Prevalence of Treponema Species Detected in Endodontic Infections: Systematic Review and Meta-regression Analysis

Introduction: This systematic review and meta-regression analysis aimed to calculate a combined prevalence estimate and evaluate the prevalence of different Treponema species in primary and secondary endodontic infections, including symptomatic and asymptomatic eases. Methods: The MEDLINE/PubMed, Embase, Scielo, Web of Knowledge, and Scopus data-bases were searched without starting date restriction up to and including March 2014. Only reports in English were included. The selected literature was reviewed by 2 authors and classified as suitable or not to be included in this review. Lists were compared, and, in case of disagreements, decisions were made after a discussion based on inclusion and exclusion criteria. A pooled prevalence of Treponema species in endodontic infections was estimated. Additionally, a meta-regression analysis was performed. Results: Among the 265 articles identified in the initial search, only 51 were included in the final analysis. The studies were classified into 2 different groups according to the type of endodontic infection and whether it was an exclusively primary/secondary study (n = 36) or a primary/secondary comparison (n = 15). The pooled prevalence of Treponema species was 41.5% (95% confidence interval, 35.9-47.0). In the multivariate model of meta-regression analysis, primary endodontic infections (P < .001), acute apical abscess, symptomatic apical periodontitis (P < .001), and concomitant presence of 2 or more species (P = .028) explained the heterogeneity regarding the prevalence rates of Treponema species. Conclusions: Our findings suggest that Treponema species are important pathogens involved in endodontic infections, particularly in cases of primary and acute infections.

Anesthesia-related and perioperative cardiac arrest in low- and high-income countries: a systematic review with meta-regression and proportional meta-analysis

The anesthesia-related cardiac arrest (CA) rate is a quality indicator to improve patient safety in the perioperative period. A systematic review with meta-analysis of the worldwide literature related to anesthesia-related CA rate has not yet been performed.This study aimed to analyze global data on anesthesia-related and perioperative CA rates according to country's Human Development Index (HDI) and by time. In addition, we compared the anesthesia-related and perioperative CA rates in low- and high-income countries in 2 time periods.A systematic review was performed using electronic databases to identify studies in which patients underwent anesthesia with anesthesia-related and/or perioperative CA rates. Meta-regression and proportional meta-analysis were performed with 95% confidence intervals (CIs) to evaluate global data on anesthesia-related and perioperative CA rates according to country's HDI and by time, and to compare the anesthesia-related and perioperative CA rates by country's HDI status (low HDI vs high HDI) and by time period (pre-1990s vs 1990s-2010s), respectively.Fifty-three studies from 21 countries assessing 11.9 million anesthetic administrations were included. Meta-regression showed that anesthesia-related (slope: -3.5729; 95% CI: -6.6306 to -0.5152; P = 0.024) and perioperative (slope: -2.4071; 95% CI: -4.0482 to -0.7659; P = 0.005) CA rates decreased with increasing HDI, but not with time. Meta-analysis showed per 10,000 anesthetics that anesthesia-related and perioperative CA rates declined in high HDI (2.3 [95% CI: 1.2-3.7] before the 1990s to 0.7 [95% CI: 0.5-1.0] in the 1990s-2010s, P < 0.001; and 8.1 [95% CI: 5.1-11.9] before the 1990s to 6.2 [95% CI: 5.1-7.4] in the 1990s-2010s, P < 0.001, respectively). In low-HDI countries, anesthesia-related CA rates did not alter significantly (9.2 [95% CI: 2.0-21.7] before the 1990s to 4.5 [95% CI: 2.4-7.2] in the 1990s-2010s, P = 0.14), whereas perioperative CA rates increased significantly (16.4 [95% CI: 1.5-47.1] before the 1990s to 19.9 [95% CI: 10.9-31.7] in the 1990s-2010s, P = 0.03).Both anesthesia-related and perioperative CA rates decrease with increasing HDI but not with time. There is a clear and consistent reduction in anesthesia-related and perioperative CA rates in high-HDI countries, but an increase in perioperative CA rates without significant alteration in the anesthesia-related CA rates in low-HDI countries comparing the 2 time periods.

Logistic regression analysis of potential prognostic factors for pulmonary thromboembolism

