Breath Duration Research Articles

Accelerating the Diagnosis of Pandemic Infection Based on Rapid Sampling Algorithm for Fast-Response Breath Gas Analyzers.

This paper presents a novel technique for extracting the alveolar part of human breath. Gas exchange occurs between blood and inhaled air in the alveoli, which is helpful in medical diagnostics based on breath analysis. Consequently, the alveolar portion of the exhaled air contains specific concentrations of endogenous EVOC (exogenous volatile organic compound), which, among other factors, depend on the person's health condition. As this part of the breath enables the screening for diseases, accurate sample collection for testing is crucial. Inaccurate sampling can significantly alter the composition of the specimen, alter the concentration of EVOC (biomarkers) and adversely affect the diagnosis. Furthermore, the volume of alveolar air is minimal (usually <350 mL), especially in the case of people affected by respiratory system problems. For these reasons, precise sampling is a key factor in the effectiveness of medical diagnostic systems. A new technique ensuring high accuracy and repeatability is presented in the article. It is based on analyzing the changes in carbon dioxide concentration in human breath using a fast and compensated non-dispersive infrared (NDIR) sensor and the simple moving adjacent average (SMAA) algorithm. Research has shown that this method accurately identifies exhalation phases with an uncertainty as low as 20 ms. This provides around 350 ms of breath duration for carrying out additional stages of the diagnostic process using various types of analyzers.

Does Maternal HIV Infection Affect Neonatal Outcomes?

Pregnancy among women infected with HIV is classified as a high-risk pregnancy. While previous research has indicated an elevated likelihood of preterm birth, low birth weight, and early gestational age in infants born to mothers with HIV, the correlation between maternal HIV infection and different neonatal results remains unclear. This study aims to investigate the impact of maternal HIV infection on after-birth neonatal outcomes using machine learning (ML) and statistical methods. A case-control study is conducted through a three-stage process: Initially, the outcomes among newborns from HIV-positive mothers are identified through a combination of literature review and expert survey. Subsequently, data are paired at a 1:2 ratio based on gestational age with infants from HIV-positive mothers (n=48) compared to HIV-negative mothers (n=96) as the control group. Finally, various feature selection techniques are applied to identify outcomes that exhibit significant differences between the two groups. The statistical analysis showed that the rate of addiction among HIV-positive mothers is higher than that of the HIV-negative group. The need for mechanical ventilation and duration of ventilator-assisted breathing in infants born to HIV-positive mothers are significantly higher than in infants born to HIV-negative mothers. Moreover, based on feature selection methods, increasing the need for mechanical ventilation and reducing surfactant administration were two important outcomes. To investigate the impact of maternal HIV infection on neonatal outcomes, various statistical and machine learning-based feature selection techniques were implemented, and the results showed that the presented methods can be utilized to examine the potential impacts of different diseases contracted by the mother on the infant.

Efficacy and Safety of Dexmedetomidine in the Prone Position in Elderly Patients with Pneumonia: A Prospective, Double-Blind, Randomized Controlled Study.

We aimed to identify a safe and effective method to assist older adults with pneumonia in tolerating the prone position for a longer duration. This was a randomized, controlled, double-blinded study performed at the Shanghai Fourth People's Hospital. Eighty patients with pneumonia aged ≥ 65years were included. The patients were able to spontaneous breath in the prone position and were administered intravenous dexmedetomidine or an isotonic sodium chloride solution. The cumulative daily durations of prone positioning for all patients in the two groups were recorded. The primary outcome was the percentage of patients who completed ≥ 9h/day in the prone position. The secondary outcomes included the incidence of complications in the prone position and patient outcomes. Eighty patients were included (average age: 79.6 ± 8.9years). The percentage of patients who completed ≥ 9h/day in the prone position was significantly higher in the dexmedetomidine group than in the placebo group (P = 0.011). The percentage of patients who completed ≥ 12h/day in the prone position was also significantly greater in the dexmedetomidine group than in the placebo group (P = 0.008). There were no significant differences in other variables between the two groups. The results of this study demonstrate that intravenous dexmedetomidine injection can significantly prolong the duration of spontaneous breathing in the prone position in elderly pneumonia patients without obvious adverse events. We provide a safe and effective method to help patients with pneumonia, especially those with delirium or cognitive impairment, who cannot tolerate the length of time needed for spontaneous breathing in the prone position to be effective. The study was registered with the Chinese Clinical Trial Center (registration number: ChiCRT2300067383) on 2023-01-05.

