The distinct category of healthcare associated bloodstream infections

<p>Abstract</p> <p>Background</p> <p>Bloodstream infections (BSI) have been traditionally classified as either community acquired (CA) or hospital acquired (HA) in origin. However, a third category of healthcare-associated (HCA) community onset disease has been increasingly recognized. The objective of this study was to compare and contrast characteristics of HCA-BSI with CA-BSI and HA-BSI.</p> <p>Methods</p> <p>All first episodes of BSI occurring among adults admitted to hospitals in a large health region in Canada during 2000-2007 were identified from regional databases. Cases were classified using a series of validated algorithms into one of HA-BSI, HCA-BSI, or CA-BSI and compared on a number of epidemiologic, microbiologic, and outcome characteristics.</p> <p>Results</p> <p>A total of 7,712 patients were included; 2,132 (28%) had HA-BSI, 2,492 (32%) HCA-BSI, and 3,088 (40%) had CA-BSI. Patients with CA-BSI were significantly younger and less likely to have co-morbid medical illnesses than patients with HCA-BSI or HA-BSI (p < 0.001). The proportion of cases in males was higher for HA-BSI (60%; p < 0.001 vs. others) as compared to HCA-BSI or CA-BSI (52% and 54%; p = 0.13). The proportion of cases that had a poly-microbial etiology was significantly lower for CA-BSI (5.5%; p < 0.001) compared to both HA and HCA (8.6 vs. 8.3%). The median length of stay following BSI diagnosis 15 days for HA, 9 days for HCA, and 8 days for CA (p < 0.001). Overall the most common species causing bloodstream infection were <it>Escherichia coli, Staphylococcus aureus</it>, and <it>Streptococcus pneumoniae</it>. The distribution and relative rank of importance of these species varied according to classification of acquisition. Twenty eight day all cause case-fatality rates were 26%, 19%, and 10% for HA-BSI, HCA-BSI, and CA-BSI, respectively (p < 0.001).</p> <p>Conclusion</p> <p>Healthcare-associated community onset infections are distinctly different from CA and HA infections based on a number of epidemiologic, microbiologic, and outcome characteristics. This study adds further support for the classification of community onset BSI into separate CA and HCA categories.</p

Completeness and timeliness of tuberculosis notification in Taiwan

Tuberculosis (TB) is a notifiable disease by the Communicable Disease Control Law in Taiwan. Several measures have been undertaken to improve reporting of TB but the completeness and timeliness of TB notification in Taiwan has not yet been systemically evaluated

Agreement among Health Care Professionals in Diagnosing Case Vignette-Based Surgical Site Infections

OBJECTIVE: To assess agreement in diagnosing surgical site infection (SSI) among healthcare professionals involved in SSI surveillance. METHODS: Case-vignette study done in 2009 in 140 healthcare professionals from seven specialties (20 in each specialty, Anesthesiologists, Surgeons, Public health specialists, Infection control physicians, Infection control nurses, Infectious diseases specialists, Microbiologists) in 29 University and 36 non-University hospitals in France. We developed 40 case-vignettes based on cardiac and gastrointestinal surgery patients with suspected SSI. Each participant scored six randomly assigned case-vignettes before and after reading the SSI definition on an online secure relational database. The intraclass correlation coefficient (ICC) was used to assess agreement regarding SSI diagnosis on a seven-point Likert scale and the kappa coefficient to assess agreement for superficial or deep SSI on a three-point scale. RESULTS: Based on a consensus, SSI was present in 21 of 40 vignettes (52.5%). Intraspecialty agreement for SSI diagnosis ranged across specialties from 0.15 (95% confidence interval, 0.00-0.59) (anesthesiologists and infection control nurses) to 0.73 (0.32-0.90) (infectious diseases specialists). Reading the SSI definition improved agreement in the specialties with poor initial agreement. Intraspecialty agreement for superficial or deep SSI ranged from 0.10 (-0.19-0.38) to 0.54 (0.25-0.83) (surgeons) and increased after reading the SSI definition only among the infection control nurses from 0.10 (-0.19-0.38) to 0.41 (-0.09-0.72). Interspecialty agreement for SSI diagnosis was 0.36 (0.22-0.54) and increased to 0.47 (0.31-0.64) after reading the SSI definition. CONCLUSION: Among healthcare professionals evaluating case-vignettes for possible surgical site infection, there was large disagreement in diagnosis that varied both between and within specialties

