Sebastian Haubitz

Excluding infection through procalcitonin testing improves outcomes of congestive heart failure patients presenting with acute respiratory symptoms: Results from the randomized ProHOSP trial

BACKGROUND/OBJECTIVES We sought to determine whether exclusion of infection and antibiotic stewardship with the infection biomarker procalcitonin improves outcomes in congestive heart failure (CHF) patients presenting to emergency departments with respiratory symptoms and suspicion of respiratory infection. METHODS We performed a secondary analysis of patients with a past medical history of CHF formerly included in a Swiss multicenter randomized-controlled trial. The trial compared antibiotic stewardship according to a procalcitonin algorithm or state-of-the-art guidelines (controls). The primary endpoint was a 30-day adverse outcome (death, intensive care unit admission); the secondary endpoints included a 30-day antibiotic exposure. RESULTS In the 110/233 analyzed patients (47.2%) with low initial procalcitonin (<0.25 μg/L), suggesting the absence of systemic bacterial infection, those randomized to procalcitonin guidance (n=50) had a significantly lower adverse outcome rate compared to controls (n=60): 4% vs. 20% (absolute difference -16.0%, 95% confidence interval (CI) -28.4% to -3.6%, P=0.01), and significantly reduced antibiotic exposure [days] (mean 3.7 ± 4.0 vs. 6.5 ± 4.4, difference -2.8 [95% CI, -4.4 to -1.2], P<0.01). When initial procalcitonin was ≥0.25 μg/L, procalcitonin-guided patients had significantly reduced antibiotic exposure due to early stop of therapy without any difference in adverse outcomes (25.8% vs. 24.6%, difference [95% CI] 1.2% [-14.5% to 16.9%, P=0.88]). CONCLUSIONS CHF patients presenting to the emergency department with respiratory symptoms and suspicion for respiratory infection had decreased antibiotic exposure and improved outcomes when procalcitonin measurement was used to exclude bacterial infection and guide antibiotic treatment. These data provide further evidence for the potential harmful effects of antibiotic / fluid treatment when used instead of diuretics and heart failure medication in clinically symptomatic CHF patients without underlying infection.

Optimizing triage and hospitalization in adult general medical emergency patients: the triage project

BackgroundPatients presenting to the emergency department (ED) currently face inacceptable delays in initial treatment, and long, costly hospital stays due to suboptimal initial triage and site-of-care decisions. Accurate ED triage should focus not only on initial treatment priority, but also on prediction of medical risk and nursing needs to improve site-of-care decisions and to simplify early discharge management. Different triage scores have been proposed, such as the Manchester triage system (MTS). Yet, these scores focus only on treatment priority, have suboptimal performance and lack validation in the Swiss health care system. Because the MTS will be introduced into clinical routine at the Kantonsspital Aarau, we propose a large prospective cohort study to optimize initial patient triage. Specifically, the aim of this trial is to derive a three-part triage algorithm to better predict (a) treatment priority; (b) medical risk and thus need for in-hospital treatment; (c) post-acute care needs of patients at the most proximal time point of ED admission.Methods/designProspective, observational, multicenter, multi-national cohort study. We will include all consecutive medical patients seeking ED care into this observational registry. There will be no exclusions except for non-adult and non-medical patients. Vital signs will be recorded and left over blood samples will be stored for later batch analysis of blood markers. Upon ED admission, the post-acute care discharge score (PACD) will be recorded. Attending ED physicians will adjudicate triage priority based on all available results at the time of ED discharge to the medical ward. Patients will be reassessed daily during the hospital course for medical stability and readiness for discharge from the nurses and if involved social workers perspective. To assess outcomes, data from electronic medical records will be used and all patients will be contacted 30 days after hospital admission to assess vital and functional status, re-hospitalization, satisfaction with care and quality of life measures.We aim to include between 5000 and 7000 patients over one year of recruitment to derive the three-part triage algorithm. The respective main endpoints were defined as (a) initial triage priority (high vs. low priority) adjudicated by the attending ED physician at ED discharge, (b) adverse 30 day outcome (death or intensive care unit admission) within 30 days following ED admission to assess patients risk and thus need for in-hospital treatment and (c) post acute care needs after hospital discharge, defined as transfer of patients to a post-acute care institution, for early recognition and planning of post-acute care needs. Other outcomes are time to first physician contact, time to initiation of adequate medical therapy, time to social worker involvement, length of hospital stay, reasons for discharge delays, patient’s satisfaction with care, overall hospital costs and patients care needs after returning home.DiscussionUsing a reliable initial triage system for estimating initial treatment priority, need for in-hospital treatment and post-acute care needs is an innovative and persuasive approach for a more targeted and efficient management of medical patients in the ED. The proposed interdisciplinary , multi-national project has unprecedented potential to improve initial triage decisions and optimize resource allocation to the sickest patients from admission to discharge. The algorithms derived in this study will be compared in a later randomized controlled trial against a usual care control group in terms of resource use, length of hospital stay, overall costs and patient’s outcomes in terms of mortality, re-hospitalization, quality of life and satisfaction with care.Trial registrationClinicalTrials.gov Identifier, NCT01768494

