A rare presentation of mycotic cerebral aneurysm, subarachnoid haemorrhage, and mitral valve aneurysm in left-sided lnfective endocarditis: a case report and literature review.

Background: Infective endocarditis (IE) can present as a syndromic-like condition with multisystem involvement; this can make early diagnosis particularly challenging. Rarely, left-sided IE can lead to mitral valve aneurysm formation. Showering of septic emboli to the cerebral circulation may result in a mycotic aneurysm that can rupture, leading to haemorrhagic stroke, as in this case. Case summary: A 28-year-old male presented with a triad of subarachnoid haemorrhage (SAH) from mycotic cerebral aneurysm rupture, left-sided aortic and mitral valve IE causing severe regurgitation and aorto-mitral curtain fistula and mitral valve aneurysm formation. The SAH was the main initial presentation and was immediately treated with coiling by an interventional radiologist. However, the patient later developed heart failure due to severe aortic and mitral valve regurgitation that led to the diagnosis of IE. The patient underwent aortic and mitral valve replacements procedure10 days after SAH presentation. He then recovered satisfactorily from the operationa and successfully discharged home after completeing his course of intravenous antibiotics. Discussion: In this article, we shed some light on this unusual syndromic presentation, elaborate on the underlying mechanism, the ultimate importance of clinical examination, pitfalls in diagnosis, the important role of the heart team in IE, and finally the timing of surgery after SAH.

Extracellular volume fraction improves risk-stratification for ventricular arrhythmias and sudden death in non-ischaemic cardiomyopathy.

AIMS: To evaluate whether cardiac magnetic resonance (CMR)-based parametric mapping and strain analysis can improve the risk-stratification for ventricular arrhythmias (VA) and sudden death (SD) in non-ischaemic cardiomyopathy (NICM). METHODS AND RESULTS: Secondary analysis of a prospective single-centre-registry (NCT02326324), including 703 consecutive NICM patients, 618 with extracellular volume (ECV) available. The combined primary endpoint included appropriate implantable cardioverter defibrillator therapies, sustained ventricular tachycardia, resuscitated cardiac arrest and SD. During a median follow-up of 21 months, 14 patients (2%) experienced the primary endpoint. Native T1 was not associated with the primary endpoint. Left ventricular global longitudinal strain lost its significant association after adjustment for left ventricular ejection fraction (LVEF). Among patients with ECV available, 11 (2%) reached the primary endpoint. Mean ECV was significantly associated with the primary endpoint and the best cut-off was 30%. ECV ≥ 30% was the strongest independent predictor of the primary endpoint (hazard ratio 14.1, P = 0.01) after adjustment for late gadolinium enhancement (LGE) and LVEF. ECV ≥ 30% discriminated the arrhythmic risk among LGE+ cases and among those with LVEF ≤ 35%. A simple clinical risk-stratification model, based on LGE, LVEF ≤ 35% and ECV ≥ 30%, achieved an excellent predictive ability (Harrell's C 0.82) and reclassified the risk of 32% of the study population as compared to LVEF ≤ 35% alone. CONCLUSIONS: Comprehensive CMR evaluation in NICM showed that ECV was the only parameter with an independent and strong predictive value for VA/SD, on top of LGE and LVEF. A risk-stratification model based on LGE, LVEF ≤ 35% and ECV ≥ 30% achieved an excellent predictive ability for VA/SD. CLINICAL TRIAL REGISTRATION: UHSM CMR study (NCT02326324) https://clinicaltrials.gov/ct2/show/NCT02326324.

Predicting hospitalisation for heart failure and death in patients with, or at risk of, heart failure before first hospitalisation: a retrospective model development and external validation study.

BACKGROUND: Identifying people who are at risk of being admitted to hospital (hospitalised) for heart failure and death, and particularly those who have not previously been hospitalised for heart failure, is a priority. We aimed to develop and externally validate a prognostic model involving contemporary deep phenotyping that can be used to generate individual risk estimates of hospitalisation for heart failure or all-cause mortality in patients with, or at risk of, heart failure, but who have not previously been hospitalised for heart failure. METHODS: Between June 1, 2016, and May 31, 2018, 3019 consecutive adult patients (aged ≥16 years) undergoing cardiac magnetic resonance (CMR) at Manchester University National Health Service Foundation Trust, Manchester, UK, were prospectively recruited into a model development cohort. Candidate predictor variables were selected according to clinical practice and literature review. Cox proportional hazards modelling was used to develop a prognostic model. The final model was validated in an external cohort of 1242 consecutive adult patients undergoing CMR at the University of Pittsburgh Medical Center Cardiovascular Magnetic Resonance Center, Pittsburgh, PA, USA, between June 1, 2010, and March 25, 2016. Exclusion criteria for both cohorts included previous hospitalisation for heart failure. Our study outcome was a composite of first hospitalisation for heart failure or all-cause mortality after CMR. Model performance was evaluated in both cohorts by discrimination (Harrell's C-index) and calibration (assessed graphically). FINDINGS: Median follow-up durations were 1118 days (IQR 950-1324) for the development cohort and 2117 days (1685-2446) for the validation cohort. The composite outcome occurred in 225 (7·5%) of 3019 patients in the development cohort and in 219 (17·6%) of 1242 patients in the validation cohort. The final, externally validated, parsimonious, multivariable model comprised the predictors: age, diabetes, chronic obstructive pulmonary disease, N-terminal pro-B-type natriuretic peptide, and the CMR variables, global longitudinal strain, myocardial infarction, and myocardial extracellular volume. The median optimism-adjusted C-index for the externally validated model across 20 imputed model development datasets was 0·805 (95% CI 0·793-0·829) in the development cohort and 0·793 (0·766-0·820) in the external validation cohort. Model calibration was excellent across the full risk profile. A risk calculator that provides an estimated risk of hospitalisation for heart failure or all-cause mortality at 3 years after CMR for individual patients was generated. INTERPRETATION: We developed and externally validated a risk prediction model that provides accurate, individualised estimates of the risk of hospitalisation for heart failure and all-cause mortality in patients with, or at risk of, heart failure, before first hospitalisation. It could be used to direct intensified therapy and closer follow-up to those at increased risk. FUNDING: The UK National Institute for Health Research, Guerbet Laboratories, and Roche Diagnostics International.