First trimester maternal level of PAPP-A, βhCG and ethnicity as predictive of Intrauterine Growth Restriction

Intrauterine growth restriction (IUGR) is one of the leading causes of perinatal mortality and morbidity. Nowadays, this condition is detected in the 3rt and last trimester of gestation when the pathology is already established and success of therapeutic strategies are limited. As the physiopathology of the disease suggests that the problem stems from poor placental implantation, it would be quite advantageous to identify women at increased risk in the first or second trimester of gestation because it then might be possible to offer treatment interventions or at least to establish increased surveillance for high risk pregnancies. Maternal levels of pregnancy-associated plasma protein-A (PAPP-A) and free β human chorionic gonadotropin (free βhCG) has been shown to be effective in first trimester screening for chromosomal abnormalities, primarily trisomies 21, 13 and 18. Previous studies evaluating PAPP-A and free βhCG measured in the first trimester in relation with IUGR have provided conflicting results. Moreover, it has been suggested that black ethnicity is another important predictive factor for fetal growth restriction.Objective: To analyse the association between first trimester serum analytes (PAPP-A and free βhCG) and ethnicity with Intrauterine Growth Restriction.Methods: The study consists in a retrospective cohort, including all singleton pregnancies with complete outcome data that had undergone first trimester screening (PAPP-A and free βhCG) at 11-13+6weeks of gestation between 1/1/2010 - 31/12/2012 in Hospital Universitari Dr Josep Trueta. Biochemical markers are converted to multiples of the median (MoMs) and percentiles 5 and 10 are calculated. The association between free βhCG and PAPP-A with the incidence of IUGR is evaluated in combination with maternal ethnicity. Bivariate and logistic regression analyses are performed to adjust this association for co variables

Predictive factors for voiding dysfunction after transobturator slings

PURPOSE: To identify the predictive factors for voiding dysfunction after transobturator slings. METHODS: We retrospectively reviewed the records of all patients who underwent a transobturator sling between March 2003 and December 2008. A total of 514 women had available data with at least a six-week follow-up. Patients' demographics, preoperative symptoms, urodynamic testing including multichannel voiding studies and surgical variables were tabulated. Voiding dysfunction was defined by a catheterized or ultrasonographic postvoid residual greater than 100 cc (≥six weeks after the procedure) associated with any complaints of abnormal voiding. Univariate logistic regression analysis was performed with respect to postoperative voiding dysfunction. RESULTS: The patient population had a mean age of 58.5±12.9 years. Thirty-three out of 514 patients (6.4%) had postoperative voiding dysfunction according to our definition, and 4 (0.78%) required sling transection. No differences were observed between normal and dysfunctional voiders in age, associated prolapse surgery, preoperative postvoid residual, preoperative urinary flow rate, prior pelvic surgery, and menopausal status. Valsalva efforts during the preoperative pressure flow study was the only predictive factor for postoperative voiding dysfunction, 72.4% dysfunctional versus 27.6% normal (p<0.001). CONCLUSION: Preoperative Valsalva maneuver during the micturition could identify those at risk for voiding dysfunction after transobturator sling, and it should be noted during preoperative counseling.

Hypomagnesemia in critically ill cancer patients: a prospective study of predictive factors

Hypomagnesemia is the most common electrolyte disturbance seen upon admission to the intensive care unit (ICU). Reliable predictors of its occurrence are not described. The objective of this prospective study was to determine factors predictive of hypomagnesemia upon admission to the ICU. In a single tertiary cancer center, 226 patients with different diagnoses upon entering were studied. Hypomagnesemia was defined by serum levels <1.5 mg/dl. Demographic data, type of cancer, cause of admission, previous history of arrhythmia, cardiovascular disease, renal failure, drug administration (particularly diuretics, antiarrhythmics, chemotherapy and platinum compounds), previous nutrition intake and presence of hypovolemia were recorded for each patient. Blood was collected for determination of serum magnesium, potassium, sodium, calcium, phosphorus, blood urea nitrogen and creatinine levels. Upon admission, 103 (45.6%) patients had hypomagnesemia and 123 (54.4%) had normomagnesemia. A normal dietary habit prior to ICU admission was associated with normal Mg levels (P = 0.007) and higher average levels of serum Mg (P = 0.002). Postoperative patients (N = 182) had lower levels of serum Mg (0.60 ± 0.14 mmol/l compared with 0.66 ± 0.17 mmol/l, P = 0.006). A stepwise multiple linear regression disclosed that only normal dietary habits (OR = 0.45; CI = 0.26-0.79) and the fact of being a postoperative patient (OR = 2.42; CI = 1.17-4.98) were significantly correlated with serum Mg levels (overall model probability = 0.001). These findings should be used to identify patients at risk for such disturbance, even in other critically ill populations.

