Comparison of Multi-Drug Resistant Organisms Causing Early Ventilator-Associated Pneumonia in Three Geographically Distinct Trauma Intensive Care Units

Abstract

Introduction:

It is unclear why differences in patient location change organisms causing ventilator-associated pneumonia (VAP). We investigated VAP organisms in three geographically separate trauma intensive care units (TICUs).

Patients and Methods:

A retrospective review of organisms causing VAP (bronchoalveolar lavage [BAL] performed ≤7 d after admission and growing ≥10⁵ cfu/mL) in three geographically separate TICUs was conducted. Patients were treated by similar multidisciplinary teams and protocolized pathways. The primary outcome was the incidence of multi-drug resistant (MDR) VAP. Secondary outcomes were the incidence of inappropriate empiric antimicrobial therapy (IEAT) and the determination of risk factors for MDR VAP. Chi-squared, Kruskal-Wallis, and multi-variable logistic regression analyses were used accordingly.

Results:

In total, 271 patients were included: 142 in TICU-1, 63 in TICU-2, and 66 in TICU-3. The incidence of MDR VAP was similar across TICUs at 33.8%, 47.6%, and 39.4%, respectively (p = 0.17). Gram-negative MDRs were more prevalent in TICU-1 (70.8%) versus TICU-2 (60.0%) or TICU-3 (26.9%) (p = 0.001). Gram-positive MDRs were identified more in TICU-3 (73.1%) versus TICU-2 (43.3%) or TICU-1 (35.4%). IEAT did not differ by unit overall but was significantly greater for MDR gram-positive organisms in TICU-3 (70.4%) versus TICU-2 (44.8%) or TICU-1 (37.5%) (p = 0.02) and highest for MDR gram-negative organisms in TICU-1 (64.6%) versus TICU-2 (62.1%) or TICU-3 (55.8%) (p = 0.02). Multi-variable regression analyses revealed antibiotic days before BAL and kidney replacement therapy (KRT) as significant predictors of MDR VAP.

Conclusions:

Different TICU locations did not influence the overall incidence of MDR VAP, but differences in MDR organisms were observed. IEAT rates for both gram-positive and gram-negative organisms in different units may necessitate changes in empiric therapy. Antibiotic days prior to the BAL and KRT significantly increased the odds of early MDR VAP.

Ventilator-associated pneumonia (VAP) is the most frequent hospital-acquired infection in mechanically ventilated patients and has been associated with longer durations of mechanical ventilation, intensive care unit (ICU) length of stay (LOS), and hospital LOS.¹ The Infectious Diseases Society of America/American Thoracic Society (IDSA/ATS) hospital-acquired pneumonia (HAP) and VAP guidelines recommend using local antibiograms to determine empiric antibiotic regimens. Use of an agent active against methicillin-resistant Staphylococcus aureus (MRSA) is recommended for units where >10%–20% of S. aureus isolates are found to be resistant to methicillin.² Inappropriate empiric antibiotic therapy (IEAT) when compared with appropriate empiric antibiotic therapy for the treatment of VAP has been associated with increased ICU LOS and crude hospital mortality.^3–5 This emphasizes the need to understand unit-specific antibiograms and target empiric antibiotic therapy accordingly. Additionally, patients in trauma intensive care units (TICUs) may not have the same comorbid conditions as those in a medical or other surgical ICUs. It is therefore unclear if risk factors for multi-drug resistant (MDR) VAP are similar.

In 1998, our institution investigated the organisms responsible for causing VAP over a two-year period resulting in a clinical pathway to guide empiric antibiotic therapy accounting for the probability of early versus late organisms.⁶ In 2005, a follow-up study was conducted and found the empiric antibiotic agents in this clinical pathway were still appropriate empiric coverage showing insignificant, modest changes in isolated organisms.⁷ However, changes in the microbial landscape worldwide showing increases in MDR organisms prompted renewed interest in the pathway’s continued utility.⁸ A 2022 study showed that trauma patients did not receive adequate empiric therapy with ampicillin/sulbactam or ceftriaxone monotherapy.⁹ We hypothesized that patients treated using the VAP pathway in three separate TICUs had different early VAP MDR pathogens. The purposes of the current study were to (1) determine the rates of MDR organisms causing early VAP and compare them between three geographically different TICUs, (2) determine if the current clinical pathway for empiric antibiotic selection for early VAPs is adequate in all three ICUs, and (3) identify patient-specific demographics that increase the odds of developing an early MDR VAP.

