Comparing Thoracoscopic and Robotic Lobectomy Using a Nationally Representative Database

Abstract

Background

Studies of robotic lobectomy (Robot-L) have been performed using data from high-volume, specialty centers which may not be generalizable. The purpose of this study was to compare mortality, length of stay (LOS), and cost between Robot-L and thoracoscopic lobectomy (VATS-L) using a nationally representative database hypothesizing they would be similar.

Methods

The Premier Healthcare Database was used to identify patients receiving elective lobectomy for lung cancer from 2009 to 2019. Patients were categorized as receiving Robot-L or VATS-L using ICD-9/10 codes. Survey methodology and patient level weighting were used to correct for sampling error and estimation of a nationally representative sample. A propensity match analysis was performed to reduce bias between the groups. Primary outcome of interest was in-hospital mortality. Secondary outcomes were LOS and patient charges.

Results

Among 62 698 patients, 19 506 (31.1%) underwent Robot-L and 43 192 (68.9%) underwent VATS-L. Differences between the groups included age, race, comorbidities, and insurance type. A propensity matched cohort demonstrated similar in-hospital mortality for Robot-L and VATS-L (.9% vs .9%, respectively, P = .91). Patients who underwent Robot-L had a shorter LOS (4 vs 5d, respectively, P < .001) but higher patient charges (90 593.0 vs 72 733.3 USD, respectively, P < .001).

Conclusions

In a nationally representative database, Robot-L and VATS-L had similar mortality. Although Robot-L was associated with shorter hospitalization, it was also associated with excess charges of almost $20,000. As Robot-L is now the most common approach for lobectomy in the U.S., further study into the cost and benefit of robotic surgery is warranted.

Keywords

classifications lung cancer robotics minimally invasive surgery thoracoscopy/VATS thoracic

Introduction

Although surgery remains the gold standard for treatment of patients with lung cancer, controversy exists regarding the optimal surgical approach for lobectomy. Since the introduction of minimally invasive surgery, thoracoscopic lobectomy (VATS-L) has been widely adopted as a safe approach for the treatment of lung cancer.¹ Multiple studies have demonstrated that VATS-L has fewer complications and improved outcomes compared to the traditional open approach.^2-5

In more recent years, robotic lobectomy (Robot-L) has become increasingly popular as an alternative minimally invasive approach to VATS-L. Studies comparing Robot-L and VATS-L have shown similar or improved postoperative outcomes regarding mortality and complication rates for patients undergoing segmentectomy or lobectomy for lung cancer.^5-13 Although these findings suggest that Robot-L is a safe alternative to VATS-L, most of these studies include data from high-volume thoracic surgeons performed at large, academic centers, which may not be representative of the entire population. Particularly there is a lack of data from patients receiving care at community hospitals which represent an important proportion of lung cancer patients within our country.

The purpose of this study was to compare in-hospital mortality, length of stay (LOS), and total patient charges between Robot-L and VATS-L using a nationally representative database. We hypothesized that patients undergoing Robot-L for lung cancer would have similar outcomes compared to VATS-L.

Patients and Methods

Data Source

The Premier Healthcare Database (PHD) was used to analyze patient outcomes of minimally invasive lobectomy for lung cancer based on robotic or thoracoscopic approach. The PHD is a nationally representative database that contains de-identified clinical data from more than a thousand participating hospitals capturing patient billing records, costs, and coding histories. It is comprised of data from more than 1 billion patient encounters, which equates to approximately twenty-five percent of all inpatient admissions in the United States. The database is maintained by Premier, Inc. (Washington, D.C.) and contains hospital admissions, hospital characteristics, surgeon characteristics, payer information, Diagnosis Related Groups, primary and secondary International Classification of Diseases (ICD) diagnosis and procedure codes, current procedural terminology codes, and resource utilization (hospital length of stay and in-hospital mortality).

Patient Selection

The PHD was queried for all adult patients with lung cancer who underwent minimally invasive lobectomy from 2009 to 2019. Minimally invasive lobectomy was defined as robotic (Robotic-L) or video-assisted thoracoscopic (VATS-L) approach. Patients less than 18 years old and those with a clinical diagnosis of metastatic cancer were excluded. Patients were categorized as receiving Robot-L or VATS-L based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) or ICD-10-CM procedure codes.

Outcome Measure

The primary outcome of interest was in-hospital mortality based on minimally invasive approach. Secondary outcomes included total patient charges, LOS, and postoperative complications. Total patient charges reflect the charge of the patient’s entire hospitalization after surgery.

