BackgroundDelayed neuropsychological sequelae (DNS) commonly occur after recovery from acute carbon monoxide (CO) poisoning. The preventive role and the indications for hyperbaric oxygen therapy in the acute setting are still controversial. Early identification of patients at risk in the Emergency Department might permit an improvement in quality of care. We conducted a retrospective study to identify predictive risk factors for DNS development in the Emergency Department.MethodsWe retrospectively considered all CO-poisoned patients admitted to the Emergency Department of Careggi University General Hospital (Florence, Italy) from 1992 to 2007. Patients were invited to participate in three follow-up visits at one, six and twelve months from hospital discharge. Clinical and biohumoral data were collected; univariate and multivariate analysis were performed to identify predictive risk factors for DNS.ResultsThree hundred forty seven patients were admitted to the Emergency Department for acute CO poisoning from 1992 to 2007; 141/347 patients participated in the follow-up visit at one month from hospital discharge. Thirty four/141 patients were diagnosed with DNS (24.1%). Five/34 patients previously diagnosed as having DNS presented to the follow-up visit at six months, reporting a complete recovery. The following variables (collected before or upon Emergency Department admission) were associated to DNS development at one month from hospital discharge in the univariate analysis: CO exposure duration >6 hours, a Glasgow Coma Scale (GCS) score <9, seizures, systolic blood pressure <90 mmHg, elevated creatine phosphokinase concentration and leukocytosis. There was no significant correlation with age, sex, voluntary exposure, headache, transient loss of consciousness, GCS between 14 and 9, arterial lactate and carboxyhemoglobin concentration. The multivariate analysis confirmed as independent prognostic factors GCS <9 (OR 7.15; CI 95%: 1.04-48.8) and leukocytosis (OR 3.31; CI 95%: 1.02-10.71).ConclusionsOur study identified several potential predictive risk factors for DNS. Treatment algorithms based on an appropriate risk-stratification of patients in the Emergency Department might reduce DNS incidence; however, more studies are needed. Adequate follow-up after hospital discharge, aimed at correct recognition of DNS, is also important.

Type A aortic dissection (AD) is a deadly disease. Rapid identification of patients requiring immediate advanced aortic imaging or transfer to specialized centers is needed to improve outcomes. We evaluated the diagnostic performance of transthoracic focus cardiac ultrasound (FOCUS) performed by emergency physicians, alone and in combination with the aortic dissection detection (ADD) risk score in suspected type A AD. This was a prospective study performed on patients with suspected type A AD. FOCUS evaluated the presence of intimal flap/intramural hematoma (direct signs of AD), ascending aorta dilatation, aortic valve insufficiency or pericardial effusion/tamponade (indirect signs of AD). The ADD risk score of each patient was calculated according to guidelines. The final diagnosis was established after review of complete clinical data. 50 (18%) patients of 281 had a final diagnosis of type A AD. Detection of any FOCUS sign (direct or indirect) of AD had a sensitivity of 88% (95% CI 76-95%) for the diagnosis of type A AD. Presence of ADD risk score > 0 or detection of any FOCUS sign increased diagnostic sensitivity to 96% (95% CI 86-99%). Detection of direct FOCUS signs had a specificity of 94% (95% CI 90-97%), while combination of ADD risk score > 1 with detection of direct FOCUS signs had a specificity of 98% (95% CI 96-99%). FOCUS demonstrated acceptable accuracy as a triage tool to rapidly identify patients with suspected type A AD needing advanced aortic imaging or transfer, but it cannot be used as a stand-alone test even if combined with ADD risk score classification.

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The ADD risk score stratifies patients for the risk of AD. ADD risk score>0 is highly sensitive and poorly specific for the diagnosis in AD. The presence of ADD risk score=0 per se does not accurately exclude AD. In patients with ADD risk score=0, chest X-ray provides limited diagnostic information.

Computational fluid dynamics (CFD) can have a complementary predictive role alongside the exquisite visualization capabilities of 4D cardiovascular magnetic resonance (CMR) imaging. In order to exploit these capabilities (e.g., for decision-making), it is necessary to validate computational models against real world data. In this study, we sought to acquire 4D CMR flow data in a controllable, experimental setup and use these data to validate a corresponding computational model. We applied this paradigm to a case of congenital heart disease, namely, transposition of the great arteries (TGA) repaired with arterial switch operation. For this purpose, a mock circulatory loop compatible with the CMR environment was constructed and two detailed aortic 3D models (i.e., one TGA case and one normal aortic anatomy) were tested under realistic hemodynamic conditions, acquiring 4D CMR flow. The same 3D domains were used for multi-scale CFD simulations, whereby the remainder of the mock circulatory system was appropriately summarized with a lumped parameter network. Boundary conditions of the simulations mirrored those measured in vitro. Results showed a very good quantitative agreement between experimental and computational models in terms of pressure (overall maximum % error = 4.4% aortic pressure in the control anatomy) and flow distribution data (overall maximum % error = 3.6% at the subclavian artery outlet of the TGA model). Very good qualitative agreement could also be appreciated in terms of streamlines, throughout the cardiac cycle. Additionally, velocity vectors in the ascending aorta revealed less symmetrical flow in the TGA model, which also exhibited higher wall shear stress in the anterior ascending aorta.