Participants

All consecutive patients diagnosed with SMA between June 2019 and June 2023 and treated by GT (onasemnogene abeparvovec) at Necker hospital were included in the study. GT indication was discussed in a bimensal national expert committee for all infants with SMA under 2 years at diagnosis and under 12 kg. Patients with severe respiratory impairment or bulbar signs, need for respiratory support or a profound motor deficit did not receive GT indication after thorough discussion by the committee and were not included in this study. Patients were excluded from the study if the IMU-based protocol could not be respected by the child (ability to crawl and flip without cooperation capacity).

GT was administered as a single dose in the intensive care unit. Specific biological monitoring and steroid prophylactic medication were carried out as recommended [7]. We did not add a minimum follow-up time as an inclusion criteria as the internal consistency and concurrent validity analyzes (see statistical analyses sub-section) do not require a minimum follow-up time.

Between June 2019 and June 2023, 23 consecutive patients were included in the study. No patient treated by GT was excluded at baseline.

Most patients had type 1 SMA (19/23), three had type 2 and one was a presymptomatic patient (sister of an index case in family). Age at diagnosis ranged from 3.1 to 20.9 months. Patient 6 is the only patient with respiratory impairment at inclusion necessitating nocturnal noninvasive ventilation. Other participant’s baseline characteristics are represented in Table 1.

Table 1 Patients’ baseline characteristics before gene therapy and IMU recordings moments during follow-up after gene therapy (last right column)Clinical follow-up

Close clinical follow-up was performed for each participant at initial stage (M0) and at M1, M3, M6, M12, M18 and M24 after GT infusion. Clinical examination was performed by experimented pediatric neurologists (ID, CB) and clinical scores (CHOPINTEND, HINE2 and Bayley III [gross motor section] scores) were performed by specifically trained occupational therapists (ED, VLG, AH). Patients living far away from the follow-up center were seen only at initial stage, at M12 and at M24 (patients 4, 10, 15 and 19).

Compound muscle action potentials (CMAPS) were measured for the 4 principal nerves (median, ulnar, fibular and tibial) at M0, M6, M12, M18 and M24 by an experimented neurophysiologist (CG) as previously described [39].

IMU measurement

IMU measurements were performed at each follow-up evaluation at M0, M1, M3, M6, M12, M18 and M24.

Sensors (four synchronized tri-axial IMUs [accelerometer, gyroscope and magnetometer] wirelessly connected to a computer, Movella XSens® MTw, weight 16 g, dimension 47 × 30 × 13 mm, sampling frequency 100 Hz) were placed on both wrists and both feet, with anatomical references accordingly to previous IMU studies [24]. In addition, movements from the elbows were also monitored because muscular weakness in SMA affects predominantly proximal muscles. Sensors were firmly fixed to the body with single use cohesive bandages (Peha-Haft®). The elbow sensors were fixed just proximal to the elbow, at the posterior side on the distal part of the upper arm, so that the child's elbow movements did not alter the sensor positioning during the measurement. The wrist sensors were fixed at the posterior side of the arm distally and the foot sensors at the dorsal side of the feet. Sensors were strongly maintained in place by cohesive bandages. Spontaneous child movements measured in the study were not strong enough to cause sensor’s displacement during the measurement.

In the case of infants’ measurements it is important to avoid any caregivers’ parasite movement [34]. In the present study, parasite accelerations provided by caregivers were avoided by asking parents to stimulate the child only vocally and visually without any physical contact during the measurement tasks. Video recordings were used to identify any physical parent/child contact. In case of prolonged parent/child contacts during the experiment, the recording segment was to be removed. In practice parents respected the directives and it was not necessary to remove any recording segments. This implied a relatively short measurement time in a semi-controlled environment in a dedicated room at the hospital. To evaluate if external stimulation had an influence on the IMU-parameters, measurements with and without playset were performed. The measurement protocol and set up is represented on Fig. 1.