Patients and Methods

Patients

This retrospective review was conducted within three TICUs that are geographically separated from each other, with two units being on the same floor (ground floor), but not connected. The third unit is located on a different floor (fourth floor). All patients were admitted to the trauma service at the hospital and treated using the same pathway for diagnosis and management of VAP. The teams caring for patients consisted of the same clinicians, but these clinicians changed weekly. Nursing staff were allowed to work in each TICU but normally staffed in the same TICU unless there was a need in a different TICU. Patients admitted between January 1, 2020, and December 31, 2022, who underwent a fiberoptic bronchoscopy with bronchoalveolar lavage (BAL) within seven days of admission were eligible for inclusion. Data were automatically abstracted from the institution’s trauma registry and manually retrieved via the electronic medical record (EMR). Data collection and study commencement were approved by the university institutional review board and the hospital office of research with exempt status, approval number 22-09173-XP. This report followed the guidelines for Strengthening the Reporting of Observational Studies in Epidemiology. Patients met inclusion criteria if they were at least 18 years of age and received a diagnosis of early (<7 d) VAP. Patients were excluded if they were pregnant or admitted to a patient care area outside one of the three TICUs, underwent a non-diagnostic BAL, had a BAL demonstrating organism growth <10⁴ cfu/mL (no VAP), or had an incomplete EMR.

Demographic data included height, weight, age, gender, race, mechanism of injury, Injury Severity Score (ISS), admission Glasgow Coma Scale (GCS) score, ICU LOS, hospital LOS, duration of mechanical ventilation, hospital day of bronchoscopy with BAL, antibiotics, and their duration of administration prior to BAL. Objective signs of infection such as white blood cell count and maximum temperature were collected at the time of the BAL. Documented comorbid conditions were collected based on past medical history reported in the EMR. IDSA/ATS HAP/VAP guideline-identified risk factors for the development of MDR VAP were collected.² Causative organisms as well as quantitative growth reported for each BAL were obtained from the microbiology culture results.

Study definitions and outcomes

Patients underwent bronchoscopy and BAL if they demonstrated clinical suspicion of VAP per the trauma-specific VAP pathway. Clinical suspicion was defined as a new or changing infiltrate on chest radiograph and at least two of the following symptoms: hyperthermia or hypothermia (>38°C or <36°C), leukocytosis or leukopenia (>12,000/mm³ or <4,000/mm³), or macroscopically purulent sputum.¹⁰ Diagnosis of VAP at the institution required a BAL with least one organism demonstrating growth of ≥10⁵ cfu/mL.^10–12 Despite not meeting institutional criteria for VAP, BALs demonstrating growth ≥10⁴ cfu/mL were also analyzed in acknowledgment of the different diagnostic thresholds recommended in the IDSA/ATS HAP/VAP guidelines.² On the basis of previously published research at the institution and other supporting literature, early VAP was defined as ≤7 days after admission.^6,12 Polymicrobial VAP was defined as more than one organism causing VAP (as defined by demonstrated growth of ≥ 10⁵ cfu/mL for more than one organism).¹³

Organisms demonstrating resistance to three or more antibiotic classes based on susceptibility reports from the microbiology culture results were classified as MDR.¹⁴ An antibiotic day was defined as at least one dose of antibiotics received in a 24-h period. A PaO₂:FiO₂ ratio <300 within 24 h of VAP diagnosis was used to screen for patients at risk of acute respiratory distress syndrome (ARDS). Medical record progress notes from the primary team documenting ARDS were required for confirmation of the diagnosis. Documentation in either the trauma team or nephrology progress note was used to identify patients receiving kidney replacement therapy (KRT) within 24 h of VAP diagnosis.

The primary outcome of this study was the incidence of early MDR VAP among three geographically separate TICUs at the study institution. Secondary outcomes included the incidence of IEAT and the identification of significant predictors for the development of early MDR VAP.