Diagnosis of patients with chronic heart failure implementing wavelet transform and machine learning techniques

Chronic heart failure (CHF) is a significant public health concern due to its increasing prevalence, high number of hospital admissions, and associated mortality. Its prevalence is progressively increasing due to the aging of the population and the decrease in mortality from acute myocardial infarction, among other medical advancements. Consequently, the incidence of CHF predominantly affects older age groups, doubling its prevalence every decade, becoming one of the main causes of mortality in patients older than 65 years. The main objective of this study is to apply machine learning based techniques to determine the best models to classify patients with chronic heart failure through their respiratory pattern. These patterns have been characterized from time series such as inspiratory and expiratory times, breathing duration, and tidal volume obtained from the respiratory flow signal. Based on the behavior of the respiratory pattern, CHF patients were classified into patients with non-periodic breathing, with periodic breathing, and with Cheyene-Stokes respiration (CSR). Time-frequency and statistical techniques have been implemented to analyze these features, and then various classification methods have been applied to define the optimal model with the best accuracy rates. These models could help to better understand the evolution of this disease and in early diagnosis.

Volitionally Regulated Breathing with Prolonged Expiration Influences Food Craving and Impulsivity

Introduction: Previously, an intervention involving volitional slow breathing reduced trait food craving with protective effects on cardiac vagal activity (CVA). Breathing with a low inspiration-to-expiration (i/e) ratio also increases CVA. High CVA was separately associated with low unregulated eating and lesser impulsivity. Hence, the present study assessed breathing with a low i/e for effects on state food craving, hunger and satiety, state impulsivity, and heart rate variability (HRV) in healthy obese persons. Methods: Forty obese persons were randomized to two groups. The intervention group (mean age ± SD, 41.15 ± 12.63, M:F, 10:10) practiced metronome-regulated breathing with low i/e at 12 breaths per minute (expiration 72% of total breath duration) and attained expiration 55.8% of total breath duration, while the active control group (mean age ± SD, 44.45 ± 11.06, M:F, 13:07) sat motionless and directed their gaze and awareness to the stationary metronome without modifying their breath consciously. The HRV was recorded before, during, and after breathing intervention (or control) (standard limb lead I, acquisition at 2,000 Hz, with an LF filter = 0.5 Hz and HF filter = 50 Hz). Time-domain and frequency-domain HRV parameters were obtained with Kubios software. State food craving, and hunger and satiety were recorded before and after the intervention/control. Results: The intervention group decreased total state food craving scores and the sub-domains (i.e., desire to eat, positive reinforcement, lack of control and hunger), increased current satisfaction with food, decreased total state impulsivity (repeated measures ANOVA, p < 0.05 in all cases), increased HF-HRV and RMSSD (linear mixed model analyses with age and gender as fixed factors; p < 0.05 in all cases) during the intervention compared to the preceding baseline. The intervention group also showed an increase in positive mood and a decrease in aroused and negative mood states. Conclusion: Changes in state food craving and impulsivity could be related to an increase in HRV or to changes in subjective relaxation and positive mood or to both.

