Abstract
Background
While high-intensity interval training (HIIT) has shown effectiveness in improving cardiorespiratory fitness (CRF) across various chronic respiratory diseases, its impacts on individuals with post-infectious bronchiolitis obliterans (PIBO) remain unexplored. Our aim was to assess the effects of a home-based, remotely supervised, HIIT programme on CRF, clinical and functional variables in patients with PIBO.
Methods
Participants of this assessor-blinded, multicentre, randomised controlled trial were individuals with PIBO aged 6–20 years. An exercise (EXE) group underwent two 40-min sessions of HIIT remotely supervised in real time per week. Sessions were continued for 16 weeks. The control (CON) group adhered to general physical activity recommendations. The primary outcome was peak oxygen uptake (V̇O2peak), time to first ventilatory threshold (VT1), percentage of V̇O2 at VT1 and ventilatory equivalent for carbon dioxide, determined via cardiopulmonary exercise testing on a treadmill. Secondary outcomes were lung function (spirometry), muscle strength (dynamometry), functional capacity (30-s sit-to-stand (30s-STS) test), body mass index and St George's Respiratory Questionnaire score.
Results
51 PIBO patients were enrolled (EXE group n=25; CON group n=26) (49% females; mean±sd age 13.3±4.2 years; forced expiratory volume in 1 s −3.56±1.28 (z-score); V̇O2peak 36.8±8.6 mL·kg−1·min−1). The HIIT intervention resulted in improvements in V̇O2peak (mean difference 3.39 mL·kg−1·min−1; p=0.04), time to VT1 (mean difference 1.05 min; p=0.04) and number of repetitions in the 30s-STS test (mean difference 2.21 repetitions; p=0.04). No differences were found in the other variables.
Conclusions
Our real-time, remotely supervised HIIT intervention was effective at significantly increasing CRF and functional capacity in children and adolescents with PIBO.
Shareable abstract
Real-time, remotely supervised, high-intensity interval training was well-tolerated and effective in improving cardiorespiratory fitness and functional capacity in children and adolescents with post-infectious bronchiolitis obliterans https://bit.ly/4wgW1m5
Introduction
Post-infectious bronchiolitis obliterans (PIBO) is a rare chronic lung disease that may occur following a severe respiratory infection [1]. The airway obliteration that patients experience has a negative impact on lung function, quality of life, and morbidity and mortality [1, 2]. Paediatric patients with chronic respiratory diseases, in general, feature a lower exercise tolerance than their healthy peers [3]. In patients with PIBO, reduced exercise tolerance may be associated with reduced cardiorespiratory fitness (CRF), as indicated by lower peak oxygen uptake (V̇O2peak) and exhaustion of the respiratory reserve [4, 5]. In addition, submaximal exercise parameters, such as time to first ventilatory threshold (VT1), percentage of V̇O2 at VT1 and ventilatory equivalent for carbon dioxide (minute ventilation (V̇E)/carbon dioxide production (V̇CO2)) at VT1, are sensitive markers for assessing exercise tolerance and ventilatory efficiency, particularly in chronic respiratory disease and in situations where maximal effort may be limited [6, 7].
Given the impairment in pulmonary function and the reduced exercise tolerance observed in patients with PIBO [5, 8], high-intensity interval training (HIIT) may be an appropriate strategy to improve CRF, together with other clinical and functional outcomes. HIIT has been shown to be effective in improving V̇O2peak, particularly in healthy paediatric populations, and to be well-tolerated in children with asthma, with associated improvements in CRF, exercise tolerance, pulmonary function, muscular strength, perceived dyspnoea, body composition, quality of life and long-term adherence [9–11]. In addition, HIIT is effective in short-duration sessions and is characterised by its dynamic and engaging nature for paediatric populations, which may further support adherence [10, 12]. However, to date, the effects of HIIT in children and adolescents diagnosed with PIBO have not been investigated, highlighting the need for research specifically targeting this population.
The implementation of exercise programmes continues to face several challenges, including adherence and the need to travel to specialised centres. For patients who are unable to attend face-to-face sessions, technology-based interventions may represent a viable option. Remotely delivered exercise programmes have been shown to be feasible, safe and associated with good adherence in children and adolescents with obesity [13, 14]. Nevertheless, professional supervision remains essential to ensure an appropriate training stimulus, promote the desired physiological adaptations and minimise disease-related risks [15, 16].
In this study, we hypothesised that, compared to usual care in patients with PIBO, a home-based, remotely supervised, real-time delivered HIIT programme would improve CRF, lung function, muscle strength, functional capacity, body composition, quality of life and dyspnoea. This is the first reported multicentre randomised controlled trial (RCT) involving an exercise intervention in children and adolescents with PIBO.