Predictive significance of standardized uptake value parameters of FDG-PET in patients with non-small cell lung carcinoma

18F-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) is widely used to diagnose and stage non-small cell lung cancer (NSCLC). The aim of this retrospective study was to evaluate the predictive ability of different FDG standardized uptake values (SUVs) in 74 patients with newly diagnosed NSCLC. 18F-FDG PET/CT scans were performed and different SUV parameters (SUVmax, SUVavg, SUVT/L, and SUVT/A) obtained, and their relationship with clinical characteristics were investigated. Meanwhile, correlation and multiple stepwise regression analyses were performed to determine the primary predictor of SUVs for NSCLC. Age, gender, and tumor size significantly affected SUV parameters. The mean SUVs of squamous cell carcinoma were higher than those of adenocarcinoma. Poorly differentiated tumors exhibited higher SUVs than well-differentiated ones. Further analyses based on the pathologic type revealed that the SUVmax, SUVavg, and SUVT/L of poorly differentiated adenocarcinoma tumors were higher than those of moderately or well-differentiated tumors. Among these four SUV parameters, SUVT/Lwas the primary predictor for tumor differentiation. However, in adenocarcinoma, SUVmax was the determining factor for tumor differentiation. Our results showed that these four SUV parameters had predictive significance related to NSCLC tumor differentiation; SUVT/L appeared to be most useful overall, but SUVmax was the best index for adenocarcinoma tumor differentiation.

Social network measures for "nosduocentered" networks, their predictive power on performance

Our purpose in this article is to define a network structure which is based on two egos instead of the egocentered (one ego) or the complete network (n egos). We describe the characteristics and properties for this kind of network which we call “nosduocentered network”, comparing it with complete and egocentered networks. The key point for this kind of network is that relations exist between the two main egos and all alters, but relations among others are not observed. After that, we use new social network measures adapted to the nosduocentered network, some of which are based on measures for complete networks such as degree, betweenness, closeness centrality or density, while some others are tailormade for nosduocentered networks. We specify three regression models to predict research performance of PhD students based on these social network measures for different networks such as advice, collaboration, emotional support and trust. Data used are from Slovenian PhD students and their s

Use of a predictive model for food insecurity estimates in Brazil

In 2004 the National Household Survey (Pesquisa Nacional par Amostras de Domicilios - PNAD) estimated the prevalence of food and nutrition insecurity in Brazil. However, PNAD data cannot be disaggregated at the municipal level. The objective of this study was to build a statistical model to predict severe food insecurity for Brazilian municipalities based on the PNAD dataset. Exclusion criteria were: incomplete food security data (19.30%); informants younger than 18 years old (0.07%); collective households (0.05%); households headed by indigenous persons (0.19%). The modeling was carried out in three stages, beginning with the selection of variables related to food insecurity using univariate logistic regression. The variables chosen to construct the municipal estimates were selected from those included in PNAD as well as the 2000 Census. Multivariate logistic regression was then initiated, removing the non-significant variables with odds ratios adjusted by multiple logistic regression. The Wald Test was applied to check the significance of the coefficients in the logistic equation. The final model included the variables: per capita income; years of schooling; race and gender of the household head; urban or rural residence; access to public water supply; presence of children; total number of household inhabitants and state of residence. The adequacy of the model was tested using the Hosmer-Lemeshow test (p=0.561) and ROC curve (area=0.823). Tests indicated that the model has strong predictive power and can be used to determine household food insecurity in Brazilian municipalities, suggesting that similar predictive models may be useful tools in other Latin American countries.