A CFD Methodology for the Modelling of Animal Thermal Welfare in Hybrid Ventilated Livestock Buildings

Computational fluid dynamics (CFD) may aid the design of barn ventilation systems by simulating indoor cattle thermal welfare. In the literature, CFD models of mechanically and naturally ventilated barns are proposed separately. Hybrid ventilation relies on cross effects between air change mechanisms that cannot be studied using existing models. The objective of this study was to develop a CFD methodology for modelling animal thermal comfort in hybrid ventilated barns. To check the capability of CFD as a design evaluation tool, a real case study (with exhaust blowers) and an alternative roof layout (with ridge gaps) were simulated in summer and winter weather. Typical phenomena of natural and mechanical ventilation were considered: buoyancy, solar radiation, and wind together with high-speed fans and exhaust blowers. Cattle thermal load was determined from a daily animal energy balance, and the assessment of thermal welfare was performed using thermohygrometric indexes. Results highlight that the current ventilation layout ensures adequate thermal welfare on average, despite large nonuniformity between stalls. The predicted intensity of heat stress was successfully compared with experimental measurements of heavy breathing duration. Results show strong interactions between natural and mechanical ventilation, underlining the need for an integrated simulation methodology.

Transient breathing dynamics of dissipative soliton in an ultrafast laser

The occurrence of periodically oscillatory behaviors in various nonlinear dissipative systems is known as breathing dynamics, which holds potential applications in spectroscopy. Herein, we have employed both experimental and numerical methods to investigate the breathing dynamics of dissipative soliton induced by Q-switched modulation in a mode-locked fiber laser. The findings indicate that the dynamics of breathing significantly influences the buildup stage of both stationary and breathing dissipative solitons. The breathing rate, breathing duration and breathing period are quite sensitive to the pump power. Numerical simulations are employed to generate similar breathing dynamics within the context of a model that combines equations describing the population inversion in a mode-locked laser. These obtained results provide confirmation that the Q-switching modulation is responsible for the initiation of breathing oscillations, and present novel prospects for the development of different operational frameworks for ultrafast lasers.

Development of a machine learning model for prediction of the duration of unassisted spontaneous breathing in patients during prolonged weaning from mechanical ventilation

PurposeTreatment of patients undergoing prolonged weaning from mechanical ventilation includes repeated spontaneous breathing trials (SBTs) without respiratory support, whose duration must be balanced critically to prevent over- and underload of respiratory musculature. This study aimed to develop a machine learning model to predict the duration of unassisted spontaneous breathing. Materials and methodsStructured clinical data of patients from a specialized weaning unit were used to develop (1) a classifier model to qualitatively predict an increase of duration, (2) a regressor model to quantitatively predict the precise duration of SBTs on the next day, and (3) the duration difference between the current and following day. 61 features, known to influence weaning, were included into a Histogram-based gradient boosting model. The models were trained and evaluated using separated data sets. Results18.948 patient-days from 1018 individual patients were included. The classifier model yielded an ROC-AUC of 0.713. The regressor models displayed a mean absolute error of 2:50 h for prediction of absolute durations and 2:47 h for day-to-day difference. ConclusionsThe developed machine learning model showed informed results when predicting the spontaneous breathing capacity of a patient in prolonged weaning, however lacking prognostic quality required for direct translation to clinical use.

Evaluation of Fetal Breathing-Related Nasal Fluid Flow Doppler in the Third Trimester in Pregnant Women with Fetal Growth Restriction: Preliminary Observations.

