Multimorbidity Patterns in Elderly Primary Health Care Patients in a South Mediterranean European Region: A Cluster Analysis

Objective

The purpose of this study was to identify clusters of diagnoses in elderly patients with multimorbidity, attended in primary care.

Design

Cross-sectional study.

Setting

251 primary care centres in Catalonia, Spain.

Participants

Individuals older than 64 years registered with participating practices.

Main outcome measures

Multimorbidity, defined as the coexistence of 2 or more ICD-10 disease categories in the electronic health record. Using hierarchical cluster analysis, multimorbidity clusters were identified by sex and age group (65–79 and ≥80 years).

Results

322,328 patients with multimorbidity were included in the analysis (mean age, 75.4 years [Standard deviation, SD: 7.4], 57.4% women; mean of 7.9 diagnoses [SD: 3.9]). For both men and women, the first cluster in both age groups included the same two diagnoses: Hypertensive diseases and Metabolic disorders. The second cluster contained three diagnoses of the musculoskeletal system in the 65- to 79-year-old group, and five diseases coincided in the ≥80 age group: varicose veins of the lower limbs, senile cataract, dorsalgia, functional intestinal disorders and shoulder lesions. The greatest overlap (54.5%) between the three most common diagnoses was observed in women aged 65–79 years.

Conclusion

This cluster analysis of elderly primary care patients with multimorbidity, revealed a single cluster of circulatory-metabolic diseases that were the most prevalent in both age groups and sex, and a cluster of second-most prevalent diagnoses that included musculoskeletal diseases. Clusters unknown to date have been identified. The clusters identified should be considered when developing clinical guidance for this population.     

OMERACT-based fibromyalgia symptom subgroups: an exploratory cluster analysis

Introduction

The aim of this study was to identify subsets of patients with fibromyalgia with similar symptom profiles using the Outcome Measures in Rheumatology (OMERACT) core symptom domains.

Methods

Female patients with a diagnosis of fibromyalgia and currently meeting fibromyalgia research survey criteria completed the Brief Pain Inventory, the 30-item Profile of Mood States, the Medical Outcomes Sleep Scale, the Multidimensional Fatigue Inventory, the Multiple Ability Self-Report Questionnaire, the Fibromyalgia Impact Questionnaire–Revised (FIQ-R) and the Short Form-36 between 1 June 2011 and 31 October 2011. Hierarchical agglomerative clustering was used to identify subgroups of patients with similar symptom profiles. To validate the results from this sample, hierarchical agglomerative clustering was repeated in an external sample of female patients with fibromyalgia with similar inclusion criteria.

Results

A total of 581 females with a mean age of 55.1 (range, 20.1 to 90.2) years were included. A four-cluster solution best fit the data, and each clustering variable differed significantly (P <0.0001) among the four clusters. The four clusters divided the sample into severity levels: Cluster 1 reflects the lowest average levels across all symptoms, and cluster 4 reflects the highest average levels. Clusters 2 and 3 capture moderate symptoms levels. Clusters 2 and 3 differed mainly in profiles of anxiety and depression, with Cluster 2 having lower levels of depression and anxiety than Cluster 3, despite higher levels of pain. The results of the cluster analysis of the external sample (n = 478) looked very similar to those found in the original cluster analysis, except for a slight difference in sleep problems. This was despite having patients in the validation sample who were significantly younger (P <0.0001) and had more severe symptoms (higher FIQ-R total scores (P = 0.0004)).

Conclusions

In our study, we incorporated core OMERACT symptom domains, which allowed for clustering based on a comprehensive symptom profile. Although our exploratory cluster solution needs confirmation in a longitudinal study, this approach could provide a rationale to support the study of individualized clinical evaluation and intervention.     

Characterization of Rhinitis According to the Asthma Status in Adults Using an Unsupervised Approach in the EGEA Study

Background

The classification of rhinitis in adults is missing in epidemiological studies.

Objective

To identify phenotypes of adult rhinitis using an unsupervised approach (data-driven) compared with a classical hypothesis-driven approach.

