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Purpose To study the impact of pre-morbid glycemic control on the association between acute hypoglycemia in intensive care unit (ICU) patients and subsequent hospital mortality in critically ill patients. Methods We performed a multicenter, multinational, retrospective observational study of patients with available HbA1c levels within the 3-month period preceding ICU admission. We separated patients into three cohorts according to pre-admission HbA1c levels (<6.5, 6.5–7.9, ≥8.0 %, respectively). Based on published data, we defined a glucose concentration of 40–69 mg/dL (2.2–3.8 mmol/L) as moderate hypoglycemia and <40 mg/dL (<2.2 mmol/L) as severe hypoglycemia. We applied logistic regression analysis to study the impact of pre-morbid glycemic control on the relationship between acute hypoglycemia and mortality. Results A total of 3084 critically ill patients were enrolled in the study. Among these patients, with increasing HbA1c levels from <6.5, to 6.5–7.9, and to ≥8.0 %, the incidence of both moderate (3.8, 11.1, and 16.4 %, respectively; p  < 0.001) and severe (0.9, 2.5, and 4.3 %, respectively; p  < 0.001) hypoglycemia progressively and significantly increased. The relationship between the occurrence of hypoglycemic episodes in the ICU and in-hospital mortality was independently and significantly affected by pre-morbid glucose control, as assessed by adjusted odds ratio (OR) and 95 % confidence interval (CI) for hospital mortality: (1) moderate hypoglycemia: in patients with <6.5, 6.5–7.9, and ≥8.0 % of HbA1c level—OR 0.54, 95 % CI 0.25–1.16; OR 0.82, 95 % CI 0.33–2.05; OR 3.42, 95 % CI 1.29–9.06, respectively; (2) severe hypoglycemia: OR 1.50, 95 % CI 0.42–5.33; OR 1.59, 95 % CI 0.36–7.10; OR 23.46, 95 % CI 5.13–107.28, respectively (interaction with pre-morbid glucose control, p  = 0.009). We found that the higher the glucose level before admission to the ICU, the higher the mortality risk when patients experienced hypoglycemia. Conclusions In critically ill patients, chronic pre-morbid hyperglycemia increases the risk of hypoglycemia and modifies the association between acute hypoglycemia and mortality.

The inflammatory biomarker pro-adrenomedullin (ProADM) provides additional prognostic information for the risk stratification of general medical emergency department (ED) patients. The aim of this analysis was to develop a triage algorithm for improved prognostication and later use in an interventional trial. We used data from the multi-national, prospective, observational TRIAGE trial including consecutive medical ED patients from Switzerland, France and the United States. We investigated triage effects when adding ProADM at two established cut-offs to a five-level ED triage score with respect to adverse clinical outcome. Mortality in the 6586 ED patients showed a step-wise, 25-fold increase from 0.6% to 4.5% and 15.4%, respectively, at the two ProADM cut-offs (≤0.75nmol/L, >0.75-1.5nmol/L, >1.5nmol/L, p ANOVA <0.0001). Risk stratification by combining ProADM within cut-off groups and the triage score resulted in the identification of 1662 patients (25.2% of the population) at a very low risk of mortality (0.3%, n = 5) and 425 patients (6.5% of the population) at very high risk of mortality (19.3%, n = 82). Risk estimation by using ProADM and the triage score from a logistic regression model allowed for a more accurate risk estimation in the whole population with a classification of 3255 patients (49.4% of the population) in the low risk group (0.3% mortality, n = 9) and 1673 (25.4% of the population) in the high-risk group (15.1% mortality, n = 252). Within this large international multicenter study, a combined triage score based on ProADM and established triage scores allowed a more accurate mortality risk discrimination. The TRIAGE-ProADM score improved identification of both patients at the highest risk of mortality who may benefit from early therapeutic interventions (rule in), and low risk patients where deferred treatment without negatively affecting outcome may be possible (rule out).

In overcrowded emergency department (ED) care, short time to start effective antibiotic treatment has been evidenced to improve infection-related clinical outcomes. Our objective was to study factors associated with delays in initial ED care within an international prospective medical ED patient population presenting with acute infections. We report data from an international prospective observational cohort study including patients with a main diagnosis of infection from three tertiary care hospitals in Switzerland, France and the United States (US). We studied predictors for delays in starting antibiotic treatment by using multivariate regression analyses. Overall, 544 medical ED patients with a main diagnosis of acute infection and antibiotic treatment were included, mainly pneumonia (n = 218; 40.1%), urinary tract (n = 141; 25.9%), and gastrointestinal infections (n = 58; 10.7%). The overall median time to start antibiotic therapy was 214 minutes (95% CI: 199, 228), with a median length of ED stay (ED LOS) of 322 minutes (95% CI: 308, 335). We found large variations of time to start antibiotic treatment depending on hospital centre and type of infection. The diagnosis of a gastrointestinal infection was the most significant predictor for delay in antibiotic treatment (+119 minutes compared to patients with pneumonia; 95% CI: 58, 181; p<0.001). We found high variations in hospital ED performance in regard to start antibiotic treatment. The implementation of measures to reduce treatment times has the potential to improve patient care.

