Individual risk prediction of nodal and distant metastasis for patients with typical bronchial carcinoid tumors

Objective: Bronchial typical carcinoid tumors are tow-grade malignancies. However, metastases are diagnosed in some patients. Predicting the individual risk of these metastases to determine patients eligible for a radical lymphadenectomy and patients to be followed-up because of distant metastasis risk is relevant. Our objective was to screen for predictive criteria of bronchial typical carcinoid tumor aggressiveness based on a logistic regression model using clinical, pathological and biomolecular data. Methods: A multicenter retrospective cohort study, including 330 consecutive patients operated on for bronchial typical carcinoid tumors and followed-up during a period more than 10 years in two university hospitals was performed. Selected data to predict the individual risk for both nodal and distant metastasis were: age, gender, TNM staging, tumor diameter and location (central/peripheral), tumor immunostaining index of p53 and Ki67, Bcl2 and the extracellular density of neoformed microvessels and of collagen/elastic extracellular fibers. Results: Nodal and distant metastasis incidence was 11% and 5%, respectively. Univariate analysis identified all the studied biomarkers as related to nodal metastasis. Multivariate analysis identified a predictive variable for nodal metastasis: neo angiogenesis, quantified by the neoformed pathological microvessels density. Distant metastasis was related to mate gender. Discussion: Predictive models based on clinical and biomolecular data could be used to predict individual risk for metastasis. Patients under a high individual risk for lymph node metastasis should be considered as candidates to mediastinal lymphadenectomy. Those under a high risk of distant metastasis should be followed-up as having an aggressive disease. Conclusion: Individual risk prediction of bronchial typical carcinoid tumor metastasis for patients operated on can be calculated in function of biomolecular data. Prediction models can detect high-risk patients and help surgeons to identify patients requiring radical lymphadenectomy and help oncologists to identify those as having an aggressive disease requiring prolonged follow-up. (C) 2008 European Association for Cardio-Thoracic Surgery. Published by Elsevier B.V. All rights reserved.

Traditional risk factors for cardiovascular disease in primary antiphospholipid syndrome (APS) when compared with secondary APS: a study with 96 patients

Objective: To evaluate the prevalence of traditional risk factors in patients with primary antiphospholipid syndrome (APS) in comparison to those with systemic lupus erythematosus-secondary APS. Methods: Transversal study of 96 APS patients (Sapporo`s criteria). Demographic and clinical data, cardiovascular risk factors and drug use were investigated. Results: Thirty-nine Primary APS and 57 secondary APS were included. The groups did not differ regarding age (38.5 +/- 9.9 vs. 39.4 +/- 10.5 years, p=0.84) and female gender (84.6 vs. 96.5%, p=0.06), respectively. Arterial events were more observed in primary than secondary APS (59 vs. 36.8%, p=0.04) patients. No difference was seen concerning venous and obstetric events. In regard to traditional risk factors for cardiovascular disease, both groups were comparable related to current or previous smoking, sedentarism, family history for coronary disease, systemic hypertension, diabetes mellitus, overweight and obesity. The frequencies of altered lipid profiles were alike in the two groups, except for a higher prevalence of low HDL-c levels in primary APS group (84.6 vs. 45.5%, p=0.0001). Concerning drug use, no significant differences were observed related to chloroquine and statin use, however the secondary APS patients had a higher rate of prednisone use (10.2 vs. 57.9%, p<0.001) as well as mean dose of corticosteroid (1.5 +/- 5.7 vs. 9.2 +/- 12.5mg/ /day, p=0.0001). Conclusion: Traditional risk factors for cardiovascular disease are present and comparable between patients with primary and secondary APS, except for a high frequency of low HDL-c in primary APS patients.

Comparison of three systems of classification in predicting the outcome of diabetic foot ulcers in a Brazilian population

Objective: The aim was to compare there ulcer classification systems as predictors of the outcome of diabetic foot ulcers; the Wagner, the University of Texas (UT) and the size (area, depth), sepsis, arteriopathy, denervation system (S(AD)SAD) systems in specialist clinic in Brazil. Methods: Ulcer area, depth, appearance, infection and associated ischaemia and neuropathy were recorded in a consecutive series of 94 subjects. A novel score, the S(AD)SAD score, was derived from the sum of individual items of the S(AD)SAD system, and was evaluated. Follow-up was for at least 6 months. The primary outcome measure was the incidence of healing. Results: Mean age was 57.6 years; 57 (60.6%) were made. Forty-eight ulcers (51.1%) healed without surgery; 11 (12.2%) subjects underwent minor amputation. Significant differences in terms of healing were observed for depth (P = 0.002), infection (P = 0.006) and denervation (P = 0.002) using the S(AD)SAD system, for UT grade (P = 0.002) and stage (P = 0.032) and for Wagner grades (P = 0.002). Ulcers with an S(AD)SAD score of <= 9 (total possible 15) were 7.6 times more likely to heal than scores >= 10 (P < 0.001). Conclusions: All three systems predicted ulcer outcome. The S(AD)SAD score of ulcer severity could represent a useful addition to routine clinical practice. The association between outcome and ulcer depth confirms earlier reports. The association with infection was stronger than that reported from the centres in Europe or North America. The very strong association with neuropathy has only previously been observed in Tanzania. Studies designed to compare the outcome in different countries should adopt systems of classification, which are valid for the populations studied.