Methods

983 adults of the French Epidemiological Study on the Genetics and Environment of Asthma (EGEA) were studied. Self-reported symptoms related to rhinitis such as nasal symptoms, hay fever, sinusitis, conjunctivitis, and sensitivities to different triggers (dust, animals, hay/flowers, cold air…) were used. Allergic sensitization was defined by at least one positive skin prick test to 12 aeroallergens. Mixture model was used to cluster participants, independently in those without (Asthma-, n = 582) and with asthma (Asthma+, n = 401).

Results

Three clusters were identified in both groups: 1) Cluster A (55% in Asthma-, and 22% in Asthma+) mainly characterized by the absence of nasal symptoms, 2) Cluster B (23% in Asthma-, 36% in Asthma+) mainly characterized by nasal symptoms all over the year, sinusitis and a low prevalence of positive skin prick tests, and 3) Cluster C (22% in Asthma-, 42% in Asthma+) mainly characterized by a peak of nasal symptoms during spring, a high prevalence of positive skin prick tests and a high report of hay fever, allergic rhinitis and conjunctivitis. The highest rate of polysensitization (80%) was found in participants with comorbid asthma and allergic rhinitis.

Conclusion

This cluster analysis highlighted three clusters of rhinitis with similar characteristics than those known by clinicians but differing according to allergic sensitization, and this whatever the asthma status. These clusters could be easily rebuilt using a small number of variables.     

Statistical Cluster Analysis of the British Thoracic Society Severe Refractory Asthma Registry: Clinical Outcomes and Phenotype Stability

Background

Severe refractory asthma is a heterogeneous disease. We sought to determine statistical clusters from the British Thoracic Society Severe refractory Asthma Registry and to examine cluster-specific outcomes and stability.

Methods

Factor analysis and statistical cluster modelling was undertaken to determine the number of clusters and their membership (N = 349). Cluster-specific outcomes were assessed after a median follow-up of 3 years. A classifier was programmed to determine cluster stability and was validated in an independent cohort of new patients recruited to the registry (n = 245).

Findings

Five clusters were identified. Cluster 1 (34%) were atopic with early onset disease, cluster 2 (21%) were obese with late onset disease, cluster 3 (15%) had the least severe disease, cluster 4 (15%) were the eosinophilic with late onset disease and cluster 5 (15%) had significant fixed airflow obstruction. At follow-up, the proportion of subjects treated with oral corticosteroids increased in all groups with an increase in body mass index. Exacerbation frequency decreased significantly in clusters 1, 2 and 4 and was associated with a significant fall in the peripheral blood eosinophil count in clusters 2 and 4. Stability of cluster membership at follow-up was 52% for the whole group with stability being best in cluster 2 (71%) and worst in cluster 4 (25%). In an independent validation cohort, the classifier identified the same 5 clusters with similar patient distribution and characteristics.

Interpretation

Statistical cluster analysis can identify distinct phenotypes with specific outcomes. Cluster membership can be determined using a classifier, but when treatment is optimised, cluster stability is poor.     

Temperament clusters in a normal population: implications for health and disease

Background

The object of this study was to identify temperament patterns in the Finnish population, and to determine the relationship between these profiles and life habits, socioeconomic status, and health.

Methods/Principal Findings

A cluster analysis of the Temperament and Character Inventory subscales was performed on 3,761 individuals from the Northern Finland Birth Cohort 1966 and replicated on 2,097 individuals from the Cardiovascular Risk in Young Finns study. Clusters were formed using the k-means method and their relationship with 115 variables from the areas of life habits, socioeconomic status and health was examined.

Results

Four clusters were identified for both genders. Individuals from Cluster I are characterized by high persistence, low extravagance and disorderliness. They have healthy life habits, and lowest scores in most of the measures for psychiatric disorders. Cluster II individuals are characterized by low harm avoidance and high novelty seeking. They report the best physical capacity and highest level of income, but also high rate of divorce, smoking, and alcohol consumption. Individuals from Cluster III are not characterized by any extreme characteristic. Individuals from Cluster IV are characterized by high levels of harm avoidance, low levels of exploratory excitability and attachment, and score the lowest in most measures of health and well-being.

Conclusions

This study shows that the temperament subscales do not distribute randomly but have an endogenous structure, and that these patterns have strong associations to health, life events, and well-being.     

