Logistic Procedures Research Articles

Vaping cannabis among adolescents: prevalence and associations with tobacco use from a cross-sectional study in the USA

ObjectivePrevious research suggests that some adolescents are using e-cigarette devices to vaporise (‘vaping’) cannabis in the form of hash oil, tetrahydrocannabinol (THC) wax or oil, or dried cannabis buds or...

Transportation mode choice binary logit model: a case study for Johor Bahru city

The mode choice stage in transportation planning is the analysis process to estimate the number or percentage of trips performed by each mode of transport. In practice, the number of trips is used to estimate the demand for each mode of transport. Such information is important for planning and designing transportation facilities in an urban area. A mathematical model of individuals’ mode choice is usually required in such an analysis. This paper discusses the result of a study carried out to evaluate the attributes that influence the mode choice of transport in Johor Bahru city by interviewing the individuals living for more than one year in the study area. The investigation conducted through one of attitudinal survey techniques known as stated preference survey. Stated preference survey conducted on a random sample of 384 respondents. Investigated attributes have been identified in analysis stage by applying binary logistic regression analysis procedure before deriving binary logit model for individuals’ mode choice of transport in Johor Bahru city. Based on stated preference survey and logistic regression analysis of data, the model of mode choice of transport in Johor Bahru has been derived and attributes of age, income, vehicle ownership, comfort of car, reliability of bus service, affective motives and instrumental motives were found statistically correlated to the mode choice of transport in Johor Bahru.

Cardiovascular biomarkers in dogs with systemic inflammatory response syndrome.

To measure plasma N-terminal fragments of pro-B-type natriuretic peptides (NT-proBNP) and cardiac troponin T (cTnT) concentration in hospitalized dogs and relate these markers to underlying conditions and evaluate their potential as prognostic markers in dogs with systemic inflammatory response syndrome (SIRS). Prospective, observational, clinical study. Emergency department of a university teaching hospital. Sixty-nine dogs with SIRS examined in the emergency department were prospectively studied. Patient age ranged from 5 months to 15 years, and weight ranged from 5.5 to 75 kg. Blood samples were obtained at presentation, during hospitalization until discharge or death, and at a "control" visit (T1m) at least 1 month after hospital discharge. NT-proBNP was assayed with a commercially available canine ELISA, while cTnT was measured with an automated immunoassay previously used in dogs. A correlation procedure, mixed procedure on a linear model, and a logistic procedure were performed. Forty-four patients survived, 19 of which had control visits. cTnT concentrations were significantly higher than T0 and T1m at T12, T24, and T72. In 28 dogs, cTnT was detected during hospitalization, but cTnT was not detected in any dog at the control visits. Higher concentrations of cTnT were negatively associated with survival, irrespective of disease category. NT-proBNP concentrations were significantly higher than T0, T6, T12, and T1m at T24, T72, and T120, but were not associated with survival. NT-proBNP and cTnT increased significantly in dogs with SIRS, regardless of the underlying disease process. Nonsurvivors displayed significantly higher cTnT concentrations during hospitalization.

0866 Does Obstructive Sleep Apnea Mediate the Relationship Between Post-Traumatic Stress Disorder and Low Back Pain in Veterans?

Abstract Introduction Low back pain (LBP) is a common complaint among veterans, leading to notable limits in function, quality of life, and an increase in healthcare cost. The incidence and prevalence of LBP have been increasing in the veterans over the past several years. Obstructive sleep apnea (OSA) has been shown to be associated with LBP and there are notable associations among post-traumatic stress disorder (PTSD), OSA and LBP in this population. Methods A random sample of veterans stratified by quarter was taken between 2007 and 2011 (index date), collecting records from 2006 to 2016. Veterans were excluded if they had a prevalent case of LBP, and/or OSA in the year of or year before to their index date (index period), or PTSD, OSA and/or LBP prior to the index period. Associations among the PTSD, LBP, and OSA were calculated using SAS PROC LOGISTIC. SAS PROC PHREG was used to calculate hazard ratios (HR) for mediation analysis and the percent of 4-year LBP risk explained by OSA in those with PTSD. Results PTSD predicted LBP diagnosis (OR 1.52 [95% CI: 1.27, 1.83]) and OSA diagnosis (OR 2.06 [1.48, 2.88]). Additionally, OSA diagnosis was predictive of LBP diagnosis (OR 8.99 [95% CI: 7.07, 11.35]). The HR for the effect of PTSD on the risk LBP diagnosis was 1.47 (95% CI: 1.25, 1.74) without adjustment for OSA. The HR for the effect of PTSD on the risk LBP diagnosis adjusted for the mediator was 1.35 (95% CI: 1.15, 1.60). The resulting percent of excess LBP risk explained by OSA is 25.5% (95% CI: 19.6%,31.1%). All analyses were adjusted for potential confounders. Conclusion OSA may mediate a significant amount of the risk of LBP diagnosis in veterans with PTSD. Prevention of OSA among veterans with PTSD may significantly reduce the risk of future LBP in veterans with PTSD. Support (If Any) This material is the result of work supported with resources and the use of facilities at the James A. Haley Veterans’ Hospital.

