Count Variables Research Articles

Accounting for Latent Covariates in Average Effects from Count Regressions

The effectiveness of a treatment on a count outcome can be assessed using a negative binomial regression, where treatment effects are defined as the difference between the expected outcome under treatment and under control. These treatment effects can to date only be estimated if all covariates are manifest (observed) variables. However, some covariates are latent variables that are measured by multiple fallible indicators. In such cases, it is important to control for measurement error of covariates in order to avoid attenuation bias and to get unbiased treatment effect estimates. In this paper, we propose a new approach to compute average and conditional treatment effects in regression models with a logarithmic link function involving multiple latent and manifest covariates. We extend the previously presented moment-based approach in several aspects: Building on a multigroup SEM framework for count variables instead of the generalized linear model, we allow for latent covariates and multiple covariates. We provide an illustrative example to explain the application and estimation in structural equation modeling software.

Neonatal reticulocyte count during the early postnatal period

There are few reports on reticulocyte count during the early postnatal period, and its clinical significance is not well understood. To examine the relationships between neonatal reticulocyte count and other perinatal variables. We conducted a retrospective cohort study of neonatal infants who were admitted to the neonatal intensive care unit (NICU) of Ohta Nishinouchi Hospital, Japan, between April 1, 2016 and July 31, 2019. All blood samples were collected within 3h after admission. Four hundred and twenty-eight infants were included, of whom 317 (74.1%) were preterm and 111 (25.9%) were term. Two hundred and ninety-nine infants (69.9%) were born by cesarean section. The median reticulocyte counts (‰) for all gestational ages (GAs) were as follows: 24-25wks (n=11), 124.1 (range: 106.3 to 148.6); 26-27wks (n=25), 111.1 (range: 55.5 to 144.3); 28-30wks (n=52), 81.9 (range: 35.6 to 131.5); 31-33wks (n=86), 71.6 (range: 28.3 to 116.6); 34-36wks (n=143); 59.6 (range: 30.2 to 110.9); and 37-41wks (n=111), 43.2 (range: 21.9 to 69.2). There were significant relationships between the neonatal reticulocyte count and gender [p<0.01, odds ratio (OR), 0.37; 95% confidence interval (CI), 0.21 to 0.64], GA (p<0.01, OR, 0.92; 95% CI, 0.90 to 0.93), delivery type (p=0.03, OR, 0.51; 95% CI, 0.28 to 0.95), maternal haemoglobin before delivery (p<0.01, OR, 0.74; 95% CI, 0.60 to 0.91), tracheal intubation at resuscitation (p=0.04, OR, 2.75; 95% CI, 1.04 to 7.32) and mean platelet volume (p<0.01, OR, 0.51; 95% CI, 0.35 to 0.74). A higher neonatal reticulocyte count in NICU infants may be one of the physiological responses to a more rapid environmental change during the early postnatal period.

Sonic irrigant activation for root canal disinfection: power modes matter!

BackgroundSonic irrigant activation has gained widespread popularity among general dentists and endodontists alike in recent years. This in vitro study aimed to evaluate the impact of three power modes of a sonic activation device (EDDY) on its antimicrobial effectiveness in infected root canals.MethodsThe root canals of straight, human roots (n = 120) were prepared to size 40/.06. In a short-term infection experiment, the root canals were inoculated with different microbial species for three days. The following irrigation protocols, using 4 ml of normal saline as irrigant, were performed: negative control, manual rinsing, sonic irrigant activation at power modes “low”, “medium” and “high”. In a second, long-term experiment, testing the same irrigation protocols, inoculation lasted 21 days and sodium hypochlorite was used as irrigant. Sequential infection control samples were assessed using culture assays. The statistical analysis included one-way analysis of variance of log10-scaled counts of colony-forming units (CFU) with post-hoc comparisons using Bonferroni corrections and Chi2 tests (α = 0.05).ResultsIn the short-term experiment, the sonic irrigation protocols decreased the number of CFUs by 1.88 log10 units compared with the negative control (p < 0.001). The power modes “medium” and “high” achieved the most effective reduction of the microbial load. In the long-term experiment, microbial regrowth occurred after 7 days unless the device was used at its highest power setting.ConclusionsThe power modes of the sonic irrigation device have a significant impact on the effectiveness for endodontic disinfection. The sonic irrigation device should always be used at the highest power setting in order to maximize its antimicrobial effectiveness.

