High-Sensitivity Cardiac Troponin I and Clinical Risk Scores in Patients With Suspected Acute Coronary Syndrome.

BACKGROUND: High-sensitivity cardiac troponin assays can help to identify patients who are at low risk of myocardial infarction in the emergency department. We aimed to determine whether the addition of clinical risk scores would improve the safety of early rule-out pathways for myocardial infarction. METHODS: In 1935 patients with suspected acute coronary syndrome, we evaluated the safety and efficacy of 2 rule-out pathways alone or in conjunction with low-risk TIMI (Thrombolysis In Myocardial Infarction) (0 or 1), GRACE (Global Registry of Acute Coronary Events) (≤108), EDACS (Emergency Department Assessment of Chest Pain Score) (<16), or HEART (History, ECG, Age, Risk factors, Troponin) (≤3) scores. The European Society of Cardiology 3-hour pathway uses a single diagnostic threshold (99th percentile), whereas the High-STEACS (High-Sensitivity Troponin in the Evaluation of Patients With Acute Coronary Syndrome) pathway applies different thresholds to rule out (<5 ng/L) and rule in (>99th percentile) myocardial infarction. RESULTS: Myocardial infarction or cardiac death during the index presentation or at 30 days occurred in 14.3% of patients (276/1935). The European Society of Cardiology pathway ruled out 70%, with 27 missed events giving a negative predictive value of 97.9% (95% CI, 97.1-98.6). The addition of a HEART score ≤3 reduced the proportion ruled out by the European Society of Cardiology pathway to 25% but improved the negative predictive value to 99.7% (95% CI, 99.0-100; P<0.001). The High-STEACS pathway ruled out 65%, with 3 missed events for a negative predictive value of 99.7% (95% CI, 99.4-99.9). No risk score improved the negative predictive value of the High-STEACS pathways, but all reduced the proportion ruled out (24% to 47%; P<0.001 for all). CONCLUSIONS: Clinical risk scores significantly improved the safety of the European Society of Cardiology 3-hour pathway, which relies on a single cardiac troponin threshold at the 99th percentile to rule in and rule out myocardial infarction. Where lower thresholds are used to rule out myocardial infarction, as applied in the High-STEACS pathway, risk scores halve the proportion of patients ruled out without improving safety. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifier: NCT01852123.

Understanding how people with Parkinson's disease turn in gait from a real-world in-home dataset.

INTRODUCTION: Turning in gait digital parameters may be useful in measuring disease progression in Parkinson's disease (PD), however challenges remain over algorithm validation in real-world settings. The influence of clinician observation on turning outcomes is poorly understood. Our objective is to describe a unique in-home video dataset and explore the use of turning parameters as biomarkers in PD. METHODS: 11 participants with PD, 11 control participants stayed in a home-like setting living freely for 5 days (with two sessions of clinical assessment), during which high-resolution video was captured. Clinicians watched the videos, identified turns and documented turning parameters. RESULTS: From 85 hours of video 3869 turns were evaluated, averaging at 22.7 turns per hour per person. 6 participants had significantly different numbers of turning steps and/or turn duration between "ON" and "OFF" medication states. Positive Spearman correlations were seen between the Movement Disorders Society-sponsored revision of the Unified Parkinson's Disease Rating Scale III score with a) number of turning steps (rho = 0.893, p < 0.001), and b) duration of turn (rho = 0.744, p = 0.009) "OFF" medications. A positive correlation was seen "ON" medications between number of turning steps and clinical rating scale score (rho = 0.618, p = 0.048). Both cohorts took more steps and shorter durations of turn during observed clinical assessments than when free-living. CONCLUSION: This study shows proof of concept that real-world free-living turn duration and number of turning steps recorded can distinguish between PD medication states and correlate with gold-standard clinical rating scale scores. It illustrates a methodology for ecological validation of real-world digital outcomes.