Social factors related to the clinical severity of influenza cases in Spain during the A(H1N1)2009 virus pandemic

Background During the 2009 influenza pandemic, a change in the type of patients most often affected by influenza was observed. The objective of this study was to assess the role of individual and social determinants in hospitalizations due to influenza A (H1N1) 2009 infection. Methods We studied hospitalized patients (cases) and outpatients (controls) with confirmed influenza A (H1N1) 2009 infection. A standardized questionnaire was used to collect data. Variables that might be related to the hospitalization of influenza cases were compared by estimation of the odds ratio (OR) and 95% confidence intervals (CI) and the variables entered into binomial logistic regression models. Results Hospitalization due to pandemic A (H1N1) 2009 influenza virus infections was associated with non-Caucasian ethnicity (OR: 2.18, 95% CI 1.17 − 4.08), overcrowding (OR: 2.84, 95% CI 1.20 − 6.72), comorbidity and the lack of previous preventive information (OR: 2.69, 95% CI: 1.50 − 4.83). Secondary or higher education was associated with a lower risk of hospitalization (OR 0.56, 95% CI: 0.36 − 0.87) Conclusions In addition to individual factors such as comorbidity, other factors such as educational level, ethnicity or overcrowding were associated with hospitalization due to A (H1N1) 2009 influenza virus infections.

Defining risk thresholds for a 10-year probability of hip fracture model that combines clinical risk factors and quantitative ultrasound: results using the EPISEM cohort.

Using a large prospective cohort of over 12,000 women, we determined 2 thresholds (high risk and low risk of hip fracture) to use in a 10-yr hip fracture probability model that we had previously described, a model combining the heel stiffness index measured by quantitative ultrasound (QUS) and a set of easily determined clinical risk factors (CRFs). The model identified a higher percentage of women with fractures as high risk than a previously reported risk score that combined QUS and CRF. In addition, it categorized women in a way that was quite consistent with the categorization that occurred using dual X-ray absorptiometry (DXA) and the World Health Organization (WHO) classification system; the 2 methods identified similar percentages of women with and without fractures in each of their 3 categories, but the 2 identified only in part the same women. Nevertheless, combining our composite probability model with DXA in a case findings strategy will likely further improve the detection of women at high risk of fragility hip fracture. We conclude that the currently proposed model may be of some use as an alternative to the WHO classification criteria for osteoporosis, at least when access to DXA is limited.

Assessment of the 10-year probability of osteoporotic hip fracture combining clinical risk factors and heel bone ultrasound: the EPISEM prospective cohort of 12,958 elderly women.

This study aimed to develop a hip screening tool that combines relevant clinical risk factors (CRFs) and quantitative ultrasound (QUS) at the heel to determine the 10-yr probability of hip fractures in elderly women. The EPISEM database, comprised of approximately 13,000 women 70 yr of age, was derived from two population-based white European cohorts in France and Switzerland. All women had baseline data on CRFs and a baseline measurement of the stiffness index (SI) derived from QUS at the heel. Women were followed prospectively to identify incident fractures. Multivariate analysis was performed to determine the CRFs that contributed significantly to hip fracture risk, and these were used to generate a CRF score. Gradients of risk (GR; RR/SD change) and areas under receiver operating characteristic curves (AUC) were calculated for the CRF score, SI, and a score combining both. The 10-yr probability of hip fracture was computed for the combined model. Three hundred seven hip fractures were observed over a mean follow-up of 3.2 yr. In addition to SI, significant CRFs for hip fracture were body mass index (BMI), history of fracture, an impaired chair test, history of a recent fall, current cigarette smoking, and diabetes mellitus. The average GR for hip fracture was 2.10 per SD with the combined SI + CRF score compared with a GR of 1.77 with SI alone and of 1.52 with the CRF score alone. Thus, the use of CRFs enhanced the predictive value of SI alone. For example, in a woman 80 yr of age, the presence of two to four CRFs increased the probability of hip fracture from 16.9% to 26.6% and from 52.6% to 70.5% for SI Z-scores of +2 and -3, respectively. The combined use of CRFs and QUS SI is a promising tool to assess hip fracture probability in elderly women, especially when access to DXA is limited.