Decomposing Inequality in Long-Term Care Need Among Older Adults with Chronic Diseases in China: A Life Course Perspective.

Background: China has the largest number of aging people in need of long-term care, among whom 70% have chronic diseases. For policy planners, it is necessary to understand the different levels of needs of long-term care and provide long-term care insurance to ensure the long-term care needs of all people can be met. Methods: This study combines the 2013 wave of CHARLS survey and the Life Course Survey of 2014. The combination allows us to factor in both childhood and adulthood data to provide life-course analysis. We identified 7,734 older adults with chronic diseases for analysis. The need for long-term care is defined by the presence of functional limitations based on the performance of basic activities of daily living (ADLs) and of instrumental activities of daily living (IADLs). Two dummy variables, ADLs disability and IADLs disability, and two count variables, ADLs score and IADLs score, were defined to measure incidence and severity of long-term care need, respectively. The concentration index was used to capture the inequality in long-term care need, and a decomposition method based on Probit Regression and Negative Binomial Regression was exploited to identify the contribution of each determination. Results: At least a little difficulty was reported in ADLs and IADLs in 20.44% and 19.25% of respondents, respectively. The concentration index of ADLs disability, ADLs score, IADLs disability, IADLs score were −0.085, −0.109, −0.095 and −0.120, respectively, all of which were statistically significant, indicating the pro-poor inequality in the incidence and severity of long-term care need. Decomposition analyses revealed that family income, education attainment, aging, and childhood experience played a significant role in explaining the inequalities. Conclusions: The long-term care need among older adults with chronic disease is high in China and low socioeconomic groups had a higher probability of needing long-term care or need more long-term care. It is urgent to implement long-term care insurance, especially for the individuals from lower socioeconomic groups.

Using Breath Metabolic Profiling to Identify Genetic Variants in Alcohol Metabolism

Aldehyde dehydrogenase 2 (ALDH2) metabolizes acetaldehyde to acetic acid. An ALDH2 genetic variant, ALDH2*2, limits acetaldehyde metabolism. As a result, after consuming alcohol, the ALDH2*2 genetic variant causes acetaldehyde accumulation, facial flushing, and tachycardia; commonly referred to as Asian glow. Here we describe how we developed a machine learning algorithm to distinguish between genetic variants of ALDH2 using data collected from the human breath mass spectrum.To develop this machine learning algorithm, we recruited human volunteers to perform an alcohol challenge after obtaining IRB approval. For these volunteers, we performed genotyping in addition to subjecting volunteers to a 0.25g/kg alcohol challenge. During the alcohol challenge, we measured the human breath mass spectra for 16 people (8 ALDH2*1*1 and 8 ALDH2*1*2) using selective ion flow mass spectrometry. This created a metabolic profile for each person of the full mass spectrum which consisted of 1,155 ion measurements complemented with 14 metabolite panel measurements.To develop a machine learning algorithm to predict ALDH2 genotype, standard scaler (SS) and principal component analysis (PCA) were applied to normalize the variance in ion counts and maximize high dimensional input. The visualization of metabolomics data showed two distinct clusters that are dependent on the ethanol intake (Figure 1A) and on ALDH2 genotype (Figure 1B). Based on the cluster distinction, we were able to verify that our data could characterize ethanol metabolism. Next, we applied ~20 classifier algorithms such as Support Vector Machine, Perceptron, Gaussian Naïve Bayes, Stochastic Gradient Descent, and Decision trees. The prediction through Random Forest yielded three novel features from the raw mass spectra that are not included in metabolite panel. These algorithms were able to achieve a training accuracy above 90% threshold for identifying between ALDH2 genotypes. These finding suggests a non‐invasive method to determine ALDH2 genotype that may be used to complement existing methods to determine the response a person has to alcohol.Support or Funding InformationThis research received grant funding from Stanford Chem‐H and NIH NIGMS GM119522.Visualization of Temporal HEB Metabolomics Profiling. Figure 1A: 3D PCA on Ethanol Catabolism with SVM distinction kernel. Blue=baseline, red=after ethanol exposure / Figure 1B: 3D Visualization of Partial Gradient of Acetaldehyde and Ethanol. Blue=ALDH2 cohort, red=ALDH2*2 cohortFigure 1

