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1.
Gait Posture ; 82: 133-137, 2020 10.
Article in English | MEDLINE | ID: mdl-32927219

ABSTRACT

BACKGROUND: In contrast to wearable tools (like in-shoe) sensors, lab-based gait assessment (using pressure-sensitive mats or cameras) only acquire data over short distances in non-ecological environments. RESEARCH QUESTION: To examine the concurrent validity of a wearable ZeroWire® footswitch system (Aurion Srl, Milan, Italy) vs. the GAITRite® walkway (CIR systems Inc., NJ, USA) for recording temporal gait parameters. METHODS: We included 40 healthy participants in a prospective, single-center study. Temporal gait parameters were recorded simultaneously with the ZeroWire® and GAITRite® systems while each participant walked at three different speeds (slow (60steps/min), comfortable and maximum). To measure the validity, we calculated the interclass correlation coefficient (ICC) and the coefficient of variation (CV) for each parameter (gait cadence, stride time, step time, stance time, and single-support and double-support times). We also performed a graphical analysis using the Bland and Altman method. RESULTS: The footswitch system showed moderate-to-excellent concurrent validity vs. the GAITRite mat. The degree of agreement between the two assessments was greatest at the maximum gait velocity showed, with very good validity (ICC > 0.91) seen for most parameters, whereas agreement ranged from moderate to very good for the other speeds. Independently of the gait speed, the highest levels of agreement were recorded for gait velocity, cadence, stride time, step time, and stance time. According to the CVs, both systems showed the same accuracy and double-support time was the more variable parameter. SIGNIFICANCE: The ZeroWire® footswitch system appears to be valid for assessing temporal gait parameters (and particularly gait cadence and stride, step and stance times in healthy participants). It is likely to be well suited to the assessment of gait parameters under ecological conditions and in dual-task gait paradigms.


Subject(s)
Foot/physiopathology , Gait/physiology , Adult , Female , Healthy Volunteers , Humans , Male , Prospective Studies
2.
Eur J Emerg Med ; 26(6): 400-404, 2019 Dec.
Article in English | MEDLINE | ID: mdl-31453847

ABSTRACT

OBJECTIVES: The early identification of patients with Acute Heart Failure Syndrome (AHFS) among patients admitted to the Emergency Department (ED) with dyspnoea can facilitate the introduction of appropriate treatments. The objectives are to identify the predictive factors for AHFS diagnosis in patients with acute dyspnoea (primary objective) and the clinical 'gestalt' (secondary objective) in ED. METHODS: PREDICA is an observational, prospective, multicentre study. The enrolment of patients admitted to the ED for nontraumatic acute dyspnoea and data collection on admission were recorded by the patient's emergency physician. The AHFS endpoints were assessed following a duplicate expert evaluation by pairs of cardiologists and emergency physicians. Step-by-step logistic regression was used to retain predictive criteria, and the area under the receiver operating characteristic (ROC) curve of the model was constructed to assess the ability of the selected factors to identify real cases. The probability of AHFS was estimated on a scale from 1 to 10 based on the emergency physician's perception and understanding (gestalt). RESULTS: Among 341 patients consecutively enrolled in three centres, 149 (44%) presented AHFS. Eight predictive factors of AHFS were detected with a performance test showing an area under the model ROC curve of 0.86. Gestalt greater than or equal to five showed sensitivity of 78% and specificity of 90% (AUC 0.91) and diagnosed 88% of AHF in our population. CONCLUSIONS: We identified several independant predictors of final AHFS diagnosis. They should contribute to the development of diagnostic strategies in ED. However, unstructured gestalts seem to perform very well alone.


Subject(s)
Dyspnea/etiology , Emergency Service, Hospital , Heart Failure/diagnosis , Acute Disease , Aged , Aged, 80 and over , Emergency Service, Hospital/statistics & numerical data , Female , Heart Failure/complications , Humans , Logistic Models , Male , Prospective Studies , ROC Curve , Risk Factors
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