The Association of Hemoglobin A1c With Incident Heart Failure Among People Without Diabetes: The Atherosclerosis Risk in Communities Study

OBJECTIVE-This study sought to investigate an association of HbA1c (A1C) with incident heart failure among individuals without diabetes and compare it to fasting glucose. RESEARCH DESIGN AND METHODS-We studied 11,057 participants of the Atherosclerosis Risk in Communities (ARIC) Study without heart failure or diabetes at baseline and estimated hazard ratios of incident heart failure by categories of A1C (<5.0, 5.0-5.4 [reference], 5 5-59, and 6.0-6.4%) and fasting glucose (<90, 90-99 [reference], 100-109, and 110-125 mg/dl) using Cox proportional hazards models. RESULTS-A total of 841 cases of incident heart failure hospitalization or deaths (International Classification of Disease, 9th/10th Revision, 428/150) occurred during a median follow-up of 14.1 years (incidence rate 5.7 per 1,000 person-years). After the adjustment for covariates including fasting glucose, the hazard ratio of incident heart failure was higher in individuals with A1C 6.0-6.4% (1.40 [95% CI, 1 09-1.79]) and 5.5-6.0% (1.16 [0.98-1 37]) as compared with the reference group. Similar results were observed when adjusting for insulin level or limiting to heart failure cases without preceding coronary events or developed diabetes during follow-up. In contrast, elevated fasting glucose was not associated with heart failure after adjustment for covariates and A1C. Similar findings were observed when the top quartile (A1C, 5.7-6.4%, and fasting glucose, 108-125 mg/dl) was compared with the lowest quartile (<5 2% and <95 mg/dl, respectively). CONCLUSIONS-Elevated A1C (>= 5.5-6 0%) was associated with incident heart failure in a middle-aged population without diabetes, suggesting that chronic hyperglycemia prior to the development of diabetes contributes to development of heart failure. Diabetes 59:2020-2026, 2010

Consumers' perceived risk: Sources versus consequences

In this study, we examine an important factor that affects consumers' acceptance of business-to-commerce (B2C) electronic commerce - perceived risk. The objective of this paper is to examine the definition of perceived risk in the context of B2C electronic commerce. The paper highlights the importance of perceived risk and the interwoven relation between perceived risk and trust. It discusses the problem of defining perceived risk in prior B2C research. This study proposes a new classification of consumers' perceived risk based on sources. It highlights the importance of identifying the sources of consumer's risk perceptions in addition to the consequences dimensions. Two focus group discussion sessions were conducted to verify the proposed classification. Results indicate that Internet consumers perceive three sources of risk in B2C electronic commerce: technology, vendor, and product. © 2003 Elsevier B.V. All rights reserved.

Risk factors for basal cell carcinoma: a case-control study

A controlled trial was performed with the purpose of investigating which factors could be considered of significant risk for the development of basal cell carcinoma. A total of 259 cases of basal cell carcinoma diagnosed from July 1991 to July 1992 were compared with 518 controls matched for age and sex. All subjects in both groups were white. Protocol data were submitted to statistical analysis by the chi-square test and by multiple conditional logistic regression analysis and the following conclusions were reached: 1) light skin color (types I and II of the Fitzpatrick classification), odds ratio of 2.8; outdoor work under constant sunlight, odds ratio of 5.0; the presence of actinic lesions due to exposure to the sun, odds ratio of 4.9, are risk factors perse. 2) Type III skin in the Fitzpatrick classification only represents a risk factor when the patient reports a history of intense sunburns, but not in the absence of such a history. 3) Sunburns per se do not represent a risk factor althorig the point made in item 2 of these conclusions is valid. 4) Other suspected risk factors whose significance was not confirmed by multiple conditioned logistic regression analysis were: residence in rural areas, light eyes and blond hair color, extent of the awareness of the "sun x skin cancer" relationship, familial occurrence of skin cancer, excessive exposure to the sun, and freckles appearing in childhood.