The Role of Multimicronutrient Supplementation in Pediatric HIV Management in Nigeria: A Randomized Controlled Study.

We aimed to compare the immunologic and hematologic effects of 3 multimicronutrient supplements in human immunodeficiency virus-positive children in Lagos, Nigeria. This double-blind, randomized controlled study included 190 children, aged 5-12 years, in Lagos, Nigeria. Sixty-four, 63, and 63 participants were assigned to multimicronutrient group A, B, or C, respectively, for 6 months. Supplements A, B, and C contained 7 micronutrients at the recommended daily allowance (RDA) (comparable to standard-of-care multivitamin), 22 micronutrients at the RDA, and 22 micronutrients at 3 times the recommended daily allowance (3RDA), respectively. Using paired sample t tests and factorial repeat-measures analysis of variance (ANOVA), within- and between-group changes in CD4 count and hemoglobin levels were evaluated after 6 months. After 6 months of supplementation, paired-sample t test showed that CD4 cell count did not significantly differ from baseline for all 3 groups. Between-subject effect also did not significantly differ in the 3 groups after 6 months (factorial repeat-measures ANOVA (F [degrees of freedom {df} = 2, 187] = 0.846; P = .436; partial η 2 = 0.009). Hemoglobin levels were significantly increased after supplementation in all 3 supplement groups. Increases were not significantly different between groups (factorial repeat-measures ANOVA (F [df = 2, 187] = 0.549; P = .591; partial η 2 = 0.006). Equivalent effects were observed. After 6 months of supplementation, mean CD4 count was not significantly different between groups. Hemoglobin concentration was significantly increased in all 3 groups, but increase did not differ between groups. NCT02552602.

Community oriented in‐network caching and edge caching for over‐the‐top services in adaptive network conditions to improve performance

SummaryOver‐the‐top (OTT) services such as Netflix, Amazon Prime, and YouTube generate the most dominant form of traffic on the Internet today. There is increasingly high demand for resource intensive 3D contents, interactive media, 360 media, and user‐generated contents. As the amount of contents keep increasing in multiple folds, it is important to cache contents intelligently. Caching algorithm needs to exploit in‐network caching, community‐based pre‐caching, and a combined approach. Hence, we survey CDN‐based edge caching infrastructures including OpenConnect (Netflix) and Google Edge, followed by CCN based in‐network caching. We implement and compare four different approaches for caching contents including (1) in‐network caching, (2) edge caching, (3) community‐based in‐network caching, and (4) community‐based edge caching. We run our algorithms on adaptive network conditions with different topologies, cache size, content popularity, and request arrivals in and compared the delay for all these four approaches. We verify our model by calculating important performance parameters including hop count, redundancy, and hop count variances. Hopcount is an important performance parameter as it influences the processing, queuing, and transmission delays. We focus on determining if an in‐network caching approach is any better than edge caching. We reach several conclusions. First, in most of the scenarios, community‐based in‐network caching performs the best. Second, if the cache size is lesser than 30% of the total content size then community‐based edge caching is better for less popular contents. Finally, our statistical analysis also reveals that a community‐based edge caching mechanism is least affected by varying cache sizes and dynamic user behavior, which makes it a better choice for providing Service Level Agreement.