Sociodemographic Factors and Clinical Conditions Associated to Hospitalization in Influenza A (H1N1) 2009 Virus Infected Patients in Spain, 2009-2010

The emergence and pandemic spread of a new strain of influenza A (H1N1) virus in 2009 resulted in a serious alarm in clinical and public health services all over the world. One distinguishing feature of this new influenza pandemic was the different profile of hospitalized patients compared to those from traditional seasonal influenza infections. Our goal was to analyze sociodemographic and clinical factors associated to hospitalization following infection by influenza A(H1N1) virus. We report the results of a Spanish nationwide study with laboratory confirmed infection by the new pandemic virus in a case-control design based on hospitalized patients. The main risk factors for hospitalization of influenza A (H1N1) 2009 were determined to be obesity (BMI≥40, with an odds-ratio [OR] 14.27), hematological neoplasia (OR 10.71), chronic heart disease, COPD (OR 5.16) and neurological disease, among the clinical conditions, whereas low education level and some ethnic backgrounds (Gypsies and Amerinds) were the sociodemographic variables found associated to hospitalization. The presence of any clinical condition of moderate risk almost triples the risk of hospitalization (OR 2.88) and high risk conditions raise this value markedly (OR 6.43). The risk of hospitalization increased proportionally when for two (OR 2.08) or for three or more (OR 4.86) risk factors were simultaneously present in the same patient. These findings should be considered when a new influenza virus appears in the human population.

Social factors related to the clinical severity of influenza cases in Spain during the A(H1N1)2009 virus pandemic

Background During the 2009 influenza pandemic, a change in the type of patients most often affected by influenza was observed. The objective of this study was to assess the role of individual and social determinants in hospitalizations due to influenza A (H1N1) 2009 infection. Methods We studied hospitalized patients (cases) and outpatients (controls) with confirmed influenza A (H1N1) 2009 infection. A standardized questionnaire was used to collect data. Variables that might be related to the hospitalization of influenza cases were compared by estimation of the odds ratio (OR) and 95% confidence intervals (CI) and the variables entered into binomial logistic regression models. Results Hospitalization due to pandemic A (H1N1) 2009 influenza virus infections was associated with non-Caucasian ethnicity (OR: 2.18, 95% CI 1.17 − 4.08), overcrowding (OR: 2.84, 95% CI 1.20 − 6.72), comorbidity and the lack of previous preventive information (OR: 2.69, 95% CI: 1.50 − 4.83). Secondary or higher education was associated with a lower risk of hospitalization (OR 0.56, 95% CI: 0.36 − 0.87) Conclusions In addition to individual factors such as comorbidity, other factors such as educational level, ethnicity or overcrowding were associated with hospitalization due to A (H1N1) 2009 influenza virus infections.

Sociodemographic Factors and Clinical Conditions Associated to Hospitalization in Influenza A (H1N1) 2009 Virus Infected Patients in Spain, 2009-2010

The emergence and pandemic spread of a new strain of influenza A (H1N1) virus in 2009 resulted in a serious alarm in clinical and public health services all over the world. One distinguishing feature of this new influenza pandemic was the different profile of hospitalized patients compared to those from traditional seasonal influenza infections. Our goal was to analyze sociodemographic and clinical factors associated to hospitalization following infection by influenza A(H1N1) virus. We report the results of a Spanish nationwide study with laboratory confirmed infection by the new pandemic virus in a case-control design based on hospitalized patients. The main risk factors for hospitalization of influenza A (H1N1) 2009 were determined to be obesity (BMI≥40, with an odds-ratio [OR] 14.27), hematological neoplasia (OR 10.71), chronic heart disease, COPD (OR 5.16) and neurological disease, among the clinical conditions, whereas low education level and some ethnic backgrounds (Gypsies and Amerinds) were the sociodemographic variables found associated to hospitalization. The presence of any clinical condition of moderate risk almost triples the risk of hospitalization (OR 2.88) and high risk conditions raise this value markedly (OR 6.43). The risk of hospitalization increased proportionally when for two (OR 2.08) or for three or more (OR 4.86) risk factors were simultaneously present in the same patient. These findings should be considered when a new influenza virus appears in the human population

Percutaneous Coronary Intervention in Patients with Atrial Fibrillation: A Study of Factors Affecting Outcome, with a Special Emphasis on Periprocedural Antithrombotic Treatment