Lateral ventricle volume trajectories predict response inhibition in older age-A longitudinal brain imaging and machine learning approach.

ObjectiveIn a three-wave 6 yrs longitudinal study we investigated if the expansion of lateral ventricle (LV) volumes (regarded as a proxy for brain tissue loss) predicts third wave performance on a test of response inhibition (RI).Participants and methodsTrajectories of left and right lateral ventricle volumes across the three waves were quantified using the longitudinal stream in Freesurfer. All participants (N = 74;48 females;mean age 66.0 yrs at the third wave) performed the Color-Word Interference Test (CWIT). Response time on the third condition of CWIT, divided into fast, medium and slow, was used as outcome measure in a machine learning framework. Initially, we performed a linear mixed-effect (LME) analysis to describe subject-specific trajectories of the left and right LV volumes (LVV). These features were input to a multinomial logistic regression classification procedure, predicting individual belongings to one of the three RI classes. To obtain results that might generalize, we evaluated the significance of a k-fold cross-validated f1-score with a permutation test, providing a p-value that approximates the probability that the score would be obtained by chance. We also calculated a corresponding confusion matrix.ResultsThe LME-model showed an annual ∼ 3.0% LVV increase. Evaluation of a cross-validated score using 500 permutations gave an f1-score of 0.462 that was above chance level (p = 0.014). 56% of the fast performers were successfully classified. All these were females, and typically older than 65 yrs at inclusion. For the true slow performers, those being correctly classified had higher LVVs than those being misclassified, and their ages at inclusion were also higher.ConclusionMajor contributions were: (i) a longitudinal design, (ii) advanced brain imaging and segmentation procedures with longitudinal data analysis, and (iii) a data driven machine learning approach including cross-validation and permutation testing to predict behaviour, solely from the individual’s brain “signatures” (LVV trajectories).

DIRECTIONS FOR IMPROVEMENT OF GOODS DECLARATION IN CONDITIONS OF INTEGRATION PROCESSES

Introduction and purpose of the study. Trends in global development in the context of the global economic crisis dictate new challenges, in particular, the simplification of customs and logistics procedures during the import and export of goods to (from) the territory of countries. Today, the maximum approximation of customs procedures in Ukraine to the European and world standards is gradually being made, their maximum simplification at all stages, the reduction of the influence of the human factor on the results of the customs introduction of the elements of the electronic document flow system in the execution of customs clearance and customs control of goods.The hypothesis of scientific research. It is anticipated that in today's conditions of openness of the Ukrainian economy the necessary condition for the organization of the customs business – in general – and customs control, in particular, is the declaration, identification and control of customs value, which has fiscal and regulatory potential, and accordingly characterized by problematic issues that require new theoretical and practical approaches to its evaluation and control. The purpose of the article is to study the current mechanism of customs declaration of goods in Ukraine.Methods of research: in the process of work, the following methods of economic research were used: system-structural, abstract-logical, comparative and balance, expert assessments, etc.Results: The state of the procedure of customs clearance of goods is considered and investigated. The given results of practical introduction of electronic document circulation with the use of electronic digital signature in the customs business of Ukraine.Conclusions. The creation of a multifunctional integrated electronic customs system is aimed at strengthening Ukraine's customs security, further developing and adapting the information systems of the State Customs Service of Ukraine to the standards of the European Union, creating conditions for accelerating customs control and customs clearance procedures, improving the level of services provided by the state in the customs sphere, restriction of the possibility of committing illegal and corrupt acts.

Predictive Factors of Vitamin D Inadequacy among Older Adults in the United States.