(Home-)Schools of Democracy? On the Intergenerational Transmission of Civic Engagement

Where do individuals learn civic engagement? While voluntary associations are often seen as the breeding grounds for democratic skills and virtues, many preferences are learned by children in their family and thus passed on between generations. The present paper uses data from the British Household Panel Survey (1991–2008) for the UK to analyze the intergenerational transmission of civic engagement and political participation preferences. It finds that both voluntary associational count variables as well as frequency and strength measures of doing volunteer work and political party support are correlated between parents and their grown up children (i.e. after leaving the parental household), even when controlling for resources like socio-economic background. The intergenerational transmission is more pronounced with regard to triggering filial civic engagement, but frequency of parental engagement is less strongly transmitted. A robustness analysis suggests that peer influences (as measured by regional levels of civic engagement) do not drive the intergenerational transmission of civic engagement.

Physical activity and sleep in patients with hypermobile Ehlers–Danlos syndrome and patients with generalized hypermobility spectrum disorder

Aims: Research objectively evaluating physical activity (PA) and sleep in adults with hypermobile Ehlers–Danlos syndrome (hEDS) and generalized hypermobility spectrum disorder (G-HSD) is lacking. Furthermore, it is not clear to what extent frequently occurring symptoms in these patients are related to their PA and sleep. Therefore, a cross-sectional study was performed to objectively evaluate, and identify factors contributing to, PA and sleep in adults with hEDS and G-HSD. Methods: Twenty female adults with hEDS, 23 with G-HSD, and 32 healthy controls participated. Physical activity and sleep were measured using two tri-axial ActiGraphs worn over seven consecutive days. Furthermore, questionnaires evaluating frequently occurring symptoms were completed. Regression analysis was performed to determine major contributors to PA and sleep. Results: Daily step counts were significantly lower in both patient groups compared to the control (CTR) group (p lessthan 0.04) and to the recommended 7500 steps (p≤0.001). Other PA and sleep variables did not differ between the groups. In the hEDS group, body mass index and kinesiophobia were related to PA, explaining 53% of the variance in step counts. In the G-HSD group, 18.5% of the variance in step counts could be attributed to the variance in pain impact. Conclusion: Adults with hEDS and G-HSD had lower step counts than healthy peers, which may be partially due to kinesiophobia and the impact of pain respectively. No differences in objectively measured sleep parameters were identified. Treatment focusing on fear-avoidance beliefs and pain relief could potentially increase daily step counts and benefit overall health in these patients.

Evaluate the correlations of maternal systemic ınflammatory markers such as neutrophil to lymphocyte ratio and platelet to lymphocyte ratio with gestation age

Objective: In this study, we aim to study the correlation between the maternal systemic inflammatory markers such as neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) including complete blood count (CBC) variables with gestation age, at the labor of our patients. Materials and Methods: This retrospective study was performed with 1127 patients and their infants. We used the maternal CBC variables analyzed within the last day before active labor. We analyzed the statistical differences between the NLR, PLR, and other CBC variables in terms of gestational age. Results: There was no statistically significant difference between the gestational age with NLR and PLR values, (P = 0.414 and P = 0.341, respectively). When we compare the NLR and PLR values in normal spontaneous vaginal delivery (NSVD) group, no statistically significant difference was found (P = 0.250; P = 0.995, respectively). In correlation analyses, no statistically significant correlation was detected between NLR and PLR with a birth weight of the infant and gestational age (P = 0.132 and P = 0.344, respectively). A linear, negative, weak correlation, and statistically significant correlation was detected between white blood cell count (WBC) with the infant's birth weight and gestational week (P Conclusions: Inflammation plays an important role especially at the beginning of the labor. In our study, we showed no correlation of the NLR and PLR with a gestational week or infant's birth weight at labor. Also, in our research, the NLR and PLR values did not differ statistically among the four groups in terms of the gestational age of delivery with the highest values in the preterm birth (

Hemoglobin, Ferritin levels and RBC Indices among children entering school and study of their correlation with one another.