Statistical analysis

Dichotomous data were compared via chi-square analysis and reported as counts with percentages, and continuous data were analyzed via the Kruskal-Wallis test and reported as medians and interquartile ranges. Known risk factors for MDR VAP reported in the IDSA/ATS HAP/VAP guidelines² (>5 d of hospital admission, previous receipt of intravenous antibiotics, shock, KRT, and ARDS) were identified a priori for inclusion into a multi-variable logistic regression model to evaluate their predictive ability in this patient population. A second multi-variable logistic regression was planned to identify population-specific risk factors; variables with p < 0.2 on uni-variable analysis were eligible for inclusion in this second model. Statistical comparisons were performed for the patient cohort who received a diagnosis of VAP based on the institution threshold using organism growth of ≥10⁵ cfu/mL. However, because the diagnosis of VAP using BAL cultures has two established thresholds,^2,10 an additional analysis of BALs with ≥10⁴ cfu/mL was also performed.

Results

A total of 1,275 patients were screened for inclusion in the study, and 956 met exclusion criteria (Fig. 1). The most common reason for exclusion was a diagnostic BAL conducted after day 7 of hospitalization. Patient groups included 142 from TICU-1, 63 from TICU-2, and 66 from TICU-3. Demographics for patients receiving a diagnosis of VAP (BAL culture demonstrating growth ≥ 10⁵ cfu/mL) are reported in Table 1. Statistically significant differences were noted between patients in the three different TICUs for gender, body mass index, admission GCS, ISS, and past medical history of diabetes mellitus. Antibiotic exposure in the three TICUs did not significantly differ except for a greater proportion of TICU-2 patients receiving antibiotics in the “other antibiotic” category.

FIG. 1.

Patient screening and inclusion.

Table 1.

Patient Demographics for Ventilator-Associated Pneumonia with ≥ 10⁵ cfu/mL Organisms

	TICU-1 (n = 142)	TICU-2 (n = 63)	TICU-3 (n = 66)	p
Age	42 (27.8–57.3)	36 (28–57)	45.5 (33.8–65)	0.06
Gender
Male	123 (86.6)	45 (71.4)	54 (81.8)	0.03
Race
White^*	66 (47.1)	30 (49.2)	29 (44.6)	0.88
Hispanic^*	11 (7.9)	4 (6.6)	1 (1.5)	0.20
Black^*	63 (45.0)	26 (42.6)	34 (52.3)	0.50
Other^*	0 (0)	1 (1.6)	1 (1.6)	0.33
Weight (kg)	86.5 (73–104.3)	82 (70–98)	81.5 (72.3–94.3)	0.14
BMI (kg/m²)	28 (24–33)	27 (24–31)	26 (23–29)	0.02
Injury mechanism
Blunt	126 (88.7)	51 (81.0)	58 (87.9)	0.30
Injury Severity Score	26 (17–34)	29 (22–35)	21.5 (17–29)	0.01
Admission GCS	5 (3–13.8)	10 (3–15)	4 (3–8)	0.003
Comorbidities
AUD	5 (3.5)	4 (6.4)	5 (7.6)	0.42
SUD	13 (9.2)	6 (9.5)	4 (6.1)	0.72
Pulmonary disease	9 (6.3)	1 (1.6)	2 (3.0)	0.26
CVD	36 (25.4)	17 (27.0)	23 (34.9)	0.36
Cirrhosis	2 (1.4)	2 (3.2)	1 (1.5)	0.69
CKD	0 (0)	1 (1.6)	2 (3.0)	0.14
Smoker	38 (26.8)	18 (28.6)	13 (19.7)	0.48
DM	10 (7.0)	3 (4.8)	14 (21.2)	0.002
Admission day of BAL	5 (4–6)	5 (4–6)	5 (4–6)	0.49
Length of stay (d)
Hospital	25.5 (18–37.5)	24 (13–38)	26 (14.8–40.3)	0.62
ICU	19 (14–26)	18 (10–27)	17 (11.8–25)	0.24
Mechanical ventilation (d)	15.5 (11–24)	15 (10–23)	13 (9.8–20)	0.16
Received IV ABX prior to BAL	84 (59.2)	39 (61.9)	32 (48.5)	0.24
Antibiotic days prior to BAL	1 (0–3)	1 (0–3)	0 (0–1)	0.05
Administered antibiotics
Cefazolin	68 (47.9)	35 (55.6)	25 (37.9)	0.13
Vancomycin	28 (19.7)	17 (27.0)	23 (34.9)	0.06
Piperacillin-tazobactam	7 (4.9)	6 (9.5)	2 (3.0)	0.25
Ceftriaxone	0 (0)	0 (0)	0 (0)	-
Ampicillin-sulbactam	4 (2.8)	0 (0)	3 (4.6)	0.26
Cefepime	6 (4.2)	0 (0)	2 (3.0)	0.26
Other	22 (15.5)	15 (23.8)	5 (7.6)	0.04
Polymicrobial infection	76 (53.5)	30 (47.6)	30 (45.5)	0.50
T_max at BAL (°C),	38.9 (38.4–39.3)	39.0 (38.3–39.4)	39.0 (38.5–39.4)	0.64
WBC count (×10⁹/L)	11.1 (8.9–14.7)	12 (9.3–15.8)	11.7 (8.7–14.7)	0.66
Vasopressors	20 (14.1)	12 (19.0)	6 (9.1)	0.27
ARDS	12 (8.5)	2 (3.2)	4 (6.1)	0.37
KRT	4 (2.8)	3 (4.8)	2 (3.0)	0.76
In-hospital mortality	31 (21.8)	17 (27.0)	19 (28.8)	0.50
Patients MDR VAP	48 (33.8)	30 (47.6)	26 (39.4)	0.17
Gram (+) MDR	17/48 (35.4)	13/30 (43.3)	19/26 (73.1)	0.007
Gram (−) MDR	34/48 (70.8)	18/30 (60.0)	7/26 (26.9)	0.001
IEAT	48 (33.8)	29 (46.0)	27 (40.9)	0.22
Gram (+) IEAT	18/48 (37.5)	13/29 (44.8)	19/27 (70.4)	0.02
Gram (−) IEAT	31/48 (64.6)	18/29 (62.1)	9/27 (55.8)	0.02