Objective: To identify potential prognostic factors for pulmonary thromboembolism (PTE), establishing a mathematical model to predict the risk for fatal PTE and nonfatal PTE.Method: the reports on 4,813 consecutive autopsies performed from 1979 to 1998 in a Brazilian tertiary referral medical school were reviewed for a retrospective study. From the medical records and autopsy reports of the 512 patients found with macroscopically and/or microscopically,documented PTE, data on demographics, underlying diseases, and probable PTE site of origin were gathered and studied by multiple logistic regression. Thereafter, the jackknife method, a statistical cross-validation technique that uses the original study patients to validate a clinical prediction rule, was performed.Results: the autopsy rate was 50.2%, and PTE prevalence was 10.6%. In 212 cases, PTE was the main cause of death (fatal PTE). The independent variables selected by the regression significance criteria that were more likely to be associated with fatal PTE were age (odds ratio [OR], 1.02; 95% confidence interval [CI], 1.00 to 1.03), trauma (OR, 8.5; 95% CI, 2.20 to 32.81), right-sided cardiac thrombi (OR, 1.96; 95% CI, 1.02 to 3.77), pelvic vein thrombi (OR, 3.46; 95% CI, 1.19 to 10.05); those most likely to be associated with nonfatal PTE were systemic arterial hypertension (OR, 0.51; 95% CI, 0.33 to 0.80), pneumonia (OR, 0.46; 95% CI, 0.30 to 0.71), and sepsis (OR, 0.16; 95% CI, 0.06 to 0.40). The results obtained from the application of the equation in the 512 cases studied using logistic regression analysis suggest the range in which logit p > 0.336 favors the occurrence of fatal PTE, logit p < - 1.142 favors nonfatal PTE, and logit P with intermediate values is not conclusive. The cross-validation prediction misclassification rate was 25.6%, meaning that the prediction equation correctly classified the majority of the cases (74.4%).Conclusions: Although the usefulness of this method in everyday medical practice needs to be confirmed by a prospective study, for the time being our results suggest that concerning prevention, diagnosis, and treatment of PTE, strict attention should be given to those patients presenting the variables that are significant in the logistic regression model.

Some practical advice on polynomial regression analysis from blocked response surface designs

It is often necessary to run response surface designs in blocks. In this paper the analysis of data from such experiments, using polynomial regression models, is discussed. The definition and estimation of pure error in blocked designs are considered. It is recommended that pure error is estimated by assuming additive block and treatment effects, as this is more consistent with designs without blocking. The recovery of inter-block information using REML analysis is discussed, although it is shown that it has very little impact if thc design is nearly orthogonally blocked. Finally prediction from blocked designs is considered and it is shown that prediction of many quantities of interest is much simpler than prediction of the response itself.

Parada cardíaca perioperatória e relacionada à anestesia: revisão sistemática com meta-análise proporcional e análise de metarregressão

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Parada cardíaca perioperatória e por fator anestésico em pacientes geriátricos: revisão sistemática com meta-análise e análise de metarregressão

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Response surface models to predict broiler performance and applications for economic analysis

A study was carried out to elaborate response surface models using broiler performance data recovered from literature in order to predict performance and elaborate economic analyses. Nineteen studies published between 1995 and 2005 were retrieved using the systematic literature review method. Weight gain and feed conversion data were collected from eight studies that fulfilled the pre-established inclusion criteria, and a response surface model was adjusted using crude protein, environmental temperature, and age as independent variables. The models produced for weight gain (r² = 0.93) and feed conversion (r² = 0.85) were accurate, precise, and not biased. Protein levels, environmental temperature and age showed linear and quadratic effects on weight gain and feed conversion. There was no interaction between protein level and environmental temperature. Age and crude protein showed interaction for weight gain and feed conversion, whereas interaction between age and temperature was detected only for weight gain. It was possible to perform economic analyses to determine maximum profit as a function of the variables that were included in the model. It was concluded that the response surface models are effective to predict the performance of broiler chickens and allow the elaboration of economic analyses to optimize profit.

Use of ridge regression for the prediction of early growth performance in crossbred calves

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Correlation between semen analysis by motile sperm organelle morphology examination and sperm DNA damage

Regression analysis of 538 semen samples demonstrated that percentages of normal nuclear sperm and all spermatozoa with abnormalities of nuclear form at high magnification had significant negative correlation with percentages of DNA fragmentation. on the other hand, there was a positive correlation between percentages of spermatozoa with nuclear vacuoles and those with DNA fragmentation. (Fertil Steril (R) 2010;94:1937-40. (C) 2010 by American Society for Reproductive Medicine.)

The effects of male age on sperm analysis by motile sperm organelle morphology examination (MSOME)

Background: This study aimed to investigate the influence of age on sperm quality, as analysed by motile sperm organelle morphology examination (MSOME).Methods: Semen samples were collected from 975 men undergoing evaluation or treatment for infertility. Sperm cells were evaluated at 8400x magnification using an inverted microscope equipped with Nomarski (differential interference contrast) optics. Two forms of spermatozoa were considered: normal spermatozoa and spermatozoa with large nuclear vacuoles (LNV, defined as vacuoles occupying > 50% of the sperm nuclear area). At least 200 spermatozoa per sample were evaluated, and the percentages of normal and LNV spermatozoa were determined. The subjects were divided into three groups according to age: Group I, less than or equal to 35 years; Group II, 36-40 years; and Group III, greater than or equal to 41 years.Results: There was no difference in the percentages of normal sperm between the two younger (I and II) groups (P > 0.05). The percentage of normal sperm in the older group (III) was significantly lower than that in the younger (I and II) groups (P < 0.05). There was no difference in the percentage of LNV spermatozoa between the younger (I and II) groups (P > 0.05). The percentage of LNV spermatozoa was significantly higher in the older group (III) than in the younger (I and II) groups (P < 0.05). Regression analysis demonstrated a significant decrease in the incidence of normal sperm with increasing age (P < 0.05; r = -0.10). However, there was a significant positive correlation between the percentage of spermatozoa with LNV and male age (P < 0.05, r = 0.10).Conclusion: The results demonstrated a consistent decline in semen quality, as reflected by morphological evaluation by MSOME, with increased age. Considering the relationship between nuclear vacuoles and DNA damage, these age-related changes predict that increased paternal age should be associated with unsuccessful or abnormal pregnancy as a consequence of fertilisation with damaged spermatozoa. Given that sperm nuclear vacuoles can be evaluated more precisely at high magnification, these results support the routine use of MSOME for ICSI as a criterion for semen analysis.