Statistical Analysis

Survey methodology was used to correct for sampling error. Patient level weighting derived from the PHD was used to estimate a nationally representative sample. Categorical variables were compared using survey weight-adjusted Pearson’s $χ$ ² test. A 1:1 propensity match was performed to reduce bias between the groups (Robot-L and VATS-L) using a caliper of .01, common support, and no replacement. Patient outcomes and postoperative complications were analyzed using symmetry test. A multivariable model of in-hospital mortality was also performed.

To address potential improvement in the quality of surgery with the newer da Vinci Xi robot system, a subgroup analysis comparing more recent robotic procedures was performed. Patients who underwent Robot-L were categorized as Xi Robot-L using ICD-10-CM procedures codes under assumptions that the platform used was based on the time that the procedure was performed. The Xi system became available in April 2015 and ICD-10-CM coding began in October 2015. Therefore, patients who had their robotic lobectomy coded with ICD-10-CM procedure codes were used as a surrogate for Xi robot use.

Statistical analysis was performed using STATA MP (Version 16.0, College Station, TX). Statistical significance was set at a P value ≤ .05. Since all patient-related data in the PHD is aggregated, de-identified, and HIPAA-compliant, this study was determined to be exempt from Institution Review Board review.

Results

In total, there were 14 155 patients who met inclusion criteria representing an estimated population size of 62 698 patients: 43 192/62 698 (68.9%) underwent VATS-L and 19 506/62 698 (31.1%) underwent Robot-L. Figure 1 represents the annual proportion of each minimally invasive approach for lung cancer lobectomy during the study period. From 2009 to 2019, the proportion of lung cancer lobectomies performed by robotic approach increased from 4.1% to 60.9%.

Figure 1.

The proportion of all adult patients who underwent minimally invasive lobectomy for lung cancer compared by robotic-assisted (Robot-L) vs thoracoscopic-assisted (VATS-L) approach from 2009 to 2019.

Patient and hospital characteristics were compared between the 2 groups and are shown in Table 1. The groups were similar in sex, hospital characteristics, and receipt of care from thoracic surgeon provider. Patients who underwent Robot-L were more likely to be older, less likely to be White, more likely to have Medicare insurance, and more likely to have certain comorbidities.

Table 1.

Patient and Hospital Characteristics of Adult Patients who Underwent Minimally Invasive Lobectomy Compared by Robot-L and VATS-L Approach Using Survey Methodology to Create National Estimates.

	Robot-L (n = 19 506)	VATS-L (n = 43 192)	P value
Age ≥ 65	14 004 (71.8%)	29 396 (68.1%)	.003
Male sex (vs female)	9052 (46.4%)	19 693 (45.6%)	.42
Race
Asian	751 (3.9%)	553 (1.3%)	<.001
Black	1267 (6.5%)	2880 (6.7%)
White	6089 (31.2%)	25 684 (59.5%)
Other	11 398 (58.4%)	14 074 (32.6%)
Elixhauser comorbidity index	3 (2-4)	3 (2-4)	<.001
Comorbidities
Congestive heart failure	1.003 (5.1%)	1973 (4.6%)	.20
Cardiac arrhythmia	2468 (12.7%)	2646 (6.1%)	<.001
Valvular disease	802 (4.1%)	1709 (4.0%)	.69
Pulmonary circulation disorders	442 (2.3%)	678 (1.6%)	.004
Peripheral vascular disease	704 (3.6%)	1554 (3.6%)	.98
Hypertension, uncomplicated	10 916 (56.0%)	24 007 (55.6%)	.72
Hypertension, complicated	2015 (10.3%)	3196 (7.4%)	<.001
Paralysis	51 (.3%)	97 (.2%)	.69
Other neurologic disorder	380 (2.0%)	652 (1.5%)	.04
Chronic pulmonary disease	10 389 (53.3%)	22 880 (53.0%)	.85
Renal failure	1717 (8.8%)	3047 (7.1%)	.004
Liver disease	290 (1.5%)	548 (1.3%)	.38
AIDS/HIV	36 (.2%)	49 (.1%)	.37
Lymphoma	192 (1.0%)	549 (1.3%)	.17
Rheumatoid arthritis/collagen vascular disorder	636 (3.3%)	1393 (3.2%)	.93
Coagulopathy	130 (.7%)	167 (.4%)	.03
Obesity	1519 (7.8%)	1371 (3.2%)	<.001
Alcohol abuse	328 (1.7%)	396 (.9%)	<.001
Drug abuse	392 (2.0%)	476 (1.1%)	<.001
Weight loss	485 (2.5%)	914 (2.1%)	.27
Fluid and electrolyte disorders	2694 (13.8%)	6850 (15.9%)	.20
Insurance type
Medicare	13 556 (69.5%)	29 148 (67.5%)	.03
Medicaid	1045 (5.4%)	2163 (5.0%)
Private/managed	4492 (23.0%)	10 386 (24.0%)
Other (includes charity, uninsured)	413 (2.1%)	1495 (3.5%)
Hospital size (by bed #)
<300	3353 (17.2%)	6127 (14.2%)	.62
300-499	5731 (29.4%)	14 687 (34.0%)
$\geq$ 500	10 423 (53.4%)	22 378 (51.8%)
Urban hospital location (vs rural)	18 161 (93.1%)	40 231 (93.1%)	.99
Hospital region
Midwest	5227 (26.8%)	11 018 (25.5%)	.73
Northeast	4313 (22.1%)	7813 (18.1%)
South	6716 (34.4%)	14 916 (34.5%)
West	3251 (16.7%)	9445 (21.9%)
Teaching hospital	12 028 (61.7)	24 639 (57.0%)	.47
Thoracic surgery provider	11 742 (60.2%)	26 125 (60.5%)	.97