Antithrombotic treatment of patients with atrial fibrillation (AF) undergoing percutaneous coronary intervention (PCI) is a delicate balancing between the risk of thromboembolism and the risk of bleeding. The purpose of this dissertation was to analyze current antithrombotic treatment strategies at the periprocedural stage and report outcomes in-hospital and at 1-month follow-up, and to evaluate the effect of renal impairment and predictive values of various bleeding scores on 1-year outcome after PCI in patients with AF. The first article was based on retrospective data from 7 Finnish hospitals between 2002–2006 (n=377), while the others were based on a prospective 17-center European register (AFCAS) gathered between 2008–2010 (n=963). The main findings in patients with AF undergoing PCI were: The use of glycoprotein IIb/IIIa inhibitors during PCI was associated with a four- to five-fold increase in the risk of major bleeding (I). Uninterrupted warfarin treatment did not increase perioperative complications and seemed to decrease bleeding complications compared to heparin bridging (II). Already mild renal impairment (eGFR 60–90mL/min) was associated with a 2.3-fold risk of all-cause mortality during the 12 months following PCI (III). Major adverse cardiac events occurred in 4.5% and bleeding complications in 7.1% of patients in the AFCAS register by 1-month follow-up (IV). In a study of patients in AFCAS register, all currently used bleeding risk scores were poor predictors of bleeding complications by 1-year follow-up (V). The findings will help improve treatment strategies for this fragile patient population with a high risk of bleeding and thrombotic complications.

Risk factors associated with the death of patients hospitalized for juvenile systemic lupus erythematosus

We assessed the risk factors associated with death in patients hospitalized for juvenile systemic lupus erythematosus (JSLE) and evaluated the autopsy reports. A total of 57,159 hospitalizations occurred in our institution from 1994 to 2003, 169 of them involving 71 patients with JSLE. The most recent hospitalization of these patients was evaluated. Patients were divided into two groups based on mortality during hospitalization: those who survived (N = 53) and those who died (N = 18). The main causes of hospitalization were JSLE activity associated with infection in 52% and isolated JSLE activity in 44%. Univariate analysis showed that a greater risk of death was due to severe sepsis (OR = 17.8, CI = 4.5-70.9), systemic lupus erythematosus disease activity index (SLEDAI) ³8 (OR = 7.6, CI = 1.1-53.8), general infections (OR = 6.1, CI = 1.5-25), fungal infections (OR = 5.4, CI = 3.2-9), acute renal failure (OR = 5.1, CI = 2.5-10.4), acute thrombocytopenia (OR = 3.9, CI = 1.9-8.4), and bacterial infections (OR = 2.3, CI = 1.2-7.5). Stratified analysis showed that severe sepsis and SLEDAI ³8 were not confounder variables. In the multivariate analysis, logistic regression showed that the only independent variable in death prediction was severe sepsis (OR = 98, CI = 16.3-586.2). Discordance between clinical diagnosis and autopsy was observed in 6/10 cases. Mortality of hospitalized JSLE patients was associated with severe sepsis. Autopsy was important to determine events not detected or doubtful in dead patients and should always be requested.

Percent body fat is a better predictor of cardiovascular risk factors than body mass index

The objective of the present study was to evaluate the predictive values of percent body fat (PBF) and body mass index (BMI) for cardiovascular risk factors, especially when PBF and BMI are conflicting. BMI was calculated by the standard formula and PBF was determined by bioelectrical impedance analysis. A total of 3859 ambulatory adult Han Chinese subjects (2173 males and 1686 females, age range: 18-85 years) without a history of cardiovascular diseases were recruited from February to September 2009. Based on BMI and PBF, they were classified into group 1 (normal BMI and PBF, N = 1961), group 2 (normal BMI, but abnormal PBF, N = 381), group 3 (abnormal BMI, but normal PBF, N = 681), and group 4 (abnormal BMI and PBF, N = 836). When age, gender, lifestyle, and family history of obesity were adjusted, PBF, but not BMI, was correlated with blood glucose and lipid levels. The odds ratio (OR) and 95% confidence interval (CI) for cardiovascular risk factors in groups 2 and 4 were 1.88 (1.45-2.45) and 2.06 (1.26-3.35) times those in group 1, respectively, but remained unchanged in group 3 (OR = 1.32, 95%CI = 0.92-1.89). Logistic regression models also demonstrated that PBF, rather than BMI, was independently associated with cardiovascular risk factors. In conclusion, PBF, and not BMI, is independently associated with cardiovascular risk factors, indicating that PBF is a better predictor.

