Typical within and between person variability in non-invasive ventilator derived variables among clinically stable, long-term users

Abstract

BackgroundDespite increasing capacity to remotely monitor non-invasive ventilation (NIV), how remote data varies from day to day and person to person is poorly described.MethodsSingle-centre, 2-month, prospective study of clinically stable adults on long-term NIV which aimed to document NIV-device variability. Participants were switched to a ventilator with tele-monitoring capabilities. Ventilation settings and masking were not altered. Raw, extensible markup language data files were provided directly from Philips Respironics (EncoreAnywhere). A nested analysis of variance was conducted on each ventilator variable to apportion the relative variation between and within participants.ResultsTwenty-nine people were recruited (four withdrew, one had insufficient data for analyses; 1364 days of data). Mean age was 54.0 years (SD 18.4), 58.3% male with body mass index of 37.0 kg/m2 (13.7). Mean adherence was 8.53 (2.23) hours/day and all participants had adherence >4 hours/day. Variance in ventilator-derived indices was predominantly driven by differences between participants; usage (61% between vs 39% within), Apnoea–Hypopnoea Index (71% vs 29%), unintentional (64% vs 36%) and total leak (83% vs 17%), tidal volume (93% vs 7%), minute ventilation (92% vs 8%), respiratory rate (92% vs 8%) and percentage of triggered breaths (93% vs 7%).InterpretationIn this clinically stable cohort, all device-derived indices were more varied between users than the day-to-day variation within individuals. We speculate that normative ranges and thresholds for clinical intervention need to be individualised, and further research is necessary to determine the clinically important relationships between clinician targets for therapy and patient-reported outcomes.

Telemonitoring for Home-assisted Ventilation: A Narrative Review

“…Normative ranges may vary more between patients rather than within patients, as demonstrated by Jeganathan and colleagues ( 10 ). Thus, intervention thresholds should be tailored to each patient’s unique physiology.…”

Technische Aspekte und Neuerungen in der nicht-invasiven und invasiven Beatmung

“…Was die Vorhersage einer klinischen Verschlechterung durch telemedizinisch übertragene Daten angeht, gibt es eine Vielzahl von Vorschlägen bezüglich der dafür relevanten Parameter [67,68,73]. Dabei scheint die Betrachtung individueller Trends sinnvoller zu sein, als generelle Schwellenwerte zu definieren [74].…”

Monitoring Systems in Home Ventilation

“…Two studies confirmed that the ventilatory rate is higher and increases in the days preceding hospitalization for COPD exacerbation [ 50 , 51 ]. However, finding a threshold for an alert is challenging because the signal is in the same range as the normal variations of respiratory rate in stable patients [ 52 ].…”