Methods
Trial design
This was a multicentre, superiority, two-arm, parallel group RCT (individual randomisation allocation ratio 1:1). The study is reported in accordance with the CONSORT (Consolidated Standards of Reporting Trials) 2025 guidelines [17], and the intervention is reported following the Consensus on Exercise Reporting Template (CERT) statement [18]. The study protocol (registered at ClinicalTrials.gov as NCT05881538 on 25 May 2023) followed the recommendations of the Declaration of Helsinki, and was approved by the ethics committees of the three participating university hospitals in Spain: Hospital Universitario Niño Jesús (Madrid), Hospital Universitario Vall d'Hebron (Barcelona) and Hospital Universitario Donostia (San Sebastián) (R-0087/22, PR(AMI)457/2022 and PI2023108, respectively). Written informed consent was obtained from all participants or their parents or legal guardians.
Participants
Participants were recruited from the paediatric pulmonology units of the participating hospitals. Inclusion criteria were: 1) diagnosis of PIBO; 2) clinical stability at the time of assessment, defined as the absence of symptom worsening and maintenance of usual treatment; and 3) age between 6 and 20 years. Exclusion criteria were: 1) symptoms of pulmonary exacerbation (evaluated by the pulmonologist) in the last 4 weeks; 2) diagnosis of other cardiopulmonary or neurological diseases; 3) difficulty in understanding instructions; 4) any musculoskeletal disorder that could affect assessment; 5) pregnancy; or 6) on transplant waiting list.
Randomisation and masking
The random assignment sequence was created by a researcher not involved in patient enrolment using R statistical software. Randomisation was conducted in blocks of 8, with stratification by sex, age and lung function (forced expiratory volume in 1 s (FEV1)). For allocation concealment, sequentially numbered opaque containers labelled with participant codes were used. Due to the nature of the intervention, it was not possible to blind the patients or the individuals supervising the intervention. However, the pulmonologists and outcomes assessors were kept blinded to participant allocation. Immediately after the baseline assessment and before opening the opaque container, an intervention supervisor took the patient and their parents or guardians to a separate room to reveal the assignment. This ensured that the assessor remained unaware of the group allocation.
Intervention and comparator
Participants were randomised to an exercise (EXE) group scheduled to undergo a remotely supervised HIIT programme delivered at home in real time or a control (CON) group, in which standardised general physical activity recommendations by their usual pulmonologist were followed. These recommendations aimed to encourage patients to meet the physical activity levels recommended by the World Health Organization [19]. Participants in the EXE group received a complimentary set of exercise equipment, including a step platform, a set of cones and an exercise mat. Additionally, a wristwatch (Polar Unite; Polar Electro, Kempele, Finland) with a heart rate monitoring strap (Polar H10; Polar Electro) was provided for exclusive use during the intervention. Participants also underwent an in-person familiarisation session with the equipment and training format. Once the training schedule was coordinated with each participant, the instructor sent a link via e-mail to access all training sessions. The intervention consisted of two sessions per week over a period of 16 weeks. Each session began with a 10-min warmup, followed by two blocks of six exercises performed in a circuit format as part of the HIIT protocol. Each exercise was performed at high intensity for 30–50 s, followed by a 60-s active recovery period. For patients who experienced increased dyspnoea during the adaptation phase or at specific times, additional rest periods were provided as needed. A 4-min rest period was also included between each exercise block. The total session duration, including warmup and cooldown, was ∼40–45 min. During the first 2–3 weeks of the intervention, high-intensity intervals were performed at 75–80% of peak heart rate (HRpeak) determined in the baseline cardiopulmonary exercise testing (CPET). Thereafter, the intensity was progressively increased to 90% of HRpeak. Heart rate was continuously monitored in each participant during all exercises and throughout the entire intervention. Each session concluded with a 5–10-min cooldown period, consisting of breathing exercises and stretching. Exercise sessions were remotely delivered in groups of no more than four participants. The training programme was designed in accordance with the CERT statement [18]. The exercises are detailed in supplementary material S1.
Outcomes
All variables were measured in two visits to the CPET laboratory of each participating hospital, before and after the interventions (T0 and T1, respectively). The study's primary outcome was V̇O2peak, time to VT1, percentage of V̇O2 at VT1 and ventilatory efficiency. Secondary outcomes were lung function, muscle strength and functionality, body composition, quality of life, and dyspnoea perception. Demographics, clinical variables and physical activity level were also recorded. All collected data were managed using the REDCap (Research Electronic Data Capture) platform [20].