To study correlation of various complete blood count variables with one another and to ascertain the values of intercept and slope among those having strong correlation. The cross-sectional study was conducted in Marach 2017 in the Rabwah town of Punjab province in Pakistan, and comprised randomly selected one in four children studying under the Nazrat Taleem School System. Serum sample from each subject was used to analyse complete blood count on an automated analyser, and ferritin levels were checked by enzyme-linked immunosorbent assay. SPSS20 was used for data analysis. There were 299 children with a median age of 67 months. Mean haemoglobin level was 12.09±0.82gm/dl. There was a very strong positive correlation between haemoglobin and haematocrit; mean corpuscular volume; and red cell distribution width; mean corpuscular volume and mean corpuscular haemoglobin; red cell distribution width and mean corpuscular haemoglobin (p<0.001).Moderate positive correlation was found between haemoglobin and red blood cell count; haematocrit and red blood cell count; mean corpuscular haemoglobin and mean corpuscular haemoglobin concentration (p<0.05). Moderate negative correlation was present between red blood cell count and mean corpuscular volume; red blood cell count and red cell distribution width; red blood cell count and mean corpuscular haemoglobin (p<0.05). There were strong to moderate correlation between various complete blood count variables in the studied population. Ferritin level was the only variable which did not have any correlation with any of the other variables.

Health Care Utilization Inequality in a Mixed Public-Private Health Care System: An Insight from the National Survey in Iran

Background: Equitable health care utilization is a pillar of the Universal Health Coverage (UHC) and is also a concern to policymakers. Measuring and quantifying the inequalities are essential in assessing the progress toward achieving the UHC goals. Several studies have focused on overall measures of unfair inequality in health care utilization. The overall approaches to outpatient and inpatient services are not representative of the differences in health care usage in public and private sectors in a mixed healthcare system, like Iran. A few studies have assessed inequality measures for general practitioners (GPs), specialists (SPs), and hospital admission services in different sectors, separately. Objectives: This study aimed at measuring health care utilization inequalities in outpatient and inpatient health services in public and private sectors in Iran. Methods: In this study, national representative data derived from the utilization of health services survey (UHSS) in 2014 was used. The concentration curve (CC) and concentration index (CI) were applied to assess inequalities in health care utilization services, including the number of GP visits, SP visits, and admission in hospitals. We used ADePT software to produce a nonlinear estimation of CI for these count variables. The indirect standardization method was used to standardize the services for differences in needs by age and gender. The inequality in health care utilization was examined in both public and private sectors, separately. Results: Based on the results, public and private outpatient settings, except for the private GP visits, followed a pro-poor pattern. Inpatient admission in the public sector had a pro-poor model, but it showed a pro-rich pattern in the private sector. GP visits in the private sector changed in favor of the poorer people and SP visits in the public sector changed toward a pro-rich pattern after standardization for differences in needs. CI for family physician (FP) and GP visits in public and private sectors, and also SP visits in public and private sectors was -0.089, -0.086, -0.010, 0.025, and -0.018, respectively. CI for the inpatient admission in public and private sectors was -0.126 and 0.157, respectively. GP, SP and hospital services utilization showed a pro-poor pattern. Conclusions: The results of this study showed that most of the health care utilization followed a pro-poor model in the mixed health care system in Iran. SP visits in the public sector changed toward a pro-rich pattern after standardization for differences in needs. Although public outpatient services need more attention to maintain their pro-poor distribution, SP visits in the public sector should be more considered to follow a pro-poor pattern. Health policymakers are recommended to take measures to eliminate barriers to access this service. This may lead to reduce a gap between the poor and rich people in the utilization of the health care and moving toward the UHC.