Automated Detection of External Ventricular and Lumbar Drain-Related Meningitis Using Laboratory and Microbiology Results and Medication Data

OBJECTIVE: Monitoring of healthcare-associated infection rates is important for infection control and hospital benchmarking. However, manual surveillance is time-consuming and susceptible to error. The aim was, therefore, to develop a prediction model to retrospectively detect drain-related meningitis (DRM), a frequently occurring nosocomial infection, using routinely collected data from a clinical data warehouse. METHODS: As part of the hospital infection control program, all patients receiving an external ventricular (EVD) or lumbar drain (ELD) (2004 to 2009; n = 742) had been evaluated for the development of DRM through chart review and standardized diagnostic criteria by infection control staff; this was the reference standard. Children, patients dying <24 hours after drain insertion or with <1 day follow-up and patients with infection at the time of insertion or multiple simultaneous drains were excluded. Logistic regression was used to develop a model predicting the occurrence of DRM. Missing data were imputed using multiple imputation. Bootstrapping was applied to increase generalizability. RESULTS: 537 patients remained after application of exclusion criteria, of which 82 developed DRM (13.5/1000 days at risk). The automated model to detect DRM included the number of drains placed, drain type, blood leukocyte count, C-reactive protein, cerebrospinal fluid leukocyte count and culture result, number of antibiotics started during admission, and empiric antibiotic therapy. Discriminatory power of this model was excellent (area under the ROC curve 0.97). The model achieved 98.8% sensitivity (95% CI 88.0% to 99.9%) and specificity of 87.9% (84.6% to 90.8%). Positive and negative predictive values were 56.9% (50.8% to 67.9%) and 99.9% (98.6% to 99.9%), respectively. Predicted yearly infection rates concurred with observed infection rates. CONCLUSION: A prediction model based on multi-source data stored in a clinical data warehouse could accurately quantify rates of DRM. Automated detection using this statistical approach is feasible and could be applied to other nosocomial infections

Postpartum women’s use of medicines and breastfeeding practices: a systematic review

The objectives of this article are to systematically review i) the extent of medicine use in postpartum women, and ii) the impact of maternal medicine use (excluding contraceptives and galactogogues) on breastfeeding outcomes (initiation and/or duration). PubMed, Medline (Ovid), Scopus (Elsevier), Cinahl (EBSCO), PsycINFO (Ovid), Embase (Ovid) and Web of Science (ISI) databases were searched to find original studies on medicine use in women after the birth. Additional studies were identified by searching Google Scholar, Wiley Online Library, Springer Link, selected journals and from the reference list of retrieved articles. Observational studies with information about postpartum women’s use of any type of medicine either for chronic or acute illnesses with or without breastfeeding information were included. The majority of relevant studies suggest that more than 50 % of postpartum women (breastfeeding or not) required at least one medicine. Due to the lack of uniform medication use reporting system and differences in study designs, settings and samples, the proportion of medicine use by postpartum women varies widely, from 34 to 100 %. Regarding the impact of postpartum women’s medicine use on breastfeeding, a few studies suggest that women’s use of certain medicines (e.g. antiepileptics, propylthiouracil, antibiotics) during lactation can reduce initiation and/ or duration of breastfeeding. These studies are limited by small sample size, and with one exception, all were conducted in Canada more than a decade ago. Large scale studies are required to establish the relationship between maternal medicine use and breastfeeding, considering type of illness, period of use and total duration of medicine use