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Abstract

Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disorder characterized by irreversible airflow limitation and respiratory muscle dysfunction. Bioactive lipid mediators such as prostaglandins, leukotrienes, and specialized pro-resolving mediators (SPMs) play critical roles in regulating inflammation, yet their relationship with diaphragmatic performance in COPD remains poorly understood. This case-control study investigated the association between circulating lipid mediators and diaphragmatic function in 40 male COPD patients and 40 age- and sex-matched healthy controls. All participants underwent clinical assessment, spirometry, C-reactive protein (CRP) measurement, blood sampling for lipid mediator profiling—including polyunsaturated fatty acid (PUFA)-derived metabolites—and diaphragmatic ultrasound evaluation of excursion and thickening fraction (TF). COPD patients exhibited significantly impaired diaphragmatic function and elevated pro-inflammatory lipid mediators compared with controls. Receiver operating characteristic (ROC) analysis identified Prostaglandin E2 (PGE₂) (area under the curve [AUC] = 0.826), Thromboxane B2 (TXB₂) (AUC = 0.832), and Leukotriene B4 (LTB₄) (AUC = 0.737) as strong diagnostic biomarkers for COPD. Among SPMs, RvD1 correlated positively with diaphragmatic excursion (r = .62) and TF (r = .58), Lipoxin A4 (LXA₄) correlated with Forced Expiratory Volume in one second (FEV₁) (r = .66), and Protectin DX (PDX) showed an inverse association with the COPD Assessment Test (CAT) score (r = −.54). Leukotriene E4 (LTE₄) and Leukotriene D4 (LTD₄) were negatively associated with diaphragmatic performance, while CRP levels inversely correlated with ultrasound parameters. Diaphragmatic TF demonstrated high sensitivity (90%) and specificity (92%) in predicting severe exacerbations. These findings suggest that lipid mediator imbalance contributes to diaphragmatic dysfunction in COPD and that combining lipidomic profiling with diaphragmatic ultrasound may offer a promising approach for assessing systemic inflammation and respiratory muscle performance in male COPD patients.

Keywords

chronic obstructive pulmonary disease lipid mediators diaphragm ultrasound biomarkers

Introduction

Chronic obstructive pulmonary disease (COPD) is a gradually progressing, inflammatory lung condition that is characterized by irreversible airflow obstruction and chronic airway inflammation. COPD is among the most common causes of morbidity and mortality across the world (Agarwal et al., 2025). Although smoking and environmental exposures are the most prominent contributors, the present evidence identifies the role of bioactive lipid mediators like leukotrienes, prostaglandins, and specialized pro-resolving mediators (SPMs) toward COPD pathogenesis (Bedi et al., 2022; Montuschi et al., 2003).

Elevated levels of pro-inflammatory lipids promote airway inflammation, neutrophilic infiltration, and tissue injury. Simultaneously, a reduction in pro-resolving mediators hinders the resolution of inflammation, exacerbating chronic lung damage (Bedi et al., 2022; Koutsokera et al., 2013).

Apart from pulmonary dysfunction, COPD has systemic consequences, more significantly at the level of the diaphragm, the principal muscle of ventilation. Diaphragmatic dysfunction with reduced thickness and excursion is a principal cause of dyspnea and limited exercise capacity. Ultrasound has the potential to provide a truly noninvasive technique for the quantitative evaluation of diaphragmatic activity, such as excursion and Thickening Fraction (TF), both reduced in COPD subjects (Lux et al., 2021).

While cytokine-induced inflammation has been implicated in respiratory muscle dysfunction, the impact of lipid mediators on diaphragm function remains poorly understood. In the present study, we attempted to evaluate the correlation between systemic inflammatory lipid mediators, notably SPMs, and diaphragmatic ultrasound measurements in COPD participants and reveal potential new biomarkers and treatment targets.

Methods

This cross-sectional observational study was conducted between September 2023 and December 2024 and included two groups. The COPD group comprised 40 male patients above 45 years of age with Global Initiative for Chronic Lung Disease (GOLD)–defined COPD, who were current or former smokers with at least 10 pack-years and had stable disease. The control group included 40 age- and sex-matched healthy individuals without any history of respiratory disease.

We included patients above 40 years old with a confirmed COPD diagnosis according to the GOLD criteria, a history of current or past cigarette smoking (>10 packages per year), and who had been in a stable condition for at least 1 month.

