Abstract
Background
Pseudomonas aeruginosa (PA) isolation in patients with chronic obstructive pulmonary disease (COPD) has been associated with a poor prognosis. This meta-analysis aimed to determine significant risk factors for PA isolation among patients with COPD.
Methods
A systematic literature retrieval from PubMed, Embase, Web of Science and China National Knowledge Infrastructure (CNKI) was conducted, including studies from January 2003 to September 2024. Case-control and cohort studies exploring the risk factors for PA isolation in patients with COPD were included in this analysis. A random-effects model was applied to estimate the pooled adjusted odds ratio (paOR) or hazard ratio (paHR) with the corresponding 95% confidence intervals (CI).
Results
Thirteen eligible studies with a total of 25,802 participants were included in this meta-analysis. Prior systemic steroid therapy (paOR: 2.67; 95% CI: 1.29–5.53; P = 0.008), previous antibiotic treatment (paOR: 2.83; 95% CI: 1.14–6.97; P = 0.02), high “Body mass index, airflow Obstruction, Dyspnea, Exercise capacity” (BODE) index (paOR: 4.13; 95% CI: 1.67–10.23; P = 0.002), 6-min walking distance (6MWD) < 250 m (paOR: 4.27; 95% CI: 2.59–7.01; P < 0.001), COPD assessment test (CAT) score > 20 points (paOR: 2.49; 95% CI: 1.46–4.23; P = 0.001), hypoproteinemia (paOR: 2.62; 95%CI: 1.32–5.19; P = 0.006), hospitalizations in the previous year (paOR: 3.74; 95%CI: 1.22–11.49; P = 0.021), Bronchiectasis (paOR = 4.81; 95% CI: 3.66–6.33; P < 0.001) and prior PA isolation (paOR: 16.39; 95% CI: 7.65–35.10; P < 0.001) were associated with PA isolation in patients with COPD.
Conclusions
Our study identified nine risk factors associated with an increased risk of PA isolation in COPD patients. These findings are significant for the early identification of patients at risk for PA isolation, which might contribute to reducing mortality and improving clinical outcomes.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12890-024-03309-x.
Keywords: Pseudomonas aeruginosa, Risk factors, COPD, Systematic review, Meta-analysis
Introduction
Chronic obstructive pulmonary disease (COPD) is characterized by an injury in airway along with the impairment of respiratory function [1, 2]. Not only does COPD elevate the likelihood of future exacerbations, but it is also linked to the emergence of respiratory conditions like pneumonia and lung cancer, in addition to non-respiratory ailments [3]. Bacterial infections are widely acknowledged as major contributors to morbidity [4], especially Pseudomonas aeruginosa (PA), which was recognized as one of the common bacterial pathogens [5].
Research has indicated that PA, noted for its ability to easily colonize and exhibit drug resistance, can be identified in approximately 4–20% of individuals experiencing AECOPD [6, 7]. The presence of PA has been shown to complicate antibiotic treatment and is linked to worse clinical outcomes [8–10]. Findings have suggested that infection with PA correlates to a heightened risk of readmission at 30 days post-discharge and hospitalization at two years [11]. A study revealed that patients with PA detected in their sputum faced an adjusted risk of mortality that was three times higher compared to those without PA [12]. Furthermore, a meta-analysis indicated that the overall mortality rate rises by 95% in patients with isolated strains of PA [11]. Additionally, another investigation demonstrated that AECOPD patients suffering from multi-resistant PA infections had an increased risk of death, suggesting that the isolation of PA serves as an independent risk predictor for negative clinical outcomes [13].
The guidelines of the European Respiratory Society provide some recommendations for suspecting a PA isolation in certain patients and several studies have investigated the risk factors for PA isolation in patients with COPD [14], however the results were inconsistent. Our study aimed to gather findings from existing literature and assess the cumulative risk of factors associated with PA isolation in individuals diagnosed with COPD.
Methods
We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to conduct this meta-analysis [15]. The protocol was published in the Database of Prospectively Registered Systematic Reviews (PROSPERO) with number CRD 42,023,399,902.