Establishing the risk of neonatal mortality using a fuzzy predictive model

O objetivo do artigo foi avaliar o uso da lógica fuzzy para estimar possibilidade de óbito neonatal. Desenvolveu-se um modelo computacional com base na teoria dos conjuntos fuzzy, tendo como variáveis peso ao nascer, idade gestacional, escore de Apgar e relato de natimorto. Empregou-se o método de inferência de Mamdani, e a variável de saída foi o risco de morte neonatal. Criaram-se 24 regras de acordo com as variáveis de entrada, e a validação do modelo utilizou um banco de dados real de uma cidade brasileira. A acurácia foi estimada pela curva ROC; os riscos foram comparados pelo teste t de Student. O programa MATLAB 6.5 foi usado para construir o modelo. Os riscos médios foram menores para os que sobreviveram (p < 0,001). A acurácia do modelo foi 0,90. A maior acurácia foi com possibilidade de risco igual ou menor que 25% (sensibilidade = 0,70, especificidade = 0,98, valor preditivo negativo = 0,99 e valor preditivo positivo = 0,22). O modelo mostrou acurácia e valor preditivo negativo bons, podendo ser utilizado em hospitais gerais.

Protein-energy malnutrition as a consequence of the hospitalization of gastroenterologic patients

The effects of the clinical and dietetics in patient managements on the protein-energy status of hospitalized patients were retrospectively (four yr) investigated in 243 adult (49 +/- 16 yr), male (168) and female (75) patients suffering from chronic liver diseases (42%), intestinal diseases with diarrhea (14%), digestive cancers (11%), chronic pancreatitis (10%), stomach and duodenum diseases (7%), acute pancreatitis (7%), primary protein-energy malnutrition (3%), esophagus diseases (3%), intestinal diseases with constipation 14 (2%) and chronic alcoholism (2%). The protein-energy nutritional status assessed by combinations of anthropometric and blood parameters showed 75% of protein energy malnutrition at the hospital entry mostly (4/5) in severe and moderate grades. The overall average of hospitalization was 20 +/- 15 days being the shortest (13 +/- 5,7 days) for esophagus diseases and the longest (28 +/- 21 days) for the intestinal diseases with diarrhea patients which also received mostly (42%) of the enteral and/or parenteral feedings followed by acute pacreatitis (41%) and digestive cancers (31%) patients. When compared to the entry the protein-energy malnutrition rate at the discharge decreased only 5% despite the increasing of 30% found on the protein-energy intake. The main improvement of the protein-energy nutritional status were attained to those patients showing protein-energy malnutrition milder degrees at the entry which belonged mostly to primary protein-energy malnutrition, acute pancreatitis and intestinal diseases with diarrhea diseases. The later two groups showed protein-energy nutritional status improvement only after the second week of hospitalization. The digestive cancers patients had their protein-energy nutritional status worsened throughout the hospitalization whereas it happened only in the first week for the intestinal diseases with diarrhea and chronic liver diseases patients, improving thereafter up to the discharge. The protein-energy nutritional status improvement found in few patients could be attributed to some complementary factors such as theirs mild degree of protein-energy malnutrition at entry and/or non-invasive propedeutics and/or enteral-parenteral feddings and/or longer hospitalization staying. The institutional causes for the unexpected lack of nutritional responses by the patients were probably the high demand for the few available beds which favour the hospitalization of the most severed patients and the university-teaching pressure for the high rotation of the available beds. Both often resulting in early discharging. In persisting the current physical area and attendance demand one could suggest an aggressive support early at the entry preceding and/or accompanying the more invasive propedeutical procedures.

Stigma and higher rates of psychiatric re-hospitalization: Sao Paulo public mental health system

Objective: The aim of this study was to assess re-hospitalization rates of individuals with psychosis and bipolar disorder and to study determinants of readmission. Methods: Prospective observational study, conducted in Sao Paulo, Brazil. One hundred-sixty-nine individuals with bipolar and psychotic disorder in need of hospitalization in the public mental health system were followed for 12 months after discharge. Their families were contacted by telephone and interviews were conducted at 1, 2, 6 and 12 months post-discharge to evaluate readmission rates and factors related. Results: One-year re-hospitalization rate was of 42.6%. Physical restraint during hospital stay was a risk factor (OR = 5.4-10.5) for readmission in most models. Not attending consultations after discharge was related to the 12-month point readmission (OR = 8.5, 95% CI 2.3-31.2) and to the survival model (OR = 3.2, 95% CI 1.5-7.2). Number of previous admissions was a risk factor for the survival model (OR = 6.6-11.9). Family's agreement with permanent hospitalization of individuals with mental illness was the predictor associated to readmission in all models (OR = 3.5-10.9) and resulted in shorter survival time to readmission; those readmitted were stereotyped as dangerous and unhealthy. Conclusions: Family's stigma towards mental illness might contribute to the increase in readmission rates of their relatives with psychiatric disorders. More studies should be conducted to depict mechanisms by which stigma increases re-hospitalization rates.