Optimal serum vitamin D levels are reported to be associated with many health benefits; however, few studies have determined predictive factors using national level data. An assessment of predictive factors for vitamin D inadequacy was conducted using National Health and Nutrition Examination Survey (NHANES) 2001-2006 data. Using the study sample including adults aged 40 years or more, data analysis was performed using the weighted multivariate logistic regression statistical procedure. The prevalence of vitamin D inadequacy (serum vitamin D <20 ng/ml) was 37.3%. Non-Hispanic Blacks were 6.4 times more likely to demonstrate vitamin D inadequacy compared to non-Hispanic Whites (ORadj=6.351; 95% CI 5.338, 7.555; p<0.0001). Also, female gender was a significant predictor of vitamin D inadequacy (ORadj=1.499; 95% CI 1.315, 1.708; p<0.0001) in multivariate models. Subjects who reported not taking vitamin D supplements in the past 30 days were more than twice as likely to be vitamin D inadequate compared with those who had taken dietary supplements containing vitamin D (ORadj=2.225; 95% CI 1.903, 2.601; p<0.0001). In conclusion, the strongest predictor of vitamin D inadequacy was non-Hispanic Black ethnicity. Other potential predictors included smoking, non-use of vitamin D supplements, abnormal BMI, collecting samples in winter, female gender, perception of own health condition as not excellent, lack of health care, and older age. More focused interventions targeting groups of United States residents with vitamin D inadequacy are needed.

HPV Prevalence and its Association with Perinatal Outcomes among Singleton Mothers: Analysis of Pregnancy Risk Assessment and Monitoring System (PRAMS) Data, 2004-2011

Background: Pregnancy may increase the risk of Human Papillomavirus (HPV) infection because of pregnancy induced immune suppression. The objective of this study was to use a large population-based dataset to estimate the prevalence of HPV infection and its association with adverse outcomes among pregnant women. Methods: We analyzed Pregnancy Risk Monitoring System data from 2004-2011 (N=26,085) to estimate the self-reported HPV infection. Survey logistic procedures were used to examine the relationship between HPV infection and adverse perinatal outcomes. Results: Approximately 1.4% of women were estimated to have HPV infection during their pregnancy. The prevalence of adverse outcomes in this sample was preterm birth (8.4%), preeclampsia (7.5%), low birth weight (6.3%) and premature rupture of membranes (2.8%). Compared to women without HPV infection, HPV infection positive women were much more likely to have had other infections such as chlamydia (9.23% vs. 2.12%, p-value &lt;.0001), Group B Strep (21.7% vs. 10.04%, p-value &lt;.0001), and herpes (7.17% vs. 1.07%, p-value &lt;.0001). After adjusting for other risk factors including other infections, HPV infection was significantly associated with low birth weight (OR: 1.94, 95% CI: 1.14-3.30). Conclusion: The study indicated a potential association between HPV infection and low birth weight. Because pregnant women with HPV infection are at higher risk of other infections, future research may focus on the roles of co-infection in the development of adverse perinatal effects.

Guidance for use of weights: an analysis of different types of weights and their implications when using SAS PROCs

SAS and other popular statistical packages provide support for survey data with sampling weights. For example, PROC MEANS and PROC LOGISTIC in SAS have their counterparts PROC SURVEYMEANS and PROC...

Abstract WP498: A Nationwide Analysis of Utilization of Life-Sustaining Treatments Following Aneurysmal Subarachnoid Hemorrhage

Introduction: Aneurysmal subarachnoid hemorrhage (aSAH) carries high mortality and disability rates, with many patients receiving life-sustaining treatments (LST). We examined utilization of LST by demographic and regional characteristics for aSAH patients using a nationwide dataset. Methods: We used Cerner Health Facts, a database of de-identified, longitudinal electronic health record information. Patients with aSAH were selected by ICD-9/10 codes for inpatient admission dates between 1/2004-6/2018. Available demographics included census region, age, race, sex, and marital status. Clinical information included admission Glasgow Coma Scale (GCS) score and aneurysm treatment modality. Primary outcome was utilization of LST, defined as cardiopulmonary resuscitation, ventilation, hemodialysis, ventriculostomy, tracheostomy, or gastrostomy. Descriptive statistics were calculated and associations with LST examined using chi-squares for categorical variables and Kruskal-Wallis tests for continuous variables. A stepwise logistic regression model selection procedure included all available data, with the final model selected by Akaike information criteria (AIC). Significance was set at p ≤0.05. Results: There were 34,021 patients with aSAH, with a mean age of 57.9±19.8 years. The sample was 72% Caucasian and 55% female, with a median GCS of 15 (IQR 10-15). Approximately 18% (n=6167) received one or more LST. Utilization varied by census region, age, race, marital status, and GCS ( p for each &lt;1E-8), with those most likely to receive support being from the West, in their 60s, non-white, single, and having lower GCS scores. Sex and aneurysm treatment method were not associated with LST ( p =0.12 and 0.77, respectively). With stepwise logistic regression, age and GCS were found to be significant, with a likelihood ratio test demonstrating independent prognostic value for each factor ( p &lt;0.02). Conclusions: Demographic factors are associated with LST. Potential confounds include clinical indicators, patient/family preference, and individual hospital practice patterns, and future work should include additional information on these characteristics.