PSIV-15 Effects of Bacillus subtilis PB6 and/or chromium propionate supplementation on health, performance, and blood parameters of high-risk cattle during the feedlot receiving period

Abstract The objective was to determine the effects of Bacillus subtilis PB6 and/or chromium propionate supplementation on health, performance, and blood parameters in high-risk beef calves during a 56-day receiving period. Four truckload blocks of crossbred beef calves (n = 384; BW=220±16.2 kg) were assigned randomly to treatments arranged in a 2 × 2 factorial. The generalized complete block design consisted of 12 pen replications per treatment with pen as the experimental unit. Treatments were: 1) placebo control (CON); 2) 13 g/animal/d Bacillus subtilis PB6 (CLOSTAT®, Kemin Industries; CST); 3) 1 g/animal/d Cr propionate (KemTRACE® Chromium, Kemin Industries; CHR); and 4) CST+CHR. Treatments were top dressed in feed bunks daily using 0.45 kg/animal/d ground corn carrier. Blood samples were collected on days 0, 14, 28, and 56 for analysis of serum chemistry and complete blood count variables from a pen subset (n = 2/pen). Data were analyzed using MIXED and GLIMMIX procedures of SAS. The DMI was increased for CST during each interim period (P ≤ 0.03) and overall DMI was increased by 0.78 lb/animal/d for CST (P = 0.01). The CST supplemented cattle had greater BW on days 14, 28, and 56 (P ≤ 0.06). Likewise, ADG was improved for CST from day 0 to 14 (P = 0.04) and for the overall receiving period (P = 0.04). Main effects of CST (P = 0.02) and CHR (P = 0.03) decreased the percentage of calves treated for bovine respiratory disease (BRD). Morbidity was 28.0 and 39.9% for cattle with and without CST supplementation and 28.6 and 39.3% for cattle with and without CHR supplementation, respectively. Cattle fed CHR had increased (P ≤ 0.04) total leukocytes, neutrophils, serum aspartate aminotransferase and less (P = 0.02) serum calcium. Performance was improved by CST and BRD morbidity was less for CST and CHR.

Penalized Splines Fitting for a Poisson Response Including Outliers

There have been various studies in the literature on investigating the relationship between a count response and several covariates. Most researchers study count variables and use traditional methods (i.e. generalized linear models- GLM). However, GLM is limited when dealing with outliers and nonlinear relationships. Generalized Additive Models (GAM) is an extension of GLM, where the assumptions on the link functions and components are additive and smooth, respectively. Our aim is to propose a flexible extension of GLM and demonstrate the usefulness and performance of GAMs for the analysis of Poisson data set including outliers in the response variable through extensive Monte Carlo Simulations and using three applications.

New prognosis score including absolute lymphocyte/monocyte ratio, red blood cell distribution width and beta-2 microglobulin in patients with diffuse large B-cell lymphoma treated with R-CHOP: Spanish Lymphoma Group Experience (GELTAMO).

The International Prognostic Index (IPI) is the most widely used score for non-Hodgkin lymphoma but lacks the ability to identify a high-risk population in diffuse large B-cell lymphoma (DLBCL). Low absolute lymphocyte count and high monocytes have proved to be unfavourable factors. Red-cell distribution width (RDW) has been associated with inflammation and beta-2 microglobulin (B2M) with tumour load. The retrospective study included 992 patients with DLBCL treated with R-CHOP. In the multivariate analysis, age, Eastern Cooperative Oncology Group performance status (ECOG-PS), stage, bulky mass, B2M, RDW, and lymphocyte/monocyte ratio (LMR) were independently related to progression-free survival (PFS). A new prognosis score was generated with these variables including age categorized into three groups (0, 1, 2 points); ECOG ≥3-4 with two; stage III/IV, bulky mass, high B2M, LMR<2·25 and RDW>0·96 with one each; for a maximum of 9. This score could improve the discrimination of a very high-risk subgroup with five-year PFS and overall survival (OS) of 19% and 24% versus 45% and 59% of R (revised)-IPI respectively. This score also showed greater predictive ability than IPI. A new score is presented including complete blood cell count variables and B2M, which are readily available in real-life practice without additional tests. Compared to R-IPI, it shows a more precise high-risk assessment and risk discrimination for both PFS and OS.

Tutorial on Using Regression Models with Count Outcomes Using R.

