BackgroundThe distribution of the microbial aetiology and mortality of community-acquired pneumonia (CAP) was investigated in relation to the clinical setting and severity scores (pneumonia severity index (PSI) and confusion, blood urea nitrogen, respiratory rate, blood pressure, age (CURB-65)). Methods 3523 patients with CAP were included (15% outpatients, 85% inpatients). The distribution of the microbial aetiology in relation to the clinical setting and severity scores (PSI, CURB-65) and the relative mortality of different aetiologies across the severity scores were analysed. Results The aetiology was established in 1463 patients (42%), of whom 257 died (7%). The ranking of aetiologies varied according to site of care, with increasing frequency of Streptococcus pneumoniae and mixed aetiologies and decreasing frequency of atypical pathogens in hospitalised patients and those in ICUs. The distribution of aetiologies according to severity scores showed corresponding patterns; however, the severity scores were more sensitive to Gram-negative enteric bacilli (GNEB) and Pseudomonas aeruginosa and less sensitive in identifying mixed aetiologies as moderateand high-risk conditions. Mortality rates according to aetiology and severity scoring showed increasing mortality rates for all pathogens except atypical pathogens. S pneumoniae had the highest number of deaths while GNEB, P aeruginosa, Staphylococcus aureus and mixed aetiologies had the highest mortality rates. Legionella pneumophila was similarly distributed according to site of care and prognostic scores. Conclusions CAP due to atypical bacterial pathogens is recognised both clinically and by severity scoring as a low-risk condition. Severity scores are more sensitive in identifying patients with GNEB and P aeruginosa as moderate-and high-risk aetiologies whereas mixed aetiologies may be underestimated.

Background: Prognostic scales provide a useful tool to predict mortality in community-acquired pneumonia (CAP). However, the inflammatory response of the host, crucial in resolution and outcome, is not included in the prognostic scales. Methods: The aim of this study was to investigate whether information about the initial inflammatory cytokine profile and markers increases the accuracy of prognostic scales to predict 30-day mortality. To this aim, a prospective cohort study in two tertiary care hospitals was designed. Procalcitonin (PCT), C-reactive protein (CRP) and the systemic cytokines tumour necrosis factor a (TNFa) and interleukins IL6, IL8 and IL10 were measured at admission. Initial severity was assessed by PSI (Pneumonia Severity Index), CURB65 (Confusion, Urea nitrogen, Respiratory rate, Blood pressure, >65 years of age) and CRB65 (Confusion, Respiratory rate, Blood pressure, >65 years of age) scales. A total of 453 hospitalised CAP patients were included. Results: The 36 patients who died (7.8%) had significantly increased levels of IL6, IL8, PCT and CRP. In regression logistic analyses, high levels of CRP and IL6 showed an independent predictive value for predicting 30-day mortality, after adjustment for prognostic scales. Adding CRP to PSI significantly increased the area under the receiver operating characteristic curve (AUC) from 0.80 to 0.85, that of CURB65 from 0.82 to 0.85 and that of CRB65 from 0.79 to 0.85. Adding IL6 or PCT values to CRP did not significantly increase the AUC of any scale. When using two scales (PSI and CURB65/CRB65) and CRP simultaneously the AUC was 0.88. Conclusions: Adding CRP levels to PSI, CURB65 and CRB65 scales improves the 30-day mortality prediction. The highest predictive value is reached with a combination of two scales and CRP. Further validation of that improvement is needed.

The relevance of the ACOS is to identify patients with COPD who may have underlying eosinophilic inflammation that responds to inhaled corticosteroids. So far, the previous diagnosis of asthma in a patient with COPD is the more reliable criterion for ACOS. Ongoing studies will clarify if concentrations of blood eosinophils may be useful to identify this subgroup of patients with COPD. If this is the case, the interest of ACOS may shift to that of eosinophilic COPD, which is easier to diagnose and has clear therapeutic implications.