A weighted bootstrap approach to logistic regression modelling in identifying risk behaviours associated with sexual activity

ABSTRACTThe latest population estimates released by Statistics South Africa indicate that 25.03% of all deaths in 2017 in South Africa were AIDS-related. Along with these results, it is also reported that 7.06% of the population were living with HIV, with the HIV-prevalence among youth (aged 15–24) at 4.64% for 2017 (STATSSA. (2018). Retrieved from Statistics South Africa: http://www.statssa.gov.za/publications/P0302/P03022017.pdf). The data used in the study contained information related to the risk-taking behaviours associated with the sexual activity of entering first-year students at the University of the Western Cape. In this study, a logistic regression modelling procedure was carried out on those students that were determined to be sexually active, therefore, in the modelling procedure significant risk behaviours of sexually active first-year students could be identified. Of the 14 variables included in the modelling procedure, six were found to be significantly associated with sexually active students. The significant variables included; the age and race of the student, whether the student had ever taken an HIV test, the importance of religion in influencing the sexual behaviour of the student, whether the student consumed alcohol and lastly whether the student smoked. This study further investigated the impact of introducing sample weighting, bootstrap sampling as well as variable selection methods into the logistic regression modelling procedure. It is shown that incorporating these techniques into the modelling procedure produces logistic regression models that are more accurate and have an increased predictive capability. The bootstrapping procedure is shown to produce logistic regression models that are more accurate than those produced without a bootstrap procedure. A comparison between 200, 500 and 1000 bootstrap samples is also incorporated into the modelling procedure with the models produced from 200 bootstrap samples shown to be just as accurate those produced from 500 or 1000 bootstrap samples. Of the five variable selection methods used, it is shown that the Newton–Raphson and Fisher methods are unreliable in producing logistic regression models. The forward, backward and stepwise variable selection methods are shown to produce very similar results.

Architectural agency in intra-organizational networks

From the concept of homophily, we argue that the pattern of strong ties (closeness) of organizational actors is mainly the result of two forces, one bureaucratic (departmental similarity) and the other positional (structural equivalence). We suggest that the moderation between these forces causes the problem of excess redundant ties and that social actors limit these relationships. We tested these hypotheses using the Logistic Regression Quadratic Assignment Procedure LR-QAP technique on 47,306 dyads collected during a sociometric survey in an intra-organizational network. We found that when two actors belong to the same department (departmental similarity), there is a greater likelihood of their being connected. We also found that this occurs when two actors have structural equivalence. In addition, we found that departmental similarity*structural equivalence moderation reduces the likelihood of the existence of strong ties between two actors, providing evidence of a type of architectural agency capability in egocentric networks.

Bayesian inference on genetic parameters for some reproductive traits in sheep using linear and threshold models