Bayesian Analysis for Nonlinear Regression Model Under Skewed Errors, with Application in Growth Curves

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew-t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.

A gene signature in histologically normal surgical margins is predictive of oral carcinoma recurrence

Background: Oral Squamous Cell Carcinoma (OSCC) is a major cause of cancer death worldwide, which is mainly due to recurrence leading to treatment failure and patient death. Histological status of surgical margins is a currently available assessment for recurrence risk in OSCC; however histological status does not predict recurrence, even in patients with histologically negative margins. Therefore, molecular analysis of histologically normal resection margins and the corresponding OSCC may aid in identifying a gene signature predictive of recurrence.Methods: We used a meta-analysis of 199 samples (OSCCs and normal oral tissues) from five public microarray datasets, in addition to our microarray analysis of 96 OSCCs and histologically normal margins from 24 patients, to train a gene signature for recurrence. Validation was performed by quantitative real-time PCR using 136 samples from an independent cohort of 30 patients.Results: We identified 138 significantly over-expressed genes (> 2-fold, false discovery rate of 0.01) in OSCC. By penalized likelihood Cox regression, we identified a 4-gene signature with prognostic value for recurrence in our training set. This signature comprised the invasion-related genes MMP1, COL4A1, P4HA2, and THBS2. Overexpression of this 4-gene signature in histologically normal margins was associated with recurrence in our training cohort (p = 0.0003, logrank test) and in our independent validation cohort (p = 0.04, HR = 6.8, logrank test).Conclusion: Gene expression alterations occur in histologically normal margins in OSCC. Over-expression of the 4-gene signature in histologically normal surgical margins was validated and highly predictive of recurrence in an independent patient cohort. Our findings may be applied to develop a molecular test, which would be clinically useful to help predict which patients are at a higher risk of local recurrence.

Predictive factors of outcome following staphylococcal peritonitis in continuous ambulatory peritoneal dialysis

Background and aims: Staphylococcus epidermidis and other coagulase-negative staphylococci (CoNS) are the most common agents of continuous ambulatory peritoneal dialysis (CAPD) peritonitis. Episodes caused by Staphylococcus aureus evolve with a high method failure rate while CoNS peritonitis is generally benign. The purpose of this study was to compare episodes of peritonitis caused by CoNS species and S. aureus to evaluate the microbiological and host factors that affect outcome. Material and methods: Microbiological and clinical data were retrospectively studied from 86 new episodes of peritonitis caused by staphylococci species between January 1996 and December 2000 in a university dialysis center. The influence of microbiological and host factors (age, sex, diabetes, use of vancomycin, exchange system and treatment time on CAPD) was analyzed by logistic regression model. The clinical outcome was classified into two results (resolution and non-resolution). Results: the odds of peritonitis resolution were not influenced by host factors. Oxacillin susceptibility was present in 30 of 35 S. aureus lineages and 22 of 51 CoNS (p = 0.001). There were 32 of 52 (61.5%) episodes caused by oxacillin-susceptible and 20 of 34 (58.8%) by oxacillin-resistant lineages resolved (p = 0.9713). of the 35 cases caused by S. aureus, 17 (48.6%) resolved and among 51 CoNS episodes 40 (78.4%) resolved. Resolution odds were 7.1 times higher for S. epidermidis than S. aureus (p = 0.0278), while other CoNS had 7.6 times higher odds resolution than S. epidermidis cases (p = 0.052). Episodes caused by S. haemolyticus had similar resolution odds to S. epidermidis (p = 0.859). Conclusions: S. aureus etiology is an independent factor associated with peritonitis non-resolution in CAPD, while S. epidermidis and S. haemolyticus have a lower resolution rate than other CoNS. Possibly the aggressive nature of these agents, particularly S. aureus, can be explained by their recognized pathogenic factors, more than antibiotic resistance.

