We describe the use of epidural analgesia for vaginal delivery of a parturient with Klippel-Trenaunay syndrome in whom the use of repeated magnetic resonance imaging during her obstetric care allowed us to see deep haemangiomata. This also allowed the safe sitting of an epidural catheter at L1-2 to provide analgesia for labour and delivery. Klippel-Trenaunay syndrome and the anaesthetic implications of the congenital vascular abnormalities and potential coagulopathy are discussed.

Pepper spray is used as a crowd control agent and for self‐defense. It has been thought to be safe; however, 27 persons have died in police custody after exposure to pepper spray. We report on a 21‐year‐old man, with no underlying heart disease and a normal ECG and echocardiogram in the past, who was pepper sprayed and developed ventricular fibrillation. An admission ECG showed marked ST segment elevation but subsequent coronary arteriography was normal. We hypothesize that pepper spray triggered coronary spasm, resulting in ventricular fibrillation. This report adds to a body of information that pepper spray is dangerous.

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Introduction: The accuracy of electronic health record (EHR) data to identify prevalent disease status and/or clinical events is a major concern for the use of ‘real world’ data for research. We assessed the accuracy of EHR data for specific CV conditions based on EHR data compared with manual chart review. Methods: Using a cloud-based infrastructure, Cerner’s HealtheIntent EHR data from two health systems were de-identified and aggregated. We created EHR-based computable phenotypes for patients with ASCVD, (based on prior diagnosis and procedure codes, to identify comorbidities and hospitalizations with acute limb ischemia (ALI), bleeding, acute coronary syndrome (ACS), and cerebrovascular events (stroke/transient ischemic attack/intracranial hemorrhage). Chart reviews were performed (n=1,869) to validate the hospitalization final diagnosis and prevalent comorbidities, with the first 100 charts undergoing review by two concurrent chart reviewers. When reviewers noted an absence of a comorbidity, but EHR data indicated it may be present, an automated cue was presented to the reviewer of “Are you Sure?”. Cohen’s kappas (κ) were calculated to indicate agreement inter-review of event types and comorbidities. The PPV of EHR data for hospitalization diagnosis and comorbidities compared with cue-augmented chart review as gold standard were assessed. Results: The inter-rater agreement for the hospitalization diagnosis was very good overall and highest for ACS (0.83), followed by ALI (0.75), , and cerebrovascular events (0.69). The PPV of EHR-based diagnoses for single chart reviewers was 0.93 for cerebrovascular events, 0.81 for bleeding, 0.78 for ACS, and 0.51 for ALI. Similarly, the predictive accuracy of the EHR-based computable phenotypes for comorbidities and events was variable: as high as 0.93 for hypertension, 0.87 for atrial fibrillation, and 0.86 for peripheral arterial disease, to as low as 0.13 for type 1 diabetes, 0.38 for prior transient ischemic attack, and 0.56 for heart failure with reduced ejection fraction. Providing the chart reviewer with automated cue for comorbidities improved PPV. Conclusions: Many, but not all, clinical outcomes and comorbidities can be identified using EHR-based algorithms, with variable performance depending on the condition. Human chart reviews, long considered a gold standard, may be improved using EHR data.

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