Genetic parameters for reproductive traits in Baluchi sheep were estimated on 3844 dams born during 1991 to 2012. The studied traits were litter size at birth (LSB), litter size at weaning (LSW), litter mean weight per lamb born (LMWLB), litter mean weight per lamb weaned (LMWLW), total litter weight at birth (TLWB) and total litter weight at weaning (TLWW). Significant effects were determined using Logistic and GLM procedure of SAS software for threshold and continuous traits, respectively. Variance components needed for breeding were estimated using Gibbs sampling methodology of Bayesian inference. The genetic parameters for LMWLB, LMWLW, TLWB TLWW were estimated by fitting a linear model. To examine the appropriateness of fitting linear or threshold model to litter size at birth and weaning, both models were used to estimate genetic parameters on the observed data. Posterior means of the heritabilities of litter size at birth and weaning by using a threshold model were estimated to be two times higher than the heritabilities based on the linear model (0.18 versus 0.09 and 0.11 versus 0.05 for LSB and LSW, respectively). Bayesian information criterion (BIC) selected the threshold model as most appropriate model for LSB and LSW given the data. The heritability estimates for LMWLB, LMWLW, TLWB TLWW resulting from linear analysis were 0.12, 0.05, 0.06 and 0.08, respectively. Genetic correlation estimates between the traits ranged from −0.67 for LMWLB–TLWW to 0.85 for LSB–TLWB. Phenotypic correlations ranged from −0.06 for LSB–LMWLW to 0.88 for LSB–TLWB and permanent environmental correlations ranged from −0.74 for LMWLB - TLWW to 0.88 for LSB–TLWB. Results of this study showed that the threshold model seems to be reliable for genetic evaluation of litter size in Baluchi sheep.

Comparison of protein intake per eating occasion, food sources of protein and general characteristics between community-dwelling older adults with a low and high protein intake

Adequate protein intake is required to maintain muscle health in old age, but a low protein intake is very common in older adults. There is little insight in the general and dietary profile of older adults with a low protein intake. Therefore, this study aimed to compare community-dwelling older adults with a low and a high protein intake with regard to protein intake per eating occasion, food sources of protein and general participant characteristics. Data were used from 727 Dutch community-dwelling older adults aged ≥70 years. Protein intake at meal and snack moments was measured with two non-consecutive dietary record assisted 24-h recalls. Low protein intake was defined as below the Recommended Dietary Allowance of 0.8g protein per kg adjusted body weight per day (g/kg aBW/d). Differences in protein and food intakes between those with a low and a high protein intake were assessed with the Mann-Whitney U test and Chi-square test. Eating occasions were compared with regard to differences between the low and high protein intake group by using MANOVA. Characteristics of older adults with low protein intake were selected by using a multiple logistic backward elimination procedure. Low protein intake was present in 15% of the participants. At all eating occasions, median protein intake was lower in the low compared to the high protein intake group (breakfast, 7.8 vs. 10.8g; lunch, 12.6 vs. 24.3g; dinner, 21.8 vs. 31.1g; snack moments, 6.7 vs. 9.7g; P<0.001), and was also consistently lower relative to energy intake. The contribution of animal protein to total protein intake was lower among the low protein intake group. Both groups obtained most protein from dairy, meat and cereals, but meat contributed less (21.5 vs. 28.2%) and cereals more (21.9 vs. 19.6%) among the low than the high protein intake group (all P<0.01). Differences in protein intake, percentage of energy from protein and contribution of animal to total protein intake between the groups were largest at lunch compared to the other eating occasions. Out of a long list of variables, low protein intake was only associated with following a diet, being obese vs. normal-weight and drinking alcohol on none vs. some but <5 days/week (P<0.05). At all eating occasions, Dutch community-dwelling older adults with a protein intake <0.8g/kg aBW/d ate less protein (also relative to their energy intake) and a lower proportion of animal protein compared to those with a high protein intake. These differences were largest at lunch. Major food sources of protein - in both groups - were dairy, meat and cereals. We could only identify following a diet, being obese and not drinking alcohol as general characteristics of older adults with a low protein intake.

Alloys selection based on the supervised learning technique for design of biocompatible medical materials

