Cerebrospinal fluid biomarker results in relation to neuropathological dementia diagnoses.

BACKGROUND: Clinical dementia diagnoses are not always consistent with neuropathological findings. As correct diagnosis is important for treatment and care, new diagnostic possibilities for dementia are in demand. Cerebrospinal fluid biomarkers should ideally be able to identify ongoing processes in the brain, but need to be further compared with neuropathological findings for evaluation of their diagnostic validity. METHODS: This study included 43 patients with a clinical dementia disorder. All patients were neuropathologically examined at the University Hospital in Lund, Sweden, during the years 2001-2008, and all had a lumbar puncture carried out as part of the clinical investigation during the time of cognitive impairment. RESULTS: Of eight patients, five with Alzheimer's disease had elevated total tau protein (T-tau) and decreased amyloid beta 1-42 protein (Abeta42), while both values for the other three patients were normal. Slightly elevated T-tau and/or decreased Abeta42 were also seen in several patients with other dementia diagnoses such as Lewy body disease, frontotemporal lobar degeneration and vascular dementia. Furthermore, T-tau levels did not differ markedly between patients with morphologically tau-positive and tau-negative frontotemporal lobar degeneration. Also, seven of nine patients with Creutzfeldt-Jacob disease exhibited pronounced elevation in T-tau concentration. CONCLUSION: From this rather limited study, being the first of its kind in Sweden, we may conclude that there is no perfect concordance between cerebrospinal fluid biomarker levels and pathological findings, which should be taken into account in the clinical diagnostic setting.

Association between use of pre-hospital ECG and 30-day mortality: A large cohort study of patients experiencing chest pain.

BACKGROUND: In the assessment of patients with chest pain, there is support for the use of pre-hospital ECG in the literature and in the care guidelines. Using propensity score methods, we aim to examine whether the mere acquisition of a pre-hospital ECG among patients with chest pain affects the outcome (30-day mortality). METHODS: The association between pre-hospital ECG and 30-day mortality was studied in the overall cohort (n=13151), as well as in the one-to-one matched cohort with 2524 patients not examined with pre-hospital ECG and 2524 patients examined with pre-hospital ECG. RESULTS: In the overall cohort, 21% (n=2809) did not undergo an ECG tracing in the pre-hospital setting. Among those who had pain during transport, 14% (n=1159) did not undergo a pre-hospital ECG while 32% (n=1135) of those who did not have pain underwent an ECG tracing. In the overall cohort, the OR for 30-day mortality in patients who had a pre-hospital ECG, as compared with those who did not, was 0.63 (95% CI 0.05-0.79; p<0.001). In the matched cohort, the OR was 0.65 (95% CI 0.49-0.85; p<0.001). Using the propensity score, in the overall cohort, the corresponding HR was 0.65 (95% CI 0.58-0.74). CONCLUSION: Using propensity score methods, we provide real-world data demonstrating that the adjusted risk of death was considerably lower among the cases in whoma pre-hospital ECG was used. The PH-ECG is underused among patients with chest discomfort and the mere acquisition of a pre-hospital ECG may reduce mortality.

Emergency medical dispatch priority in chest pain patients due to life threatening conditions: A cohort study examining circadian variations and impact of the education.

