Australasian ED doctors, predominantly specialist emergency physicians or trainees, perform the majority of ED intubations using rapid sequence induction as their preferred technique mainly for medical indications. First attempt success rate was not different between different types of EDs, and is comparable published international data. Complications are not infrequent, and are comparable to other published series. Monitoring and reporting of ED intubation practice will enable continued improvements in the safety of this high-risk procedure.
Objective
We aim to investigate whether a bundle of changes made to the practice of endotracheal intubation in our ED was associated with an improvement in first pass success rate and a reduction in the incidence of complications.
Methods
We used a prospective observational study.
Results
The data on 360 patients who were intubated during an 18‐month period following the introduction of these changes were compared with our previously published observational data. Success on first attempt at intubation improved 83.4% to 93.9% (P < 0.0001). The proportion of patients with one or more complication fell from 29.0% to 19.4% (P < 0.042). Oesophageal intubation fell from 4.0% to 0.3% (P < 0.001), and there was a non‐significant reduction in the rate of desaturation, from 15.6% to 10.9% (P < 0.07).
Conclusion
We have shown that, through the introduction of a bundle of changes that spans the domains of staff training, equipment and practice standardisation, we have made significant improvements in the safety of patients undergoing endotracheal intubation in our ED.
Background: Mast cells modulate events in wound healing. Results: Shorter forms of perlecan are produced by mast cells via proteolytic processing and alternative splicing, which contain domain V and functional endorepellin.
Conclusion:The production of these shorter forms modulates endothelial cell adhesion, proliferation, and migration. Significance: Mast cells produce specific forms of perlecan that affect endothelial cell behavior.
CXCL10 (IP10) is involved in mast cell migration to airway smooth muscle (ASM) bundles in asthma. We aimed to investigate the role of cytokine-induced MAPK activation in CXCL10 production by ASM cells from people with and without asthma. Confluent growth-arrested ASM cells were treated with inhibitors of the MAPKs ERK, p38, and JNK and transcription factor NF-κB, or vehicle, and stimulated with IL-1β, TNF-α, or IFN-γ, alone or combined (cytomix). CXCL10 mRNA and protein, JNK, NF-κB p65 phosphorylation, and Iκ-Bα protein degradation were assessed using real-time PCR, ELISA, and immunoblotting, respectively. Cytomix, IL-1β, and TNF-α induced CXCL10 mRNA expression more rapidly in asthmatic than nonasthmatic ASM cells. IL-1β and/or TNF-α combined with IFN-γ synergistically increased asthmatic ASM cell CXCL10 release. Inhibitor effects were similar in asthmatic and nonasthmatic cells, but cytomix-induced release was least affected, with only JNK and NF-κB inhibitors halving it. Notably, JNK phosphorylation was markedly less in asthmatic compared with nonasthmatic cells. However, in both, the JNK inhibitor SP600125 reduced JNK phosphorylation and CXCL10 mRNA levels but did not affect CXCL10 mRNA stability or Iκ-Bα degradation. Together, the JNK and NF-κB inhibitors completely inhibited their CXCL10 release. We concluded that, in asthmatic compared with nonasthmatic ASM cells, JNK activation was reduced and CXCL10 gene expression was more rapid following cytomix stimulation. However, in both, JNK activation did not regulate early events leading to NF-κB activation. Thus JNK and NF-κB provide independent therapeutic targets for limiting CXCL10 production and mast cell migration to the ASM in asthma.
PurposeAbstractTo determine the validity of the Australian clinical prediction tool Criteria for Screening and Triaging to Appropriate aLternative care (CRISTAL) based on objective clinical criteria to accurately identify risk of death within 3 months of admission among older patients.MethodsProspective study of ≥ 65 year-olds presenting at emergency departments in five Australian (Aus) and four Danish (DK) hospitals. Logistic regression analysis was used to model factors for death prediction; Sensitivity, specificity, area under the ROC curve and calibration with bootstrapping techniques were used to describe predictive accuracy.Results2493 patients, with median age 78–80 years (DK–Aus). The deceased had significantly higher mean CriSTAL with Australian mean of 8.1 (95% CI 7.7–8.6 vs. 5.8 95% CI 5.6–5.9) and Danish mean 7.1 (95% CI 6.6–7.5 vs. 5.5 95% CI 5.4–5.6). The model with Fried Frailty score was optimal for the Australian cohort but prediction with the Clinical Frailty Scale (CFS) was also good (AUROC 0.825 and 0.81, respectively). Values for the Danish cohort were AUROC 0.764 with Fried and 0.794 using CFS. The most significant independent predictors of short-term death in both cohorts were advanced malignancy, frailty, male gender and advanced age. CriSTAL’s accuracy was only modest for in-hospital death prediction in either setting.ConclusionsThe modified CriSTAL tool (with CFS instead of Fried’s frailty instrument) has good discriminant power to improve prognostic certainty of short-term mortality for ED physicians in both health systems. This shows promise in enhancing clinician’s confidence in initiating earlier end-of-life discussions.Electronic supplementary materialThe online version of this article (10.1007/s41999-018-0123-6) contains supplementary material, which is available to authorized users.
Background
Emergency departments (EDs) are pressured environment where patients with supportive and palliative care needs may not be identified. We aimed to test the predictive ability of the CriSTAL (Criteria for Screening and Triaging to Appropriate aLternative care) checklist to flag patients at risk of death within 3 months who may benefit from timely end‐of‐life discussions.
Methods
Prospective cohorts of >65‐year‐old patients admitted for at least one night via EDs in five Australian hospitals and one Irish hospital. Purpose‐trained nurses and medical students screened for frailty using two instruments concurrently and completed the other risk factors on the CriSTAL tool at admission. Postdischarge telephone follow‐up was used to determine survival status. Logistic regression and bootstrapping techniques were used to test the predictive accuracy of CriSTAL for death within 90 days of admission as primary outcome. Predictability of in‐hospital death was the secondary outcome.
Results
A total of 1,182 patients, with median age 76 to 80 years (IRE‐AUS), were included. The deceased had significantly higher mean CriSTAL with Australian mean of 8.1 (95% confidence interval [CI] = 7.7–8.6) versus 5.7 (95% CI = 5.1–6.2) and Irish mean of 7.7 (95% CI = 6.9–8.5) versus 5.7 (95% CI = 5.1–6.2). The model with Fried frailty score was optimal for the derivation (Australian) cohort but prediction with the Clinical Frailty Scale (CFS) was also good (areas under the receiver‐operating characteristic [AUROC] = 0.825 and 0.81, respectively). Values for the validation (Irish) cohort were AUROC = 0.70 with Fried and 0.77 using CFS. A minimum of five of 29 variables were sufficient for accurate prediction, and a cut point of 7+ or 6+ depending on the cohort was strongly indicative of risk of death. The most significant independent predictor of short‐term death in both cohorts was frailty, carrying a twofold risk of death. CriSTAL's accuracy for in‐hospital death prediction was also good (AUROC = 0.795 and 0.81 in Australia and Ireland, respectively), with high specificity and negative predictive values.
Conclusions
The modified CriSTAL tool (with CFS instead of Fried's frailty instrument) had good discriminant power to improve certainty of short‐term mortality prediction in both health systems. The predictive ability of models is anticipated to help clinicians gain confidence in initiating earlier end‐of‐life discussions. The practicalities of embedding screening for risk of death in routine practice warrant further investigation.
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