Purpose: The main aim of this paper is development, software implementation and use of the alloys selection method for the design of biocompatible materials in medical production. It is based on the use of Ito decomposition and Logistic Regression. Design/methodology/approach: The technology of machine learning is used to solve the task. The developed classification method is based on the application of multiclass Logistic Regression. In order to reduce the probability of incorrect alloy identification, expansion of the input characteristics based on the Ito decomposition of the second order has been made. On the one hand, it increased the dimension of the input features space, and as a result, it increased the time for training procedure, but on the other, it increased the solution accuracy of the alloys selection task. The accuracy evaluation of the method was carried out using different criteria. In particular, the method accuracy was estimated based on the ratio of correctly classified titanium alloys samples to the test sample dimension. This measure was used to assess the classification accuracy in the training and test modes. For a more detailed analysis of the classification method results, two additional measures were further used: Precision and Recall. Their calculation was based on the constructed confusion matrix. This made it possible to assess the ability of the developed method to find the instances of each individual alloy as a whole, as well as the ability to distinguish instances of one class from representatives on the other. The combination of these indicators allowed to evaluate the classification task accuracy in the conditions of the imbalance dataset for each class of the investigated material separately. Findings: The simulation results confirmed the effectiveness of the use of machine learning tools to solve this task. High indicators of the method’s accuracy based on the experimental results were established. In particular, the overall accuracy of the method is 96.875%, and the average values of Precision and Recall for all four classes are 94% and 98% respectively. Expansion of each vector's features from the training dataset by using Ito decomposition increased the method accuracy by more than 33% compared to the basic Logistic Regression. Research limitations/implications: The Logistic Regression's training procedure, as well as the increase of the space size of the investigated alloy's input features by using Ito decomposition, imposes a number of limitations on the application of the method in tasks that depend on the duration of the work. Practical implications: The proposed machine learning approach foralloys selection allows reducing the time, material and human resources needed to investigate the titanium alloys properties. The developed method increases the accuracy of the selection alloys task compared to the four known methods, an average of 14.5%. It can be used to select materials with appropriate properties for the design of biocompatible medical products. Originality/value: A method and software product for the titanium alloys classification task using a supervised learning technique has been developed. For this aim, the method of Logistic Regression with expanding inputs based on the second-order Ito decomposition is used.

Greedy active learning algorithm for logistic regression models

We study a logistic model-based active learning procedure for binary classification problems, in which we adopt a batch subject selection strategy with a modified sequential experimental design method. Moreover, accompanying the proposed subject selection scheme, we simultaneously conduct a greedy variable selection procedure such that we can update the classification model with all labeled training subjects. The proposed algorithm repeatedly performs both subject and variable selection steps until a prefixed stopping criterion is reached. Our numerical results show that the proposed procedure has competitive performance, with smaller training size and a more compact model compared with that of the classifier trained with all variables and a full data set. We also apply the proposed procedure to a well-known wave data set (Breiman et al., 1984) and a MAGIC gamma telescope data set to confirm the performance of our method.

A feasibility study prior to an international multicentre paediatric study to assess pharmacokinetic/pharmacodynamic sampling and sample preparation procedures, logistics and bioanalysis.

BackgroundVariability in pre-analytical procedures such as blood sampling, sample preparation and transport can substantially influence bioanalytical results and subsequently impair reliability of data gathered during clinical trials. Especially in vulnerable populations, all efforts should be made to facilitate high-quality data extraction excluding unnecessary or repeated intervention.MethodsThe EU-funded LENA project (Labeling of Enalapril from Neonates up to Adolescents) included a feasibility study in its preparatory procedures prior to first-in-child studies. Derived from a regular study visit, it encompassed all procedures, from sampling of two study-specific drugs and four sensitive humoral parameters to bioanalysis, to evaluate the quality of obtained samples and applicability of logistical and bioanalytical procedures. Drug administration to healthy adults was circumvented by pre-spiking the blood collection tubes with a drug solution. Five clinical sites were evaluated.ResultsClinical teams' preparedness and applicability of required sampling procedures was investigated in 18 volunteers, on-site. 97% of collected pharmacokinetic (PK) samples and 93% of samples for humoral parameters were obtained eligibly. Results met expectations, though one team had to be re-trained and performed a re-run. Planned procedures for sampling, sample preparation, transport and analysis were found to be suitable for being applied within paediatric trials.ConclusionThe concept of the presented feasibility study that simultaneously assesses PK/PD sampling, sample preparation, logistics and bioanalysis proved to be a promising tool for trial preparation. It revealed improperly installed processes and bottlenecks that required adjustments prior to start of recruitment. It facilitated high-quality conduct from the first moment of paediatric pivotal studies.

Prognosis of Clostridium difficile infection in adult oncohaematological patients: experience from a large prospective observational study.