ObjectivesThe National Early Warning Score (NEWS) helps to estimate mortality risk in emergency department (ED) patients. This study aimed to investigate whether the prognostic value of the NEWS at ED admission could be further improved by adding inflammatory blood markers (ie, white cell count (WCC), procalcitonin (PCT) and midregional-proadrenomedullin (MR-proADM).DesignSecondary analysis of a multinational, observational study (TRIAGE study, March 2013–October 2014).SettingThree tertiary care centres in France, Switzerland and the USA.ParticipantsA total of 1303 adult medical patients with complete NEWS data seeking ED care were included in the final analysis. NEWS was calculated retrospectively based on admission data.Main outcome measuresThe primary outcome was all-cause 30-day mortality. Secondary outcome was intensive care unit (ICU) admission. We used multivariate regression analyses to investigate associations of NEWS and blood markers with outcomes and area under the receiver operating curve (AUC) as a measure of discrimination.ResultsOf the 1303 included patients, 54 (4.1%) died within 30 days. The NEWS alone showed fair prognostic accuracy for all-cause 30-day mortality (AUC 0.73), with a multivariate adjusted OR of 1.26 (95% CI 1.13 to 1.40, p<0.001). The AUCs for the prediction of mortality using the inflammatory markers WCC, PCT and MR-proADM were 0.64, 0.71 and 0.78, respectively. Combining NEWS with all three blood markers or only with MR-proADM clearly improved discrimination with an AUC of 0.82 (p=0.002). Combining the three inflammatory markers with NEWS improved prediction of ICU admission (AUC 0.70vs0.65 when using NEWS alone, p=0.006).ConclusionNEWS is helpful in risk stratification of ED patients and can be further improved by the addition of inflammatory blood markers. Future studies should investigate whether risk stratification by NEWS in addition to biomarkers improve site-of-care decision in this patient population.Trial registration number NCT01768494; Post-results.

Introduction Early risk stratification in the emergency department (ED) is vital to reduce time to effective treatment in high-risk patients and to improve patient flow. Yet, there is a lack of investigations evaluating the incremental usefulness of multiple biomarkers measured upon admission from distinct biological pathways for predicting fatal outcome and high initial treatment urgency in unselected ED patients in a multicenter and multinational setting. Method We included consecutive, adult, medical patients seeking ED care into this observational, cohort study in Switzerland, France and the USA. We recorded initial clinical parameters and batch-measured prognostic biomarkers of inflammation (pro-adrenomedullin [ProADM]), stress (copeptin) and infection (procalcitonin). Results During a 30-day follow-up, 331 of 7132 (4.6 %) participants reached the primary endpoint of death within 30 days. In logistic regression models adjusted for conventional risk factors available at ED admission, all three biomarkers strongly predicted the risk of death (AUC 0.83, 0.78 and 0.75), ICU admission (AUC 0.67, 0.69 and 0.62) and high initial triage priority (0.67, 0.66 and 0.58). For the prediction of death, ProADM significantly improved regression models including (a) clinical information available at ED admission (AUC increase from 0.79 to 0.84), (b) full clinical information at ED discharge (AUC increase from 0.85 to 0.88), and (c) triage information (AUC increase from 0.67 to 0.83) ( p <0.01 for each comparison). Similarly, ProADM also improved clinical models for prediction of ICU admission and high initial treatment urgency. Results were robust in regard to predefined patient subgroups by center, main diagnosis, presenting symptoms, age and gender. Conclusions Combination of clinical information with results of blood biomarkers measured upon ED admission allows early and more adequate risk stratification in individual unselected medical ED patients. A randomized trial is needed to answer the question whether biomarker-guided initial patient triage reduces time to initial treatment of high-risk patients in the ED and thereby improves patient flow and clinical outcomes. Trial registration ClinicalTrials.gov NCT01768494 . Registered January 9, 2013.

Reducing delays in hospital discharge is important to improve transition processes and reduce health care costs. The recently proposed post-acute care discharge score focusing on the self-care abilities before hospital admission allows early identification of patients with a need for post-acute care. New limitations in self-care abilities identified during hospitalization may also indicate a risk. Our aim was to investigate whether the addition of the post-acute care discharge score and a validated self-care instrument would improve the prognostic accuracy to predict post-acute discharge needs in unselected medical inpatients. We included consecutive adult medical and neurological inpatients. Logistic regression models with area under the receiver operating characteristic curve were calculated to study associations of post-acute discharge score and self-care index with post-acute discharge risk. We calculated joint regression models and reclassification statistics including the net reclassification index and integrated discrimination improvement to investigate whether merging the self-care index and the post-acute discharge score leads to better diagnostic accuracy. Out of 1342 medical and 402 neurological patients, 150 (11.18%) and 94 (23.38%) have reached the primary endpoint of being discharged to a post-acute care facility. Multivariate analysis showed that the self-care index is an outcome predictor (OR 0.897, 95%CI 0.864-0.930). By combining the self-care index and the post-acute care discharge score discrimination for medical (from area under the curve 0.77 to 0.83) and neurological patients (from area under the curve 0.68 to 0.78) could be significantly improved. Reclassification statistics also showed significant improvements with regard to net reclassification index (14.2%, p<0.05) and integrated discrimination improvement (4.83%, p<0.05). Incorporating an early assessment of patients' actual intrahospital self-care ability to the post-acute care discharge score led to an improved prognostic accuracy for identifying adult, medical and neurological patients at risk for discharge to a post-acute care facility.

Background Patients 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/design Prospective, 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. Discussion Using 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 registration ClinicalTrials.gov Identifier, NCT01768494

The use of nanotechnology has the potential to revolutionize the detection and treatment of cancer. Developments in protein engineering and materials science have led to the emergence of new nanoscale targeting techniques, which offer renewed hope for cancer patients. While several nanocarriers for medicinal purposes have been approved for human trials, only a few have been authorized for clinical use in targeting cancer cells. In this review, we analyze some of the authorized formulations and discuss the challenges of translating findings from the lab to the clinic. This study highlights the various nanocarriers and compounds that can be used for selective tumor targeting and the inherent difficulties in cancer therapy. Nanotechnology provides a promising platform for improving cancer detection and treatment in the future, but further research is needed to overcome the current limitations in clinical translation. Graphical Abstract