To investigate the fetal breathing-related nasal fluid flow Doppler waveforms as an indicator of fetal respiratory function in fetuses diagnosed with fetal growth restriction (FGR) in the third trimester. This prospective, non-interventional case-control study was conducted on 96 pregnant women, including 23 pregnant women diagnosed with FGR in the third trimester as the FGR group and 73 healthy pregnant women with fetuses appropriate for gestational age (AGA) as the control group. Fetal breathing-related nasal fluid flow Doppler was examined in the fetuses of the participants. Inspiration and expiration duration, inspiration and expiration peak velocity, total breathing duration, and number of fetal breaths per minute were calculated. Both groups were similar in terms of the duration of inspiration, duration of expiration, and total breathing duration (p=0.463, p=0.711, p=0.520, respectively). Peak inspiratory velocity and peak expiratory velocity were significantly lower in the FGR group than in the control group, and the number of fetal breaths per minute was similar in both groups (p=0.027, p=0.012, p=0.768, respectively). When participants were regrouped into those whose newborn was admitted to the neonatal intensive care unit (NICU) after birth and those who were not, all fetal nasal fluid flow Doppler parameters were similar in both groups. Although the number of participants was too small to draw a definitive conclusion, FGR appears to be associated with a decrease in peak inspiratory and expiratory velocity. The clinical significance of changes in fetal breathing-related nasal fluid flow Doppler parameters in FGR is as yet unclear, and their use in clinical follow-up and predicting unfavorable perinatal outcomes are the subjects of future research.

Transient breathing dynamics during extinction of dissipative solitons in mode-locked fiber lasers

The utilization of the dispersive Fourier transformation approach has enabled comprehensive observation of the birth process of dissipative solitons in fiber lasers. However, there is still a dearth of deep understanding regarding the extinction process of dissipative solitons. In this study, we have utilized a combination of experimental and numerical techniques to thoroughly examine the breathing dynamics of dissipative solitons during the extinction process in an Er-doped mode-locked fiber laser. The results demonstrate that the transient breathing dynamics have a substantial impact on the extinction stage of both steady-state and breathing-state dissipative solitons. The duration of transient breathing exhibits a high degree of sensitivity to variations in pump power. Numerical simulations are utilized to produce analogous breathing dynamics within the framework of a model that integrates equations characterizing the population inversion in a mode-locked laser. These results corroborate the role of Q-switching instability in the onset of breathing oscillations. Furthermore, these findings offer new possibilities for the advancement of various operational frameworks for ultrafast lasers.Graphical abstract

Infant periodic breathing and apneic threshold.

A mathematical model was proposed to predict the role played by apneic threshold in periodic breathing in preterm infants. Prior models have mainly applied linear control theory which predicted instability but could not explain sustained periodic breathing. Apneic threshold to CO2 which has been postulated to play a major role in infant periodic breathing is a nonlinear effect and cannot be described by linear theory. Another previously unexplored nonlinear factor affecting instability is brain vascular volume change with CO2 which affects time delay to chemoreceptors. The current model explored the influences of apneic threshold, central and peripheral chemoreceptor gains, cardiac output, lung volume, and circulatory time delay on periodic breathing. Apneic threshold was found to play a major role in ventilatory responses to spontaneous sighs. Sighs led to apneic pauses followed by periods of periodic breathing with peripheral chemoreceptor CO2 gain, cardiac output, and lung volume were at reported normal levels. Apneic threshold when exceeded was observed to cause an asymmetry in the periodic breathing cycling and an increased periodic breathing frequency. Sighs in infants occur frequently enough to lead to repeated stimulation within the epoch duration of periodic breathing for a single sigh. Multiple sighs may then play a major role in promoting continuous periodic breathing in infants. Peripheral chemoreceptor gain estimated using endogenous CO2 led to validated predicted periodic breathing cycle duration as a function of age. Brain vascular volume increase with CO2 contributes to periodic breathing in very young (1-2 day old) preterm infants.

Health-improving effect of running for students of technical specialties.

Aim: To study the dynamics of indicators of the functional state and health of technical specialties students during their long-term running engagement. Materials and Methods: The research involved 112 students (59 men and 53 women) aged 17-20 years. Two groups of students were formed: group 1 included students who, in addition to compulsory academic physical education training sessions, were not engaged in any type of motor activity on their own; group 2 included students who independently were engaged in recreational running 3 times a week in extracurricular time. Results: It was found that during the research period, both male and female students who were independently engaged in recreational running in extracurricular time showed a significant improvement of such indicators as resting heart rate, vital capacity of the lungs, duration of breath holding during inhalation and exhalation, duration of heart rate recovery after standard exercise, level of endurance development, level of physical health. Conclusions: The positive influence of independent running with moderate intensity on the functional state and health of students of technical specialties has been proved. The low efficiency of the physical education system in Ukraine and, accordingly, the insufficient level of motor activity, indicators of functional status, and health of students who, in addition to academic physical education training sessions, did not exercise on their own, were also confirmed.