We excluded patients with chronic lung diseases other than COPD, known diaphragmatic paralysis, oncological diseases, a life expectancy less than 6 months, significant cognitive impairment, those taking statins or polyunsaturated fatty acid (PUFA) supplements, or following anti-inflammatory diets, as well as patients unable to complete interviews, questionnaires, or tests. In addition, patients who experienced a COPD exacerbation within 4 weeks prior to the initial visit, had recent corticosteroid or immunosuppressive therapy, or had incomplete data were also excluded.

We evaluated dyspnea using the modified Medical Research Council (mMRC) scale and symptom impact using the COPD Assessment Test (CAT).

Bronchodilators were discontinued prior to spirometry, for 6 hr in the case of short-acting agents and 12 to 24 hr for long-acting agents. Spirometry was performed using a plethysmograph (Medisoft Bodybox 5500).

Lung function tests were performed according to international guidelines, using local reference values and by the same trained technician. A bronchodilator responsiveness test was performed by giving the patient an inhalation of a Salbutamol-type bronchodilator at a dose of 400 μg.

The following parameters were recorded: forced vital capacity (FVC), expiratory reserve volume (ERV), inspiratory reserve volume (IRV), forced expiratory volume in one second (FEV1), vital capacity (VC), and residual volume (RV).

RV is calculated from the equation: RV = FVC – ERV.

Tiffeneau’s index is calculated from the equation: Tiffeneau’s index = FEV1/FVC

Ultrasound examinations were performed using a nonportable Esaote ultrasound system equipped with B-mode and M-mode capabilities, with patients positioned in a semi-recumbent posture. An eight-zone lung ultrasound protocol was used to assess B-lines, pleural effusion, and consolidation to evaluate potential pulmonary influences on diaphragmatic motion. Diaphragmatic excursion (DE) was measured using a convex probe in M-mode during deep breathing:

DE measured with a convex probe in M-mode during quiet and deep breathing.

Diaphragmatic Thickening (DT) and TF measured with a linear probe at the zone of apposition using B- and M-mode. TF was calculated as:

$\begin{matrix} T F (%) = [(T h i c k n e s s a t e n d - i n s p i r a t i o n - \\ T h i c k n e s s a t e n d - e x p i r a t i o n) / \\ T h i c k n e s s a t e n d - e x p i r a t i o n] \times 100 \end{matrix}$

Fasting blood samples were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to quantify the following:

Lipid mediators, including prostaglandins, leukotrienes, and SPMs such as resolvin D1 (RvD1), lipoxin A4 (LXA4), protectin DX (PDX), 18-hydroxyeicosapentaenoic acid (18-HEPE), and 15-epi-lipoxin A4 (15-epi-LXA4).

Polyunsaturated fatty acids (PUFA), including eicosapentaenoic acid (EPA), alpha-linolenic acid (ALA), docosahexaenoic acid (DHA), docosapentaenoic acid (DPA), and arachidonic acid (AA).

CRP via immunoassay.

Data were analyzed using SPSS 25, Metaboanalyst 5.0 and GraphPad Prism 9. Tests included t tests, analysis of variance (ANOVA), Mann–Whitney U, correlation analysis, receiver operating characteristic (ROC) analysis, and multivariate regression. Significance was set at p < .05.

This work was approved by the ethics committee. Patients and controls were included after being informed of the objectives of the study and after the collection of free and informed written consent.

Results

General Characteristics

Table 1 summarizes the general characteristics of the COPD and control groups, including demographic factors, smoking history, and relevant clinical parameters, providing a baseline comparison between the two populations.

Table 1.

Summary of Characteristics in COPD Patients and Controls.

Variable	COPD (n = 40)	Control (n = 40)	p value
Age (years)	63.78 ± 7.96	59.08 ± 6.90	.291
BMI (kg/m²)	22.69 [17–31.3]	22.23 [16.9–32]	.12
Smokers (%)	100%	100%	.520
Smoking (pack-years)	67.8 ± 30.4	17.25 ± 5.37	<.001
Hypertension (%)	35%	35%	.99
Diabetes (%)	7.5%	10%	.692
Dyslipidemia (%)	5%	7.5%	.644
Coronary Heart Disease (%)	10%	10%	.98

Lung Function and Diaphragmatic Performance

COPD patients exhibited significantly reduced pulmonary function, accompanied by decreased diaphragmatic mobility, reflecting both airflow limitation and impaired respiratory muscle performance. Table 2 features pulmonary function and diaphragmatic mobility in patients and controls.

