Supplemental Data 2

Double cycling (DC) cluster computation

The computation of DC clusters was based on the definition of clusters of ineffective

efforts (IEs) published by Vaporidi et al. (S1), where a cluster was defined as 30 wasted

efforts occurring in a period of 3 minutes (a frequency of approximately 50%),

assuming a respiratory rate of 20 breaths per minute. Taking into account that the

incidence of DC is lower than the incidence of IEs, and that DC may be potentially

more harmful than IEs, we decided to use a lower threshold to define the presence of a

DC cluster. Thus, we explored clusters in 3-min periods with 3 different thresholds

selected at 10%, 20%, and 30% (i.e., at least 6, 12, or 18 DC breaths in a 3-minute

period, respectively). Once clusters were identified, they were characterized in terms of

their power (i.e. number of DC events contained in the cluster), duration and area under

the curve (AUC) determined by integrating the portion of the DC event time-series

conforming the cluster. Next table summarizes the mean characteristics of DC clusters.

Adjunct figure shows a portion of waveforms (airflow, airway pressure and volume)

from a representative patient where an episode of DC cluster was identified.

In the table: Characteristics of double cycling clusters in terms of their power, duration

and area under the curve, for the three different thresholds used to define a DC cluster.

Values are indicated as median (25th, 75th percentiles) unless otherwise specified

AUC=area under the curve; bpm=breaths per minute

Threshold (minimum number of DC events in 3-min. period assuming a respiratory rate of 20 bpm)

10% (6) 20% (12) 30% (18)

Patients with DC cluster, n(% of total patients)

40(59.7%) 17(40.3%) 15(22.4%)

Cluster per patient, n 5.5(2, 12.5) 2(1, 5.5) 2(1, 3)

Power 41(19.7, 55.8) 76.7(43, 135.3) 144(76.8, 556)

Duration (min) 15.5(9.1, 29.3) 24.2(17, 43.7) 25(18, 86.4)

AUC 20.3(9.8, 27.7) 36.9(20.4, 65.1) 71.6(38.2, 278)

In the figure: (a) Clusters of double cycling in a representative patient. Time series of

double-cycling events (black trace) computed for non-overlapping 30-second intervals

in a selected time-frame: clusters are shown as shaded areas. We characterized the

clusters by their power, duration and area under the curve (AUC). The blue trace

represents the smoothed time series (running average with n = 6 points) used by the

algorithm to identify clusters. Starting and ending points are set at the 80% point from

the maximum value of the smoothed time series. Computations were based on the

original mathematical description by Vaporidi et al. (S1), and 3 different thresholds

were explored (as reported in the table). In this particular example, clusters were

defined as period of time where double cycling represented at least a 20% breaths (i.e.,

≥2 events in 30-second intervals, assuming a respiratory rate of 20 breaths per minute).

(b) Tracings of airflow, airway pressure and volume where episodes (red marks) of

double cycling were identified by Better Care™ software. This segment corresponds to

2 min of the 26-minute cluster of the double cycling episode represented in (a).

10620 10640 10660 10680 10700 10720 10740

0

1

2

3

4

num

ber o

f DC

Power = 61 Duration (min) = 26

AUC = 30.5

(a)

(b)

time (min)

Supplemental References

S1. Vaporidi K, Babalis D, Chytas A, Lilitsis E, Kondili E, Amargianitakis V,

Chouvarda I, Maglaveras N, Georgopoulos D. Clusters of ineffective efforts during

mechanical ventilation: impact on outcome. Intensive Care Med 2017; 43:184-191.