Education researchers often study count variables, such as times a student reached a goal, discipline referrals, and absences. Most researchers that study these variables use typical regression methods (i.e., ordinary least-squares) either with or without transforming the count variables. In either case, using typical regression for count data can produce parameter estimates that are biased, thus diminishing any inferences made from such data. As count-variable regression models are seldom taught in training programs, we present a tutorial to help educational researchers use such methods in their own research. We demonstrate analyzing and interpreting count data using Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial regression models. The count regression methods are introduced through an example using the number of times students skipped class. The data for this example are freely available and the R syntax used run the example analyses are included in the Appendix. Count variables such as number of times a student reached a goal, discipline referrals, and absences are ubiquitous in school settings. After a review of published single-case design studies Shadish and Sullivan (2011) recently concluded that nearly all outcome variables were some form of a count. Yet, most analyses they reviewed used traditional data analysis methods designed for normally-distributed continuous data.

The value of cellular components of blood in the setting of trimodal therapy for esophageal cancer.

Inflammation status plays an important role in the natural history of malignancy. Consequently, hematological markers of systemic inflammation may predict prognosis in neoplasms. This study evaluated the value of cellular blood components changes during neoadjuvant chemoradiotherapy followed by esophagectomy for cancer in predicting prognosis. A cohort of 149 patients was analyzed. Cellular components of blood were assessed before neoadjuvant therapy (A); before surgery (B); and 3 to 5 months after surgery (C); for the following outcomes: pathological response, overall survival (OS), and disease-free survival (DFS). Univariate and multivariate Cox regression models were applied to evaluate the independent prognostic significance of blood count variables. Low hematocrit (Ht) (C) (HR, 0.85; 95% CI, 0.79-0.92) and high neutrophil-to-lymphocyte ratio (NLR) (C) (HR, 1.07; 95% CI, 1.07-1.10) were related to poor OS. Low Hb (C) (HR, 0.72; 95% CI, 0.58-0.88), red cell distribution width (RDW) (C-A) (HR, 1.16; 95% CI, 1.02-1.31), and NLR (C-A) (1.06; 95% CI, 1.03-1.09) were related to poor DFS. RDW (B-A) (HR, 1.15; 95% CI, 1.08-1.22), RDW (C) (HR, 1.12; 95% CI, 1.04-1.2), NLR (C) (HR, 1.12; 95% CI, 1.08-1.17) were related to systemic recurrence. Variables of routine blood count are easily assessable and their changes throughout trimodal therapy for esophageal carcinoma provide important information for cancer patient's prognosis.

Low gait speed is associated with low physical activity and high sedentary time following stroke

Purpose This study describes physical activity levels and factors associated with physical activity at the end of stroke rehabilitation. Methods Primary stroke survivors were assessed at completion of physical rehabilitation. Outcomes included physical activity (e.g. step count, moderate-vigorous physical activity duration) and sedentary time measured with the Sensewear Armband, gait speed, and cognition. The number of participants meeting physical activity recommendations was calculated. Differences in physical activity were examined between household ambulators (gait speed <0.4 m/s), limited community ambulators (0.4–0.8 m/s), and unlimited community ambulators (>0.8 m/s). The influence of age, cognition, and gait speed on physical activity was determined by multiple regression. Results Seventy-nine stroke survivors participated. Twenty-one participants achieved 30 min/day of moderate-vigorous physical activity accumulated in 10 min bouts. Unlimited community ambulators took more steps/day (median 4975 vs. 469 limited, 355 household, p < 0.001), had higher moderate-vigorous physical activity (median 74 min/day vs. 22 limited, 31 household, p < 0.001) and lower sedentary time (mean 1105 vs. 1239 limited, 1232 household minutes/day, p < 0.001). Age, gait speed, and cognition predicted 21.3% of the variance in moderate-vigorous physical activity (p = 0.001); adding employment status to the model predicted 57.3% of the variance in step count (p < 0.001). Conclusions Physical activity is low following stroke and should be a target for treatment, particularly in those with gait speeds ≤0.8 m/s. Implications for rehabilitation Seventy-three percent of stroke survivors performed ≥30 minutes of moderate to vigorous physical activity throughout the day. Twenty-seven percent of stroke survivors accumulated ≥30 minutes of moderate to vigorous physical activity in 10 minute bouts. Despite relatively good physical ability, daily step count was low in this sample. Those with gait speeds ≤0.8 m/s had lower physical activity levels and higher sedentary time.