Fig. 1

Schematic representation of the IMU-measurement protocol. One measurement was made of 3 acquisitions. Acquisition 1: participant lying on the back wearing 4 IMUs on both wrist and both feet without a playset for 10 min (left illustration). Acquisition 2: participant lying on the back wearing 4 IMUs on both wrist and both feet with a playset for 10 min (middle illustration). Acquisition 3: participant lying on the back wearing 4 IMUs on both wrist and both elbows with a playset for 5 min (right illustration). The total measurement duration was 25 min. IMU: Inertial Measurement Unit

One measurement included 3 distinct acquisitions.

Acquisition 1: participant lying on the back wearing 4 IMUs on both wrists and both feet without a playset for 10 min.

Acquisition 2: participant lying on the back wearing 4 IMUs on both wrists and both feet with a playset (SOLINI® reference 171,803, see Supplementary material 2) for 10 min.

Acquisition 3: participant lying on the back wearing 4 IMUs on both wrists and both elbows with a playset for 5 min.

The total measurement duration was 25 min.

To control the readiness of the child to participate, the time of the evaluation, the duration since last meal and the duration since last sleep was systematically registered. Tolerance and participation of the child was evaluated with Brazelton scale. Brazelton 4 and 5 (respectively “awake, alert state” and “alert but fussy state”) were considered as good participation and Brazelton states 3 and 6 (respectively “drowsy state” and “cry”) were considered as poor participation. For Brazelton states 1 and 2 the measures were postponed by 1 h to allow a better participation of the child.

Parameter computation

IMU-based parameters were computed on the norm of the free acceleration (acceleration without gravity given by the sensors) as follows:

$$a\left(t\right)=\sqrt_(t)}^+_(t)}^+_(t)}^}$$

\(_\), \(_\) and \(_\) being the free accelerations (acceleration without gravity) given by the sensors in tri-axial coordinates of the sensor frame, t being the time.

XSens® MTw sensors provide two acceleration outputs: the acceleration in the sensor’s frame which includes the gravity component in it and the free acceleration which is the acceleration sensed by the IMU without the gravity component expressed in the Earth-reference frame. Free acceleration is obtained by 3D angular velocity, 3D acceleration and 3D earth magnetic field combined with Xsens® sensor fusion algorithms. We ensured that magnetic field was not disturbed by ferromagnetic material. A 3D calibration measurement was performed before each measurement for the four sensors as recommended by the device supplier.

We computed following parameters:

Norm acceleration 95th centile (||A||_95). The computation process is simple and reproducible. The statistic 95th centile is a measure of the children’s peak performance outliers excluded, representing the higher values of accelerations the wearer is able to produce over the 10 or 5 min acquisitions [31, 38].

Counts per minute computed on the norm acceleration (||A||_CPM). Counts per minute are widely used in actimetric studies and allow comparison of our results with literature. To increase comparability, we used the open Python library agcounts version 0.2.0 function get_counts by Neishaboury et al. 2022 [35] with 60 s epochs length. The mean values of the counts of the 60 s epochs over the 10 or 5 min acquisitions were taken.

For each parameter, we computed the mean value of the right and the left sensors. Hence, we obtained four parameters for each acquisition: two (i.e. ||A||_95 and ||A||_CPM) for the wrist sensors and two for the foot sensors in acquisition 1 and 2; two for the wrist sensors and two for the elbow sensors in acquisition 3.

The raw norm acceleration and the movement counts obtained for one typical severe SMA infant over a 24 months follow-up period for the wrist and the foot sensors of acquisition 1 are represented on Fig. 2. Corresponding parameters ||A||_95 and ||A||_CPM are also represented using horizontal dashed lines on Fig. 2. Note the visual increase of the norm of the acceleration and of the computed parameters with time.