Ruling Out Legionella in Community-acquired Pneumonia

BACKGROUND Assessing the likelihood for Legionella sp. in community-acquired pneumonia is important because of differences in treatment regimens. Currently used antigen tests and culture have limited sensitivity with important time delays, making empirical broad-spectrum coverage necessary. Therefore, a score with 6 variables recently has been proposed. We sought to validate these parameters in an independent cohort. METHODS We analyzed adult patients with community-acquired pneumonia from a large multinational database (Community Acquired Pneumonia Organization) who were treated between 2001 and 2012 with more than 4 of the 6 prespecified clinical variables available. Association and discrimination were assessed using logistic regression analysis and area under the curve (AUC). RESULTS Of 1939 included patients, the infectious cause was known in 594 (28.9%), including Streptococcus pneumoniae in 264 (13.6%) and Legionella sp. in 37 (1.9%). The proposed clinical predictors fever, cough, hyponatremia, lactate dehydrogenase, C-reactive protein, and platelet count were all associated or tended to be associated with Legionella cause. A logistic regression analysis including all these predictors showed excellent discrimination with an AUC of 0.91 (95% confidence interval, 0.87-0.94). The original dichotomized score showed good discrimination (AUC, 0.73; 95% confidence interval, 0.65-0.81) and a high negative predictive value of 99% for patients with less than 2 parameters present. CONCLUSIONS With the use of a large independent patient sample from an international database, this analysis validates previously proposed clinical variables to accurately rule out Legionella sp., which may help to optimize initial empiric therapy.

Do sepsis biomarkers in the emergency room allow transition from bundled sepsis care to personalized patient care

Purpose of reviewThere is convincing evidence linking early start of fluid resuscitation and initiation of appropriate antimicrobial therapy to improved outcomes in patients with sepsis in the emergency department. Blood biomarkers measured on admission and during follow-up have the ability to guide early sepsis recognition, severity assessment and therapeutic decisions in individual patients and may allow transition from bundled sepsis care to more individualized management in single patients. Recent findingsAlthough a large number of promising diagnostic and prognostic biomarkers have been put forward in observational studies, only few have been evaluated in prospective randomized-controlled intervention trials. Markers such as lactate for risk stratification and guidance of fluid resuscitation, procalcitonin for assessing risk of bacterial infections and guiding therapeutic decisions about initiation and duration of antimicrobial therapy, and recently proadrenomedullin for early mortality prediction and site-of-care decisions in respiratory infections, have shown to improve patient management. SummaryFor few biomarkers, recent study results demonstrate that well defined clinical protocols have the potential to guide decisions about the individual risk stratification and treatment of patients with suspicion of sepsis ultimately leading to improved patient care and outcomes. For other biomarkers, promising observation data have been put forward, but their potential needs to be evaluated in large-scale, well designed prospective intervention studies before clinical use can be recommended.

Performance of the Manchester Triage System in Adult Medical Emergency Patients: A Prospective Cohort Study

BACKGROUND Accurate initial patient triage in the emergency department (ED) is pivotal in reducing time to effective treatment by the medical team and in expediting patient flow. The Manchester Triage System (MTS) is widely implemented for this purpose. Yet the overall effectiveness of its performance remains unclear. OBJECTIVES We investigated the ability of MTS to accurately assess high treatment priority and to predict adverse clinical outcomes in a large unselected population of medical ED patients. METHODS We prospectively followed consecutive medical patients seeking ED care for 30 days. Triage nurses implemented MTS upon arrival of patients admitted to the ED. The primary endpoint was high initial treatment priority adjudicated by two independent physicians. Secondary endpoints were 30-day all-cause mortality, admission to the intensive care unit (ICU), and length of stay. We used regression models with area under the receiver operating characteristic curve (AUC) as a measure of discrimination. RESULTS Of the 2407 patients, 524 (21.8%) included patients (60.5 years, 55.7% males) who were classified as high treatment priority; 3.9% (n = 93) were transferred to the ICU; and 5.7% (n = 136) died. The initial MTS showed fair prognostic accuracy in predicting treatment priority (AUC 0.71) and ICU admission (AUC 0.68), but not in predicting mortality (AUC 0.55). Results were robust across most predefined subgroups, including patients diagnosed with infections, or cardiovascular or gastrointestinal diseases. In the subgroup of neurological symptoms and disorders, the MTS showed the best performance. CONCLUSION The MTS showed fair performance in predicting high treatment priority and adverse clinical outcomes across different medical ED patient populations. Future research should focus on further refinement of the MTS so that its performance can be improved. TRIAL REGISTRATION Clinicaltrials.gov: NCT01768494.