Estimation of dyadic characteristics of family networks using sample survey data

We consider the use of sample survey data to estimate dyadic characteristics of family networks, with an application to noncoresident parent–child dyads. We suppose that survey respondents report either from a parent or child perspective about a dyad, depending on their membership of the dyad. We construct separate estimators of common dyadic characteristics using data from both a parent and a child perspective and show how comparisons of these estimators can shed light on data quality issues including differential missingness and reporting error. In our application we find that a simple missingness model explains some striking patterns of discrepancies between the estimators and consider the use of poststratification and a related redefinition of count variables to adjust for these discrepancies. We also develop approaches to combining the separate estimators efficiently to estimate means and frequency distributions within subpopulations.

Novel organic-based postharvest sanitizer formulation using Box Behnken design and mathematical modeling approach: A case study of fresh pistachio storage under modified atmosphere packaging

In the present study Box Behnken Design (BBD) and Artificial Neural Network-Genetic Algorithm (ANN-GA) hybrid system were used for predicting and optimizing a new organic-based postharvest sanitizer for fresh pistachio nuts under modified atmosphere packaging, combining different concentrations of five generally recognized as safe (GRAS) ingredients including H2O2 (1, 3 and 5%), Na2CO3 (1, 3 and 5%), K2CO3 (1, 3 and 5%), citric acid (CA) and acetic acid (AA, 1000, 5500 and 10,000 mg L−1). The nuts were submerged in sanitizer solutions for two minutes then dried for five minutes in ambient condition and packaged in polyethylene bags injected with ambient atmospheric gas (21% O2, 0.03% CO2, and 87% N2). BBD as a computer-based design of experiment (DOE) tool reduced the cost, labor and time needed to perform the experiment by reducing the number of treatments from 243 to 40 while ensuring the well-sampled experiment design. NaOCl (100 mg L−1) and distilled water (DW) were used as controls for the validation experiment. The ANN-GA described relations between five input (H2O2, Na2CO3, K2CO3, CA, and AA) and four output (total viable count, enzymatic browning, overall acceptability, and taste) variables. Sensitivity analysis was used to find the most important ingredient as input variable affecting output variables. ANN-based models could effectively fit the supplied data on the total viable count and quality parameters of pistachios to various concentrations of the ingredients in the sanitizers. Based on the ANN-GA results, the input variables concentrations of 3.6% H2O2, 3.9% Na2CO3, 3.2% K2CO3, 8118.5 (mg L−1) CA, and 8202.8 mg L−1 AA could result in the lowest total viable count (0.07 log colony forming units (CFU g-1)). The lowest amount of enzymatic browning (1.48%) can be obtained by applying a mixture of 4.26% H2O2, 3.7% Na2CO3, 3.7% K2CO3, 7785.4 mg L−1 CA, and 7363.5 mg L−1 AA. The highest overall acceptability (1.38) can be achieved using a mixture of 3.0% H2O2, 3.0% Na2CO3, 3.4% K2CO3, 8190.1 mg L−1 CA, and 8316.7 mg L−1 AA. The best taste (1.21) was predicted to be attained using a combination of 3.3% H2O2, 4.1% Na2CO3, 3.9% K2CO3, 8114.5 mg L−1 CA, and 7574.0 mg L−1 AA. According to the sensitivity analysis, AA was the most important factor in reducing total viable count and enzymatic browning and enhancing overall acceptability. The validation test showed that the optimized sanitizer for total viable count was superior to the 100 mg L−1 NaOCl which is the most used commercial sanitizer for fresh crops.