Authorship, Collaboration, and Funding Trends in Implantology Literature: Analysis of Five Journals From 2005 to 2009

Purpose: To identify the trend of authorship in dental implant by exploring the prevalence of coauthored articles and to investigate the collaboration efforts, trends in funding involved in original articles, and their relationships. Materials: Articles published in the Clinical Oral Implants Research, International Journal of Oral & Maxillofacial Implants, Clinical Implant Dentistry and Related Research, Implant Dentistry, and Journal of Oral Implantology from 2005 to 2009 were reviewed. Nonoriginal articles were excluded. For each included articles, number of authors, collaboration efforts, and extramural funding were recorded. Descriptive and analytical statistics (alpha = 0.05), including logistic regression analysis and chi(2) test, were used. Results: From a total of 2085 articles, 1503 met the inclusion criteria. Publications with 5 or more authors increased over time (P = 0.813). The amount of collaboration among different disciplines, institutions, and countries all increased. The greatest increase of collaboration was seen among institutions (P = 0.09). Non-funding studies decreased over time (P = 0.031). There was a strong association between collaboration and funding for the manuscripts during the years studied (OR, 1.5). Conclusion: The number of authors per articles and collaborative studies increased over time in implant-related journals. Collaborative studies were more likely to be funded. (Implant Dent 2011;20:68-75)

Statistical methods applied to the analysis of blasting vibrations in a diabase quarry in the city of Campinas, (SP) Brazil

Statistical methods of multiple regression analysis, trend surface analysis and principal components analysis were applied to seismographic data recorded during production blasting at a diabase quarry in the urban area of Campinas (SP), Brazil. The purpose of these analyses was to determine the influence of the following variables: distance (D), charge weight per delay (W), and scaled distance (SD) associated with properties of the rock body (orientation, frequency and angle of geological discontinuities; depth of bedrock and thickness of the soil overburden) in the variation of the peak particle velocity (PPV). This approach yielded variables with larger influences (loads) on the variation of ground vibration, as well as behavior and space tendency of this variation. The results showed a better relationship between PPV and D, with D being the most important factor in the attenuation of the ground vibrations. The geological joints and the depth to bedrock have a larger influence than the explosive charges in the variation of the vibration levels, but frequencies appear to be more influenced by the amount of soil overburden.

Short-term multinodal load forecasting in distribution systems using general regression neural networks

Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, trustable and has a short-time processing. This paper proposes two methodologies based on general regression neural networks for short-term multinodal load forecasting. The first individually forecast the local loads and the second forecast the global load and individually forecast the load participation factors to estimate the local loads. To design the forecasters it wasn't necessary the previous study of the local loads. Tests were made using a New Zealand distribution subsystem and the results obtained are compatible with the ones founded in the specialized literature. © 2011 IEEE.

Comparison of random regression models to estimate genetic parameters for milk production in Guzerat (Bos indicus) cows

Random regression models have been widely used to estimate genetic parameters that influence milk production in Bos taurus breeds, and more recently in B. indicus breeds. With the aim of finding appropriate random regression model to analyze milk yield, different parametric functions were compared, applied to 20,524 test-day milk yield records of 2816 first-lactation Guzerat (B. indicus) cows in Brazilian herds. The records were analyzed by random regression models whose random effects were additive genetic, permanent environmental and residual, and whose fixed effects were contemporary group, the covariable cow age at calving (linear and quadratic effects), and the herd lactation curve. The additive genetic and permanent environmental effects were modeled by the Wilmink function, a modified Wilmink function (with the second term divided by 100), a function that combined third-order Legendre polynomials with the last term of the Wilmink function, and the Ali and Schaeffer function. The residual variances were modeled by means of 1, 4, 6, or 10 heterogeneous classes, with the exception of the last term of the Wilmink function, for which there were 1, from 0.20 to 0.33. Genetic correlations between adjacent records were high values (0.83-0.99), but they declined when the interval between the test-day records increased, and were negative between the first and last records. The model employing the Ali and Schaeffer function with six residual variance classes was the most suitable for fitting the data. © FUNPEC-RP.