Blood transfusion utilization and recipient survival at Hospital das Clinicas in Sao Paulo, Brazil

BACKGROUND: The characteristics of blood recipients including diagnoses associated with transfusion and posttransfusion survival are unreported in Brazil. The goals of this analysis were: 1) to describe blood utilization according to clinical diagnoses and patient characteristics and 2) to determine the factors associated with survival of blood recipients. STUDY DESIGN AND METHODS: A retrospective cross-sectional analysis was conducted on all inpatients in 2004. Data came from three sources: The first two files consist of data about patient characteristics, clinical diagnosis, and transfusion. Analyses comparing transfused and nontransfused patients were conducted. The third file was used to determine survival recipients up to 3 years after transfusion. Logistic regression was conducted among transfused patients to examine characteristics associated with survival. RESULTS: In 2004, a total of 30,779 patients were admitted, with 3835 (12.4%) transfused. These patients had 10,479 transfusions episodes, consisting of 39,561 transfused components: 16,748 (42%) red blood cells, 15,828 (40%) platelets (PLTs), and 6190 (16%) plasma. The median number of components transfused was three (range, 1-656) per patient admission. Mortality during hospitalization was different for patients whose admissions included transfusion or not (24% vs. 4%). After 1 year, 56% of transfusion recipients were alive. The multivariable model of factors associated with mortality after transfusion showed that the most significant factors in descending order were hospital ward, increasing age, increasing number of components transfused, and type of components received. CONCLUSION: Ward and transfusion are markers of underlying medical conditions and are associated with the probability of survival. PLT transfusions are common and likely reflect the types of patients treated. This comprehensive blood utilization study, the first of its kind in Brazil, can help in developing transfusion policy analyses in South America.

Extraoral Implants in the Rehabilitation of Craniofacial Defects: Implant and Prosthesis Survival Rates and Peri-Implant Soft Tissue Evaluation

Purpose: Few reports have evaluated cumulative survival rates of extraoral rehabilitation and peri-implant soft tissue reaction at long-term follow-up. The objective of this study was to evaluate implant and prosthesis survival rates and the soft tissue reactions around the extraoral implants used to support craniofacial prostheses. Materials and Methods: A retrospective study was performed of patients who received implants for craniofacial rehabilitation from 2003 to 2010. Two outcome variables were considered: implant and prosthetic success. The following predictor variables were recorded: gender, age, implant placement location, number and size of implants, irradiation status in the treated field, date of prosthesis delivery, soft tissue response, and date of last follow-up. A statistical model was used to estimate survival rates and associated confidence intervals. We randomly selected 1 implant per patient for analysis. Data were analyzed using the Kaplan-Meier method and log-rank test to compare survival curves. Results: A total of 150 titanium implants were placed in 56 patients. The 2-year overall implant survival rates were 94.1% for auricular implants, 90.9% for nasal implants, 100% for orbital implants, and 100% for complex midfacial implants (P = .585). The implant survival rates were 100% for implants placed in irradiated patients and 94.4% for those placed in nonirradiated patients (P = .324). The 2-year overall prosthesis survival rates were 100% for auricular implants, 90.0% for nasal implants, 92.3% for orbital implants, and 100% for complex midfacial implants (P = .363). The evaluation of the peri-implant soft tissue response showed that 15 patients (26.7%) had a grade 0 soft tissue reaction, 30 (53.5%) had grade 1, 6 (10.7%) had grade 2, and 5 (8.9%) had grade 3. Conclusions: From this study, it was concluded that craniofacial rehabilitation with extraoral implants is a safe, reliable, and predictable method to restore the patient's normal appearance. (C) 2012 American Association of Oral and Maxillofacial Surgeons J Oral Maxillofac Surg 70:1551-1557, 2012

Endostatin gene therapy stimulates upregulation of ICAM-1 and VCAM-1 in a metastatic renal cell carcinoma model

One of the greatest challenges in urological oncology is renal cell carcinoma (RCC), which is the third leading cause of death in genitourinary cancers. RCCs are highly vascularized and respond positively to antiangiogenic therapy. Endostatin (ES) is a fragment of collagen XVIII that possesses antiangiogenic activity. In this study, we examined the potential of ES-based antiangiogenic therapy to activate tumor-associated endothelial cells in metastatic RCC (mRCC). Balb/c-bearing Renca cells were treated with NIH/3T3-LendSN or, as a control, with NIH/3T3-LXSN cells. The T-cell subsets and lymphocyte populations of tumors, mediastinal lymph nodes and the spleen were assessed by flow cytometry. The expression of intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1) was assessed by real-time PCR, flow cytometry and immunohistochemistry analysis. ES gene therapy led to an increase in the percentage of infiltrating CD4-interferon (IFN)-gamma cells (P<0.05), CD8-IFN-gamma cells (P<0.01) and CD49b-tumor necrosis factor-alpha cells (P<0.01). In addition, ES therapy caused an increase at the mRNA level of ICAM-1 (1.4-fold; P<0.01) and VCAM-1 (1.5-fold) (control vs treated group; P<0.001). Through flow cytometry, we found a significant increase in the CD34/ICAM-1 cells (8.1-fold; P<0.001) and CD34/VCAM-1 cells (1.6-fold; P<0.05). ES gene therapy induced a significant increase in both T CD4 and CD8 cells in the lymph nodes and the spleen, suggesting that ES therapy may facilitate cell survival or clonal expansion. CD49b cells were also present in increased quantities in all of these organs. In this study, we demonstrate an antitumor inflammatory effect of ES in an mRCC model, and this effect is mediated by an increase in ICAM-1 and VCAM-1 expression in tumor-associated endothelial cells.