Table 2.

Pulmonary Function and Diaphragmatic Mobility in Patients and Controls.

Parameter	COPD (n = 40)	Control (n = 40)	p value
FVC (L)	2.15 ± 0.77	3.53 ± 0.34	<.001
FVC (% predicted)	63.78 ± 11.23	91.42 ± 8.03	<.001
FEV1 (L)	1.47 ± 0.49	3.42 ± 0.35	<.001
FEV1 (% predicted)	47.87 ± 13.78	89.48 ± 5.79	<.001
Tiffeneau’s Index (FEV1/FVC %)	55.41 ± 8.99	90.98 ± 6.89	<.001
Diaphragmatic Excursion (cm)	2.3 ± 0.6	4.1 ± 0.7	<.001
Thickening Fraction (%)	23 ± 8	45 ± 9	<.001

Lipid Mediators Profiles

Tables 3 and 4 compare lipid mediator profiles between COPD patients and controls, with Table 3 showing pro-inflammatory mediators and polyunsaturated fatty acids, and Table 4 presenting specialized pro-resolving mediators.

Table 3.

Comparison of Pro-Inflammatory Lipid Mediators and Polyunsaturated Fatty Acids Levels Between Patients and Controls Values Are Expressed as Median [25th–75th Percentile].

Biomarker	Patients	Controls	p value
Polyunsaturated Fatty Acids (PUFA)
Arachidonic Acid (AA), ng/ml	598190 [305121–9753821]	420638 [221309–881828]	.083
Eicosapentaenoic Acid (EPA), ng/ml	75327 [33020–121411]	37739 [25298–88225]	.021
Alpha-linolenic Acid (ALA), ng/ml	595964 [262563–1113355]	526456 [240195–758129]	.125
Docosahexaenoic Acid (DHA), ng/ml	370385 [197724–711177]	265204 [170532–505653]	.100
Docosapentaenoic Acid (DPA), ng/ml	164654 [82151–292044]	108386 [71808–210616]	.100
Prostaglandins and Leukotrienes
PGD2, pg/ml	16.09 [8.62–31.53]	7.56 [4.40–10.19]	<.001
PGE2, pg/ml	20.51 [11.02–38.80]	5.17 [3.42–8.03]	<.001
PGF2α, pg/ml	27.78 [18.78–40.24]	21.82 [15.44–31.99]	<.001
6-keto-PGF1α, pg/ml	19.35 [6.53–4.77]	10.99 [6.51–19.35]	<.001
LTB4, pg/ml	625.60 [373.44–1141]	305.32 [203.97–524.04]	<.001
LTD4, pg/ml	22.88 [8.01–82.50]	13.66 [8.49–32.52]	.117
LTE4, pg/ml	9.93 [5.99–15.34]	7.59 [3.53–11.03]	.028
LTF4, pg/ml	7.11 [4.58–16.47]	5.29 [3.24–12.25]	.204
TXB2, pg/ml	407.73 [166.7–1176]	56.06 [21.26–107.65]	<.001
Inflammatory Marker
CRP, mg/L	2.2 [1.35–9.00]	0.5 [0.5–1.73]	.01

Bold p values indicate statistical significance (p < .05).

Table 4.

Comparison of Specialized Pro-Resolving Mediators Levels Between Patients and Controls.

Specialized pro-resolving mediators (SPMS)
Resolvin D1, pg/ml	1.27 [0.74–2.20]	1.64 [0.86–2.44]	0.252
Resolvin D5, pg/ml	2.96 [1.96–4.91]	3.41 [1.61–4.92]	0.897
Protectin D1 (PDX), pg/ml	2.18 [1.58–3.02]	2.15 [1.73–3.13]	0.926
Lipoxin A4, pg/ml	1.95 [1.30–3.64]	1.68 [1.19–2.72]	0.356
Lipoxin B4, pg/ml	2.58 [1.73–5.38]	3.79 [2.46–5.69]	0.148
6-epi-Lipoxin A4, pg/ml	2.17 [1.04–4.36]	2.34 [1.45–3.41]	0.470
15-epi-Lipoxin B4, pg/ml	0.52 [0.23–0.81]	0.43 [0.30–0.64]	0.693

The ROC curve analysis showed a significant diagnostic value of the following biomarkers in COPD: EPA (area under the curve [AUC] = 0.624; p = .021), PGD2 (AUC = 0.693, p < 10⁻³), PGE2 (AUC = 0.826, p < 10^-3), PGF2α (AUC = 0.607, p < 10⁻³), Thromboxane B2 (TXB2) (AUC = 0.832, p < 10⁻³), Leukotriene B4 (LTB4) (AUC = 0.737, p < 10⁻³), 6-keto-PGF 1α (AUC = 0.724, p < 10⁻³), LTE4 (AUC = 0.647, p = .028). Figure 1 features only the most significant biomarkers.