Data are presented as median (IQR) or N (%) as appropriate.

Missing data on race/ethnicity for five patients.

TICU = trauma intensive care unit; BMI = body mass index; GCS = Glasgow Coma Scale; AUD = alcohol use disorder; SUD = substance use disorder; CKD = chronic kidney disease; CVD = cardiovascular disease; DM = diabetes mellitus; BAL = bronchoalveolar lavage; IV = intravenous; ABX = antibiotics; T_max = maximum temperature; WBC = white blood cell; ARDS = acute respiratory distress syndrome; KRT = kidney replacement therapy; MDR = multi-drug resistant; VAP = ventilator-associated pneumonia; IEAT = inadequate empirical antibiotic therapy.

Incidence of MDR VAP

The proportion of patients with VAP caused by an MDR organism was not significantly different between the three TICUs. However, all three TICUs had MDR VAP rates greater than 30% (Table 1). TICU-3 had significantly more VAP caused by gram-positive MDR organisms, whereas TICU-1 had significantly more gram-negative MDR VAP. Overall, the incidence of IEAT was not significantly different between the three TICUs (Table 1). However, TICU-2 had a significantly greater proportion of gram-positive organisms causing early VAP with IEAT, and TICU-1 had significantly more IEAT because of gram-negative organisms (Table 1).

A total of 490 organisms causing early VAP were identified in the 271 enrolled patients. Organisms causing VAP in each TICU and their distribution based on gram stain and susceptibility are shown in Table 2. Supplementary Table S1 depicts the specific organisms by unit. The number of non-MDR and MDR organisms causing VAP was significantly different between TICU-1, TICU-2, and TICU-3 (Table 2). Significantly more gram-positive MDR organisms were observed in TICU-3. Gram-negative MDR organisms were identified more frequently in TICU-1. MRSA comprised over 10%−20% of S. aureus isolates causing early VAP (TICU-1 = 27.9%, TICU-2 = 50%, and TICU-3 = 48.3%). Additionally, MRSA was significantly more common in TICU-3, whereas non-fermenting gram-negative bacilli made up a significantly greater proportion of identified organisms causing VAP in TICU-2 (Table 2). Data for the BAL ≥10⁴ cfu/mL cohort are reported in Supplementary Table S2.

Table 2.