Positive fluid balance is associated with reduced survival in critically ill patients with cancer

Background There are no studies that describe the impact of the cumulative fluid balance on the outcomes of cancer patients admitted to intensive care units ICUs. The aim of our study was to evaluate the relationship between fluid balance and clinical outcomes in these patients. Method One hundred twenty-two cancer patients were prospectively evaluated for survival during a 30-day period. Univariate (Chi-square, t-test, MannWhitney) and multiple logistic regression analyses were used to identify the admission parameters associated with mortality. Results The mean cumulative fluid balance was significantly higher in non-survivors than in survivors [1675?ml/24?h (4712921) vs. 887?ml/24?h (104557), P?=?0.017]. We used the area under the curve and the intersection of the sensibility and specificity curves to define a cumulative fluid balance value of 1100?ml/24?h. This value was used in the univariate model. In the multivariate model, the following variables were significantly associated with mortality in cancer patients: the Acute Physiology and Chronic Health Evaluation II score at admission [Odds ratio (OR) 1.15; 95% confidence interval (CI) (1.051.26), P?=?0.003], the Lung Injury Score at admission [OR 2.23; 95% CI (1.293.87), P?=?0.004] and a positive fluid balance higher than 1100?ml/24?h at ICU [OR 5.14; 95% CI (1.4518.24), P?=?0.011]. Conclusion A cumulative positive fluid balance higher than 1100?ml/24?h was independently associated with mortality in patients with cancer. These findings highlight the importance of improving the evaluation of these patients' volemic state and indicate that defined goals should be used to guide fluid therapy.

Integrodifference model for blowfly invasion

We propose a stage-structured integrodifference model for blowflies' growth and dispersion taking into account the density dependence of fertility and survival rates and the non-overlap of generations. We assume a discrete-time, stage-structured, model. The spatial dynamics is introduced by means of a redistribution kernel. We treat one and two dimensional cases, the latter on the semi-plane, with a reflexive boundary. We analytically show that the upper bound for the invasion front speed is the same as in the one-dimensional case. Using laboratory data for fertility and survival parameters and dispersal data of a single generation from a capture-recapture experiment in South Africa, we obtain an estimate for the velocity of invasion of blowflies of the species Chrysomya albiceps. This model predicts a speed of invasion which was compared to actual observational data for the invasion of the focal species in the Neotropics. Good agreement was found between model and observations.

The Poisson-exponential regression model under different latent activation schemes

In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activation schemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer.

The log-exponentiated generalized gamma regression model for censored data

For the first time, we introduce a generalized form of the exponentiated generalized gamma distribution [Cordeiro et al. The exponentiated generalized gamma distribution with application to lifetime data, J. Statist. Comput. Simul. 81 (2011), pp. 827-842.] that is the baseline for the log-exponentiated generalized gamma regression model. The new distribution can accommodate increasing, decreasing, bathtub- and unimodal-shaped hazard functions. A second advantage is that it includes classical distributions reported in the lifetime literature as special cases. We obtain explicit expressions for the moments of the baseline distribution of the new regression model. The proposed model can be applied to censored data since it includes as sub-models several widely known regression models. It therefore can be used more effectively in the analysis of survival data. We obtain maximum likelihood estimates for the model parameters by considering censored data. We show that our extended regression model is very useful by means of two applications to real data.