Search strategy
We performed a systematic literature retrieval from PubMed, Embase, Web of Science, and China National Knowledge Infrastructure (CNKI) from January 2003 to September 2024. Our search strategy included both keywords and free-language terms for chronic obstructive pulmonary disease, Pseudomonas aeruginosa and risk factors. No geographic area or language was restricted in the publications. Additional studies were identified by manually searching the references lists of the included studies. The search strategy was showed in the supplementary materials.
Inclusion and exclusion criteria
The studies were considered eligible when they met the following criteria: (1) case-control or cohort study design; (2) patients with confirmed COPD diagnosis in a stable state or with acute exacerbations; (3) PA isolation was defined as PA presence in sputum samples; and (4) exposure to factors examined in at least two studies. We excluded conference abstracts, case reports, animal studies, and republished researches.
Data extraction and literature quality evaluation
Two independent reviewers examined the titles and abstracts of all the studies retrieved, determined the eligible ones based on the criteria listed above, and extracted the basic information from selected studies, including the first author, country, study design, COPD diagnosis, study population and outcome definition. The adjusted estimated effects expressed as odds ratios (OR) or hazard ratios (HR), and the original data were both extracted for a more comprehensive evaluation of the relevant risk factors. The study quality was assessed using the Newcastle–Ottawa Scale (NOS), comprising eight items from three different aspects (selection, comparability, and exposure/outcome). The study quality was judged as high (scores of 7–9), medium (4–6), or low (1–3). Any discrepancy in judgement was resolved by discussion.
Statistical analysis
Stata17.0 (Stata Corp LLC, College Station, TX, USA) was used to perform the statistical analysis. The studies were divided into groups based on the type of risk factors. Estimates that used the same effect measures (OR or HR) from at least two studies were included in the analysis. If the adjusted estimated effect was unavailable, the original data were used to calculate a crude estimated effect. We focused on the adjusted outcomes, and the crude outcomes were included as a sensitivity analysis. Heterogeneity was assessed using the I2 test: a high heterogeneity was expected, thus no threshold was formulated for the I2 test, and we utilized a random-effects model to estimate the pooled effects. The data are presented graphically using forest plots. Publication bias was not assessed due to the limited number of eligible studies.
Results
Characteristics of the eligible studies
A total of 1884 relevant studies were identified from our search, and thirteen were finally included in our meta-analysis: six cohort and seven case-control studies (Fig. 1). The sample size ranged from 90 to 21,408, and a pooled total of 25,802 participants were enrolled. These studies were conducted in four countries, and the majority in Spain and China. Nine studies were published in English and four in Chinese. The years of publication ranged from 2003 to 2023. All the included studies assessed the presence of PA in the sputum of individuals during acute exacerbation or stable states of COPD. The characteristics of the thirteen studies included are presented in Table 1.
Fig. 1.
Flow diagram of search strategy and selection of studies
Table 1.
Characteristics of eligible studies
| Study | Country | Design | COPD diagnosis | Study population | Outcome definition | Adjusted OR/HR (95% CI) | Crude OR (95% CI) |