Figure 1.

Diagnostic and Predictive Lipid Mediators in COPD.

The risk of COPD was positively associated with LTB4, TXB2, 6-keto-PGF 1α and with PGD2, PGE2 and PGF2a. Values above the threshold for these biomarkers were associated with a higher risk of COPD (Figure 2).

Figure 2.

Odds Ratios of Proinflammatory Lipid Mediators.

In patients with COPD, RvD1 was positively correlated with DE (r = .62) and TF (r = .58). LXA4 showed a positive correlation with FEV₁ (r = .66). Protectin DX (PDX) was negatively correlated with the CAT score (r = −.54).

Figure 3 shows the different correlations between peripheral oxygen saturation and Prostaglandin D2 (PGD2), Prostaglandin 2a (PGF2α), Leukotriene F4 (LTF4) and C-reactive protein (CRP) levels.

Figure 3.

Correlations Between Peripheral Oxygen Saturation and PGD2, PGF2α, LTF4 and CRP Levels.

A significant canonical correlation was identified between diaphragmatic ultrasound parameters and leukotriene levels in COPD patients. Specifically, DT was negatively correlated with LTE4 levels in Group E patients (r = −.377, p < .001), and Leukotriene D4 (LTD₄) levels were inversely associated with TF in individuals with chronic respiratory failure (r = −.347, p < .001) (Figure 4).

Figure 4.

Diaphragmatic Ultrasound Correlations With Leukotrienes and CAT Score.

TF demonstrated a high predictive capacity for identifying patients at risk of severe COPD exacerbations, with a sensitivity of 90% and specificity of 92%. In addition, CRP levels were significantly and inversely associated with diaphragmatic ultrasound parameters, including excursion (r = −.45; p < .01) and TF (r = −.42; p < .01).

Discussion

This study provides compelling evidence that systemic lipid mediator imbalances are strongly associated with diaphragmatic dysfunction in male patients with COPD.

DE and TF were significantly reduced in the COPD group compared with controls, reflecting impaired respiratory muscle performance, a hallmark of advanced disease. These findings are consistent with previous reports that describe respiratory muscle dysfunction as a systemic consequence of chronic inflammation in COPD (Ottenheijm et al., 2008; Umbrello et al., 2015).

Dietary variations may partially explain these differences. In our cohort, the Mediterranean diet, rich in omega-3 PUFAs, could account for the observed results. Our study showed a significant increase in the omega-3 fatty acid EPA in COPD patients compared with controls; this assay was discriminatory according to the ROC curve, with the risk of COPD 2.5 times higher for values above the threshold. This aligns with the systematic review by Evan Atlantis and Belinda Cochrane on PUFA intake and inflammation in COPD, which found no evidence that low or high dietary intake of specific omega-3 fatty acids, including EPA, affects inflammation (Atlantis & Cochrane, 2016). Consistently, levels of DHA, DPA, Alphalinoleic Acid (ALA), and AA were similar in COPD and control groups, in agreement with a cross-sectional study of the Australian population by Fulton AS et al., which reported no differences in plasma PUFA levels or intake between COPD patients and controls (Fulton et al., 2013).

Moderate, regular exercise has been shown to reduce pro-inflammatory lipid mediators while sustaining pro-resolving mediators, modulating macrophage-driven immune responses across tissues, and potentially complementing dietary effects in regulating systemic inflammation (Halade et al., 2024).

