Gram-negative bloodstream infections

Over the last 22 years we have prospectively recorded data for bloodstream infections (BSIs) in our institution. We reflect the experience of a tertiary teaching hospital with 1750-2500 beds that served a population ranging during the study period from 650,000 to 750,000 inhabitants. Definitions and microbiological methods were standard. The microbiological workload of blood cultures was analysed and the evolution of the incidence of BSI episodes, provided as episodes per 1000 admissions and per 100000 inhabitants, is reported. During the study period, our institution had over one million admissions; blood culturing increased from 299 blood cultures/1000 admissions in the year 1985 to 720/1000 admissions in 2006. Overall, there were 65475 blood cultures with recovery of significant microorganisms, representing 27 419 episodes of significant BSI (22626 patients). The present paper describes the Gram-negative organisms recovered from the blood cultures and discusses their clinical significance.     

Candida tropicalis fungaemia: incidence,risk factors and mortality in a general hospital

The risk factors and clinical features of patients with Candida tropicalis fungaemia have not been fully defined. We performed a case–control study comparing 59 cases of C. tropicalis fungaemia with 177 episodes of fungaemia caused by other species of Candida in our hospital over a 24-year period (January 1985 to December 2008). Patients with C. tropicalis fungaemia were more likely to be older (median age, 67 vs. 56 years; p 0.01), to have cancer (45.5% vs. 31.6%, p 0.04), and to have the abdomen as the portal of entry (32.2% vs. 11.9%, p 0.001), and had a higher in-hospital mortality rate (61% vs. 44%, p 0.03). Multivariate analysis showed that the independent risk factors for C. tropicalis fungaemia were cancer (OR 4.5; 95% CI 1.05–3.83; p 0.03) and the abdomen as the portal of entry (OR 13.6; 95% CI 1.9–8.2; p <0.001). When survivors were compared with non-survivors, the risk factors associated with a poor outcome were neutropenia (19.4% vs. 0; p 0.03), corticosteroid treatment (36% vs. 13%; p 0.07), and septic shock (50% vs. 17.4%; p 0.01). The independent risk factors for mortality in the multivariate analysis were corticosteroid treatment (OR 8.2; 95% CI 0.9–27.7; p 0.04) and septic shock (OR 14.6; 95% CI 2.4–90.2; p 0.004), whereas urinary tract infection (OR 0.07; 95% CI 0.01–0.8; p 0.03) and catheter removal (OR 0.06; 95% CI 0.01–0.4; p 0.002) were protective factors. C. tropicalis is the fourth most common cause of fungaemia in our hospital. It is associated with underlying malignancy, the abdomen as the portal of entry, and poor outcome.     

Comparison of real-time RT-PCR, shell vial culture, and conventional cell culture for the detection of the pandemic influenza A (H1N1) in hospitalized patients

The emergence of the pandemic influenza virus A H1N1 has made fast and accurate diagnosis essential. However, few well-validated diagnostic techniques exist. The real-time RT-PCR developed by the Centers for Disease Control and Prevention (CDC) is the recommended technique. Our objective was to compare the CDC real-time RT-PCR assay, shell vial (SV), and conventional cell culture [with Madine-Darby canine kidney (MDCK) cells and A549] for the detection of pandemic influenza A H1N1 in hospitalized patients. We performed a prospective study comparing the efficacy of 5 diagnostic techniques (RTPCR, SV in A549, SV in MDCK, conventional cell culture in A549, and conventional cell culture in MDCK) using nasopharyngeal swabs from patients ≥18 years of age hospitalized with clinical symptoms of influenza at our institution. Detection of the virus by conventional culture was considered the gold standard. An "extended gold standard" was also used to recalculate validity values. The sensitivities, specificities, positive predictive values, and negative predictive values (NPVs) for the detection of influenza A H1N1, determined using conventional culture as the gold standard, were, respectively, as follows: RT-PCR: 95.6, 82.3, 78.3, 96.5%; SVA549: 91.2, 99.01, 98.4, 94.4%; SV-MDCK: 82.3, 100, 100, 89.4%; tube-A549: 94.12, 100, 100, 96.2%; tube-MDCK: 86.7, 100, 100, 91.9%. Sensitivities and NPVs using an extended gold standard were as follows: RT-PCR: 96.5%, 96.6%; SV-A549: 73.3%, 78.5%; SV-MDCK: 65.1%, 73.7%; tube-A549: 74.4%, 79.2%; tube-MDCK: 68.6%, 75.7%. The average time to detect pandemic influenza A H1N1 by RT-PCR, SV culture, and conventional culture was, respectively, 4 h, 48 h, and 7 days. Real-time RT-PCR displayed high sensitivity and specificity for the detection of influenza A H1N1 in adult patients when compared with conventional techniques. In addition, the A549 cell line was not inferior to the MDCK line.     

Trends on schizophrenia admissions during the deinstitutionalisation process in Spain (1980–2004)

Background  

The deinstitutionalisation reform in Spain started after 1980 with the aim of reducing the need for hospitalisation, length of stay and the number of psychiatric hospital beds, as well as fostering psychiatric patient’s involvement in the community. The aim of this study was to review how this reform process has affected the management of schizophrenic patients from 1980 to 2004.     

Recommendations for the management of influenza A (H1N1) in rheumatic patients with immunosuppression

The Spanish Society of Rheumatology (SER), through a multidiscipline task force, has elaborated a document with specific recommendations for specialists in Rheumatology, emphasizing the special needs of patients with rheumatic diseases, with the objective of informing and orienting health professionals about the current influenza A/H1N1 virus pandemic. All of the recommendations are based on prior documents elaborated by the Ministry of Health and Social Policy task forces, as well as those from the autonomous communities, which are themselves based on the guidelines and documents routinely published by the Centers for Disease Control (CDC) in the US, this being the center designated by WHO for the coordination of efforts against the pandemic. All rheumatologists and potential users of these recommendations are encouraged to consult the original documents, as well as the general guidelines established at each health center.     

Differences in the robustness of clusters involving the Mycobacterium tuberculosis strains most frequently isolated from immigrant cases in Madrid

Tuberculosis cases infected by the same Mycobacterium tuberculosis (MTB) strain are considered to be clustered and involved in a transmission chain. Large clusters are assumed to represent active transmission chains in a population. In the present study, we focused on the analysis of large clusters defined by IS6110-restriction fragment length polymorphism (RFLP) typing in the immigrant population in Madrid. We identified 12 large clusters (involving 43% of the isolates) comprising 4–23 representatives. We proposed a gradient of epidemiological certainty for these large clusters. For a cluster to be considered robust and a good indicator of recent transmission, the MTB strain involved should not have been identified in a geographically and epidemiologically unrelated population and the cluster had to be re-confirmed by another highly discriminative molecular marker (MIRU-VNTR). The clusters that we discovered were classified into three categories: high, intermediate and low expected epidemiological value. In the largest cluster in the study (cluster M6; 23 representatives), failures by both criteria were identified: the representative seven-band RFLP pattern was also the most prevalent in the unrelated population (25 cases) and the cluster was fully split by MIRU-15, suggesting a lack of epidemiological value. The RFLP pattern representative of this cluster was also identified in 64 isolates from five countries in the Latin American genotype database, and again proved to be heterogeneous according to the MIRU-15 analysis. Specific analysis of large clusters, combined with the application of criteria for evaluating their robustness, could help identify uninformative clusters and target epidemiological resources towards those clusters with higher expected epidemiological value.