Incidence of Multi-Drug Resistant Organisms

	TICU-1 (n = 267)	TICU-2 (n = 108)	TICU-3 (n = 115)	p
Non-MDR VAP organisms	210 (78.7)	70 (64.8)	88 (76.5)	0.02
Gram (+)	112/210 (53.3)	30/70 (42.9)	57/88 (64.8)	0.02
Gram (−)	98/210 (46.7)	40/70 (57.1)	31/88 (35.2)	0.02
MDR VAP organisms	57 (21.4)	38 (35.2)	27 (23.5)	0.02
Gram (+)	18/57 (31.6)	16/38 (42.1)	18/27 (66.7)	0.01
Gram (−)	39/57 (68.4)	22/38 (57.9)	9/27 (33.3)	0.01
MRSA VAP	12 (4.5)	11 (10.2)	14 (12.2)	0.02
NFGNB VAP	25 (9.4)	17 (15.7)	4 (3.5)	0.007

MDR = multi-drug resistant; VAP = ventilator-associated pneumonia; MRSA = methicillin-resistant Staphylococcus aureus; NFGNB = non-fermenting gram-negative bacilli.

Risk factors

Variables included in the multi-variable logistic regression that could predict early MDR VAP are presented in Table 3. Admission to TICU-2 was included in the model as the rate of early VAP caused by MDR organisms was highest in this unit at 47.6% (Table 1). Antibiotic days prior to undergoing the diagnostic BAL were the only variable independently associated with the development of early MDR VAP (Table 3). The multi-variable regression model including the IDSA/ATS guideline-recommended risk factors found KRT to be the only variable independently associated with an increased odds of early MDR VAP (Table 4).

Table 3.

Multi-Variable Logistic Regression of Demographics for Development of Multi-Drug Resistant Early Ventilator-Associated Pneumonia

Variable	OR (95% CI)	p
Admission to TICU-2	1.63 (0.89–2.99)	0.11
Age	1.01 (0.99–1.03)	0.10
Antibiotic days prior to BAL	1.41 (1.19–1.68)	<0.001
Vancomycin prior to BAL	1.02 (0.55–1.89)	0.95
Diabetes mellitus	1.53 (0.62–3.76)	0.36
ISS	1.00 (0.97–1.02)	0.87

OR = odds ratio; CI = confidence interval; TICU = trauma intensive care unit; BAL = bronchoalveolar lavage; ISS = Injury Severity Score.

Table 4.

Multi-Variable Logistic Regression of Known Risk Factors for Development of Multi-Drug Resistant Early Ventilator-Associated Pneumonia

Variable	OR (95% CI)	p
Admission day of BAL	1.09 (0.90–1.31)	0.37
ARDS	0.75 (0.26–2.15)	0.58
IV antibiotics prior to BAL	1.51 (0.88–2.59)	0.13
KRT	13.08 (1.57–108.78)	0.002
Vasopressors (shock)	1.33 (0.64–2.77)	0.45

OR = odds ratio; CI = confidence interval; BAL = bronchoalveolar lavage; ARDS = acute respiratory distress syndrome; IV = intravenous; KRT = kidney replacement therapy.

Discussion

This study capitalized on the unique environment of our institution to investigate the organisms causing early VAP. Despite traumatically injured patients being cared for by the same team and using the same trauma-specific protocols and treatment pathways, early MDR VAP rates were different in the three geographically distinct intensive care units. Of note, TICU-2 had a greater MDR early VAP rate overall at 47.6%, compared with 33.8% and 39.4% for TICU-1 and TICU-3, respectively. Interestingly, the two units with similar overall early MDR VAP rates differed in the gram stain of the causative VAP organisms. Although MRSA VAP rates differed, all three units exceeded the IDSA/ATA guideline threshold of 10%−20% of S. aureus isolates. Previous institutional antibiogram evaluations suggested an MRSA rate below the guideline threshold, thus emphasizing the importance of continually monitoring changes in pathogen susceptibilities. Although overall rates of IEAT didn’t differ between the three TICUs, they were greater than desired. Multi-variable regression analysis found that for each day of antibiotics administered to the patient prior to the diagnostic BAL, the odds of developing an MDR VAP were increased by 41%. This finding supports previous work at the institution identifying prophylactic antibiotic days as a risk factor for the development of MDR VAP throughout the ICU stay.¹⁵ The only guideline-identified risk factor for developing MDR VAP that was found to independently increase the odds of early MDR VAP was KRT. However, it is important to take into consideration that only nine patients required KRT, and the increased odds found on the multi-variable regression should be interpreted with caution.

