum of cations and the sum of anions besides HCO3. Therefore, if this mathematical expression is substituted for HCO3 in the Henderson-Hasselbalch equation, all independent variables of pH can be demonstrated. Our aim is to test this theory in this study. This prospective observational study was conducted between 2019 and 2020. All admitted patients to the intensive care unit who were >18 years old were included. Demographic data, blood gas parameters, albumin, magnesium, and inorganic phosphorus levels, and outcomes were recorded twice (at admission and at the 24th hour). The multivariate linear regression model was used to determine pH's independent variables. In the multivariate linear regression model, pH was significantly increased by each unit increase in Na, K, Ca, and Mg (mmol L-1). In contrast, pH was significantly decreased by each unit increase in CO2, Cl, lactate, albumin (g dL-1), inorganic phosphorus (mg dL-1), and the strong ion gap. Ten independent variables can accurately predict the changes in pH. For this reason, all ten independent variables should be separately evaluated when interpreting the acid-base status. With this understanding, all algorithms regarding acid-base evaluation may become unnecessary.

Importance Assigned to Breastfeeding by Spanish Pregnant Women and Associated Factors: A Survey-Based Multivariate Linear Correlation Study.

Breastfeeding education, across all disciplines, is often inconsistent and lacking in expertise and confidence. However, recommendations from health professionals, the sociocultural environment, and previous knowledge and experiences significantly influence women's decision to breastfeed. This study aimed to identify factors that promote the assignment of greater importance to breastfeeding and associated practical benefits. This retrospective cross-sectional study included 276 participants who completed a self-administered questionnaire. Descriptive and bivariate analyses were performed, and multivariate linear models were applied to identify factors influencing the importance assigned to breastfeeding. Most participants were married or in a relationship, were native Spaniards, had secondary or higher education, and had an average age of 32.6 years. Seventy percent met the physical activity recommendations, and 91% felt comfortable with their body image during pregnancy. The importance assigned to breastfeeding was high across various aspects, except for postpartum weight loss and body image. Group prenatal care was only significantly associated with the importance assigned to the breastfeeding technique (how to breastfeed). The obesogenic environment and the importance assigned to nutritional aspects and physical activity also turned out to be predictors, although not for all models. In our region, the educational strategy of antenatal care groups could contain gaps regarding the mother's health, which should be addressed in the future to improve results regarding the initiation and continuation of breastfeeding.

High-dimensional multi-omics measured in controlled conditions are useful for maize platform and field trait predictions.

KEY MESSAGE: Transcriptomics and proteomics information collected on a platform can predict additive and non-additive effects for platform traits and additive effects for field traits. The effects of climate change in the form of drought, heat stress, and irregular seasonal changes threaten global crop production. The ability of multi-omics data, such as transcripts and proteins, to reflect a plant's response to such climatic factors can be capitalized in prediction models to maximize crop improvement. Implementing multi-omics characterization in field evaluations is challenging due to high costs. It is, however, possible to do it on reference genotypes in controlled conditions. Using omics measured on a platform, we tested different multi-omics-based prediction approaches, using a high dimensional linear mixed model (MegaLMM) to predict genotypes for platform traits and agronomic field traits in a panel of 244 maize hybrids. We considered two prediction scenarios: in the first one, new hybrids are predicted (CV-NH), and in the second one, partially observed hybrids are predicted (CV-POH). For both scenarios, all hybrids were characterized for omics on the platform. We observed that omics can predict both additive and non-additive genetic effects for the platform traits, resulting in much higher predictive abilities than GBLUP. It highlights their efficiency in capturing regulatory processes in relation to growth conditions. For the field traits, we observed that the additive components of omics only slightly improved predictive abilities for predicting new hybrids (CV-NH, model MegaGAO) and for predicting partially observed hybrids (CV-POH, model GAOxW-BLUP) in comparison to GBLUP. We conclude that measuring the omics in the fields would be of considerable interest in predicting productivity if the costs of omics drop significantly.

An Analysis of Optic Disc Parameters in Patients with Peripheral Retinal Tears Following Acute Posterior Vitreous Detachment: A Cross-Sectional Study.