Unraveling the Link between Malnutrition and Adverse Clinical Outcomes: Association of Acute and Chronic Malnutrition Measures with Blood Biomarkers from Different Pathophysiological States

Background and Aims: Malnutrition is associated with poor clinical outcomes. Whether there is a causal relationship or it merely mirrors a severe patient condition remains unclear. We examined the association of malnutrition with biomarkers characteristic of different pathophysiological states to better understand the underlying etiological mechanisms. Methods: We prospectively followed consecutive adult medical inpatients. Multivariable regression models were used to investigate the associations between malnutrition - as assessed using the Nutritional Risk Screening (NRS 2002) - and biomarkers linked to inflammation, stress, renal dysfunction, nutritional status and hematologic function. Results: A total of 529 patients were included. In a fully adjusted model, malnutrition was significantly associated with the inflammatory markers procalcitonin (0.20, 95% CI 0.03-0.37), proadrenomedullin (0.28, 95% CI 0.12-0.43) and albumin (-0.39, 95% CI -0.57 to -0.21), the stress marker copeptin (0.34, 95% CI 0.17-0.51), the renal function marker urea (0.23, 95% CI 0.07-0.38), the nutritional markers vitamin D25 (-0.22, 95% CI -0.41 to -0.02) and corrected calcium (0.29, 95% CI 0.10-0.49) and the hematological markers hemoglobin (-0.27, 95% CI -0.43 to -0.10) and red blood cell distribution width (0.26, 95% CI 0.07-0.44). Subgroup analysis suggested that acute malnutrition rather than chronic malnutrition was associated with elevated biomarker levels. Conclusion: Acute malnutrition was associated with a pronounced inflammatory response and an alteration in biomarkers associated with different pathophysiological states. Interventional trials are needed to prove causality.

Can We Reduce Negative Blood Cultures With Clinical Scores and Blood Markers? Results From an Observational Cohort Study

AbstractOnly a small proportion of blood cultures routinely performed in emergency department (ED) patients is positive. Multiple clinical scores and biomarkers have previously been examined for their ability to predict bacteremia. Conclusive clinical validation of these scores and biomarkers is essential.This observational cohort study included patients with suspected infection who had blood culture sampling at ED admission. We assessed 5 clinical scores and admission concentrations of procalcitonin (PCT), C-reactive protein (CRP), lymphocyte and white blood cell counts, the neutrophil-lymphocyte count ratio (NLCR), and the red blood cell distribution width (RDW). Two independent physicians assessed true blood culture positivity. We used logistic regression models with area under the curve (AUC) analysis.Of 1083 patients, 104 (9.6%) had positive blood cultures. Of the clinical scores, the Shapiro score performed best (AUC 0.729). The best biomarkers were PCT (AUC 0.803) and NLCR (AUC 0.700). Combining the Shapiro score with PCT levels significantly increased the AUC to 0.827. Limiting blood cultures only to patients with either a Shapiro score of ≥4 or PCT > 0.1 &mgr;g/L would reduce negative sampling by 20.2% while still identifying 100% of positive cultures. Similarly, a Shapiro score ≥3 or PCT >0.25 &mgr;g/L would reduce cultures by 41.7% and still identify 96.1% of positive blood cultures.Combination of the Shapiro score with admission levels of PCT can help reduce unnecessary blood cultures with minimal false negative rates.The study was registered on January 9, 2013 at the ‘ClinicalTrials.gov’ registration web site (NCT01768494).