Multicollinearity and financial constraint in investment decisions: a bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

Prevalence of the hepatitis C virus among university employees in São Paulo, southeastern Brazil: predictive factors and geoprocessing spatial analysis

Background There are limited studies on the prevalence and risk factors associated with hepatitis C virus (HCV) infection. Objective Identify the prevalence and risk factors for HCV infection in university employees of the state of São Paulo, Brazil. Methods Digital serological tests for anti-HCV have been performed in 3153 volunteers. For the application of digital testing was necessary to withdraw a drop of blood through a needlestick. The positive cases were performed for genotyping and RNA. Chi-square and Fisher’s exact test were used, with P-value <0.05 indicating statistical significance. Univariate and multivariate logistic regression were also used. Results Prevalence of anti-HCV was 0.7%. The risk factors associated with HCV infection were: age >40 years, blood transfusion, injectable drugs, inhalable drugs (InDU), injectable Gluconergam®, glass syringes, tattoos, hemodialysis and sexual promiscuity. Age (P=0.01, OR 5.6, CI 1.4 to 22.8), InDU (P<0.0001, OR=96.8, CI 24.1 to 388.2), Gluconergam® (P=0.0009, OR=44.4, CI 4.7 to 412.7) and hemodialysis (P=0.0004, OR=90.1, CI 7.5 – 407.1) were independent predictors. Spatial analysis of the prevalence with socioeconomic indices, Gross Domestic Product and Human Development Index by the geoprocessing technique showed no positive correlation. Conclusions The prevalence of HCV infection was 0.7%. The independent risk factors for HCV infection were age, InDU, Gluconergan® and hemodialysis. There was no spatial correlation of HCV prevalence with local economic factors.

GIS-based analytical tools for transport planning: spatial regression models for transportation demand forecast

Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.

Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients

Background: Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Methods: Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. Results: We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. Conclusions: The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in countries with limited resources.

Accuracy of positron emission tomography/computed tomography and clinical assessment in the detection of complete rectal tumor regression after neoadjuvant chemoradiation Long-Term Results of a Prospective Trial (National Clinical Trial 00254683)

BACKGROUND: Neoadjuvant chemoradiation (CRT) therapy may result in significant tumor regression in patients with rectal cancer. Patients who develop complete tumor regression have been managed by treatment strategies that are alternatives to standard total mesorectal excision. Therefore, assessment of tumor response with positron emission tomography/computed tomography (PET/CT) after neoadjuvant treatment may offer relevant information for the selection of patients to receive alternative treatment strategies. METHODS: Patients with clinical T2 (cT2) through cT4NxM0 rectal adenocarcinoma were included prospectively. Neoadjuvant therapy consisted of 54 grays of radiation and 5-fluorouracil-based chemotherapy. Baseline PET/CT studies were obtained before CRT followed by PET/CT studies at 6 weeks and 12 weeks after the completion of CRT. Clinical assessment was performed at 12 weeks after CRT completion. PET/CT results were compared with clinical and pathologic data. RESULTS: In total, 99 patients were included in the study. Twenty-three patients were complete responders (16 had a complete clinical response, and 7 had a complete pathologic response). The PET/CT response evaluation at 12 weeks indicated that 18 patients had a complete response, and 81 patients had an incomplete response. There were 5 false-negative and 10 false-positive PET/CT results. PET/CT for the detection of residual cancer had 93% sensitivity, 53% specificity, a 73% negative predictive value, an 87% positive predictive value, and 85% accuracy. Clinical assessment alone resulted in an accuracy of 91%. PET/CT information may have detected misdiagnoses made by clinical assessment alone, improving overall accuracy to 96%. CONCLUSIONS: Assessment of tumor response at 12 weeks after CRT completion with PET/CT imaging may provide a useful additional tool with good overall accuracy for the selection of patients who may avoid unnecessary radical resection after achieving a complete clinical response. Cancer 2012;35013511. (C) 2011 American Cancer Society.