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The metabolic syndrome shows a variable prevalence in obstructive sleep apnoea (OSA), and its association with insulin resistance or excessive daytime sleepiness in OSA is unclear. This study assessed the following in consecutive patients with newly diagnosed OSA: 1) the prevalence of metabolic syndrome; and 2) its association with insulin resistance and daytime sleepiness.Metabolic syndrome (National Cholesterol Education Program Adult Treatment Panel (NCEP-ATP) III criteria), insulin resistance (Homeostatic Model Assessment (HOMA) index, n5288) and daytime sleepiness (Epworth Sleepiness Scale) were assessed in 529 OSA patients.The prevalence of metabolic syndrome was 51.2%, which increased with OSA severity. Each metabolic syndrome component correlated with apnoea/hypopnoea index, but only blood pressure retained significance after correction for confounders. Both obesity and OSA contributed to metabolic abnormalities, with different sex-related patterns, since diagnosis of metabolic syndrome was significantly associated with neck circumference, age, body mass index and lowest arterial oxygen saturation in males, and with age and arousal index in females. The number of metabolic syndrome components increased with HOMA index (p,0.001). Prevalence of sleepiness was the same in patients with and without metabolic syndrome.The metabolic syndrome occurs in about half of ''real-life'' OSA patients, irrespective of daytime sleepiness, and is a reliable marker of insulin resistance.

In alpha-1 antitrypsin deficiency (AATD), the Z allele is present in 98% of cases with severe disease, and knowledge of the frequency of this allele is essential from a public health perspective. However, there is a remarkable lack of epidemiological data on AATD worldwide, and many of the data currently used are outdated. Therefore, the objective of this study was to update the knowledge of the frequency of the Z allele to achieve accurate estimates of the prevalence and number of Pi*ZZ genotypes worldwide based on studies performed according to the following criteria: 1) samples representative of the general population, 2) AAT phenotyping characterized by adequate methods, and 3) measurements performed using a coefficient of variation calculated from the sample size and 95% confidence intervals. Studies fulfilling these criteria were used to develop maps with an inverse distance weighted (IDW)-interpolation method, providing numerical and graphical information of Pi*Z distribution worldwide. A total of 224 cohorts from 65 countries were included in the study. With the data provided by these cohorts, a total of 253,404 Pi*ZZ were estimated worldwide: 119,594 in Europe, 91,490 in America and Caribbean, 3,824 in Africa, 32,154 in Asia, 4,126 in Australia, and 2,216 in New Zealand. In addition, the IDW-interpolation maps predicted Pi*Z frequencies throughout the world even in some areas that lack real data. In conclusion, the inclusion of new well-designed studies and the exclusion of the low-quality ones have significantly improved the reliability of results, which may be useful to plan strategies for future research and diagnosis and to rationalize the therapeutic resources available.

Initial treatment patterns in newly diagnosed COPD patients often do no comply with guidelines. The use of ICS is excessive but has decreased mainly in non exacerbator patients. Many COPD patients still remain untreated after diagnosis, although this has decreased. Some GOLD 4 patients are still receiving SABD or no treatment at all after diagnosis.

Background: Biological markers as an expression of systemic inflammation have been recognised as useful for evaluating the host response in community-acquired pneumonia (CAP). The objective of this study was to evaluate whether the biological markers procalcitonin (PCT) and C-reactive protein (CRP) might reflect stability after 72 h of treatment and the absence of subsequent severe complications. Methods: A prospective cohort study was performed in 394 hospitalised patients with CAP. Clinical stability was evaluated using modified Halm's criteria: temperature (37.2uC; heart rate (100 beats/min; respiratory rate (24 breaths/min; systolic blood pressure >90 mm Hg; oxygen saturation >90%; or arterial oxygen tension >60 mm Hg. PCT and CRP levels were measured on day 1 and after 72 h. Severe complications were defined as mechanical ventilation, shock and/or intensive care unit (ICU) admission, or death after 72 h of treatment. Results: 220 patients achieved clinical stability at 72 h and had significantly lower levels of CRP (4.2 vs 7 mg/dl) and of PCT (0.33 vs 0.48 ng/ml). Regression logistic analyses were performed to calculate several areas under the ROC curve (AUC) to predict severe complications. The AUC for clinical stability was 0.77, 0.84 when CRP was added (p = 0.059) and 0.77 when PCT was added (p = 0.45). When clinical stability was achieved within 72 h and marker levels were below the cut-off points (0.25 ng/ml for PCT and 3 mg/dl for CRP), no severe complications occurred. Conclusions: Low levels of CRP and PCT at 72 h in addition to clinical criteria might improve the prediction of absence of severe complications.Prognostic scales provide key information on predicting mortality, but this information is insufficient for assessing the response to antibiotic treatment and clinical stability.