Cardiorespiratory fitness
Cardiorespiratory fitness was determined using a treadmill (RAM 870; Medisoft, Sorinnes, Belgium) incremental exercise test following the recommendations of the European Respiratory Society [21]. Treadmill speed began at 2.5 km·h−1 (patients <120 cm) or 3.5 km·h−1 (patients >120 cm). The incline was set at 0.5%. The protocol consisted of a 3-min warmup with speed increments of 0.2–0.6 km·h−1, depending on the patient's initial FEV1, and 0.5% incline increments every 60 s. Gas exchange data were measured breath-by-breath via open-circuit spirometry (Ergocard CPX/Medisoft ExpAIR; Medisoft). The variables recorded were V̇O2, V̇E, respiratory exchange ratio (RER), ventilatory equivalent for oxygen and carbon dioxide (V̇E/V̇O2 and V̇E/V̇CO2, respectively), breathing reserve, oxygen pulse, peripheral oxygen saturation (SpO2), and HRpeak. V̇O2peak was recorded as the highest value obtained for any continuous 20-s period and is presented as both absolute and percentile values [22]. Breathing reserve was calculated as the difference between maximum voluntary volume (MVV) and maximum V̇E at peak exercise. An indirect estimate was used to predict MVV consisting of multiplying FEV1 by 40 [21]. We also measured HRpeak (wristwatch with heart rate monitoring strap; Polar), SpO2 (pulse oximeter; Nonin, Plymouth, MN, USA), blood pressure (manual sphygmomanometer; Riester, Jungingen, Germany), rating of perceived exertion for the lower extremities and dyspnoea (modified Borg scale 0–10) at baseline, immediately after the end of the test, and after 1 and 3 min of recovery. V̇O2peak changes for each participant (between T0 and T1) were also classified as an increase (favourable), reduction or no change, considering a cut-off point of 3.5 mL·kg−1·min−1 (1 metabolic equivalent of task (MET)). VT1 was determined non-invasively by the ventilatory equivalent method. The test was considered maximal if at least two of the following criteria were met: visible exhaustion, RER >1.05, HRpeak >85% of predicted maximum (208−age×0.7), ventilatory limitation (breathing reserve <20%) and presence of a plateau in V̇O2 [21]. Tests were interrupted if SpO2 ≤85% [21]. Only tests meeting the criteria for maximal effort were included.
Lung function
Lung function was assessed by spirometry (Ergocard CPX) following American Thoracic Society/European Respiratory Society guidelines [23]. The main variables recorded were FEV1, forced vital capacity (FVC), FEV1/FVC ratio and forced expiratory flow at 25–75% of FVC (FEF25–75%). All data were expressed as absolute values, and z-scores were calculated using the Global Lung Initiative 2012 (GLI) equations [24].
Muscle strength and functional capacity
Handgrip strength was assessed in a seated position (elbow at 90°) with a hand dynamometer (Jamar; Lafayette Instrument, Lafayette, IN, USA). A digital handheld dynamometer (MicroFET 2; Hoggan Health Industries, West Jordan, UT, USA) was used to assess the strength of the arms (in a supine decubitus position with 90° arm flexion) and legs (seated with the hip at 90° and the knees flexed to determine isometric strength for both leg extension and flexion) [25]. The highest value was recorded and then adjusted for body weight. Functional capacity was assessed in the 30-s sit-to-stand test (30s-STS). Participants were instructed to stand up and sit down, and to perform as many cycles of sit–stand–sit as possible in 30 s with their arms crossed over the chest. Two trials with a 60-s rest period were performed [26].
Body composition
Body weight and fat percentage were measured through bioelectrical impedance analysis (BC-545n; Tanita, Tokyo, Japan). Height was measured with a stadiometer. Waist/hip ratio (WHR) was calculated using the waist circumference (at the belly button) divided by the circumference of the fullest curve of the hip measured with wrap tape. Body mass index (BMI) was calculated as weight divided by height2 (kg·m−2). Weight, height and BMI data were expressed as absolute values and z-scores using the Ped(z) online calculator [27].
Quality of life
The St George's Respiratory Questionnaire (SGRQ) grades 50 items divided into three subscales: Symptoms, Activity and Impacts. Results are presented as an overall total score from 0 to 100, where 0 indicates no respiratory impairment [28].
Dyspnoea
To assess dyspnoea levels during daily life activities, we used the five-point modified Medical Research Council scale (mMRC) scale. Participants were asked about their perceived breathlessness according to descriptive statements and classified according to their mMRC dyspnoea scores (from 0 to 4) [29].
Demographic and other variables
Demographics (sex, age and parental educational level) and clinical data (medical history) were collected both directly from the participants and from their medical records.
Physical activity
To measure physical activity levels, we used Physical Activity Questionnaires for Adolescents (PAQ-A) and Children (PAQ-C). Each item is scored on a 5-point scale, and the total score is an average of the scores of all items. Total scores ranged from 1 (very low levels) to 5 (higher levels) [30].
Sample size
The sample size calculation was performed using the pmsampsize package in R. In the absence of previous studies evaluating the efficacy of HIIT or similar exercise protocols in patients with PIBO, parameter estimates were derived from two related studies [4, 9]. For our RCT, we assumed an expected effect size of 6.5 mL·kg−1·min−1 for V̇O2peak and a pooled standard deviation of 8.3. Considering a type I error rate of 5% and a statistical power of 80%, the required sample size was estimated at 52 participants, 26 in each group.