Heterogeneous Evolution of HIV-1 CRF01_AE in Men Who Have Sex with Men (MSM) and Other Populations in China

Introduction

The HIV epidemic in men who have sex with men (MSM) continues to grow in most countries. However, the phylodynamic and virological differences among HIV-1 strains circulating in MSM and other populations are not well characterized.

Methods

Nearly full-length genomes (NFLGs) of the HIV-1 CRF01_AE were obtained from the Los Alamos HIV database. Phylogenetic analyses were conducted using the NFLG, gag, pol and env genes, using the maximum likelihood method. Selection pressure analyses at the codon level were performed for each gene in the phylogenetic clusters using PAML.

Results

Sequences isolated from MSM in China clustered in Clusters 1 (92.5%) and 2 (85.71%). The major risk factor for Cluster 3 was heterosexual transmission (62.16%). The ratio of non-synonymous to synonymous substitutions in the env gene (0.7–0.75) was higher than the gag (0.26–0.34) or pol (0.21–0.26) genes. In env gene, Cluster 1 (4.56×10^-3subs/site/year) and 2 (6.01×10^-3subs/site/year) had higher evolutionary rates than Cluster 3 (1.14×10^-3subs/site/year). Positive selection affected 4.2–6.58% of the amino acid sites in the env gene. Two sites (HXB2:136 and 316) evolved similarly in Clusters 1 and 2, but not Cluster 3.

Conclusion

The HIV-1 CRF01_AE in MSM is evolving differently than in other populations.     

Non-ischemic cardiomyopathy patients derive superior mortality benefit from cardiac resynchronization therapy

Background

Cardiac Resynchronization Therapy (CRT) is indicated for the treatment of advanced heart failure with severe systolic dysfunction and intraventricular conduction delay. Patient selection for this technology is vital, though it remains unclear which patients benefit most from CRT. We tested the hypothesis that patients with non-ischemic cardiomyopathy have a superior mortality benefit from CRT than ischemic cardiomyopathy patients.

Methods

We evaluated 95 CRT patients to determine which factors predict mortality.

Results

Patients with non-ischemic cardiomyopathy had a significantly better prognosis than patients with ischemic cardiomyopathy.

Conclusion

Larger prospective studies can substantiate this finding and better delineate which patients benefit most from CRT.     

Cluster Analysis in Patients with GOLD 1 Chronic Obstructive Pulmonary Disease

Background

We hypothesized that heterogeneity exists within the Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1 spirometric category and that different subgroups could be identified within this GOLD category.

Methods

Pre-randomization study participants from two clinical trials were symptomatic/asymptomatic GOLD 1 chronic obstructive pulmonary disease (COPD) patients and healthy controls. A hierarchical cluster analysis used pre-randomization demographics, symptom scores, lung function, peak exercise response and daily physical activity levels to derive population subgroups.

Results

Considerable heterogeneity existed for clinical variables among patients with GOLD 1 COPD. All parameters, except forced expiratory volume in 1 second (FEV₁)/forced vital capacity (FVC), had considerable overlap between GOLD 1 COPD and controls. Three-clusters were identified: cluster I (18 [15%] COPD patients; 105 [85%] controls); cluster II (45 [80%] COPD patients; 11 [20%] controls); and cluster III (22 [92%] COPD patients; 2 [8%] controls). Apart from reduced diffusion capacity and lower baseline dyspnea index versus controls, cluster I COPD patients had otherwise preserved lung volumes, exercise capacity and physical activity levels. Cluster II COPD patients had a higher smoking history and greater hyperinflation versus cluster I COPD patients. Cluster III COPD patients had reduced physical activity versus controls and clusters I and II COPD patients, and lower FEV₁/FVC versus clusters I and II COPD patients.

Conclusions

The results emphasize heterogeneity within GOLD 1 COPD, supporting an individualized therapeutic approach to patients.

Trial registration

www.clinicaltrials.gov. NCT01360788 and NCT01072396.     