The principle that different patient populations in different locations develop infections caused by different organisms is well established.^2,16–19 The driving factors for these differences are less clear. The current study clarifies that standardized treatment protocols and pathways, consistent healthcare staff, and a similar patient population do not mean that VAP pathogen patterns will be the same. As our trauma service expanded beyond the capacity of our trauma-specific ICU, patients had to be cared for in three geographically distinct locations. However, care was standardized for all patients to ensure continuity. Although the rates of IEAT for the three TICUs didn’t differ overall, analysis based on gram stain found significant differences. However, mortality rates were not different among study groups or from previously reported studies at the institution.^15,20 The between-unit differences found in the current study and the rates of IEAT reported will require further monitoring of antibiograms and BAL culture data for each geographically separate TICU. Ultimately, it will require changes to the current VAP treatment pathway with considerations for the differences when selecting empiric antibiotics. These data reinforce the IDSA/ATS guideline recommendation for clinicians to regularly review the microbiologic data from specific patient care areas and adapt empiric therapy to address the unique pathogens.

Selective antibiotic pressure has driven the development of MDR and extensively drug-resistant (XDR) organisms because of the initial use of antibiotics to treat infections.^2,21–24 Prina et al. evaluated 1,597 patients who received a diagnosis of community-acquired pneumonia (CAP) because of Pseudomonas aeruginosa, Enterobacterales extended spectrum β-lactamase-positive, and methicillin-resistant S. aureus (“PES”). Patients with CAP caused by PES more likely received previous antibiotics in the past month (odds ratio [OR] 2.48, 95% confidence interval [CI] 1.56–3.94, p < 0.001).²⁵ A French study found that any antibiotic use as well as broad-spectrum antibiotic use increased the odds of developing VAP because of MRSA, P. aeruginosa, Acinetobacter baumannii, or Stenotrophomonas maltophilia (OR 13.46, 95% CI 3.3–55, and OR 4.12 95% CI 1.2–14.2 respectively).²⁴ Similarly, Teshome and colleagues noted that in patients with severe sepsis or septic shock, treatment with any antipseudomonal β-lactam resulted in an adjusted hazard ratio of 1.04 (95% CI 1.04–1.05) for development of a new resistant infection.²³ Additionally, each additional day of cefepime, meropenem, or piperacillin/tazobactam exposure resulted in an 8%, 2%, or 8% increase in the development of new resistant infections, respectively. These data support our finding that the total duration of antibiotic use increases the odds of developing early MDR VAP, not just the spectrum of antibiotic use. Most of the antibiotic use prior to the BAL in this study was for surgical prophylaxis with predominately narrower spectrum drugs such as cefazolin and vancomycin. This highlights that even intermittent exposure to prophylactic antibiotics must be considered regarding the development of resistant infections.

The limitations of this study should be acknowledged for proper interpretation of the findings. First, only trauma patients were enrolled, so extrapolation to other critically ill patient populations treated by the same team in different locations should be done with caution. Several demographic parameters of patients treated in the three TICUs were different, which may have contributed to the patterns of MDR organisms causing early VAP. However, the variable found to independently increase the odds of MDR VAP, antibiotic days prior to the BAL, was not significantly different between the three TICUs. The finding that KRT increased the odds of MDR VAP should be considered in the context of the small number of patients requiring this therapy and the wide confidence interval reported. Finally, because of the nature of traumatic injuries, it is difficult to accurately determine previous intravenous antibiotic exposure in the 90 days prior to admission. Therefore, these data were not available to be evaluated. Although this is a limitation, it reflects the reality of caring for trauma patients and will continue to be an unknown factor in many cases.

Conclusion

This study highlights the importance of evaluating causative organisms for VAP in patients based on geographic location. The incidence of MDR early VAP differed in three TICUs despite being treated by the same healthcare team and using the same VAP diagnosis and treatment pathway. Antibiotic days prior to BAL independently increased the risk of MDR early VAP in this cohort of traumatically injured patients.

Footnotes

Authors’ Contributions

J.M.S.: Conceptualization, methodology, validation, writing, visualization, supervision, project administration. P.C.C.: Conceptualization, methodology, validation, investigation, data curation, writing. J.E.F.: Conceptualization, methodology, validation, formal analysis, data curation, writing, visualization, supervision. K.L.S.: Conceptualization, methodology, validation, writing. A.J.K.: Conceptualization, resources, writing, visualization, supervision, project administration. G.C.W.: Conceptualization, methodology, writing, visualization, supervision. D.M.F.: Conceptualization, methodology, validation, writing, visualization, supervision, project administration.

Author Disclosure Statement

The authors have no conflicts of interest to report.

Funding Information

The research reported in this article was not supported by any grant funding.

Supplementary Material

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