Statistical analysis
Continuous variables were summarised as mean with standard deviation for normally distributed data and median (interquartile range (IQR)) for skewed distributions. Categorical variables were summarised as count (percentage). Study outcomes for all randomised participants with valid outcome data were analysed using linear mixed effects models within a constrained longitudinal data analysis framework, in which baseline (T0) and post-intervention (T1) measurements were modelled jointly as the dependent variable. The primary analysis was performed using unadjusted models including fixed effects for time, group allocation and their interaction, with the time×group interaction estimating the between-group difference in change over time (intervention effect). A random intercept for each participant was included to account for within-participant correlation across repeated measurements. As complementary analyses, models were additionally adjusted for study site, age and sex. The analytical approach and covariates were selected post hoc based on the longitudinal structure of the data and established methodological recommendations for the analysis of repeated measures outcomes [31]. Exploratory analyses were conducted by age subgroups (6–12 and 13–20 years). Analyses were conducted using complete cases for the study outcomes. Model assumptions were assessed by visual inspection of residual Q–Q plots, residual versus fitted plots and random effects diagnostics, with no evidence of violations of normality or homoscedasticity. For each outcome, the intervention effect was estimated from the time×group interaction at T1, with corresponding 95% confidence intervals and p-values extracted from the fitted models. For prespecified primary outcomes, p-values were additionally adjusted for multiple comparisons using the Holm–Bonferroni method. Significance was set at p<0.05. Cohen's d effect sizes were calculated by standardising the estimated between-group difference in change using the pooled baseline standard deviation. All statistical tests were conducted using R statistical software [32].
Results
Participants
Of 63 eligible participants, 53 were initially randomised and allocated to the two groups (EXE group n=26; CON group n=27) between 29 May 2023 and 29 July 2024. Two participants were excluded from the analyses because of non-valid CPET data (submaximal) in the baseline (T0) assessment, leaving 25 participants in the EXE group and 26 participants in the CON group. The complete flow diagram is presented in figure 1. The characteristics of the participants are provided in table 1. Approximately half of the participants (49%) were female, mean participant age was 13.3±4.2 years and BMI was 0.06±1.20 (z-score). 34 patients had an identifiable infectious agent upon diagnosis. Additional clinical information is presented in supplementary material S2.
FIGURE 1.
Flow diagram of participant selection. CPET: cardiopulmonary exercise testing.
TABLE 1.
Characteristics of the participants (n=51), stratified by group (control (CON) versus exercise (EXE)) and assessment time (pre-intervention (T0) versus post-intervention (T1))
| CON group (n=26) | EXE group (n=25) | |||
|---|---|---|---|---|
| T0 | T1 | T0 | T1 | |
| Demographics | ||||
| Female | 13 (50) | 12 (48) | ||
| Age, years | 14.0±3.8 | 12.5±4.5 | ||
| Anthropometrics | ||||
| Weight, kg | 52.7±15.2 | 53.0±14.4 | 44.6±18.0 | 45.8±18.5 |
| Weight, z-score | 0.06±0.96 | 0.10±0.97 | −0.32±1.35 | −0.13±1.29 |
| Height, cm | 157±14.3 | 158±13.5 | 151±19.2 | 152±18.7 |
| Height, z-score | −0.43±0.82 | −0.27±0.89 | −0.34±1.18 | −0.12±1.30 |
| BMI, kg·m−2 | 20.8±3.8 | 20.7±3.7 | 18.8±4.2 | 18.9±4.3 |
| BMI, z-score | 0.31±1.06 | 0.29±1.02 | −0.20±1.30 | −0.15±1.29 |
| Fat mass, % | 22.9±7.3 | 23.1±7.1 | 21.5±8.1 | 22.2±8.1 |
| WHR | 0.81±0.07 | 0.82±0.06 | 0.82±0.05 | 0.83±0.06 |
| Cardiorespiratory fitness | ||||
| VT1 | ||||