Background: To investigate association between optic disc parameters analyzed by optical coherence tomography (OCT) and occurrence of peripheral retinal tears in patients with symptomatic posterior vitreous detachment (PVD). Methods: This cross-sectional study enrolled 75 patients with symptoms of acute PVD, who were allocated into two groups based on whether a peripheral retinal tear occurred or not. Results: When comparing the average retinal nerve fiber layer (RNFL) thickness (µm) between retinal tear and control groups, it was shown that patients with a retinal tear have a significantly higher (87.18 [95% confidence interval (CI), 84.47 to 89.9] vs 81.14 [95% CI, 77.81 to 84.46], P = 0.005) average RNFL thickness. Furthermore, we observed a significant difference (0.13, 0.06 to 0.22 vs 0.07, 0.04 to 0.1, P = 0.036, Mann-Whitney U-test) in the size of cup volume (mm3) between the tear and control groups, respectively. Linear regression showed a significant decrease (P = 0.029) in average RNFL thickness with increasing age, but without a significant difference between the two groups. There was no statistically significant difference between the tear and control groups in terms of rim area, disc area, and average cup-to-disc ratio. Conclusion: Patients with a higher average RNFL thickness and larger cup volume measured by OCT were more prone to develop a peripheral retinal tear. Increased peripapillary average RNFL thickness due to trauma and subsequent inflammation, possibly related to the more adherent posterior hyaloid membrane to the retina, may also indicate strengthened adhesions in the areas of the peripheral retina where retinal tears occur. OCT analysis of the optic nerve head may be used in everyday clinical practice as a predictor of the development of peripheral retinal tears in patients with symptomatic PVD.

Expiratory Venous Volume and Arterial Tortuosity are Associated with Disease Severity and Mortality Risk in Patients with COPD: Results from COSYCONET.

Purpose: The aim of this study was to evaluate the association between computed tomography (CT) quantitative pulmonary vessel morphology and lung function, disease severity, and mortality risk in patients with chronic obstructive pulmonary disease (COPD). Patients and Methods: Participants of the prospective nationwide COSYCONET cohort study with paired inspiratory-expiratory CT were included. Fully automatic software, developed in-house, segmented arterial and venous pulmonary vessels and quantified volume and tortuosity on inspiratory and expiratory scans. The association between vessel volume normalised to lung volume and tortuosity versus lung function (forced expiratory volume in 1 sec [FEV1]), air trapping (residual volume to total lung capacity ratio [RV/TLC]), transfer factor for carbon monoxide (TLCO), disease severity in terms of Global Initiative for Chronic Obstructive Lung Disease (GOLD) group D, and mortality were analysed by linear, logistic or Cox proportional hazard regression. Results: Complete data were available from 138 patients (39% female, mean age 65 years). FEV1, RV/TLC and TLCO, all as % predicted, were significantly (p < 0.05 each) associated with expiratory vessel characteristics, predominantly venous volume and arterial tortuosity. Associations with inspiratory vessel characteristics were absent or negligible. The patterns were similar for relationships between GOLD D and mortality with vessel characteristics. Expiratory venous volume was an independent predictor of mortality, in addition to FEV1. Conclusion: By using automated software in patients with COPD, clinically relevant information on pulmonary vasculature can be extracted from expiratory CT scans (although not inspiratory scans); in particular, expiratory pulmonary venous volume predicted mortality. Trial Registration: NCT01245933.

Association Between Osteoporosis Self-Assessment Tool for Asians and Airflow Limitation in Japanese Post-Menopausal Women.

Purpose: This study aimed to reveal the association between the osteoporosis self-assessment tool for Asians (OSTA) and airflow limitation (AL) in post-menopausal Japanese women. Participants and Methods: This cross-sectional study included 1580 participants undergoing a comprehensive health examination using spirometry and dual-energy X-ray absorptiometry. The OSTA was calculated by subtracting the age in years from the body weight (BW) in kilograms, and the result was multiplied by 0.2. The OSTA risk level was defined as low (>-1), moderate (-4 to -1), or high (<-4). AL was defined as forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) <0.7. The association between the OSTA and AL was assessed using logistic regression analysis. Results: The prevalence of AL was significantly higher in the high OSTA group (15.3%) than in the low OSTA group (3.1%) (p<0.001). In multiple linear regression analysis, the OSTA was independently associated with FEV1/FVC. In logistic regression models adjusted for smoking status, alcohol consumption, current use of medication for diabetes, hyperglycemia, rheumatoid arthritis, second-hand smoke, and ovary removal showed a significantly higher risk of AL (odds ratio: 5.48; 95% confidence interval: 2.90-10.37; p<0.001) in participants with OSTA high risk than in those with OSTA low risk. Conclusion: These results suggest that the OSTA high risk indicates reduced BMD at the femoral neck and presence of AL in Japanese post-menopausal women aged ≥45 years.