Comorbidity adjustment index for the international classification of diseases, 10

OBJECTIVE: To develop a Charlson-like comorbidity index based on clinical conditions and weights of the original Charlson comorbidity index. METHODS: Clinical conditions and weights were adapted from the International Classification of Diseases, 10th revision and applied to a single hospital admission diagnosis. The study included 3,733 patients over 18 years of age who were admitted to a public general hospital in the city of Rio de Janeiro, southeast Brazil, between Jan 2001 and Jan 2003. The index distribution was analyzed by gender, type of admission, blood transfusion, intensive care unit admission, age and length of hospital stay. Two logistic regression models were developed to predict in-hospital mortality including: a) the aforementioned variables and the risk-adjustment index (full model); and b) the risk-adjustment index and patient's age (reduced model). RESULTS: Of all patients analyzed, 22.3% had risk scores >1, and their mortality rate was 4.5% (66.0% of them had scores >1). Except for gender and type of admission, all variables were retained in the logistic regression. The models including the developed risk index had an area under the receiver operating characteristic curve of 0.86 (full model), and 0.76 (reduced model). Each unit increase in the risk score was associated with nearly 50% increase in the odds of in-hospital death. CONCLUSIONS: The risk index developed was able to effectively discriminate the odds of in-hospital death which can be useful when limited information is available from hospital databases.

Impact of RIFLE Classification in Liver Transplantation

Acute renal failure (ARF) is common after orthotopic liver transplantation (OLT). The aim of this study was to evaluate the prognostic value of RIFLE classification in the development of CKD, hemodialysis requirement, and mortality. Patients were categorized as risk (R), injury (I) or failure (F) according to renal function at day 1, 7 and 21. Final renal function was classified according to K/DIGO guidelines. We studied 708 OLT recipients, transplanted between September 1992 and March 2007; mean age 44 +/- 12.6 yr, mean follow-up 3.6 yr (28.8% > or = 5 yr). Renal dysfunction before OLT was known in 21.6%. According to the RIFLE classification, ARF occurred in 33.2%: 16.8% were R class, 8.5% I class and 7.9% F class. CKD developed in 45.6%, with stages 4 or 5d in 11.3%. Mortality for R, I and F classes were, respectively, 10.9%, 13.3% and 39.3%. Severity of ARF correlated with development of CKD: stage 3 was associated with all classes of ARF, stages 4 and 5d only with severe ARF. Hemodialysis requirement (23%) and mortality were only correlated with the most severe form of ARF (F class). In conclusion, RIFLE classification is a useful tool to stratify the severity of early ARF providing a prognostic indicator for the risk of CKD occurrence and death.

Diagnosic Classification: Results from a Clinical Experience of Three Years with DC: 0–3

Infancy and early childhood are characterized by a dynamic and ever changing process. Since the beginning of their clinical work at the Infancy Unit, the authors were concerned with individual assessment and the questions about the role played by parents as well as by babies in pathology and intervention.In this article, the authors begin with a description of the path that led them to the selection of DC 0–3 as a diagnostic classification system and how this has been instrumental in helping them to better define infant psychopathology and guide them in treatment orientations. Next, they present the results of the applicationof Axis I and II of DC: 0–3 in their clinical population in the years 1997, 1998, and 1999. The objectives of this study were to learn more about the distribution of mental disorders in a clinical population up tofour years of age. The authors attempted to separate infants at risk for developing psychic disorders from those presenting current psychopathology as well as the possible influence of demographic features on this distribution, to define a target population and design adapted therapeutic measures. The identification of these objectives provides the rationale for the use of a diagnostic tool, like DC: 0–3, which is essential to plan clinical activity, to evaluate therapeutic efficacy, and to develop specific programs.

Intraventricular hemorrhage in very low birth weight infants: associated risk factors and outcome in the neonatal period

Intraventricular hemorrhage (IVH) is a severe complication in very low birth weight (VLBW) newborns (NB). With the purpose of studying the incidence of IVH, the associated risk factors, and the outcomes for these neonates, we studied all the VLBW infants born in our neonatal unit. Birth weight, gestational age, presence of perinatal asphyxia, mechanical ventilation, length of hospitalization, apnea crisis, hydrocephalus, and periventricular leukomalacia were analyzed. The diagnosis of IVH was based on ultrasound scan studies (Papile's classification) performed until the tenth day of life and repeated weekly in the presence of abnormalities. Sixty-seven/101 neonates were studied. The mortality rate was 30.6% (31/101) and the incidence of IVH was 29.8% (20/67) : 70% grade I, 20% grade III and 10% grade IV. The incidence of IVH in NB <1,000 g was 53.8% (p = 0.035) and for gestational age <30 weeks was 47.3% (p = 0.04), both considered risk factors for IVH. The length of hospitalization (p = 0.00015) and mechanical ventilation (p = 0.038) were longer in IHV NB. The IVH NB had a relative risk of 2.3 of developing apnea (p = 0.02), 3.7 of hydrocephalus (p = 0.0007), and 7.7 of periventricular leukomalacia (p < 0.00001). The authors emphasize the importance of knowing the risk factors related to IVH so as to introduce prevention schemes to reduce IVH and to improve outcomes of affected newborns.