NOS score |
|---|---|---|---|---|---|---|---|---|
| Sim et al. [20] |
Republic of Korea |
Cohort |
Post-bronchodilator FEV1/FVC<70% |
1177 patients with AECOPD (118 cases) |
Sputum polymerase chain reaction for PA detection |
SCS (prior 6 months) aOR, 1.62(1.01–2.60) |
7 | |
|
Pascual-Guardia et al. [25] |
37 countries | Observational | GOLD criteria | 689 COPD patients |
PA was detected in respiratory samples |
Bronchiectasis: aOR, 3.2(1.41- 2.73) Prior PA isolation: aOR, 14.2(5.74 - 35.2) Hospital admissions in previous year: aOR, 3.73 (1.5 - 9.26) |
8 | |
| Feng et al. [24] | China | Case-control |
Post-bronchodilator FEVI/FVC<70% |
1014 inpatients with COPD (338 casea and 676 controls) |
PA- positive sputum |
Albumin < 35 g/L: aOR, 1.4 (1.04 - 1.88) Bronchiectasis: aOR, 4.97 (3.7 - 6.67) |
8 | |
|
Eklöf et al. [23] |
Danish | Cohort |
Danish Register of COPD |
21 408 outpatients with COPD (763 cases) |
PA-positive lower respiratory tract culture |
ICS: aHR, 2.26 (1.76-2.89) Antibiotics: aOR, 1.14 (1.07 -1.23) |
9 | |
|
Shafiek et al. [46] |
Spain | Case-control | GOLD criteria |
358 frequent exacerbated patients with COPD (173 cases and 185 controls) |
A sputum bacterial load ≥106 or bronchial aspirate bronchial load | ICS: aHR, 0.61 (0.26-1.42) | 9 | |
| He et al. [22] | China | Case-control |
Post -bronchodilator FEV1/FVC<70% |
126 hospitalized patients with COPD (78 cases and 48 controls) |
PA- positive sputum |
Hypoproteinemia: aOR, 2.71 (1.07-6.83) 6MWD < 250 m: aOR, 3.54 (1.39-9.04) CAT score> 20 points: aOR, 2.70 (1.07-6.79) |
SCS (prior 3 months): cOR, 2.11 (1.00-4.44) |
8 |
|
Martínez-García et al. [16] |
Spain | Cohort | GOLD criteria |
170 GOLD II-IV patients (41 cases) |
A cutoff point of ≥103 CFU was used to identify abnormal positive culture results for PA |
Previous HI isolation: aHR, 2.85 (1.51-5.50) Previous severe exacerbations: aHR, 1.50(1.23-1.83) Cumulative smoking exposure: aHR, 1.01(1-1.02) |
SCS: cOR,10.11(1.02-99.98) |
8 |
| Chen et al. [17] | China | Case-control |
Post-bronchodilator FEV1/FVC<70% |
122 hospitalized patients with COPD (62 cases and 60 controls) | PA-positive sputum culture by MIC or K-B |
Hypoproteinemia: aOR, 3.92 (2.10-7.64) 6MWD < 250 m: aOR, 4.59 (2.18-7.05) CAT score > 20 points: aOR, 2.39 (1.01-3.70) BODE index: aOR, 3.18 (1.36-5.11) Antibiotics (prior 3 months): aOR, 3.57 (1.81-5.30) SCS(prior 3 months): aOR, 2.94 (1,10-7.64) |
8 | |
|
Rodrigo- Troyano et al. [12] |
Spain | Cohort |
Post-bronchodilator FEV1/FVC≤70% |
106 frequent exacerbated patients with COPD (21 cases) |
PA-positive sputum culture with sputum samples were defined as < 10 squamous epithelial cells and > 25 leukocytes per field. |
SCS (prior 3 months): cOR, 3.38 (1.20-9.10) Antibiotics (prior 3 months): cOR, 1.27 (0.46-3.47) |
5 | |
| Guo et al. [21] | China | Case-control |
Post-bronchodilator FEV1/FVC<70% |
236 patients with hospitalization for AECOPD (44 cases and 192 controls) |
Semi-quantitative culture of sputum bacteria (+++) -(++++) |
Hospital admissions in previous year: aOR, 18.96 (3.35-107.14) BODE index: aOR, 14.57 (4.82-44.08) Antibiotics (prior 3 months): aOR, 4.17 (1.71-10.18) Hypoproteinemia: aOR, 5.11 (1.27-20.57) |
SCS (prior 3 months): cOR, 3.03(1.49-6.19) |
7 |
| Gallego et al. [26] | Spain | Cohort | GOLD criteria |
118 patients with severe COPD (41 cases) |
PA- positive sputum |
Bronchiectasis: aOR, 9.8(1.7- 54.8) |
8 | |
|
Garcia-Vidal et al. [18] |
Spain | Cohort | Post-bronchodilator FEV1/FVC<70% |
188 patients with hospitalization for AECOPD (31 cases) |
PA- positive sputum |