Stigma and higher rates of psychiatric re-hospitalization: São Paulo public mental health system

OBJECTIVE: The aim of this study was to assess re-hospitalization rates of individuals with psychosis and bipolar disorder and to study determinants of readmission. METHODS: Prospective observational study, conducted in São Paulo, Brazil. One hundred-sixty-nine individuals with bipolar and psychotic disorder in need of hospitalization in the public mental health system were followed for 12 months after discharge. Their families were contacted by telephone and interviews were conducted at 1, 2, 6 and 12 months post-discharge to evaluate readmission rates and factors related. RESULTSOne-year re-hospitalization rate was of 42.6%. Physical restraint during hospital stay was a risk factor (OR = 5.4-10.5) for readmission in most models. Not attending consultations after discharge was related to the 12-month point readmission (OR = 8.5, 95%CI 2.3-31.2) and to the survival model (OR = 3.2, 95%CI 1.5-7.2). Number of previous admissions was a risk factor for the survival model (OR = 6.6-11.9). Family's agreement with permanent hospitalization of individuals with mental illness was the predictor associated to readmission in all models (OR = 3.5-10.9) and resulted in shorter survival time to readmission; those readmitted were stereotyped as dangerous and unhealthy. CONCLUSIONS: Family's stigma towards mental illness might contribute to the increase in readmission rates of their relatives with psychiatric disorders. More studies should be conducted to depict mechanisms by which stigma increases re-hospitalization rates.

Identification of prognostic factors for chronicity in patients with low back pain: a review of screening instruments

Low back pain (LBP) is currently the most prevalent and costly musculoskeletal problem in modern societies. Screening instruments for the identification of prognostic factors in LBP may help to identify patients with an unfavourable outcome. In this systematic review screening instruments published between 1970 and 2007 were identified by a literature search. Nine different instruments were analysed and their different items grouped into ten structures. Finally, the predictive effectiveness of these structures was examined for the dependent variables including "work status", "functional limitation", and "pain". The strongest predictors for "work status" were psychosocial and occupational structures, whereas for "functional limitation" and "pain" psychological structures were dominating. Psychological and occupational factors show a high reliability for the prognosis of patients with LBP. Screening instruments for the identification of prognostic factors in patients with LBP should include these factors as a minimum core set.

The additional facet of immunoscore: immunoprofiling as a possible predictive tool for cancer treatment

Recent investigations of the tumor microenvironment have shown that many tumors are infiltrated by inflammatory and lymphocytic cells. Increasing evidence suggests that the number, type and location of these tumor-infiltrating lymphocytes in primary tumors has prognostic value, and this has led to the development of an 'immunoscore. As well as providing useful prognostic information, the immunoscore concept also has the potential to help predict response to treatment, thereby improving decision- making with regard to choice of therapy. This predictive aspect of the tumor microenvironment forms the basis for the concept of immunoprofiling, which can be described as 'using an individual's immune system signature (or profile) to predict that patient's response to therapy' The immunoprofile of an individual can be genetically determined or tumor-induced (and therefore dynamic). Ipilimumab is the first in a series of immunomodulating antibodies and has been shown to be associated with improved overall survival in patients with advanced melanoma. Other immunotherapies in development include anti-programmed death 1 protein (nivolumab), anti-PD-ligand 1, anti-CD137 (urelumab), and anti-OX40. Biomarkers that can be used as predictive factors for these treatments have not yet been clinically validated. However, there is already evidence that the tumor microenvironment can have a predictive role, with clinical activity of ipilimumab related to high baseline expression of the immune-related genes FoxP3 and indoleamine 2,3-dioxygenase and an increase in tumor-infiltrating lymphocytes. These biomarkers could represent the first potential proposal for an immunoprofiling panel in patients for whom anti-CTLA-4 therapy is being considered, although prospective data are required. In conclusion, the evaluation of systemic and local immunological biomarkers could offer useful prognostic information and facilitate clinical decision making. The challenge will be to identify the individual immunoprofile of each patient and the consequent choice of optimal therapy or combination of therapies to be used.