| Time, min | 5.1±1.38 | 5.3±1.39 | 5.3±1.39 | 6.5±2.5 |
| V̇O2 at VT1, % | 60.6±11.8 | 56.3±14.5 | 59.3±13.9 | 55.9±10.6 |
| V̇E/V̇CO2 | 32.9±5.5 | 34.7±14.1 | 31.1±4.8 | 30.8±6.7 |
| Peak | ||||
| V̇O2, mL·kg−1·min−1 | 36.5±8.5 | 35.8±8.6 | 37.0±8.9 | 39.6±9.2 |
| V̇E/V̇CO2 | 33.6±5.2 | 34.2±6.5 | 31.3±5.1 | 31.8±5.3 |
| Lung function | ||||
| Spirometry | ||||
| FEV1, L | 1.77±0.61 | 1.81±0.56 | 1.49±0.72 | 1.52±0.71 |
| FEV1, z-score | −3.4±1.27 | −3.4±1.16 | −3.7±1.28 | −3.8±1.18 |
| FVC, L | 2.9±0.98 | 2.9±0.95 | 2.5±1.26 | 2.6±1.26 |
| FVC, z-score | −1.65±1.35 | −1.65±1.33 | −1.87±1.26 | −1.73±1.15 |
| FEV1/FVC | 0.64±0.13 | 0.64±0.11 | 0.61±0.11 | 0.59±0.11 |
| FEF25–75%, L·min−1 | 1.29±0.83 | 1.63±0.95 | 0.93±0.57 | 1.20±1.05 |
| FEF25–75%, z-score | −3.5±1.65 | −3.0±1.56 | −3.9±1.36 | −3.7±1.47 |
| Muscle strength | ||||
| Upper limb, kg·kg−1 | ||||
| Dominant handgrip | 0.50±0.13 | 0.51±0.12 | 0.48±0.15 | 0.49±0.15 |
| Dominant arm flexion | 0.35±0.10 | 0.35±0.06 | 0.36±0.13 | 0.34±0.05 |
| Lower limb, kg·kg−1 | ||||
| Dominant leg extension | 0.62±0.12 | 0.65±0.13 | 0.62±0.26 | 0.63±0.19 |
| Dominant leg flexion | 0.42±0.13 | 0.42±0.08 | 0.40±0.20 | 0.42±0.10 |
| Functional capacity | ||||
| 30s-STS test, repetitions | 27.0±6.4 | 29.3±4.6 | 27.5±4.9 | 32.0±4.9 |
| Questionnaires | ||||
| SGRQ total score | 22.2±10.7 | 20.3±12.3 | 17.9±10.7 | 17.9±11.3 |
| PAQ-A/C score | 1.80±0.43 | 1.78±0.46 | 1.98±0.47 | 1.99±0.42 |
| mMRC dyspnoea score | 0.50±0.51 | 0.46±0.51 | 0.52±0.71 | 0.32±0.48 |
Data are presented as n (%) or mean±sd. BMI: body mass index; WHR: waist/hip ratio; VT1: first ventilatory threshold; V̇O2: oxygen uptake; V̇E: minute ventilation; V̇CO2: carbon dioxide production; FVC: forced vital capacity; FEV1: forced expiratory volume in 1 s; FEF25–75%: forced expiratory flow at 25–75% of FVC; 30s-STS: 30-s sit-to-stand; SGRQ: St George's Respiratory Questionnaire; PAQ-A/C: Physical Activity Questionnaire for Adolescents/Children; mMRC: modified Medical Research Council.
Primary outcomes
Participants in the EXE group showed significantly greater improvements in V̇O2peak (T0: 37.0±8.9 versus T1: 39.6±9.2 mL·kg−1·min−1) compared to those in the CON group (T0: 36.5±8.5 versus T1: 35.8±8.6 mL·kg−1·min−1). The mean difference between the two assessments was 3.39 (95% CI 0.82–5.97) mL·kg−1·min−1 (p=0.04) in favour of the EXE group. A significant increase in time to VT1 was also observed in favour of the EXE group compared to the CON group (mean difference between groups 1.05 (95% CI 0.28–1.82) min; p=0.04). No significant changes were observed for the other primary outcomes (table 2). The V̇O2peak changes observed for each participant (between T0 and T1) are presented in figure 2.
TABLE 2.
Effects of a home-based, remotely supervised high-intensity interval training programme on cardiorespiratory fitness and secondary outcomes (unadjusted analyses)
| Between-group mean difference (95% CI) |
p-value | Cohen's d | p-value Holm# | |
|---|---|---|---|---|
| Cardiorespiratory fitness | ||||
| VT1 | ||||
| Time, min | 1.05 (0.28–1.82) | 0.01 | 0.75 | 0.04 |
| V̇O2 at VT1, % | 0.96 (−6.7–8.6) | 0.81 | 0.07 | 0.81 |
| V̇E/V̇CO2 | −2.2 (−7.0–2.6) | 0.38 | −0.42 | 0.76 |
| Peak | ||||
| V̇O2, mL·kg−1·min−1 | 3.39 (0.82–5.97) | 0.01 | 0.39 | 0.04 |
| V̇E/V̇CO2 | −0.20 (−2.9–2.5) | 0.89 | −0.04 | |
| Lung function | ||||
| FEV1, L | −0.01 (−0.08–0.06) | 0.79 | −0.02 | |
| FEV1, z-score | −0.08 (−0.33–0.18) | 0.56 | −0.06 | |
| FVC, L | 0.07 (−0.04–0.18) | 0.24 | 0.06 | |
| FVC, z-score | 0.14 (−0.18–0.45) | 0.40 | 0.10 | |
| FEF25–75%, L·min−1 | −0.07 (−0.46–0.32) | 0.73 | −0.10 | |
| FEF25–75%, z-score | −0.30 (−0.91–0.31) | 0.34 | −0.20 | |
| Muscle strength | ||||
| Dominant handgrip, kg·kg−1 | −0.01 (−0.04–0.03) | 0.70 | −0.05 | |
| Dominant arm flexion, kg·kg−1 | −0.02 (−0.07–0.04) | 0.49 | −0.17 | |
| Dominant leg extension, kg·kg−1 | −0.02 (−0.13–0.09) | 0.71 | −0.10 | |
| Dominant leg flexion, kg·kg−1 | 0.02 (−0.08–0.11) | 0.71 | 0.10 | |