The Relationship between Cortisol Activity during Cognitive Task and Posttraumatic Stress Symptom Clusters

Background

The latest development in the dimensional structure of posttraumatic stress disorder (PTSD) is a novel 6-factor model, which builds on the newly released DSM-5. One notable gap in the literature is that little is known about how distinct symptom clusters of PTSD are related to hypothalamic–pituitary–adrenal (HPA) axis activity when people perform a relatively less stressful cognitive task. The purpose of this study was to investigate the relationship between cortisol activity when individuals perform cognitive tasks in the laboratory and a contemporary phenotypic model of posttraumatic stress symptomatology in earthquake survivors.

Methods

Salivary cortisol while performing cognitive tasks was collected and analyzed in 89 adult earthquake survivors. The PTSD Checklist for the DSM-5 (PCL-5) was used to assess the severity of total PTSD as well as six distinct symptom clusters. Regression analyses were conducted to examine the associations between the six distinct PTSD symptom clusters and cortisol profiles.

Results

The results showed that the score of the negative affect symptom cluster, but not anhedonia or other clusters, was positively associated with cortisol levels before and during the cognitive tasks.

Conclusion

The results showed that higher cortisol levels before and during cognitive tasks might be specifically linked to a distinct symptom cluster of PTSD—negative affect symptomatology. This suggests that a distinction should be made between negative affect and anhedonia symptom clusters, as the 6-factor model proposed.     

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data

Purpose

To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment.

Material and Methods

The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters.

Results

The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters.

Conclusion

The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes.     

Bacterial Factors Associated with Lethal Outcome of Enteropathogenic Escherichia coli Infection: Genomic Case-Control Studies

Background

Typical enteropathogenic Escherichia coli (tEPEC) strains were associated with mortality in the Global Enteric Multicenter Study (GEMS). Genetic differences in tEPEC strains could underlie some of the variability in clinical outcome.

Methods

We produced draft genome sequences of all available tEPEC strains from GEMS lethal infections (LIs) and of closely matched EPEC strains from GEMS subjects with non-lethal symptomatic infections (NSIs) and asymptomatic infections (AIs) to identify gene clusters (potential protein encoding sequences sharing ≥90% nucleotide sequence identity) associated with lethality.

Results

Among 14,412 gene clusters identified, the presence or absence of 392 was associated with clinical outcome. As expected, more gene clusters were associated with LI versus AI than LI versus NSI. The gene clusters more prevalent in strains from LI than those from NSI and AI included those encoding proteins involved in O-antigen biogenesis, while clusters encoding type 3 secretion effectors EspJ and OspB were among those more prevalent in strains from non-lethal infections. One gene cluster encoding a variant of an NleG ubiquitin ligase was associated with LI versus AI, while two other nleG clusters had the opposite association. Similar associations were found for two nleG gene clusters in an additional, larger sample of NSI and AI GEMS strains.

Conclusions

Particular genes are associated with lethal tEPEC infections. Further study of these factors holds potential to unravel the mechanisms underlying severe disease and to prevent adverse outcomes.     

Burn Injury-Specific Home Safety Assessment: A Cross-Sectional Study in Iran

Background

The aim of this study was to assess the feasibility of injury specific home safety investigation and to examine the home safety status focused on burn related safety in a rural population in the North-West of Iran.

Methods

A cross-sectional study was conducted on 265 rural households of rural Meshkinshahr, Iran. Cluster sampling method was used in 38 clusters with 7 households in each cluster. Clusters were selected on a probability proportional to size (PPS) basis using the available health census database called D-Tarh. Data were analyzed using the statistical software package STATA 8.

Results

Possible risks were explored in fields of house structure; cooking and eating attitudes and behaviors; cooking appliances, specific appliances such as picnic gas burners, valors (traditional heaters), samovars (traditional water boilers), and air-heating appliances. Many safety concerns were explored needing to draw the attention of researchers and public health policy makers.

Conclusion

Injury specific home safety surveys are useful and may provide useful information for safety promotion interventions.     

Evidence of Uncoupling between Renal Dysfunction and Injury in Cardiorenal Syndrome: Insights from the BIONICS Study

Objective

The objective of the study was to assess urinary biomarkers of renal injury for their individual or collective ability to predict Worsening renal function (WRF) in patients with acutely decompensated heart failure (ADHF).