Survival Analysis of Patients with Heart Failure: Implications of Time-Varying Regression Effects in Modeling Mortality

Background: Several models have been designed to predict survival of patients with heart failure. These, while available and widely used for both stratifying and deciding upon different treatment options on the individual level, have several limitations. Specifically, some clinical variables that may influence prognosis may have an influence that change over time. Statistical models that include such characteristic may help in evaluating prognosis. The aim of the present study was to analyze and quantify the impact of modeling heart failure survival allowing for covariates with time-varying effects known to be independent predictors of overall mortality in this clinical setting. Methodology: Survival data from an inception cohort of five hundred patients diagnosed with heart failure functional class III and IV between 2002 and 2004 and followed-up to 2006 were analyzed by using the proportional hazards Cox model and variations of the Cox's model and also of the Aalen's additive model. Principal Findings: One-hundred and eighty eight (188) patients died during follow-up. For patients under study, age, serum sodium, hemoglobin, serum creatinine, and left ventricular ejection fraction were significantly associated with mortality. Evidence of time-varying effect was suggested for the last three. Both high hemoglobin and high LV ejection fraction were associated with a reduced risk of dying with a stronger initial effect. High creatinine, associated with an increased risk of dying, also presented an initial stronger effect. The impact of age and sodium were constant over time. Conclusions: The current study points to the importance of evaluating covariates with time-varying effects in heart failure models. The analysis performed suggests that variations of Cox and Aalen models constitute a valuable tool for identifying these variables. The implementation of covariates with time-varying effects into heart failure prognostication models may reduce bias and increase the specificity of such models.

The negative binomial-beta Weibull regression model to predict the cure of prostate cancer

In this article, for the first time, we propose the negative binomial-beta Weibull (BW) regression model for studying the recurrence of prostate cancer and to predict the cure fraction for patients with clinically localized prostate cancer treated by open radical prostatectomy. The cure model considers that a fraction of the survivors are cured of the disease. The survival function for the population of patients can be modeled by a cure parametric model using the BW distribution. We derive an explicit expansion for the moments of the recurrence time distribution for the uncured individuals. The proposed distribution can be used to model survival data when the hazard rate function is increasing, decreasing, unimodal and bathtub shaped. Another advantage is that the proposed model includes as special sub-models some of the well-known cure rate models discussed in the literature. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. We analyze a real data set for localized prostate cancer patients after open radical prostatectomy.

A log-linear regression model for the beta-Birnbaum-Saunders distribution with censored data

The beta-Birnbaum-Saunders (Cordeiro and Lemonte, 2011) and Birnbaum-Saunders (Birnbaum and Saunders, 1969a) distributions have been used quite effectively to model failure times for materials subject to fatigue and lifetime data. We define the log-beta-Birnbaum-Saunders distribution by the logarithm of the beta-Birnbaum-Saunders distribution. Explicit expressions for its generating function and moments are derived. We propose a new log-beta-Birnbaum-Saunders regression model that can be applied to censored data and be used more effectively in survival analysis. We obtain the maximum likelihood estimates of the model parameters for censored data and investigate influence diagnostics. The new location-scale regression model is modified for the possibility that long-term survivors may be presented in the data. Its usefulness is illustrated by means of two real data sets. (C) 2011 Elsevier B.V. All rights reserved.

Evaluation of the probiotic potential and effect of encapsulation on survival for Lactobacillus plantarum ST16Pa isolated from papaya

Capability to produce antilisterial bacteriocins by lactic acid bacteria (LAB) can be explored by the food industry as a tool to increase the safety of foods. Furthermore, probiotic activity of bacteriogenic LAB brings extra advantages to these strains, as they can confer health benefits to the consumer. Beneficial effects depend on the ability of the probiotic strains to maintain viability in the food during shelf-life and to survive the natural defenses of the host and multiply in the gastrointestinal tract (GIT). This study evaluated the probiotic potential of a bacteriocinogenic Lactobacillus plantarum strain (Lb. plantarum ST16Pa) isolated from papaya fruit and studied the effect of encapsulation in alginate on survival in conditions simulating the human GIT. Good growth of Lb. plantarum ST16Pa was recorded in MRS broth with initial pH values between 5.0 and 9.0 and good capability to survive in pH 4.0, 11.0 and 13.0. Lb. plantarum ST16Pa grew well in the presence of oxbile at concentrations ranging from 0.2 to 3.0%. The level of auto-aggregation was 37%, and various degrees of co-aggregation were observed with different strains of Lb. plantarum, Enterococcus spp., Lb. sakei and Listeria, which are important features for probiotic activity. Growth was affected negatively by several medicaments used for human therapy, mainly anti-inflammatory drugs and antibiotics. Adhesion to Caco-2 cells was within the range reported for other probiotic strains, and PCR analysis indicated that the strain harbored the adhesion genes mapA, mub and EF-Tu. Encapsulation in 2, 3 and 4% alginate protected the cells from exposure to 1 or 2% oxbile added to MRS broth. Studies in a model simulating the transit through the GIT indicated that encapsulated cells were protected from the acidic conditions in the stomach but were less resistant when in conditions simulating the duodenum, jejunum, ileum and first section of the colon. To our knowledge, this is the first report on a bacteriocinogenic LAB isolated from papaya that presents application in food biopreservation and may be beneficial to the consumer health due to its potential probiotic characteristics.