Fig. 2

Typical norm acceleration raw data as a function of time for acquisition 1 for one SMA type 1 infant before gene therapy (M0) and 3, 6, 12 and 24 months (M3, M6, M12, M24) after gene therapy for the left wrist sensor (A/) and for the left foot sensor (B/). Sampling frequency is 100 Hz. Corresponding movement counts computed for the norm acceleration with Neishaboury et al. 2022 [35] open Python library with 60 s epochs length for the left wrist sensor (C/) and for the left foot sensor (D/). The horizontal grey dashed lines represent the norm acceleration 95th centile for each measurement (M0, M3, M6…) in graphic A/ and B/ and the mean of movement counts for each measurement (M0, M3, M6…) in graphic C/ and D/. Note the visual increase of the norm of the acceleration and of the computed parameters with time. IMU: Inertial Measurement Unit; SMA: spinal muscular atrophy

Statistical analysis

The definition for reliability, internal consistency, concurrent validity and responsiveness are those previously given in COSMIN study consensus statement [40, 41].

Internal consistency analysis (reliability analysis)

Reliability of IMU-parameters in semi-controlled tasks has already been established through test/retest experiments [30], thus no test–retest experiment was performed.

It is established that IMU recordings are variable within a day as a function of the daily life activities [42]. As our recording protocol is short, we oriented our study design to evaluate if the IMU-parameters were impacted by external stimulation. External simulation was provided by the use or not of a playset, and measurement with and without playset were performed. IMU-parameters obtained from acquisition with and without a playset were compared (intra-protocol robustness of the measure). The Interclass Correlation Coefficient (ICC) between acquisition 1 (without playset) versus acquisition 2 (with playset) of a same measurement for wrist and foot sensors were computed.

As the IMUs may not have negligible weigh (16 g) for infants with poor motor function, the effect of the presence or not of an elbow sensor on the wrist sensor parameters was evaluated. The IMU-parameters form the wrist sensors obtained from acquisition with and without the elbow sensors were compared. The ICCs between acquisition 2 (without elbow sensors) versus acquisition 3 (with elbow sensors) of a same measurement for wrist sensors were computed.

Concurrent validity analysis

Concurrent validity of IMU-based parameters was evaluated with the correlation with gold-standards evaluating the motor function of the patients (i.e. CHOPINTEND and median CMAP) with Pearson correlation coefficient. Correlation between age, clinical scores (CHOPINTEND, HINE2, Bayley), CMAPs (median, ulnar, fibular, tibial) and IMU-based parameters (||A||_95 and ||A||_CPM for the foot, the wrist, the elbow sensors) were also computed with the Pearson correlation coefficient. Significant p-values for the correlations were set < 0.0001 after Bonferoni correction because multiple tests were performed.

All patients were included in the internal consistency and concurrent validity analysis.

Responsiveness analysis

Responsiveness of the IMU-parameters was evaluated by comparing ||A||_95 and ||A||_CPM for foot (acquisition 1), wrist (acquisition 1) and elbow (acquisition 3) sensors represented in mean and standard deviation at baseline before gene replacement therapy (M0) and at the 12 month follow-up visit (M12) with a paired student t-test (p-value for significance set at 0.05). For this analysis, only patients with an available IMU-measurement at M0 and M12 were included.

Additionally, the correlations between the differences between M0 and M12 for IMU-parameters (||A||_95 computed on the wrist-sensors in acquisition 1, on the foot-sensors in acquisition 1, on the elbow-sensors in acquisition 3 and for ||A||_CPM computed on the wrist-sensors in acquisition 1, on the foot-sensors in acquisition 1, on the elbow-sensors in acquisition 3) and the difference between M0 and M12 for the CHOPINTEND score were evaluated using Pearson correlation coefficient.

Clinical relevance analysis

Means of ||A||_95 and ||A||_CPM computed on the foot (acquisition 1), the wrist (acquisition 1) and the elbow (acquisition 3) sensors were compared with a paired student t-test (p-value for significance set at 0.05) at baseline and at M12.

The association of IMU-parameters and the acquisition of 30 s unaided sitting (a patient centered outcome) was evaluated using the area under the ROC curve (comparison between a continuous variable i.e. IMU-based parameters, motor scores and CMAPs) and compared with the area under the ROC curve of the motor scores (CHOPINTEND score, Bayley III motor score and HINE2 score) and CMAPs (median, ulnar, fibular and tibial).