Methods

In a prospective, blinded international study, 87 emergency department (ED) patients with ADHF were evaluated with biomarkers of cardiac stretch (B type natriuretic peptide [BNP] and its amino terminal equivalent [NT-proBNP], ST2), biomarkers of renal function (creatinine, estimated glomerular filtration rate [eGFR]) and biomarkers of renal injury (plasma neutrophil gelatinase associated lipocalin [pNGAL], urine kidney injury molecule-1 [KIM-1], urine N-acetyl-beta-D-glucosaminidase [NAG], urine Cystatin C, urine fibrinogen). The primary endpoint was WRF.

Results

26% developed WRF; baseline characteristics of subjects who developed WRF were generally comparable to those who did not. Biomarkers of renal function and urine biomarkers of renal injury were not correlated, while urine biomarkers of renal injury correlated between each other. Biomarker concentrations were similar between patients with and without WRF except for baseline BNP. Although plasma NGAL was associated with the combined endpoint, none of the biomarker showed predictive accuracy for WRF.

Conclusions

In ED patients with ADHF, urine biomarkers of renal injury did not predict WRF. Our data suggest that a weak association exists between renal dysfunction and renal injury in this setting (Clinicaltrials.gov NCT#0150153).     

Degenerative Pathways of Lumbar Motion Segments - A Comparison in Two Samples of Patients with Persistent Low Back Pain

Background

Magnetic resonance imaging (MRI) is used to identify spinal pathoanatomy in people with persistent low back pain. However, the clinical relevance of spinal degenerative MRI findings remains uncertain. Although multiple MRI findings are almost always present at the same time, research into the association with clinical outcomes (such as pain) has predominantly focused on individual MRI findings. This study aimed to: (i) investigate how multiple MRI lumbar spine findings cluster together within two different samples of patients with low back pain, (ii) classify these clusters into hypothetical pathways of degeneration based on scientific knowledge of disco-vertebral degeneration, and (iii) compare these clusters and degenerative pathways between samples.

Methods

We performed a secondary cross-sectional analysis on two dissimilar MRI samples collected in a hospital department: (1) data from the spinal MRI reports of 4,162 low back pain patients and (2) data from an MRI research protocol of 631 low back pain patients. Latent Class Analysis was used in both samples to cluster MRI findings from lumbar motion segments. Using content analysis, each cluster was then categorised into hypothetical pathways of degeneration.

Results

Six clusters of MRI findings were identified in each of the two samples. The content of the clusters in the two samples displayed some differences but had the same overall pattern of MRI findings. Although the hypothetical degenerative pathways identified in the two samples were not identical, the overall pattern of increasing degeneration within the pathways was the same.

Conclusions

It was expected that different clusters could emerge from different samples, however, when organised into hypothetical pathways of degeneration, the overall pattern of increasing degeneration was similar and biologically plausible. This evidence of reproducibility suggests that Latent Class Analysis may provide a new approach to investigating the relationship between MRI findings and clinically important characteristics such as pain and activity limitation.     

Defining adult asthma endotypes by clinical features and patterns of volatile organic compounds in exhaled air

Background

Several classifications of adult asthma patients using cluster analyses based on clinical and demographic information has resulted in clinical phenotypic clusters that do not address molecular mechanisms. Volatile organic compounds (VOC) in exhaled air are released during inflammation in response to oxidative stress as a result of activated leukocytes. VOC profiles in exhaled air could distinguish between asthma patients and healthy subjects. In this study, we aimed to classify new asthma endotypes by combining inflammatory mechanisms investigated by VOC profiles in exhaled air and clinical information of asthma patients.

Methods

Breath samples were analyzed for VOC profiles by gas chromatography–mass spectrometry from asthma patients (n = 195) and healthy controls (n = 40). A total of 945 determined compounds were subjected to discriminant analysis to find those that could discriminate healthy from asthmatic subjects. 2-step cluster analysis based on clinical information and VOCs in exhaled air were used to form asthma endotypes.

