Outbreak of multi-drug resistant Staphylococcus aureus: a cluster analysis

Cluster analysis of angiotensin biomarkers to identify antihypertensive drug treatment in population studies

BACKGROUND

The recent progress in molecular biology generates an increasing interest in investigating molecular biomarkers as markers of response to treatments. The present work is motivated by a study, where the objective was to explore the potential of the molecular biomarkers of renin-angiotensin-aldosterone system (RAAS) to identify the undertaken antihypertensive treatments in the general population. Population-based studies offer an opportunity to assess the effectiveness of treatments in real-world scenarios. However, lack of quality documentation, especially when electronic health record linkage is unavailable, leads to inaccurate reporting and classification bias.

METHOD

We present a machine learning clustering technique to determine the potential of measured RAAS biomarkers for the identification of undertaken treatments in the general population. The biomarkers were simultaneously determined through a novel mass-spectrometry analysis in 800 participants of the Cooperative Health Research In South Tyrol (CHRIS) study with documented antihypertensive treatments. We assessed the agreement, sensitivity and specificity of the resulting clusters against known treatment types. Through the lasso penalized regression, we identified clinical characteristics associated with the biomarkers, accounting for the effects of cluster and treatment classifications.

RESULTS

We identified three well-separated clusters: cluster 1 (n = 444) preferentially including individuals not receiving RAAS-targeting drugs; cluster 2 (n = 235) identifying angiotensin type 1 receptor blockers (ARB) users (weighted kappa κw = 74%; sensitivity = 73%; specificity = 83%); and cluster 3 (n = 121) well discriminating angiotensin-converting enzyme inhibitors (ACEi) users (κw = 81%; sensitivity = 55%; specificity = 90%). Individuals in clusters 2 and 3 had higher frequency of diabetes as well as higher fasting glucose and BMI levels. Age, sex and kidney function were strong predictors of the RAAS biomarkers independently of the cluster structure.

CONCLUSIONS

Unsupervised clustering of angiotensin-based biomarkers is a viable technique to identify individuals on specific antihypertensive treatments, pointing to a potential application of the biomarkers as useful clinical diagnostic tools even outside of a controlled clinical setting.

Simple methodology for detecting time shifts in surgical site infections: a study in digestive, breast, and thoracic surgery

To simplify the data mining surveillance system for the monitoring of surgical site infections (SSIs), electronic analysis of a total of 3100 patients was done. Using Layered Analyses, the Cross-Table option of a globally available software detected emerging or disappearing SSIs according to specific parameters. This methodology may facilitate the detection of SSI shifts.

Cluster analysis on multiple drugs susceptibility supplements genotyping of methicillin-resistant Staphylococcus aureus

OBJECTIVE

To evaluate the typing power of cluster analysis of antimicrobial susceptibility.

METHODS

Results of pulsed-field gel electrophoresis in 71 strains of methicillin-resistant Staphylococcus aureus were compared with cluster analysis of the diameter of growth inhibition in 11 drugs. Subjects were a consecutive series of patients (n = 71) from the wards and outpatient units of a community teaching hospital.

RESULTS

The cluster analysis took 2 to 3 seconds once the data were entered into a computer. The sensitivity, specificity, and accuracy of the cluster analysis were 76.3%, 58.3%, and 73.2%, respectively, using genotyping as the reference.

CONCLUSIONS

The cluster analysis offered real-time epidemiologic data at minimal cost and labor, warranting its cost-effective role.

Infection in the chronically critically ill: unique risk profile in a newly defined population

Although CCI is defined as prolonged ventilatory failure with tracheotomy stemming from preceding critical illness, the contention that multisystem debilities impact on most CCI patients' care and recovery is a central thesis of this volume. Perhaps reflecting the combined debilities inherent in CCI, infectious complications take their toll in morbidity, mortality, and persistent ventilatory insufficiency. Enhanced susceptibility to infection results from a potent admixture of barrier breakdown, exposure to virulent and resistant nosocomial pathogens, and postulated "immune exhaustion" that stems from the combined impact of comorbidities and the sequellae of critical illness. Strategies to improve outcome in CCI-related infection include standard measures of support especially nutrition, reducing environmental inoculum through pulmonary hygiene measures, skin care, and limiting barrier breaches, and appropriate antimicrobials directed at likely pathogens. Future stratification of patient risk on the basis of immune phenotype or genotype and potential immunomodulatory prophylaxis may be around the corner, as new prospects in the pharmaceutical armamentarium are presently undergoing testing.

Evidence-based infection control in thoracic surgery

OBJECTIVES

Methicillin-resistant Staphylococcus aureus (MRSA) continues to pose a major threat to the lung and cardiovascular surgery patients. We propose evidence-based infection control (EBIC) against MRSA.

METHODS

We conducted a basic study comparing genotyping to cluster analysis using minimal inhibition concentration on 17 drugs for 21 MRSA strains. With or without EBIC using cluster analysis and global evidence, we compared the incidence of postoperative MRSA infection. Notably, we eliminated tweezers stands and emesis basins.

RESULTS

Cluster analysis showed a typing sensitivity of 72%. The use of EBIC decreased MRSA cross-infection in the recovery room. A lung surgery series showed an MRSA incidence of 1/190 before and 0/200 after EBIC was introduced. For a cardiovascular surgery series, the MRSA incidence was 2/169 before and 0/84 after EBIC was introduced. Across wards, MRSA among Staphylococcus aureus in patient fell from 68% in 1999 to 57% in 2000.

CONCLUSIONS

EBIC consisting of global guidelines and cluster analysis was useful in controlling MRSA in lung and cardiovascular surgery patients.