Multifactorial assessment of braking time predictors in a driving simulator among older adults according to gender.

CONTEXT: Vehicle driving depends on the integration of motor, visual, and cognitive skills to respond appropriately to different situations that occur in traffic. OBJECTIVES: To analyze a model of performance predictor for braking time in the driving simulator, using a battery of tests divided by gender. METHODS: Selected were 100 male drivers with a mean age of 72.6 ± 5.7 years. Sociodemographic variables, braking time in the driving simulator, and motor, visual, and cognitive skills were evaluated. RESULTS: Comparing genders, men were older than women (p = 0.002) and had longer driving times (p = 0.001). Men had more strength in hand grip (p ≤ 0.001). In the linear regression analysis, the model explained 68 % of the braking time in men and 50.8 % in women. In the stepwise multiple linear regression analysis, the variable that remained in the model was the strength of the right plantar flexors, which explained 13 % of the braking time in women and men, and the cognitive variables explained 38.9 %. CONCLUSION: Sociodemographic, motor, visual, and cognitive variables, explained a substantial portion of the variability in braking time for both older women and men, the specific variables driving this performance differed between the sexes. For older women, factors such as muscle strength emerged as critical determinants of braking ability, highlighting the importance of physical health in maintaining driving skills. On the other hand, cognitive conditions emerged as the primary predictor of braking performance in older men, underscoring the role of mental acuity and decision-making processes in safe driving.

The Effects of Different Blood Sample and Anticoagulant Types on Quantitative Tests of B-Type Natriuretic Peptide.

BACKGROUND: BNP is a sensitive and widely used biomarker for an early diagnosis of heart failure. Currently, most commercial BNP detection products use EDTA plasma samples. The aim of this study was to evaluate the clinical performance of the BNP test by using whole blood samples compared to plasma samples, and to evaluate the effect of the anticoagulant type on the BNP test result. METHODS: In total, 106 patients with different BNP levels from the Dahua Hospital volunteered for this study. Clinically homogenous samples, including EDTA anticoagulant plasma, EDTA whole blood, and heparin anticoagulant plasma, were collected and analyzed by using i-Reader S automatic immuno-analyzer and its supporting reagent kits. Pearson's correlation and weighted least squares linear regression analysis, Bland-Altman plotting, and Kappa test were used for statistical analysis. RESULTS: Correlation analysis showed that BNP concentrations, measured from EDTA anticoagulated plasma samples, had a good linear regression relationship with BNP from whole blood samples, with a slope of 0.9477, r = 0.9978, p < 0.05. A similar correlation was observed between EDTA anticoagulated plasma samples and heparin anticoagulant plasma, with a slope of 0.8413, r = 0.9793, p < 0.05. The BNP concentration measured from the heparin plasma samples were lower than of the EDTA plasma samples. Bland-Altman analysis for assessing BNP concentration agreement showed there was no outlier ratio between EDTA whole blood and EDTA plasma within the range of the detection system, as well as no outlier between EDTA anticoagulated and heparin anticoagulant plasma. Kappa coefficient of BNP concentration between homologous EDTA anticoagulated and heparin anticoagulant plasma was 0.8553 (p < 0.001), and for EDTA anticoagulated plasma and homologous whole blood it was 0.8941 (p < 0.001). CONCLUSIONS: The diagnostic performance of EDTA anticoagulated whole blood samples did not differ significantly from EDTA anticoagulated plasma samples for the BNP test. This study showed no big significant difference between EDTA anticoagulated and heparin anticoagulated plasma measurements within 2 hours. The type of anticoagulant should be carefully chosen when performing the BNP test if BNP samples were in vitro for a long time.

Development and validation of an ultrafast method of quantification of rivaroxaban in human serum using laser diode thermal desorption coupled to triple quadrupole mass spectrometry.