To address differences between the groups, a propensity match analysis was performed. Patients who underwent Robot-L were matched with patients who underwent VATS-L based on statistically significant differences on bivariable analysis and clinically salient variables in a 1:1 propensity match. Propensity matching resulted in 4279 matched pairs. Table 2 and Figure 2 demonstrate the effectiveness of propensity matching which reduced bias between the groups. Patient and hospital characteristics among the propensity matched cohort were similar except patients who received care in the Midwest were more likely to have a Robot-L (26.2% Robot-L vs 22.8% VATS-L, P < .001), whereas patients in the South were less likely to have a Robot-L (40.6% Robot-L vs 43.1% VATS-L, P < .001) (Supplemental Table 1). In addition, patients who received care at a teaching hospital were more likely to undergo VATS-L (62.7% vs 59.4%, P = .002).

Table 2.

A Propensity Matched Cohort of Patients With Lung Cancer in the Premier Health Database Who Underwent Minimally Invasive Resection Compared by Robot-L vs VATS-L Approach.

	Unmatched (U)	Mean	Mean	Percent	Percent reduction bias	t-test
	Matched (M)	Treated	Control	Bias	Percent reduction bias	P value
Age65	U	.718	.681	8.2		<.001
Age65	M	.706	.708	−0.5	93.8	.81
Male sex (vs female)	U	.466	.461	1.1		.53
Male sex (vs female)	M	.470	.454	3.0	−172.5	.16
Thoracic surgery provider	U	.603	.584	3.9		.03
Thoracic surgery provider	M	.596	.599	−0.6	84.0	.77
Congestive heart failure	U	.052	.045	3.1		.08
Congestive heart failure	M	.050	.045	2.4	22.1	.26
Cardiac arrhythmia	U	.126	.068	19.6		<.001
Cardiac arrhythmia	M	.122	.113	2.9	85.0	.21
Pulmonary circulation disorders	U	.023	.017	4.4		.01
Pulmonary circulation disorders	M	.021	.021	0.3	92.4	.88
Peripheral vascular disease	U	.036	.036	−0.0		1.00
Peripheral vascular disease	M	.039	.035	2.0	−48,547.8	.36
Chronic pulmonary disease	U	.535	.529	1.3		.46
Chronic pulmonary disease	M	.532	.531	0.1	89.4	.95
Renal failure	U	.087	.071	6.2		<.001
Renal failure	M	.085	.080	1.9	69.2	.39
Liver disease	U	.015	.013	2.1		.23
Liver disease	M	.015	.014	0.6	71.5	.79
Coagulopathy	U	.007	.004	3.2		.06
Coagulopathy	M	.007	.006	1.3	61.1	.59
Obesity	U	.078	.036	18.4		<.001
Obesity	M	.071	.065	2.6	85.7	.26
Weight loss	U	.025	.021	2.6		.13
Weight loss	M	.023	.023	0.0	100.0	1.00
Fluid and electrolyte disorders	U	.138	.153	−4.2		.02
Fluid and electrolyte disorders	M	.140	.131	2.1	50.9	.33
Hypertension, complicated	U	.103	.076	9.7		<.001
Hypertension, complicated	M	.098	.092	2.0	79.0	.36
Hospital size, 300-499 beds	U	.280	.351	−15.1		<.001
Hospital size, 300-499 beds	M	.303	.292	2.3	84.7	.28
Hospital size, 500 beds	U	.553	.499	10.9		<.001
Hospital size, 500 beds	M	.530	.550	−4.0	63.5	.07
Teaching hospital	U	1.615	1.548	13.7		<.001