BODE index: aOR, 2.18 (1.26-3.78) SCS (prior 3 months): aOR, 14.7 (2.28-94.8) Prior PA isolation: aOR, 23.1 (5.7-94.3) Hospital admissions in previous year: aOR, 1.65 (1.13-2.43) |
Antibiotics (prior 3 months): cOR, 1.14 (0.51–2.57) |
|
|
Monsó et al. [19] |
Spain | Case-control |
Guidelines of the European Respiratory Society for COPD |
90 exacerbated patients with COPD (12 cases and 78 controls) |
A sputum culture bacterial counts of ≥103 c.f.u./ml with samples obtained using a protected specimen brush |
SCS: aOR, 2.52 (0.58-10.84) Antibiotics (prior 3 months): aOR, 6.06 (1.29-28.44) |
7 |
Abbreviations COPD, chronic obstructive pulmonary disease; AECOPD, acute exacerbation of chronic obstructive pulmonary disease; FEV1, forced expiratory volume in 1 s; FVC, forced vital capacity; PA, Pseudomonas aeruginosa; GOLD, Global Initiative for Chronic Obstructive Lung Diseases; aOR, adjusted odds ratio; aHR, adjusted hazard ratio; cOR, crude odds ratio; CI, confidence interval; BODE: Body mass index, airflow Obstruction, Dyspnea, Exercise capacity; SCS, systemic corticosteroids; ICS, inhaled corticosteroids; CAT, COPD assessment test; 6MWD, 6-min walking distance; HI, Haemophilus influenzae; MIC, minimum inhibitory concentration; K-B, kriby-bauer; NOS, Newcastle–Ottawa Scale
Quality assessment
Using the NOS, the quality of twelve studies was judged as high (score ≥ 7), and one study was rated of medium quality (score 5). A detailed assessment of the studies analyzed is provided in the Supplementary Material (Table S1, S2).
Risk factors for PA isolation
Overall, ten probable risk factors were identified: prior systemic steroid or antibiotic treatment, inhaled corticosteroids (ICS), high “Body mass index, airflow Obstruction, Dyspnea, Exercise capacity” (BODE) index, short 6-min walking distance (6MWD), high COPD assessment test (CAT) score, hypoproteinemia, hospitalizations in the previous year, Bronchiectasis and prior PA isolation.
Prior systemic steroid therapy
Eight studies [12, 16–22] reported the risk of PA isolation in patients with COPD who accepted prior systemic steroid therapy, and four [17–20] provided the adjusted ORs. The pooled results showed that prior systemic steroid treatment was significantly associated with an increased risk of PA isolation (pooled adjusted OR [paOR]: 2.67; 95% confidence interval [CI]:1.29–5.53; P = 0.008; I2 = 48.7%; Fig. 2A). We performed a sensitivity analysis of all the studies providing ORs, and the results were similar (OR: 2.57; 95% CI: 1.78–3.70; P < 0.001; I2 = 21.6%; Fig. 2A).
Fig. 2.
Prior systemic steroid therapy, inhaled corticosteroids and risk of PA isolation
ICS use
The risk of PA isolation in patients with COPD using ICS was reported in two studies [18, 21]. The pooled results showed that ICS use was not associated with the risk of PA isolation (HR: 1.25; 95% CI: 0.35–4.50; P = 0.7; I2 = 88.1%; Fig. 2B).
Previous antibiotics treatment
Exposure to previous antibiotic therapy could increase the incidence of PA isolation [17, 19, 21, 23] (OR: 2.83; 95% CI: 1.14–6.97; P = 0.02; I2 = 89.7%; number of studies [N] = 4; Fig. 3). We found consistent evidence (OR: 2.09; 95% CI: 1.13–3.88; P = 0.02; I2 = 82.9%; N = 6; Fig. 3) by conducting a sensitivity analysis.
Fig. 3.
Previous antibiotics treatment and risk of PA isolation
BODE index, 6MWD, CAT score
High BODE index [17, 18, 21] (OR: 4.13; 95% CI: 1.67–10.23; P = 0.002; I2 = 78%; N = 3; Fig. 4A), 6MWD < 250 m [17, 22] (OR: 4.27; 95% CI: 2.59–7.01; P < 0.001; I2 = 0%; N = 2; Fig. 4B) and CAT score > 20 points [17, 22] (OR: 2.49, 95% CI: 1.46–4.23; P = 0.001; I2 = 0%; N = 2; Fig. 4C) were risk factors for the likelihood of PA isolation in patients with COPD.
Fig. 4.