CT data analysis of temporomandibular joint morphology in patients with Open-mouth breathing

ObjectiveThis study aims to investigate the correlation between open-mouth breathing and temporomandibular joint morphology by examining CT data in patients. MethodsFrom January to December 2022, 31 patients with open-mouth breathing and 20 with normal breathing were chosen from those attending the Stomatological Hospital of Chongqing Medical University. We compared condylar measurements among normal breathers (NB), pre-operative open-mouth breathers (Pre-OB), and post-operative open-mouth breathers (Post-OB) to identify statistically significant differences. ResultsUpon comparing the measurement parameters of the NB with the Pre-OB, we found significant statistical differences in the bilateral condylar height, depth of the articular fossa, anterior joint space, and the anterior inclined plane length of the condyle (p < 0.05).Further examination of the Pre-OB, when considering duration of open-mouth breathing, revealed pronounced differences in the condylar mediolateral diameter, fossa depth, anterior joint space, condylar height, and the condyle's horizontal angle (p < 0.05).Regarding the A/N ratio, it showed no significant correlation with the preoperative oral breathing group. Lastly, compared with Pre-OB, Post-OB highlighted a distinct statistical increase in the anterior slope length of the condyle (p < 0.05). ConclusionA discernible correlation between open-mouth breathing and condylar morphology exists. Continuous open-mouth breathing contributes to adaptive changes in the condylar morphology. Although limited post-operative data suggests that halting open-mouth breathing doesn't immediately result in condylar modifications, a relationship between the two phenomena remains evident.

Cardiorespiratory coupling in the bottlenose dolphin (Tursiops truncatus).

Introduction: The bottlenose dolphin (Tursiops truncatus) is an intermittent breather, where the breath begins with an exhalation followed by inhalation and an extended inter-breath interval ranging from 10 to 40s. Breathing has been shown to alter both the instantaneous heart rate (if H) and stroke volume (iSV) in the bottlenose dolphin, with a transitory ventilatory tachycardia following the breath, and an exponential decrease to a stable if H around 40 beats • min-1 during the inter-breath period. As the total breath duration in the dolphin is around 1s, it is not possible to assess the contribution of exhalation and inhalation to these changes in cardiac function during normal breathing. Methods: In the current study, we evaluated the if H response by separating expiration and inspiration of a breath, which allowed us to distinguish their respective contribution to the changes in if H. We studied 3 individual male bottlenose dolphins trained to hold their breath between the different respiratory phases (expiration and inhalation). Results: Our data show that inspiration causes an increase in if H, while expiration appears to result in a decrease in if H. Discussion: These data provide improved understanding of the cardiorespiratory coupling in dolphins, and show how both exhalation and inhalation alters if H.

Nasal Pressure Derived Airflow Limitation and Ventilation Measurements are Resilient to Reduced Signal Quality.