| Functional capacity | ||||
| 30s-STS test, repetitions | 2.21 (0.12–4.31) | 0.04 | 0.39 | |
| Body composition | ||||
| Height, cm | 0.45 (−0.37–1.26) | 0.29 | 0.03 | |
| Height, z-score | 0.06 (−0.07–0.18) | 0.36 | 0.06 | |
| Weight, kg | 0.98 (−0.23–2.2) | 0.12 | 0.06 | |
| Weight, z-score | 0.15 (0.01–0.29) | 0.05 | 0.13 | |
| Fat mass, % | 0.52 (−0.87–1.92) | 0.47 | 0.07 | |
| BMI, kg·m−2 | 0.22 (−0.22–0.65) | 0.34 | 0.05 | |
| BMI, z-score | 0.07 (−0.10–0.23) | 0.44 | 0.05 | |
| WHR | 0.01 (−0.01–0.02) | 0.40 | 0.12 | |
| Quality of life | ||||
| SGRQ total score | 1.80 (−2.4–6.0) | 0.40 | 0.17 | |
| Dyspnoea | ||||
| mMRC dyspnoea score | −0.16 (−0.52–0.20) | 0.38 | −0.26 | |
| Level of physical activity | ||||
| PAQ-A/C score | 0.03 (−0.14–0.19) | 0.75 | 0.06 |
VT1: first ventilatory threshold; V̇O2: oxygen uptake; V̇E: minute ventilation; V̇CO2: carbon dioxide production; FVC: forced vital capacity; FEV1: forced expiratory volume in 1 s; FEF25–75%: forced expiratory flow at 25–75% of FVC; 30s-STS: 30-s sit-to-stand; BMI: body mass index; WHR: waist/hip ratio; SGRQ: St George's Respiratory Questionnaire; mMRC: modified Medical Research Council; PAQ-A/C: Physical Activity Questionnaire for Adolescents/Children. #: p-value with Holm–Bonferroni correction. The reported effects and p-values are derived from linear mixed effects models. p-values in bold indicate significant results (p<0.05).
FIGURE 2.
Individual changes observed in V̇O2peak between the pre-intervention (T0) and post-intervention (T1) assessments for both the control (CON) and exercise (EXE) groups. Favourable changes, i.e. an increase in V̇O2peak of ≥3.5 mL·kg−1·min−1, are shown in green, while reductions of ≥3.5 mL·kg−1·min−1 are shown in red. Changes in V̇O2peak within the range ±3.5 mL·kg−1·min−1 are shown in yellow. Mean difference and 95% confidence interval between T0 and T1 are shown for each group.
Secondary outcomes
In our analysis of secondary outcomes, significant increases were observed in the number of 30s-STS test repetitions (mean difference between groups 2.21 (95% CI 0.12–4.31) repetitions; p=0.04), indicating a functional capacity improvement in the EXE group. No significant changes were detected in variables indicating lung function, muscle strength, body composition, quality of life or dyspnoea. The results for all study outcomes are presented in table 2.
Exploratory analyses
Additional exploratory analyses are presented in supplementary material S2, including stratified analyses by age group (6–12 and 13–20 years) and analyses of other variables of interest. The latter showed significant changes in favour of the EXE group, including V̇O2 (mL·kg−1·min−1) at VT1, percentage time at VT1, and breathing reserve and oxygen pulse at peak exercise. In addition, the programme was well-tolerated, with no cardiorespiratory or musculoskeletal adverse events. Exercise intensity was adjusted according to individual physical fitness levels and parameters obtained from CPET. The exercises were modified to avoid impact during their execution (with no influence on session intensity or volume) in two participants who sustained mild ankle sprains during school activities. In order to clarify intervention fidelity, HRpeak recorded during the HIIT sessions is shown in supplementary material S2. All patients followed their routine treatment during the trial period. Mean adherence was 92%; median (IQR) adherence was 100% (15.63%), with a median (IQR) of 32 (4.3) completed sessions.
Discussion
The results of our RCT reveal that a 16-week, remotely supervised, real-time delivered home HIIT programme led to significant improvements in CRF, as reflected by increases in V̇O2peak, time to VT1 and functional capacity, as indicated by a greater number of repetitions in the 30s-STS test. This is the first study to provide evidence of the effectiveness of an exercise-based intervention in children and adolescents with PIBO.