RATIONALE: Rivaroxaban is an anticoagulant prescribed to patients who are at risk of medical conditions such as deep-vein thrombosis, pulmonary embolisms, and strokes caused by blood clots. The administration of this drug is monitored to adjust the dosage and evaluate patients' blood concentration. Rapid quantification of this drug in plasma could make it possible to ensure that the dose present in the blood of patients does not represent a danger for the medical intervention to be carried out. METHODS: Liquid chromatography-tandem mass spectrometry is usually employed to quantify rivaroxaban in blood, plasma, and serum. Here, an alternative method of analysis based on laser diode thermal desorption-triple quadrupole mass spectrometry (LDTD-QqQMS) was developed and comprehensively validated. This new method allows the quantification of rivaroxaban in less than 13 s from sample to sample. The extraction of rivaroxaban in human serum was done by a salting-out liquid-liquid extraction with acetonitrile and a saturated sodium chloride solution. RESULTS: The proposed method allows the quantification of rivaroxaban in less than 13 s from sample to sample. During validation, all criteria were respected. The accuracy was <15% of the nominal value, the precision was <15%CV, and the recovery was ≥89.9%. There were no observed carryover or matrix effects. Analysis of the extracted samples established the stability of dry (24 h) and wet samples (1 week) when samples cannot be analyzed immediately, a considerable advantage in a clinical setting. CONCLUSIONS: This method improves sample throughput by more than 1200% compared to liquid chromatography-tandem mass spectrometry methods of analysis of rivaroxaban and decreases analysis costs by reducing solvent consumption and instrument time.

Relationship between preoperative hemoglobin levels and length of stay in elderly patients with hip fractures: A retrospective cohort study.

Globally, hip fractures in elderly individuals are a prevalent and serious issue. Patients typically have a longer length of stay (LOS), which increases the risk of complications and increases hospitalization costs. Hemoglobin (Hb) is a routine blood test that is associated with disease prognosis. This study aimed to investigate the relationship between preoperative Hb and LOS in elderly hip fracture patients and to determine a reliable transfusion threshold. The clinical data of hip fracture patients (aged ≥ 60 years) admitted to the Department of Orthopaedics, Shenzhen Second People's Hospital, between January 2012 and December 2021 were retrospectively analyzed. Multiple linear regression analysis was used to assess the linear relationship between preoperative Hb and LOS. Smooth curve fitting was performed to investigate potential nonlinear relationships. In the case of discovering nonlinear relationships, a weighted two-piecewise linear regression model was built, and the inflection points were determined using a recursive algorithm. Subgroup analyses were conducted based on age and gender. A total of 1444 patients with an average age of (77.54 ±â€…8.73) years were enrolled. After adjusting for covariates, a nonlinear relationship was found between preoperative Hb and LOS. The two-piecewise linear regression model revealed an inflection point of 10 g/dL. On the left of the inflection point (Hb < 10 g/dL), the LOS was reduced by 0.735 days for every 1 g/dL increase in Hb (ß = -0.735, 95% confidence interval: -1.346 to -0.124, P = .019). On the right side of the inflection point (Hb > 10 g/dL), the relationship was not statistically significant (ß = 0.001, 95% confidence interval: -0.293 to 0.296, P = .992). In elderly hip fracture patients, there is a nonlinear association between preoperative Hb and LOS. However, when Hb levels were <10 g/dL, there was a negative correlation with the LOS. No correlation was observed when Hb levels were >10 g/dL. These findings underscore the importance of timely intervention to manage Hb levels in elderly patients with hip fractures, potentially reducing hospitalization durations and associated complications.

Smoothing in linear multicompartment biological processes subject to stochastic input.

Many physical and biological systems rely on the progression of material through multiple independent stages. In viral replication, for example, virions enter a cell to undergo a complex process comprising several disparate stages before the eventual accumulation and release of replicated virions. While such systems may have some control over the internal dynamics that make up this progression, a challenge for many is to regulate behavior under what are often highly variable external environments acting as system inputs. In this work, we study a simple analog of this problem through a linear multicompartment model subject to a stochastic input in the form of a mean-reverting Ornstein-Uhlenbeck process, a type of Gaussian process. By expressing the system as a multidimensional Gaussian process, we derive several closed-form analytical results relating to the covariances and autocorrelations of the system, quantifying the smoothing effect discrete compartments afford multicompartment systems. Semianalytical results demonstrate that feedback and feedforward loops can enhance system robustness, and simulation results probe the intractable problem of the first passage time distribution, which has specific relevance to eventual cell lysis in the viral replication cycle. Finally, we demonstrate that the smoothing seen in the process is a consequence of the discreteness of the system, and does not manifest in systems with continuous transport. While we make progress through analysis of a simple linear problem, many of our insights are applicable more generally, and our work enables future analysis into multicompartment processes subject to stochastic inputs.

Tuberculosis incidence in Brazil: time series analysis between 2001 and 2021 and projection until 2030.