Our results indicate that circulating levels of pro-inflammatory lipid mediators, including prostaglandins (PGD2, PGE2, PGF2α), leukotrienes (LTB4, LTE4), and TXB2, were significantly elevated in COPD patients. These mediators are well known for promoting neutrophilic inflammation, increasing vascular permeability, and contributing to pulmonary and extrapulmonary tissue injury (Barnes, 2016; Peters-Golden & Henderson, 2007). Prostaglandins PGD2, PGE2, PGF2α, and 6-keto-PGF1α were significantly higher in COPD patients than in controls, with PGE2 showing the best discrimination on ROC curves, followed by PGD2 and PGF2α. Previous studies, mainly in asthmatic patients, have linked increased PGD2 to inflammation, as it is produced by activated mast cells or T cells (W. L. Smith et al., 2011), and is generated in the airways following antigen challenge (Murray et al., 1992). PGD2 is a powerful bronchoconstrictor and the main prostanoid inflammatory biomarker in asthma (Hardy et al., 1984), mediating eosinophil and CD4+ T lymphocyte recruitment (Baothman et al., 2018). Evidence suggests it also contributes to COPD, as smokers and COPD patients have increased mast cells in the bronchial epithelium (Grashoff et al., 1997), consistent with the elevated plasma PGD2 observed in our study. PGE2 levels are increased in COPD patients’ exhaled breath and sputum, particularly in current smokers (Profita et al., 2003). PGF2α, originally identified by Samuelsson et al. (1978), is elevated in COPD exhaled breath condensate and bronchoalveolar lavage fluid (BALF) (Montuschi, 2005; Watson et al., 1992) and can reduce airway conductance in humans and animals (A. P. Smith & Cuthbert, 1972). Together, these findings support the involvement of prostaglandins in systemic and airway inflammation in COPD.

Notably, PGE2, which exhibited the highest discriminatory power among prostaglandins (AUC = 0.826), has been implicated in skeletal muscle wasting via activation of NF-κB and ubiquitin-proteasome pathways (Liu et al., 2016; Standley et al., 2013). Elevated TXB2 and LTB4 levels were also associated with increased COPD risk and showed robust performance in ROC analysis (AUC = 0.832 and 0.737, respectively).

LTE4 was significantly related to body mass index (BMI), implying that there was a metabolic aspect to its elevation, and PGD2 and LTF4 were negatively related to oxygen saturation, potentially associating inflammatory load with gas exchange impairment. CRP measurements were likewise substantially elevated in the COPD group, supporting the presence of systemic inflammation.

Correspondingly, SPMs such as RvD1, LXA4, and PDX were lower among COPD participants. These are important molecules that have principal roles in resolving inflammation and restoring tissue homeostasis (Hsiao et al., 2013; Serhan, 2014). RvD1 decrease was significantly related with DE (r = .62; TF: r = .58), LXA4 with FEV1 (r = .66), and PDX with CAT score (r = −.54), suggesting clinical relevance.

We identified a significant canonical correlation between leukotrienes and diaphragmatic performance. Specifically, DT was inversely correlated with LTE4 in Group E patients (r = −.377; p < .001), and LTD4 showed a negative correlation with TF in those with chronic respiratory failure (r = −.347; p < .001). These findings imply that persistent inflammation may contribute directly to respiratory muscle impairment (Scheibe et al., 2015).

In the predictive studies, the TF showed high sensitivity (90%) and specificity (92%) for detecting at-risk patients with severe COPD exacerbations and may serve as a valuable noninvasive biomarker. The ROC study identified some lipid mediators with remarkable diagnostic potential, such as PGE2, TXB2, LTB4, PGD2, and 6-keto-PGF1α.

The observed pattern of elevated pro-inflammatory and diminished pro-resolving lipid mediators supports the hypothesis of impaired lipid mediator class switching (Bozinovski et al., 2014; Levy et al., 2001). This dysregulation may perpetuate unresolved inflammation and oxidative stress, leading to progressive diaphragm dysfunction.

Importantly, diaphragmatic ultrasound, a simple point-of-care tool, correlated with multiple biomarkers of inflammation and disease severity, reinforcing its value in clinical phenotyping and risk stratification. In addition, CRP levels were inversely correlated with diaphragmatic parameters, including TF and DE, further supporting the link between systemic inflammation and respiratory muscle dysfunction in COPD.

It is the first case-control study that investigated the link between diaphragmatic function, assessed by ultrasound, and systemic inflammatory lipid mediators, including PUFA, pro-inflammatory mediators, and SPMs, in COPD patients. These findings provide new evidence of the complex interplay between systemic inflammation and respiratory muscle dysfunction in COPD that is defined by lipid mediator profiles related to diaphragmatic dysfunction and disease severity.