Participants in our study had a mean baseline V̇O2peak of 36.8 mL·kg−1·min−1, comparable to values reported in other studies of patients with PIBO [4]. The intervention led to an improvement in V̇O2peak of nearly 1 MET (3.5 mL·kg−1·min−1), a value commonly associated with functional changes in CRF in the adult population [33]. According to the literature, in the general adult population, this increase would be associated with an 11–17% reduction in the risk of all-cause mortality [33], while in children and adolescents there are several established associations between CRF and health-related outcomes [34]. In patients with cystic fibrosis (CF), V̇O2peak <82% predicted or <45 mL·kg−1·min−1 has been associated with a 4.9-fold increased risk of mortality [35], as well as a significantly higher risk of hospitalisation [36]. However, the prognostic impact of an improvement of ∼3.4 mL·kg−1·min−1 in PIBO is unknown and does not directly indicate improved survival. When analysing normalised V̇O2peak values [22], we observed that at baseline, 48% of patients in our EXE group showed a V̇O2peak below the 10th percentile, indicating reduced CRF. In contrast, after the intervention, the majority of participants (56%) returned V̇O2peak values between the 26th and 75th percentiles. This difference highlights the importance of adequate training planning to elicit beneficial adaptations in physical fitness, including improvements in V̇O2peak [37]. It is well-established that V̇O2 is associated with physical fitness. Evidence suggests that improved long-term health outcomes in healthy children and adolescents are mostly the consequence of maintaining a physically active lifestyle with regular engagement in moderate/vigorous-intensity activities [38]. High-intensity training in healthy children has been shown to be 25% more effective in increasing V̇O2peak compared to low/moderate-intensity training [11]. We also observed a significant increase in time to VT1, a variable recognised as an important marker of exercise tolerance. This finding suggests an improvement in aerobic capacity and a potential enhancement in the ability to perform activities of daily living [6]. Our findings illustrate the potential of a HIIT programme as an effective therapeutic tool to improve CRF in children and adolescents with PIBO, highlighting its clinical relevance.
In addition to an increase in V̇O2peak in response to training, we observed an improvement in functional capacity, as indicated by a higher number of repetitions in the 30s-STS test. Similar results have been reported previously in a telerehabilitation study conducted in children with CF [39]. Although functional capacity does not always correlate directly with V̇O2, it is linked to quadriceps muscle strength [40, 41]. Accordingly, the STS test shows significant correlation with maximal voluntary contraction of the quadriceps in healthy children [42] and is strongly associated with mortality and quality of life in patients with COPD [43]. The HIIT programme in the present study proved effective at enhancing functional capacity, likely due to the inclusion of body weight-based lower limb exercises, similar to those proposed by Bossmann et al. [10]. Muscle strength is an important predictor of paediatric health [44] and is recognised as a strong, independent predictor of improved insulin sensitivity in children [45]. However, despite the strong link between STS test performance and lower limb strength [42], we observed no improvement in muscle strength in response to our intervention. This could be attributed, at least in part, to the fact that the exercises included in our intervention were dynamic in nature, whereas muscle strength was measured through an isometric test. Considering the clinical importance of muscle strength, we propose the addition of specific exercise resistance training prescription [46] to target peripheral muscle strength gains.
The present study was also designed to analyse the effects of the HIIT programme on lung function, quality of life and dyspnoea. The participants included in this study had lung function similar to that reported in other studies of patients with PIBO [4]. Our results revealed no significant effects on lung function parameters, consistent with previous findings [47]. Furthermore, questionnaire scores for quality of life also indicated no change in this measure following the intervention. This could be partly due to the fact that the instrument used was designed for chronic respiratory diseases in general, and its items may not accurately reflect the specific needs of children and adolescents with PIBO. Additionally, it could also be related to the high quality of life scores awarded at baseline, which would have limited room for improvement. Baseline levels of dyspnoea during activities of daily living showed a small, although not significant, reduction, and only 22% of participants in the EXE group reported an improved level of dyspnoea after the intervention. Other studies have shown reductions in perceived dyspnoea levels after HIIT programmes, suggesting that such interventions could promote beneficial adaptations that enhance performance in daily living activities [48]. As occurred for quality of life, we believe the low baseline dyspnoea levels left little room for measurable improvement. In addition, other variables were also collected, such as physical activity levels. Although measurements were performed before and after the study, no attention-matched intervention or systematic monitoring was addressed to the CON group. This, together with additional factors, such as the tool validity or changes in habitual physical activity induced by the intervention, could have influenced the lack of differences between times and groups.
Although V̇O2peak is recognised as the primary marker of CRF, we also explored other variables that reflect cardiometabolic and cardiorespiratory adaptations. Hence, at peak exercise intensity, significant differences between groups emerged in breathing reserve and oxygen pulse, as well as improvements in V̇O2 (mL·kg−1·min−1) at VT1 and the percentage of time at VT1 in favour of the EXE group. While these results are of interest, they should be interpreted with caution given the exploratory nature of the analyses. Taken together, these findings point to a comprehensive improvement in CRF and exercise tolerance, further supporting the value of incorporating multiple physiological indicators to provide a more complete picture of a training programme's effects [9]. In addition, although the wide age range included in the study may influence the response to training due to maturation-related physiological changes [22], exploratory analyses conducted separately in children and adolescents did not show significant differences in the primary outcomes. When interpreting these findings, the reduced statistical power of the subgroup analyses should be taken into account. Therefore, further studies specifically designed to investigate differences related to biological maturation are warranted to better understand the influence of age on training adaptations in this population.