Results

We identified 16 VOCs, which could distinguish between healthy and asthma subjects with a sensitivity of 100% and a specificity of 91.1%. Cluster analysis based on VOCs in exhaled air and the clinical parameters FEV1, FEV1 change after 3 weeks of hospitalization, allergic sensitization, Junipers symptoms score and asthma medications resulted in the formation of 7 different asthma endotype clusters. We identified asthma clusters with different VOC profiles but similar clinical characteristics and endotypes with similar VOC profiles, but distinct clinical characteristics.

Conclusion

This study demonstrates that both, clinical presentation of asthma and inflammatory mechanisms in the airways should be considered for classification of asthma subtypes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12931-014-0136-8) contains supplementary material, which is available to authorized users.     

Clinical Significance of Asthma Clusters by Longitudinal Analysis in Korean Asthma Cohort

Background

We have previously identified four distinct groups of asthma patients in Korean cohorts using cluster analysis: (A) smoking asthma, (B) severe obstructive asthma, (C) early-onset atopic asthma, and (D) late-onset mild asthma.

Methods and Results

A longitudinal analysis of each cluster in a Korean adult asthma cohort was performed to investigate the clinical significance of asthma clusters over 12 months.Cluster A showed relatively high asthma control test (ACT) scores but relatively low FEV₁ scores, despite a high percentage of systemic corticosteroid use. Cluster B had the lowest mean FEV₁, ACT, and the quality of life questionnaire for adult Korean asthmatics (QLQAKA) scores throughout the year, even though the percentage of systemic corticosteroid use was the highest among the four clusters. Cluster C was ranked second in terms of FEV₁, with the second lowest percentage of systemic corticosteroid use, and showed a marked improvement in subjective symptoms over time. Cluster D consistently showed the highest FEV₁, the lowest systemic corticosteroid use, and had high ACT and QLQAKA scores.

Conclusion

Our asthma clusters had clinical significance with consistency among clusters over 12 months. These distinctive phenotypes may be useful in classifying asthma in real practice.     

GRACE Score among Six Risk Scoring Systems (CADILLAC,PAMI, TIMI,Dynamic TIMI,Zwolle) Demonstrated the Best Predictive Value for Prediction of Long-Term Mortality in Patients with ST-Elevation Myocardial Infarction

Aim

To compare the prognostic accuracy of six scoring models for up to three-year mortality and rates of hospitalisation due to acute decompensated heart failure (ADHF) in STEMI patients.

Methods and Results

A total of 593 patients treated with primary PCI were evaluated. Prospective follow-up of patients was ≥3 years. Thirty-day, one-year, two-year, and three-year mortality rates were 4.0%, 7.3%, 8.9%, and 10.6%, respectively. Six risk scores—the TIMI score and derived dynamic TIMI, CADILLAC, PAMI, Zwolle, and GRACE—showed a high predictive accuracy for six- and 12-month mortality with area under the receiver operating characteristic curve (AUC) values of 0.73–0.85. The best predictive values for long-term mortality were obtained by GRACE. The next best-performing scores were CADILLAC, Zwolle, and Dynamic TIMI. All risk scores had a lower prediction accuracy for repeat hospitalisation due to ADHF, except Zwolle with the discriminatory capacity for hospitalisation up to two years (AUC, 0.80–0.83).

Conclusions

All tested models showed a high predictive value for the estimation of one-year mortality, but GRACE appears to be the most suitable for the prediction for a longer follow-up period. The tested models exhibited an ability to predict the risk of ADHF, especially the Zwolle model.     

Instant Typing Is Essential to Detect Transmission of Extended-Spectrum Beta-Lactamase-Producing Klebsiella Species

Background

Infections with multidrug-resistant (MDR) microorganisms are an increasing threat to hospitalized patients. Although rapid typing of MDR microorganisms is required to apply targeted prevention measures, technical barriers often prevent this. We aimed to assess whether extended-spectrum beta-lactamase (ESBL)-producing Klebsiella species are transmitted between patients and whether routine, rapid typing is needed.

Methods

For 43 months, the clonality of all ESBL-producing Klebsiella isolates from patients admitted to Erasmus MC University Medical Center in Rotterdam, the Netherlands was assessed with Raman spectroscopy. A cluster was defined as n ≥2 patients who had identical isolates. Primary patients were the first patients in each cluster. Secondary patients were those identified with an isolate clonally related to the isolate of the primary patient.