Prognostic factors for survival in patients with colorectal liver metastases: experience of a single brazilian cancer center

CONTEXT: Liver metastases are a common event in the clinical outcome of patients with colorectal cancer and account for 2/3 of deaths from this disease. There is considerable controversy among the data in the literature regarding the results of surgical treatment and prognostic factors of survival, and no analysis have been done in a large cohort of patients in Brazil. OBJECTIVES: To characterize the results of surgical treatment of patients with colorectal liver metastases, and to establish prognostic factors of survival in a Brazilian population. METHOD: This was a retrospective study of patients undergoing liver resection for colorectal metastases in a tertiary cancer hospital from 1998 to 2009. We analyzed epidemiologic variables and the clinical characteristics of primary tumors, metastatic disease and its treatment, surgical procedures and follow-up, and survival results. Survival analyzes were done by the Kaplan-Meier method and the log-rank test was applied to determine the influence of variables on overall and disease-free survival. All variables associated with survival with P<0.20 in univariate analysis, were included in multivariate analysis using a Cox proportional hazard regression model. RESULTS: During the period analyzed, 209 procedures were performed on 170 patients. Postope-rative mortality in 90 days was 2.9% and 5-year overall survival was 64.9%. Its independent prognostic factors were the presence of extrahepatic disease at diagnosis of liver metastases, bilateral nodules and the occurrence of major complications after liver surgery. The estimated 5-year disease-free survival was 39.1% and its prognostic factors included R1 resection, extrahepatic disease, bilateral nodules, lymph node involvement in the primary tumor and primary tumors located in the rectum. CONCLUSION: Liver resection for colorectal metastases is safe and effective and the analysis of prognostic factors of survival in a large cohort of Brazilian patients showed similar results to those pointed in international series. The occurrence of major postoperative complications appears to be able to compromise overall survival and further investigation in needed in this topic.

Modified crop model estimation of depleted and potential soybean yield

Despite the great importance of soybeans in Brazil, there have been few applications of soybean crop modeling on Brazilian conditions. Thus, the objective of this study was to use modified crop models to estimate the depleted and potential soybean crop yield in Brazil. The climatic variable data used in the modified simulation of the soybean crop models were temperature, insolation and rainfall. The data set was taken from 33 counties (28 Sao Paulo state counties, and 5 counties from other states that neighbor São Paulo). Among the models, modifications in the estimation of the leaf area of the soybean crop, which includes corrections for the temperature, shading, senescence, CO2, and biomass partition were proposed; also, the methods of input for the model's simulation of the climatic variables were reconsidered. The depleted yields were estimated through a water balance, from which the depletion coefficient was estimated. It can be concluded that the adaptation soybean growth crop model might be used to predict the results of the depleted and potential yield of soybeans, and it can also be used to indicate better locations and periods of tillage.

A mathematical model for optimizing the indications of liver transplantation in patients with hepatocellular carcinoma

Abstract Background The criteria for organ sharing has developed a system that prioritizes liver transplantation (LT) for patients with hepatocellular carcinoma (HCC) who have the highest risk of wait-list mortality. In some countries this model allows patients only within the Milan Criteria (MC, defined by the presence of a single nodule up to 5 cm, up to three nodules none larger than 3 cm, with no evidence of extrahepatic spread or macrovascular invasion) to be evaluated for liver transplantation. This police implies that some patients with HCC slightly more advanced than those allowed by the current strict selection criteria will be excluded, even though LT for these patients might be associated with acceptable long-term outcomes. Methods We propose a mathematical approach to study the consequences of relaxing the MC for patients with HCC that do not comply with the current rules for inclusion in the transplantation candidate list. We consider overall 5-years survival rates compatible with the ones reported in the literature. We calculate the best strategy that would minimize the total mortality of the affected population, that is, the total number of people in both groups of HCC patients that die after 5 years of the implementation of the strategy, either by post-transplantation death or by death due to the basic HCC. We illustrate the above analysis with a simulation of a theoretical population of 1,500 HCC patients with tumor size exponentially. The parameter λ obtained from the literature was equal to 0.3. As the total number of patients in these real samples was 327 patients, this implied in an average size of 3.3 cm and a 95% confidence interval of [2.9; 3.7]. The total number of available livers to be grafted was assumed to be 500. Results With 1500 patients in the waiting list and 500 grafts available we simulated the total number of deaths in both transplanted and non-transplanted HCC patients after 5 years as a function of the tumor size of transplanted patients. The total number of deaths drops down monotonically with tumor size, reaching a minimum at size equals to 7 cm, increasing from thereafter. With tumor size equals to 10 cm the total mortality is equal to the 5 cm threshold of the Milan criteria. Conclusion We concluded that it is possible to include patients with tumor size up to 10 cm without increasing the total mortality of this population.