High BODE index, 6MWD < 250 m, CAT score > 20 points and risk of PA isolation
Hypoproteinemia
The association between hypoproteinemia and risk of PA isolation in patients with COPD was reported in four studies [17, 21, 22, 24]. The pooled results suggested the patients with hypoproteinemia had an increased risk of PA isolation (OR: 2.62; 95% CI: 1.32–5.19; P = 0.006; I2 = 73.3%; Fig. 5).
Fig. 5.
Hypoproteinemia and risk of PA isolation
Hospitalizations in the previous year
Consistent evidence was found for the correlation between hospitalizations in the previous year and PA isolation in three studies [18, 21, 25]; Our pooled results found that hospital admissions in the previous year were also associated with PA isolates in the sputum (OR: 3.74; 95% CI: 1.22–11.49; P = 0.021; I2 = 78.3% Fig. 6).
Fig. 6.
Hospitalizations in the previous year and the risk of PA isolation
Bronchiectasis
The overall OR for patients combined with Bronchiectasis was 4.81 (95% CI: 3.66–6.33; P < 0.001; I2 = 0.0%), which showed the risk of PA infection in COPD patients was significantly increased in populations who combined with Bronchiectasis [24–26]. The overall effect was weaker (OR = 2.92; 95%CI, 1.79–7.76; P < 0.001; I2 = 72.2%) after performing a sensitivity analysis (Fig. 7).
Fig. 7.
Bronchiectasis and the risk of PA isolation
Prior PA isolation
Three studies analyzed prior PA isolation and PA isolation in COPD patients, which indicated that prior PA isolation as independent risk factor [12, 18, 25]. Our pooled outcome showed the overall risk of was significantly higher (OR: 16.39; 95% CI: 7.65–35.10; P < 0.001; I2 = 0.0%; Fig. 8). The results were still stable after pooling all related studies (OR: 10.84; 95% CI: 4.30–27.33; P = 0.011; I2 = 50.4%).
Fig. 8.
Prior PA isolation and the risk of PA isolation
Discussion
Our meta-analysis aimed to summarize the current evidence on the risk factors for PA isolation in COPD patients. We found that prior systemic steroid or antibiotic therapy, high BODE index, 6MWD < 250 m, CAT score > 20 points, hypoproteinemia, hospitalizations in the previous year, Bronchiectasis and prior PA isolation are significant risk factors for PA isolation.
Our results showed that prior systemic corticosteroid therapy was important risk factor for PA isolation among patients with COPD, which was consistent with previous studies [18, 20].Corticosteroids have been reported to promote PA bonding to the respiratory epithelium by increasing the expression of syndecan-1, a key molecule mediating PA infection [27]. And the impairment of the innate and acquired immune system induced by corticosteroids [28], might contribute to the poor elimination of pathogens in the airways [29].
A positive relationship between previous antibiotic use and the risk of PA isolation in COPD is established in this study. A possible explanation is the use of antibiotics promotes the imbalance of normal bacterial flora in the respiratory tract, and the dominant growth of opportunistic pathogens increases the risk of PA infection [30]. And the alteration of the microbiological environment in the airways caused by antibiotics led to PA colonization and transformation towards resistant strains in the respiratory tracts [31].
Our study demonstrated that patients with high BODE index, 6MWD < 250 m, CAT score > 20 points were more likely infected by PA. Various tools (e.g. the forced expiratory volume in 1s (FEV1), BODE index, 6MWD and CAT score) are used to evaluate the severity of lung function impairment in COPD patients [32–35]. The BODE index is a multi-dimensional grading system to assess COPD severity, providing more information to estimate the prognosis and the risk of hospital admission [33, 36]. 6WMD is an effective index to evaluate the exercise capacity of patients with COPD, which was closely related to the condition of COPD [32]. CAT score is used to assess the impact of COPD on the patient’s health and quality of life, and the higher the score, the more severe the disease state [34]. As expected, patients with a more severe form of the disease (higher BODE index, shorter 6MWD or higher CAT score) had an increased risk of PA isolation.