OBJECTIVE: To assess the incidence of tuberculosis in Brazil between 2001 and 2022 and estimate the monthly incidence forecast until 2030. METHODS: This is a time-series study based on monthly tuberculosis records from the Notifiable Diseases Information System and official projections of the Brazilian population. The monthly incidence of tuberculosis from 2001 to 2022 was evaluated using segmented linear regression to identify trend breaks. Seasonal autoregressive integrated moving average (Sarima) was used to predict the monthly incidence from 2023 to 2030, deadline for achieving the sustainable development goals (SDGs). RESULTS: There was a decrease in incidence between January/2001 and December/2014 (4.60 to 3.19 cases-month/100,000 inhabitants; ß=-0.005; p<0.001), followed by an increase between January/2015 and March /2020 (ß=0.013; p<0.001). There was a sharp drop in cases in April/2020, with the onset of the pandemic, and acceleration of the increase in cases since then (ß=0.025; p<0.001). A projection of 124,245 cases in 2030 was made, with an estimated incidence of 4.64 cases-month/100,000 inhabitants, levels similar to those in the 2000s. The Sarima model proved to be robust, with error of 4.1% when removing the pandemic period. CONCLUSION: The decreasing trend in tuberculosis cases was reversed from 2015 onwards, a period of economic crisis, and was also impacted by the pandemic when there was a reduction in records. The Sarima model can be a useful forecasting tool for epidemiological surveillance. Greater investments in prevention and control need to be made to reduce the occurrence of tuberculosis, in line with the SDGs.

Software and equations using segmental measures to estimate height in children and adolescents with cerebral palsy considering the level of gross motor function.

BACKGROUND & AIMS: In children with Cerebral palsy (CP) bone deformities create a difficulty in the collection of height measures by direct methods. Body segments are an alternative to study for anthropometric evaluation in children with CP. Motor compromise affects growth in these children. To our knowledge, no equations have been developed to estimate height that consider the level of involvement of children with CP. The aim was to develop equations to estimate height using segmental measures for children with cerebral palsy (CP). METHODS: This was a cross-sectional study. The sample consisted of children and adolescents with CP of both sexes from 2 to 19 years old from five cities in Argentina. Children whose height and knee-heel height (KH) could be measured were included. Height, KH, and clinical covariables were collected. Linear regression models with height as the dependent variable and KH as predictors adjusted for significant covariates were developed and compared for R2, adjusted R2, and the root mean square of the error. RESULTS: 242 children and adolescents (mean age 9 ± 4 years) with a confirmed diagnosis of CP were included. The interaction between height and other variables such KH, sex, GMFCS, and age was analyzed. Two equations were developed to estimate height according to GMFCS level (GMFCS Level I-III: H = 1.5 × KH(cm) + 2.28 × age(years) + 51; GMFCS Level IV-V: H = 2.13 × KH (cm)+ 0.91 × age(years) + 37). The concordance correlation coefficient between estimated and observed height was 0.95 (95%CI [0.94; 0.96]). CONCLUSION: Height in children and adolescents with CP can be predicted using KH, GMFCS, and age. The equations and software can estimate height when this cannot be obtained directly.

The Association between Dietary Nutrient Intake and Acceleration of Aging: Evidence from NHANES.

The acceleration of aging is a risk factor for numerous diseases, and diet has been identified as an especially effective anti-aging method. Currently, research on the relationship between dietary nutrient intake and accelerated aging remains limited, with existing studies focusing on the intake of a small number of individual dietary nutrients. Comprehensive research on the single and mixed anti-aging effects of dietary nutrients has not been conducted. This study aimed to comprehensively explore the effects of numerous dietary nutrient intakes, both singly and in combination, on the acceleration of aging. Data for this study were extracted from the 2015-2018 National Health and Nutrition Examination Surveys (NHANES). The acceleration of aging was measured by phenotypic age acceleration. Linear regression (linear), restricted cubic spline (RCS) (nonlinear), and weighted quantile sum (WQS) (mixed effect) models were used to explore the association between dietary nutrient intake and accelerated aging. A total of 4692 participants aged ≥ 20 were included in this study. In fully adjusted models, intakes of 16 nutrients were negatively associated with accelerated aging (protein, vitamin E, vitamin A, beta-carotene, vitamin B1, vitamin B2, vitamin B6, vitamin K, phosphorus, magnesium, iron, zinc, copper, potassium, dietary fiber, and alcohol). Intakes of total sugars, vitamin C, vitamin K, caffeine, and alcohol showed significant nonlinear associations with accelerated aging. Additionally, mixed dietary nutrient intakes were negatively associated with accelerated aging. Single dietary nutrients as well as mixed nutrient intake may mitigate accelerated aging. Moderately increasing the intake of specific dietary nutrients and maintaining dietary balance may be key strategies to prevent accelerated aging.