Results

Isolates from 132 patients were analyzed. We identified 17 clusters, with 17 primary and 56 secondary patients. Fifty-nine patients had a unique isolate. Patients (n = 15) in four out of the 17 clusters were epidemiologically related. Ten of these 15 patients developed an infection.

Conclusions

Clonal outbreaks of ESBL-producing Klebsiella species were detected in our hospital. Theoretically, after Raman spectroscopy had detected a cluster of n ≥2, six infections in secondary patients could have been prevented. These findings demonstrate that spread of ESBL-producing Klebsiella species occurs, even in a non-outbreak setting, and underscore the need for routine rapid typing of these MDR bacteria.     

Attenuation of Post-Shock Increases in Brain Natriuretic Peptide with Post Shock Overdrive Pacing

Background

Predischarge defibrillation threshold testing is often performed a few days after ICD implantation in order to validate defibrillation thresholds obtained at the time of implant. Ventricular fibrillation is induced with such testing and causes an increase in serum Brain Natriuretic Peptide (BNP) levels. BNP is an indicator for cardiac stress. We wanted to examine the feasibility to alter the trend of BNP after predischarge testing in VVI, DDD and CRT ICD''s.

Methods

We measured BNP before predischarge testing and 5, 10, 20 and 40 minutes after predischarge testing in 13 groups with each 20 patients. We evaluated patients without post shock pacing and patients with a post shock pacing frequency of 60, 70, 80, 90 and 100 bpm and a duration of 30 and 60 sec as well as a post shock pacing frequency of 80 and 90 bpm and a duration of 120 sec post shock pacing.

Results

Patients without post shock pacing showed the highest BNP during the follow-up. The percentage values of BNP increased consistent significantly after 5 minutes compared with BNP before predischarge testing. The percentage values of BNP trend was significantly lower with a post shock pacing of 90 bpm and duration of 60 sec. In addition, we excluded a cardiac necrosis by predischarge testing because of similar values of myoglobin, cardiac troponin I and creatine kinase during the follow-up.

Conclusions

Our results suggested that post shock pacing with 90 bpm and duration of 60 sec as the best optimized post shock pacing frequency and duration for VVI, DDD and CRT ICD''s. A reduction of cardiac stress is going to be achieved with the optimization of the post shock pacing frequency and duration.     

Prognostic Impact of Renal Dysfunction Does Not Differ According to the Clinical Profiles of Patients: Insight from the Acute Decompensated Heart Failure Syndromes (ATTEND) Registry

Background

Renal dysfunction associated with acute decompensated heart failure (ADHF) is associated with impaired outcomes. Its mechanism is attributed to renal arterial hypoperfusion or venous congestion, but its prognostic impact based on each of these clinical profiles requires elucidation.

Methods and Results

ADHF syndromes registry subjects were evaluated (N = 4,321). Logistic regression modeling calculated adjusted odds ratios (OR) for in-hospital mortality for patients with and without renal dysfunction. Renal dysfunction risk was calculated for subgroups with hypoperfusion-dominant (eg. cold extremities, a low mean blood pressure or a low proportional pulse pressure) or congestion-dominant clinical profiles (eg. peripheral edema, jugular venous distension, or elevated brain natriuretic peptide) to evaluate renal dysfunction''s prognostic impact in the context of the two underlying mechanisms. On admission, 2,150 (49.8%) patients aged 73.3±13.6 years had renal dysfunction. Compared with patients without renal dysfunction, those with renal dysfunction were older and had dominant ischemic etiology jugular venous distension, more frequent cold extremities, and higher brain natriuretic peptide levels. Renal dysfunction was associated with in-hospital mortality (OR 2.36; 95% confidence interval 1.75–3.18, p<0.001), and the prognostic impact of renal dysfunction was similar in subgroup of patients with hypoperfusion- or congestion-dominant clinical profiles (p-value for the interaction ranged from 0.104–0.924, and was always >0.05).

Conclusions

Baseline renal dysfunction was significantly associated with in-hospital mortality in ADHF patients. The prognostic impact of renal dysfunction was the same, regardless of its underlying etiologic mechanism.