Stroke Risk Analysis, a System With a High Detection Rate of Atrial Fibrillation in Stroke and Transient Ischemic Attack.

Background and Purpose- Stroke Risk Analysis (SRA) comprises an algorithm for automated analysis of ECG monitoring, enabling the detection of paroxysmal atrial fibrillation (pxAF) and identifying patterns indicating a high risk of atrial fibrillation (R_AF). We compared Holter-enabled continuous ECG monitoring in combination with SRA (hSRA) with standard continuous ECG monitoring for pxAF detection in patients with acute ischemic stroke. Also, we sought to identify whether the detection of R_AF patterns during the first cycle (first 2 hours) of hSRA recording was associated with the detection of pxAF during the Stroke Unit stay. Methods- We enrolled 524 consecutive patients admitted in the Stroke Unit with acute ischemic stroke or transient ischemic attack with neither history of AF nor AF at admission into a prospective multicentric observational analytic clinical study with intrapatient comparison, who received both continuous ECG monitoring as well as hSRA up to 7 days. Investigators were blinded to hSRA results unless pxAF was detected on SRA. Results- Of the 524 consecutive acute stroke patients (median age, 70.0 years; 60% male; acute ischemic stroke 93%, transient ischemic attack 7%), 462 were eligible and included in the study. Among 462 patients with hSRA available for 66 hours, AF was documented by hSRA in 79 patients (17.1%). From this group, 45 AF cases (9.7%) were confirmed after review by an independent and blinded cardiologist. continuous ECG monitoring detected 21 AF cases (4.3%; P<0.0001). hSRA detected R_AF patterns in 92 patients. 35 out of the 92 R_AF patients showed an episode of AF during the Stroke Unit stay. Predictive values of R_AF patterns within the first cycle of hSRA were: sensitivity 71%, specificity 86%, positive predictive value 38%, and negative predictive value 96%. Conclusions- Automated analysis using SRA technology strongly improves pxAF detection in acute ischemic stroke patients compared with continuous ECG monitoring. The predictive value of a R_AF pattern, as detected by hSRA during the first few hours after admission, deserves further investigation.

Validation of the Spanish Version of the Pain Assessment in Advanced Dementia Scale (PAINAD-Sp) in Hospitalized Patients with Neurologic Disorders and Oncologic Patients Unable to Self-Report Their Pain.

BACKGROUND: Pain has a significant impact on hospitalized patients and is a quality indicator for nursing care. The Pain Assessment in Advanced Dementia (PAINAD) scale measures pain in people with communication disorders and advanced dementia, but it has not been validated in any other population. AIMS: The aim of this study was to validate the Spanish version (PAINAD-Sp) in hospitalized patients with neurologic disorders and in end-of-life cancer patients with difficulty self-reporting. DESIGN: The study had two phases: (1) analysis of the content by a committee of experts and (2) a cross-sectional study. SETTINGS: We collected phase 2 data from January 2017 to December 2017 in four hospitals in Barcelona: Hospital Germans Trias i Pujol, Institut Català d'Oncologia, Hospital Vall d'Hebron, and Hospital de Bellvitge. PARTICIPANTS/SUBJECTS: We included all adults who had either a neurological disorder affecting language or an oncological disease with an end-of-life prognosis and difficulty self-reporting pain. We excluded patients with a diagnosis of dementia. METHODS: The cross-sectional study included 325 patients who were simultaneously evaluated by two observers both at rest and in movement. We analyzed psychometric properties in terms of construct validity, reliability, and sensitivity to change. RESULTS: We obtained Cronbach α > .70 in both situations and an inter-rater reliability of 0.80. Confirmatory factor analysis indicated that the model adjusted adequately to a unidimensional structure. In terms of sensitivity to change, the mean difference was greater in movement than at rest (difference in means was 1.15). CONCLUSIONS: The PAINAD-Sp_Hosp scale had good psychometric qualities in terms of validity and reliability in neurology and oncology patients unable to self-report pain.