Our study indicated that hypoproteinemia is a significant risk factor for PA isolation. Hypoproteinemia can lead to metabolic disorders in tissue cells and associated enzymes, as well as impaired immunity, thereby increasing the likelihood of infections, particularly those caused by PA [37]. Furthermore, patients with hypoproteinemia experience alterations in the pharmacokinetics of antimicrobial agents. The reduction in plasma colloid osmotic pressure in these patients enhance fluid leakage, consequently decreasing the local drug concentration at the site of infection, which diminishes the effectiveness of anti-infection treatments [38]. Additionally, hypoproteinemia can disrupt both cellular and humoral immunity, resulting in reduced lymphocyte proliferation and interleukin (IL)-6 release, as well as causing dysfunction in granulocytes [39].
Our results revealed that hospitalizations in previous years were also related with the increased risk of PA isolation. The number of hospitalizations in the previous years was closely related with the readmission of COPD patients. PA infection was common in that population [40].
Our results also indicated that COPD patients combined with Bronchiectasis were more intended to increase the risk of PA isolation. Bronchiectasis is a structural lung disease [41]. Combined with Bronchiectasis in COPD patients (Bronchiectasis-chronic obstructive pulmonary disease overlap syndrome, BCOS), the lung structure and internal environment were more complex. Research has indicated that PA is the most common pathogen of BCOS. It has strong pathogenicity by secreting exotoxins and pathogenic factors that combine with specific sites in the host body and are able to form biofilms and related quorum-sensing systems, form protective barriers of bacteria, and participate in antimicrobial resistance. Pseudomonas aeruginosa is more susceptible to colonize and become chronic infection in that environment [42].
Our results also revealed that prior PA isolation as one of the risk factors for PA isolation. PA infection often induced the death of lung epithelial cells, caused the host inflammatory response, and triggered serious damage to the respiratory system, which increased the risk of PA reinfection [43]. Additionally, the overuse of antibiotics during treatment accelerates the development of multidrug-resistant PA strains, resulting in ineffective empirical antibiotic treatment against this organism [44]. The bacteria were more likely to be isolated from sputum of patients who had been priorly infected with PA.
However, the evidence for an association between ICS and PA isolation is still controversial. ICS use was related with increased bacterial load in the airway and the long-term treatment of COPD patients with ICS might have blunted the normal response that is orchestrated by alveolar macrophages after PA infection. Most studies [23, 45] indicated that ICS use was related with a significant and dose-related of PA isolation in COPD, while some studies suggested that ICS dose, rather than its use, was associated with PA isolation among patients with COPD [46]. Our study did not find an association between ICS therapy and PA isolation in patients with COPD, and the relationships need further investigation.
The limitations of our study are as follows: Heterogeneity was higher in our study due to different baseline populations, methodologies, and sample sizes. PA colonization and infection in the lower airways cannot be distinguished in included studies. The studies included in our analysis were published only in English or Chinese, potentially omitting relevant publications reporting PA isolation in COPD patients in other languages. Some risk factors cannot be analyzed for the limited number of included studies, and further studies are still essential to explore the risk factors for PA isolation.
Conclusions
Our study identified nine risk factors associated with an increased risk of AP isolation in patients with COPD. These findings are significant for the early identification and better management of COPD patients at risk for PA isolation, which may help reduce mortality and improve clinical outcomes.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
Not applicable.
Abbreviations
- PA
Pseudomonas aeruginosa
- COPD
Chronic obstructive pulmonary disease
- CNKI
China National Knowledge Infrastructure
- PaOR
Pooled adjusted odds ratio
- PaHR
Hazard ratio
- CI
Confidence intervals
- BODE
Body mass index, airflow Obstruction, Dyspnea, Exercise capacity
- 6MWD
6-min walking distance
- CAT
COPD assessment test
- AECOPD
Acute exacerbations of COPD
- PROSPERO
Database of Prospectively Registered Systematic Reviews
- OR
Odds Ratios
- HR
Hazard ratios
- NOS
Newcastle-Ottawa Scale
- ICS
Inhaled corticosteroids
- FEV1
The forced expiratory volume in 1s
Author contributions
Wei Ge proposed the scientific question and designed the study. Yuyu Zhang and Nini Zhang selected and analyzed the data, and wrote the manuscript. Tingting Li participated in data analysis and edit the manuscript. Lanrui Jing and Yu Wang assessed the quality of included studies. All authors read and approved the final manuscript.
Funding
This study received no funding.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethical approval
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
No datasets were generated or analysed during the current study.