Obstructive sleep apnea is a disorder characterized by partial or complete airway obstructions during sleep. Our previously published algorithms use the minimally invasive nasal pressure signal routinely collected during diagnostic polysomnography (PSG) to segment breaths and estimate airflow limitation (using flow:drive) and minute ventilation for each breath. The first aim of this study was to investigate the effect of airflow signal quality on these algorithms, which can be influenced by oronasal breathing and signal-to-noise ratio (SNR). It was hypothesized that these algorithms would make inaccurate estimates when the expiratory portion of breaths is attenuated to simulate oronasal breathing, and pink noise is added to the airflow signal to reduce SNR. At maximum SNR and 0% expiratory amplitude, the average error was 2.7% for flow:drive, -0.5% eupnea for ventilation, and 19.7 milliseconds for breath duration (n = 257,131 breaths). At 20 dB and 0% expiratory amplitude, the average error was -15.1% for flow:drive, 0.1% eupnea for ventilation, and 28.4 milliseconds for breath duration (n = 247,160 breaths). Unexpectedly, simulated oronasal breathing had a negligible effect on flow:drive, ventilation, and breath segmentation algorithms across all SNRs. Airflow SNR ≥ 20 dB had a negligible effect on ventilation and breath segmentation, whereas airflow SNR ≥ 30 dB had a negligible effect on flow:drive. The second aim of this study was to explore the possibility of correcting these algorithms to compensate for airflow signal asymmetry and low SNR. An offset based on estimated SNR applied to individual breath flow:drive estimates reduced the average error to ≤ 1.3% across all SNRs at patient and breath levels, thereby facilitating for flow:drive to be more accurately estimated from PSGs with low airflow SNR.Clinical Relevance- This study demonstrates that our airflow limitation, ventilation, and breath segmentation algorithms are robust to reduced airflow signal quality.

Features of Cheyne-Stokes respiration automatically extracted from CPAP airflow signal raw data: Identification of discriminating features to detect heart failure

BackgroundContinuous positive airway pressure (CPAP) telemonitoring data is collected daily from millions of sleep apnea patients. This huge amount of data can be used for the early detection of treatment failures and could reveal incident acute or chronic cardiovascular events. However, the available automatically computed metrics do not fully characterize sleep-disordered breathing. ObjectiveTo find methods to process metrics characterizing Cheyne-Stokes respiration (CSR) that are able to discriminate between CSR related to heart failure (HF) and CSR related to other underlying conditions. MethodsThe raw airflow signals recorded by CPAP devices were analysed. Change point detection methods were used to isolate each respiratory cycle and CSR cycle. Simple algorithms were implemented to extract key features from the signal. Binary logistic regression was performed to identify the characteristics of the CSR airflow signal that is associated with the presence of underlying HF. ResultsLonger CSR cycles, a longer CSR episode, a greater variation in the amplitude of inspiration, a smaller increase in big breaths, a lower inter-cycle variability and a shorter breath duration were features associated with the occurrence of CSR in the context of HF. ConclusionThe proposed automated computation of CSR characteristics presents a novel tool to include in the CPAP software or remote monitoring platforms for monitoring patients’ treatment and comorbidities; and a step towards cross-disciplinary patient management.

A deep learning model to forecast cattle heat stress

The accurate forecasting of feedlot cattle heat stress is pivotal to improving animal welfare and reducing the economic losses associated with heat events. This study investigated how autonomously recorded cattle behaviour datasets can be leveraged to propose new approaches to cattle heat stress forecasting. Behaviour data acquired by accelerometer sensors in two experiments using mixed breed feedlot cattle were utilised, with duration of heavy breathing used to quantify heat stress. Two time-forecasting methods were proposed for predicting the average panting duration of a herd of cattle 24-hours into the future using meteorological data, animal characteristics and treatment factors as input. The first method utilised a simple deep learning framework based on Long-Short Term Memory networks, while the second applied traditional statistical methods to HLI, AHL and animal characteristic data. An optimisation algorithm was used to select which meteorological factors and how much historic data should be considered by the deep learning model. The experiments conducted emphasise that the deep learning approach was able to effectively model the lagged effect of weather on cattle heat stress. Consequently, it was found to be more accurate than traditional statistical methods and climate indices at forecasting the cattle heat response recorded in this study. A final experiment investigated the potential for using these time forecasting models to provide decision support to producers. This preliminary study thus emphasises that autonomously derived behaviour datasets and deep learning have the potential to improve animal welfare and productivity.