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Prospective assessment of different indices of cardiac risk for patients undergoing noncardiac surgeries

OBJECTIVE: To compare the accuracy of 4 different indices of cardiac risk currently used for predicting perioperative cardiac complications. METHODS: We studied 119 patients at a university-affiliated hospital whose cardiac assessment had been required for noncardiac surgery. Predictive factors of high risk for perioperative cardiac complications were assessed through clinical history and physical examination, and the patients were followed up after surgery until the 4th postoperative day to assess the occurrence of cardiac events. All patients were classified according to 4 indices of cardiac risk: the Goldman risk-factor index, Detsky modified risk index, Larsen index, and the American Society of Anesthesiologists' physical status classification and their compared accuracies, examining the areas under their respective receiver operating characteristic (ROC) curves. RESULTS: Cardiac complications occurred in 16% of the patients. The areas under the ROC curves were equal for the Goldman risk-factor index, the Larsen index, and the American Society of Anesthesiologists' physical status classification: 0.48 (SEM ± 0.03). For the Detsky index, the value found was 0.38 (SEM ± 0.03). This difference in the values was not statistically significant. CONCLUSION: The cardiac risk indices currently used did not show a better accuracy than that obtained randomly. None of the indices proved to be significantly better than the others. Studies to improve our ability to predict such complications are still required.

Validation of the Killip-Kimball Classification and Late Mortality after Acute Myocardial Infarction

Background: The classification or index of heart failure severity in patients with acute myocardial infarction (AMI) was proposed by Killip and Kimball aiming at assessing the risk of in-hospital death and the potential benefit of specific management of care provided in Coronary Care Units (CCU) during the decade of 60. Objective: To validate the risk stratification of Killip classification in the long-term mortality and compare the prognostic value in patients with non-ST-segment elevation MI (NSTEMI) relative to patients with ST-segment elevation MI (STEMI), in the era of reperfusion and modern antithrombotic therapies. Methods: We evaluated 1906 patients with documented AMI and admitted to the CCU, from 1995 to 2011, with a mean follow-up of 05 years to assess total mortality. Kaplan-Meier (KM) curves were developed for comparison between survival distributions according to Killip class and NSTEMI versus STEMI. Cox proportional regression models were developed to determine the independent association between Killip class and mortality, with sensitivity analyses based on type of AMI. Results: The proportions of deaths and the KM survival distributions were significantly different across Killip class >1 (p <0.001) and with a similar pattern between patients with NSTEMI and STEMI. Cox models identified the Killip classification as a significant, sustained, consistent predictor and independent of relevant covariables (Wald χ2 16.5 [p = 0.001], NSTEMI) and (Wald χ2 11.9 [p = 0.008], STEMI). Conclusion: The Killip and Kimball classification performs relevant prognostic role in mortality at mean follow-up of 05 years post-AMI, with a similar pattern between NSTEMI and STEMI patients.

The use of classification and regression trees to predict the likelihood of seasonal influenza.

Background Individual signs and symptoms are of limited value for the diagnosis of influenza. Objective To develop a decision tree for the diagnosis of influenza based on a classification and regression tree (CART) analysis. Methods Data from two previous similar cohort studies were assembled into a single dataset. The data were randomly divided into a development set (70%) and a validation set (30%). We used CART analysis to develop three models that maximize the number of patients who do not require diagnostic testing prior to treatment decisions. The validation set was used to evaluate overfitting of the model to the training set. Results Model 1 has seven terminal nodes based on temperature, the onset of symptoms and the presence of chills, cough and myalgia. Model 2 was a simpler tree with only two splits based on temperature and the presence of chills. Model 3 was developed with temperature as a dichotomous variable (≥38°C) and had only two splits based on the presence of fever and myalgia. The area under the receiver operating characteristic curves (AUROCC) for the development and validation sets, respectively, were 0.82 and 0.80 for Model 1, 0.75 and 0.76 for Model 2 and 0.76 and 0.77 for Model 3. Model 2 classified 67% of patients in the validation group into a high- or low-risk group compared with only 38% for Model 1 and 54% for Model 3. Conclusions A simple decision tree (Model 2) classified two-thirds of patients as low or high risk and had an AUROCC of 0.76. After further validation in an independent population, this CART model could support clinical decision making regarding influenza, with low-risk patients requiring no further evaluation for influenza and high-risk patients being candidates for empiric symptomatic or drug therapy.