The aim of the study is to evaluate demographics, epidemiology, clinical characteristics, treatment and outcomes of Clostridium difficile infection (CDI) in patients with and without concurrent cancer. This is a prospective cohort study of consecutive primary CDI episodes in adults (January 2006-December 2016). CDI was diagnosed on the presence of diarrhoea and positive stool testing for toxigenic C. difficile. Univariate analysis assessed differences between cancer and non-cancer patients. Risk factors of all-cause 30-day mortality were determinate using the logistic multivariable procedure. In total, 787 CDI episodes were recorded, 191 in cancer patients (median age 64, IQR 50-73). Of these, 120 (63%) had solid and 71 (37%) haematological malignancies (24 received a stem cell transplant). At the CDI diagnosis, 158 (82.7%) cancer patients had prior antibiotics and 150 (78.5%) were receiving proton pump inhibitors. Fifty-seven (80.3%) patients with haematological and 52 (43.3%) with solid malignancies were under chemotherapy at diagnosis; 25 (35.2%) with haematological and 11 (9.2%) with solid malignancies had an absolute neutrophil count < 1000/mm3. Overall, 30-day mortality was higher in cancer patients than in those without (19.2 vs. 8.6% respectively, p < 0.001); recurrence rates did not vary significantly (11.1 vs. 11%, p = 0.936). By type of neoplasm, 30-day mortality was higher in patients with haematological malignancies and solid tumours than in patients without cancer (respectively, 25.4 vs. 8.6%; p < 0.001 and 15 vs. 8.6%; p < 0.001). Our results suggest that the prognosis of CDI (30-day mortality) is poorer in patients with cancer than in those without although percentages of recurrent infection are similar in these two patient populations.

Association of SNP markers in immune response genes with resistance or susceptibility to Mycobacteriun avium paratuberculosis in Cattle

Background: Bovine paratuberculosis, also known as Johne's disease (JD), is a chronic, granulomatous inflammatory disease of the intestines of ruminants and some wild-type species caused by Mycobacterium avium spp. paratuberculosis (MAP). The present study was conducted to find the association between SNPs in TLR 1 gene and occurrence of paratuberculosis in cattle. Methods & Materials: A total of 178 cattle were subjected to Johnin PPD, ELISA test (indigenous as well as Parachek kit method), faecal microscopy and faecal culture for detection of presence of bovine paratuberculosis infection. Based on the results of diagnostic tests, 45 animals each were assigned to case and control population. Two SNPs viz. rs135207279 and rs437316199 in TLR 1 gene were validated using PCR-RFLP with restriction enzymes TspRI. For SNP rs135207279, three genotypes i.e. AA, AC and CC were observed with genotype frequencies in case as 24, 54 and 22% respectively while in control population as 33, 24 and 43% respectively. The association study was carried out by PROC LOGISTIC procedure of SAS 9.3. Results: AA, AC and CC genotypes significantly different (p < 0.05) between case and control cattle. The ODDs of AA and AC genotypes verses CC genotype were 1.00 (0.0301-3.321; 95% CI) and 3.66 (1.2-11.17; 95%CI) respectively. For rs437316199, the genotype frequencies of GG, GT and TT in case and control population were 36, 18, 46%; and 40, 16and 44% respectively. AA, AC and CC genotypes were not significantly (P > 0.05) different in case than control population. Conclusion: Genotypes in SNP rs135207279 showed significant association with occurrence of paratuberculosis in the analyzed cattle population. There is further need to confirm the association of TLR 1 gene with bovine tuberculosis infection status in a larger population of cattle.

Effect of leptin genetic polymorphism on lameness prevalence in Tunisian Holstein cows

Abstract. Lameness is the third most important infection affecting dairy cattle in modern stabling barns. Environmental (food, stables and injuries) and genetic factors are responsible for this pathology. This study aims to investigate the screening of leptin genetic polymorphism and its effect on lameness prevalence. DNA was extracted from 412 blood samples from Holstein cows (lame and healthy). Genotyping was performed by the PCR-RFLP using the Sau3AI restriction enzyme. Prevalence of parity, calving season, age at calving, test-day milk yields, calving year and leptin/Sau3AI genotype was evaluated by the logistics procedure. Results showed that allelic frequencies are 0.68 and 0.32 respectively for the A and B allele. Frequencies for the AA, AB and BB genotypes are 0.52, 032 and 0.16 respectively. All factors included in the logistic regression model significantly affect the prevalence of lameness in Holstein cows (P&lt;0.01). The probability of lameness incidence varied between 37 % and 99 % respectively for the second and the third parity. The lameness incidence recorded in multiparous is higher than primiparous cows. This recorded incidence is greater in winter and autumn than in the summer and spring. The genetic polymorphism affects the prevalence of lameness in Holstein cows. The incidence of lameness in AB genotype is lower than that in BB and AA genotype. These results can be a way to improve length of productive life for cattle breeds in Tunisia.