We employed a rigorous methodology to minimize bias and limit biological variability, enrolling a representative sample of COPD patients routinely followed in our department. COPD and control groups were carefully matched for age, smoking history, and comorbidities, and only patients with isolated COPD or comorbidities unlikely to affect systemic lipid mediator levels were included. The cohort comprised only male participants, reflecting the higher COPD prevalence in men and departmental recruitment criteria, although this limits generalizability to women. Participants were not taking statins, PUFA supplements, or following anti-inflammatory diets. We acknowledge the biological variability of lipid mediators, including inter- and intra-individual differences (genetics, age, comorbidities, physical activity, circadian rhythms, acute inflammation), and minimized these effects through standardized fasting blood collection at consistent times and controlled medications and diet. This approach allowed identification of key lipid mediators associated with diaphragmatic dysfunction and establishment of thresholds distinguishing COPD patients from controls, advancing understanding of mechanisms linking systemic inflammation and respiratory muscle impairment, with a focus on systemic rather than local airway markers.

Combining traditional physiology (spirometry, the 6-min walk test), diaphragm mechanics (thickening fraction, DE), and lipid mediator profiling provides a three-dimensional view of COPD, linking airflow limitation, diaphragmatic function, and inflammation/resolution balance; for example, in stable patients with frequent exacerbations, lipid mediators profiling may reveal a persistent pro-inflammatory state.

These findings not only improve understanding of the link between systemic inflammation and diaphragmatic dysfunction in COPD but also suggest potential therapeutic implications, such as targeting SPMs to restore inflammatory balance and support respiratory muscle function.

Incorporating TF measurement and lipidomic profiling into routine assessment could enable early detection of diaphragmatic impairment, risk stratification, and personalized management of COPD.

Conclusion

This study establishes that imbalances in lipid mediators are directly related with diaphragmatic dysfunction among male COPD subjects. Increased pro-inflammatory lipid mediators and lower concentration of SPMs are aligned with abnormal diaphragm ultrasound parameters and severity. These findings suggest a pathophysiological link between unresolved inflammation and diaphragm impairment in COPD, opening the door to lipid-targeted therapeutic strategies.

Footnotes

ORCID iD

Warda Jelassi

Author Contributions

Abir Hedhli: Study design and development; Data analysis and interpretation; Writing the article; Drafting the work or revising it critically for important intellectual content; Final approval of the submitted version; Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Warda Jelassi: Study design and development; Data analysis and interpretation; Writing the article; Drafting the work or revising it critically for important intellectual content; Final approval of the submitted version; Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Sameh Hajtaeib: Study design and development; Data analysis and interpretation; Writing the article; Drafting the work or revising it critically for important intellectual content; Final approval of the submitted version; Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Khadija Euchi: Study design and development; Data analysis and interpretation; Writing the article; Drafting the work or revising it critically for important intellectual content; Final approval of the submitted version; Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Mohamed Kacem Ben Fraj: Study design and development; Data analysis and interpretation; Writing the article; Drafting the work or revising it critically for important intellectual content; Final approval of the submitted version; Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Yacine Ouahchi: Study design and development; Data analysis and interpretation; Writing the article; Drafting the work or revising it critically for important intellectual content; Final approval of the submitted version; Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Meriem Mjid: Study design and development; Data analysis and interpretation; Writing the article; Drafting the work or revising it critically for important intellectual content; Final approval of the submitted version; Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work is appropriately investigated and resolved.

Sana Cheikhrouhou: Study design and development; Data analysis and interpretation; Writing the article; Drafting the work or revising it critically for important intellectual content; Final approval of the submitted version; Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Sonia Toujani: Study design and development; Data analysis and interpretation; Writing the article; Drafting the work or revising it critically for important intellectual content; Final approval of the submitted version; Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work is appropriately investigated and resolved.

Moncef Feki: Study design and development; Data analysis and interpretation; Writing the article; Drafting the work or revising it critically for important intellectual content; Final approval of the submitted version; Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work is appropriately investigated and resolved.

Besma Dhahri: Study design and development; Data analysis and interpretation; Writing the article; Drafting the work or revising it critically for important intellectual content; Final approval of the submitted version; Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work is appropriately investigated and resolved.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Exploring the Relationship Between Diaphragmatic Ultrasound Parameters and Lipid Mediators in Chronic Obstructive Pulmonary Disease: A Case Control Study

Abstract

Keywords

Introduction

Methods

Results

General Characteristics

Lung Function and Diaphragmatic Performance

Lipid Mediators Profiles

Discussion

Conclusion

Footnotes

ORCID iD

Author Contributions

Funding

Declaration of Conflicting Interests

References