Use of procalcitonin, C-reactive protein and white blood cell count to distinguish between lower limb erysipelas and deep vein thrombosis in the emergency department: A prospective observational study

Early differentiation of erysipelas from deep vein thrombosis (DVT) based solely on clinical signs and symptoms is challenging. There is a lack of data regarding the usefulness of the inflammatory biomarkers procalcitonin (PCT), C‐reactive protein (CRP) and white blood cell (WBC) count in the diagnosis of localized cutaneous infections. Herein, we investigated the diagnostic value of inflammatory markers in a prospective at‐risk patient population. This is an observational quality control study including consecutive patients presenting with a final diagnosis of either erysipelas or DVT. The association of PCT (μg/L) and CRP (mg/L) levels and WBC counts (g/L) with the primary outcome was assessed using logistic regression models with area under the receiver–operator curve. Forty‐eight patients (erysipelas, n = 31; DVT, n = 17) were included. Compared with patients with DVT, those with erysipelas had significantly higher PCT concentrations. No significant differences in CRP concentrations and WBC counts were found between the two groups. At a PCT threshold of 0.1 μg/L or more, specificity and positive predictive values (PPV) for erysipelas were 82.4% and 85.7%, respectively, and increased to 100% and 100% at a threshold of more than 0.25 μg/L. Levels of PCT also correlated with the severity of erysipelas, with a stepwise increase according to systemic inflammatory response syndrome criteria. We found a high discriminatory value of PCT for differentiation between erysipelas and DVT, in contrast to other commonly used inflammatory biomarkers. Whether the use of PCT levels for early differentiation of erysipelas from DVT reduces unnecessary antibiotic exposure needs to be assessed in an interventional trial.

Are admission procalcitonin levels universal mortality predictors across different medical emergency patient populations? Results from the multi-national, prospective, observational TRIAGE study

Abstract Background: Procalcitonin (PCT), an inflammatory blood biomarker, is well studied in infectious diseases. Its prognostic value in unselected emergency department (ED) patients remains yet undefined. Herein, we investigated association of admission PCT levels and mortality in a large, international-multicenter ED patient cohort. Methods: We prospectively enrolled 6970 unselected, consecutive, adult, medical patients seeking ED care in three tertiary-care hospitals in Switzerland, France and the USA. We used multivariable logistic regression models to examine association of admission PCT levels (as a continuous predictor and across cut-offs) and 30-day mortality. We also investigated subgroup effects by main diagnosis, comorbidities and clinical features at presentation. Results: During the 30-day follow-up, 328 (4.7%) participants died. Mortality increased stepwise within higher PCT cut-offs (0.05, 0.1, 0.25, 0.5 ng/mL) from 1%, 3%, 7%, 13% to 15%, respectively. This association was also confirmed in a fully-adjusted model including age, gender, main symptom, main diagnosis and vital parameters on admission. Receiver operating characteristic (ROC) curve analysis showed that PCT differentiated well between survivors and non-survivors in the overall cohort (area under ROC curve [AUC] 0.75) with best results for patient with metabolic (AUC: 0.85) and cardiovascular disease (AUC: 0.82). Addition of PCT also improved the prognostic accuracy of the quick sequential organ failure assessment (qSOFA) score from an AUC of from 0.61 to 0.76 (p<0.001). Results were similar for other secondary endpoints including intensive care unit (ICU) admission and hospital readmission. Conclusions: In this large and heterogenous medical ED patient cohort, admission PCT was a strong and independent outcome predictor for 30-day mortality across different medical diagnoses independent of underlying infection. PCT may help to improve risk stratification in unselected medical ED patients.

Procalcitonin Improves the Glasgow Prognostic Score for Outcome Prediction in Emergency Patients with Cancer: A Cohort Study

The Glasgow Prognostic Score (GPS) is useful for predicting long-term mortality in cancer patients. Our aim was to validate the GPS in ED patients with different cancer-related urgency and investigate whether biomarkers would improve its accuracy. We followed consecutive medical patients presenting with a cancer-related medical urgency to a tertiary care hospital in Switzerland. Upon admission, we measured procalcitonin (PCT), white blood cell count, urea, 25-hydroxyvitamin D, corrected calcium, C-reactive protein, and albumin and calculated the GPS. Of 341 included patients (median age 68 years, 61% males), 81 (23.8%) died within 30 days after admission. The GPS showed moderate prognostic accuracy (AUC 0.67) for mortality. Among the different biomarkers, PCT provided the highest prognostic accuracy (odds ratio 1.6 (95% confidence interval 1.3 to 1.9), P < 0.001, AUC 0.69) and significantly improved the GPS to a combined AUC of 0.74 (P = 0.007). Considering all investigated biomarkers, the AUC increased to 0.76 (P < 0.001). The GPS performance was significantly improved by the addition of PCT and other biomarkers for risk stratification in ED cancer patients. The benefit of early risk stratification by the GPS in combination with biomarkers from different pathways should be investigated in further interventional trials.