Methods for Heart Rate Variability Biofeedback (HRVB): A Systematic Review and Guidelines.

Heart Rate Variability Biofeedback (HRVB) has been widely used to improve cardiovascular health and well-being. HRVB is based on breathing at an individual's resonance frequency, which stimulates respiratory sinus arrhythmia (RSA) and the baroreflex. There is, however, no methodological consensus on how to apply HRVB, while details about the protocol used are often not well reported. Thus, the objectives of this systematic review are to describe the different HRVB protocols and detect methodological concerns. PsycINFO, CINALH, Medline and Web of Science were searched between 2000 and April 2021. Data extraction and quality assessment were based on PRISMA guidelines. A total of 143 studies were finally included from any scientific field and any type of sample. Three protocols for HRVB were found: (i) "Optimal RF" (n = 37), each participant breathes at their previously detected RF; (ii) "Individual RF" (n = 48), each participant follows a biofeedback device that shows the optimal breathing rate based on cardiovascular data in real time, and (iii) "Preset-pace RF" (n = 51), all participants breathe at the same rate rate, usually 6 breaths/minute. In addition, we found several methodological differences for applying HRVB in terms of number of weeks, duration of breathing or combination of laboratory and home sessions. Remarkably, almost 2/3 of the studies did not report enough information to replicate the HRVB protocol in terms of breathing duration, inhalation/exhalation ratio, breathing control or body position. Methodological guidelines and a checklist are proposed to enhance the methodological quality of future HRVB studies and increase the information reported.

Monitoring Respiratory Effort and Lung-distending Pressure Noninvasively during Mechanical Ventilation: Ready for Prime Time.

Monitoring Respiratory Effort and Lung-distending Pressure Noninvasively during Mechanical Ventilation: Ready for Prime Time.

An Impairment in Resting and Exertional Breathing Pattern May Occur in Long-COVID Patients with Normal Spirometry and Unexplained Dyspnoea.

Background: Long-term sequelae, called Long-COVID (LC), may occur after SARS-CoV-2 infection, with unexplained dyspnoea as the most common symptom. The breathing pattern (BP) analysis, by means of the ratio of the inspiratory time (TI) during the tidal volume (VT) to the total breath duration (TI/TTOT) and by the VT/TI ratio, could further elucidate the underlying mechanisms of the unexplained dyspnoea in LC patients. Therefore, we analysed TI/TTOT and VT/TI at rest and during maximal exercise in LC patients with unexplained dyspnoea, compared to a control group. Methods: In this cross-sectional study, we enrolled LC patients with normal spirometry, who were required to perform a cardio-pulmonary exercise test (CPET) for unexplained dyspnoea, lasting at least 3 months after SARS-CoV-2 infection. As a control group, we recruited healthy age and sex-matched subjects (HS). All subjects performed spirometry and CPET, according to standardized procedures. Results: We found that 42 LC patients (23 females) had lower maximal exercise capacity, both in terms of maximal O2 uptake (VO2peak) and workload, compared to 40 HS (22 females) (p < 0.05). LC patients also showed significantly higher values of TI/TTOT at rest and at peak, and lower values in VT/TI at peak (p < 0.05). In LC patients, values of TI/TTOT at peak were significantly related to ∆PETCO2, i.e., the end-tidal pressure of CO2 at peak minus the one at rest (p < 0.05). When LC patients were categorized by the TI/TTOT 0.38 cut-off value, patients with TI/TTOT > 0.38 showed lower values in VO2peak and maximal workload, and greater values in the ventilation/CO2 linear relationship slope than patients with TI/TTOT ≤ 0.38 (p < 0.05). Conclusions: Our findings show that LC patients with unexplained dyspnoea have resting and exertional BP more prone to diaphragmatic fatigue, and less effective than controls. Pulmonary rehabilitation might be useful to revert this unpleasant condition.