Here we selected a HIIT modality, as high-intensity exercise has proven more effective than lower intensity exercise at improving V̇O2peak in children [11]. Our results indicate that the HIIT intervention was safe, well-tolerated and failed to give rise to adverse events in children and adolescents with PIBO. These findings are consistent with those noted in other cohorts in response to HIIT, such as in subjects with pulmonary embolism [49], CF [50], COPD [48], and in healthy children and adolescents [10]. This type of training has proved highly effective, as significant improvements in V̇O2peak can be achieved within a relatively short training session duration [10, 12]. Moreover, its dynamic and engaging nature makes it particularly appealing to paediatric and adolescent populations [10], and this has a beneficial effect on programme adherence. Despite considerable variability among participants in terms of age, pulmonary function and physical condition, our proposed training intervention successfully achieved target heart rates during high-intensity intervals, HRpeak consistently exceeding 90%, as recommended by Eddolls et al. [12]. Circuit-based HIIT is a highly reproducible intervention due to its design, which is tailored for home-based implementation in limited spaces, with or without specialised equipment. This expands access to exercise in individuals who are unable to regularly attend specialised facilities. It should not be overlooked, however, that evidence exists to support the importance of supervision during exercise sessions [16]. In consequence, the remote delivery strategy with real-time guided sessions used in the present study may have played a role in the good results obtained, suggesting the effectiveness of intensity progression to better obtain cardiorespiratory adaptations. Future studies could also address the effects of moderate-intensity interval training, as well as the effects of programme supervision.
One of the main strengths of our study lies in its RCT design, which enhances the validity of its results. Notably, there were no losses related to the intervention, and the final analysis included 96% of the originally randomised participants, thereby minimising the risk of bias. Furthermore, the assessment tools used were validated and reliable. This study has some limitations. The self-reported physical activity questionnaire may be prone to bias, as it may not accurately reflect participants’ actual activity levels. The home-based remotely supervised delivery model, while practical and accessible, relied partly on self-reported adherence and self-monitoring of heart rate, which could determine a risk of variability in exercise intensity.
Conclusions
This multicentre study conducted in children and adolescents with PIBO reveals that a real-time, remotely supervised home HIIT intervention is effective in producing significant improvements in both CRF (V̇O2peak and time to VT1) and functional capacity (30s-STS test). No effects were seen on lung function, muscle strength, body composition, quality of life and dyspnoea. This is the first RCT to examine the benefits of an exercise-based intervention in this population, providing preliminary guidance for healthcare professionals on exercise responses in patients with PIBO, while emphasising the need for further studies to confirm these findings.
Acknowledgements
We would like to thank the undergraduate students Ángela Blanco Velasco, Nicola Pinna Manchia, Lina Keijzer, Cristina De Fuentes Miret, Elena Tundidor Canfran and Cristina Pérez Manen for their active participation in helping deliver the intervention, as well as the patients and their families for their cooperation.
Footnotes
This clinical trial is prospectively registered with ClinicalTrials.gov as NCT05881538.
Ethics statement: The study protocol followed the recommendations of the Declaration of Helsinki, and was approved by the ethics committees of the three participating university hospitals (Hospital Universitario Niño Jesús Madrid (R-0087/22), Hospital Universitario Vall d'Hebron Barcelona (PR(AMI)457/2022) and Hospital Universitario Donostia, San Sebastián (PI2023108)). Written informed consent was obtained from all participants or their parents or legal guardians.
Conflict of interest: The authors have no potential conflicts of interest to disclose.
Support statement: This study was funded by the Spanish Sports Council (Proyectos de Investigación en Ciencia y Tecnología aplicada a la Actividad Física Beneficiosa para la Salud (AFBS) y la Medicina Deportiva), with support from the European Union “NextGenerationEU” initiative, and the Sociedad Española de Neumología y Cirugía Torácica (SEPAR) through its research grant programme. M.V.F. Donadio was supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico. The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript. Funding information for this article has been deposited with the Open Funder Registry.
Supplementary material
Please note: supplementary material is not edited by the Editorial Office, and is uploaded as it has been supplied by the author.
Supplementary material 1
ERJ-00265-2026.Supplement_1
Supplementary material 2
ERJ-00265-2026.Supplement_2
Data availability
De-identified individual participant data underlying the results reported in this article are publicly available in the Zenodo repository at https://doi.org/10.5281/zenodo.17545876. The dataset includes anonymised participant-level data and a data dictionary. The complete R code used for the analyses is also accessible at https://doi.org/10.5281/zenodo.18457270. All materials are openly available without restriction for reuse under a Creative Commons licence.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Please note: supplementary material is not edited by the Editorial Office, and is uploaded as it has been supplied by the author.
Supplementary material 1
ERJ-00265-2026.Supplement_1
Supplementary material 2
ERJ-00265-2026.Supplement_2
Data Availability Statement
De-identified individual participant data underlying the results reported in this article are publicly available in the Zenodo repository at https://doi.org/10.5281/zenodo.17545876. The dataset includes anonymised participant-level data and a data dictionary. The complete R code used for the analyses is also accessible at https://doi.org/10.5281/zenodo.18457270. All materials are openly available without restriction for reuse under a Creative Commons licence.