BACKGROUND AND AIMS: We examined the accuracy in assessments of emergency dispatchers according to their education and time of the day. We examined this in chest pain patients who were diagnosed with a potentially life-threatening condition (LTC) or died within 30days. METHODS: Among 2205 persons, 482 died, 1631 experienced an acute coronary syndrome (ACS), 1914 had a LTC. Multivariable logistic regression was used to study how time of the call and the dispatcher's education were associated with the risk of missing to give priority 1 (the highest). RESULTS: Among patients who died, a 7-fold increase in odds of missing to give priority 1 was noted at 1.00pm, as compared with midnight. Compared with assistant nurses, odds ratio for dispatchers with no (medical) training was 0.34 (95% CI 0.14 to 0.77). Among patients with an ACS, odds ratio for calls arriving before lunch was 2.02 (95% CI 1.22 to 3.43), compared with midnight. Compared with assistant nurses, odds ratio for operators with no training was 0.23 (95% CI 0.13 to 0.40). Similar associations were noted for those with any LTC. Dispatcher's education was not associated with the patient's survival. CONCLUSIONS: In this group of patients, which experience substantial mortality and morbidity, the risk of not obtaining highest dispatch priority was increased up to 7-fold during lunchtime. Dispatch operators without medical education had the lowest risk, compared with nurses and assistant nurses, of missing to give priority 1, at the expense of lower positive predictive value. KEY MESSAGES: What is already known about this subject? Use of the emergency medical service (EMS) increases survival among patients with acute coronary syndromes. It is unknown whether the efficiency - as judged by the ability to identify life-threatening cases among patients with chest pain - varies according to the dispatcher's educational level and the time of day. What does this study add? We provide evidence that the dispatcher's education does not influence survival among patients calling the EMS due to chest discomfort. However, medically educated dispatchers are at greatest risk of missing to identify life-threatening cases, which is explained by more parsimonious use of the highest dispatch priority. We also show that the risk of missing life-threatening cases is at highest around lunch time. How might this impact on clinical practice? Dispatch centers are operated differently all over the world and chest discomfort is one of the most frequent symptoms encountered; we provide evidence that it is safe to operate a dispatch center without medically trained personnel, who actually miss fewer cases of acute coronary syndromes. However, non-medically trained dispatchers consume more pre-hospital resources.

Could prioritisation by emergency medicine dispatchers be improved by using computer-based decision support? A cohort of patients with chest pain.

BACKGROUND: To evaluate whether a computer-based decision support system could improve the allocation of patients with acute coronary syndrome (ACS) or a life-threatening condition (LTC). We hypothesised that a system of this kind would improve sensitivity without compromising specificity. METHODS: A total of 2285 consecutive patients who dialed 112 due to chest pain were asked 10 specific questions and a prediction model was constructed based on the answers. We compared the sensitivity of the dispatchers' decisions with that of the model-based decision support model. RESULTS: A total of 2048 patients answered all 10 questions. Among the 235 patients with ACS, 194 were allocated the highest prioritisation by dispatchers (sensitivity 82.6%) and 41 patients were given a lower prioritisation (17.4% false negatives). The allocation suggested by the model used the highest prioritisation in 212 of the patients with ACS (sensitivity of 90.2%), while 23 patients were underprioritised (9.8% false negatives). The results were similar when the two systems were compared with regard to LTC and 30-day mortality. This indicates that computer-based decision support could be used either for increasing sensitivity or for saving resources. Three questions proved to be most important in terms of predicting ACS/LTC, [1] the intensity of pain, [2] the localisation of pain and [3] a history of ACS. CONCLUSION: Among patients with acute chest pain, computer-based decision support with a model based on a few fundamental questions could improve sensitivity and reduce the number of cases with the highest prioritisation without endangering the patients.

Could ten questions asked by the dispatch center predict the outcome for patients with chest discomfort?

BACKGROUND AND AIMS: From 2009 to 2010, approximately 14,000 consecutive persons who called for the EMS due to chest discomfort were registered. From the seventh month, dispatchers ask 2285 patient ten pre-specified questions. We evaluate which of these questions was independently able to predict an acute coronary syndrome (ACS), life-threatening condition (LTC) and death. METHODS: The questions asked mainly dealt with previous history and type of symptoms, each with yes/no answers. The dispatcher took a decision on priority; 1) immediately with sirens/blue light; 2) EMS on the scene within 30min; 3) normal waiting time.We examined the relationship between the answers to these questions and subsequent dispatch priority, as well as outcome, in terms of ACS, LTC and all-cause mortality. RESULTS: 2285 patients (mean age 67years, 49% women) took part, of which 12% had a final diagnosis of ACS and 15% had a LTC. There was a significant relationship between all the ten questions and the priority given by dispatchers. Localisation of the discomfort to the center of the chest, more intensive pain, history of angina or myocardial infarction as well as experience of cold sweat were the most important predictors when evaluating the probability of ACS and LTC. Not breathing normally and having diabetes were related to 30-day mortality. CONCLUSIONS: Among individuals, who call for the EMS due to chest discomfort, the intensity and the localisation of the pain, as well as a history of ischemic heart disease, appeared to be the most strongly associated with outcome.