Teaching hospital	M	1.594	1.627	−6.6	51.4	.002
Medicaid insurance	U	.052	.050	0.9		.62
Medicaid insurance	M	.054	.054	0.0	100.0	1.00
Private/managed insurance	U	.228	.235	−1.6		.38
Private/managed insurance	M	.232	.234	−0.5	68.1	.82
Other insurance (includes charity, uninsured)	U	.022	.037	−8.5		<.001
Other insurance (includes charity, uninsured)	M	.024	.022	1.2	85.4	.52
Urban hospital location (vs rural)	U	.931	.927	1.4		.42
Urban hospital location (vs rural)	M	.928	.931	−1.1	24.5	.61
Year 2010	U	.016	.080	−29.9		<.001
Year 2010	M	.018	.016	0.9	97.0	.50
Year 2011	U	.042	.094	−20.7		<.001
Year 2011	M	.046	.048	−0.7	96.8	.72
Year 2012	U	.063	.103	−14.4		<.001
Year 2012	M	.070	.068	0.7	95.3	.73
Year 2013	U	.089	.114	−8.2		<.001
Year 2013	M	.099	.105	−1.9	76.5	.37
Year 2014	U	.099	.121	−6.9		<.001
Year 2014	M	.110	.103	2.1	69.5	.33
Year 2015	U	.100	.125	−7.8		<.001
Year 2015	M	.111	.111	−0.1	98.1	.95
Year 2016	U	.090	.085	2.0		.26
Year 2016	M	.100	.108	−2.9	−45.5	.22
Year 2017	U	.141	.084	18.2		<.001
Year 2017	M	.155	.154	0.4	98.0	.88
Year 2018	U	.164	.070	29.8		<.001
Year 2018	M	.156	.147	2.6	91.1	.28
Year 2019	U	.188	.062	38.8		<.001
Year 2019	M	.129	.132	−1.0	97.4	.65

Figure 2.

The standardized difference before (blue circle) and after (red circle) propensity score match.

Table 3 shows the unadjusted outcomes among the propensity matched cohort. There was no difference in in-hospital mortality between Robot-L and VATS-L (.9% vs .9% respectively, P = .91). Patients who underwent Robot-L had a shorter hospital stay (4 vs 5 median days, respectively, P < .001), but higher total patient charges (90 593.0 vs 72 733.3 median USD respectively, P < .001). Patients who underwent VATS-L were more likely to have a postoperative bleed (8.9% vs 6.9%, P < .001). However, there was no difference in need for blood transfusion between the 2 groups (10.6% Robot-L vs 11.0% VATS-L, P = .62). Multivariable Cox analysis showed similar in-hospital mortality for Robot-L compared to VATS-L (HR .98, P = .96, data not shown).

Table 3.

Unadjusted Analysis of Patient Outcomes and Complications Among Propensity Matched Cohort Who Underwent Minimally Invasive Lobectomy for Lung Cancer Compared by Robotic-Assisted (Robot-L) vs Video-Assisted (VATS-L) Approach.

	Robot-L (n = 4279)	VATS-L (n = 4279)	P value
In-hospital mortality	40 (.9%)	38 (.9%)	.91
Length of stay (days)	4 (3-7)	5 (3-7)	<.001
Patient charges (USD)	90 593.0 (66 387.2-123,621.7)	72 733.3 (52 488.5-102,335.1)	<.001
Respiratory failure	242 (5.7%)	214 (5.0%)	.19
Bronchopleural fistula	50 (1.2%)	50 (1.2%)	1.00
Empyema	6 (.1%)	9 (.2%)	.61
Pneumonia	166 (3.9%)	178 (4.2%)	.54
Myocardial infarction	11 (.3%)	13 (.3%)	.84
Chylothorax	20 (.5%)	20 (.5%)	1.00
Wound complication	6 (.1%)	6 (.1%)	1.00
Intraoperative bleed	32 (.8%)	23 (.5%)	.26
Postoperative bleed	296 (6.9%)	381 (8.9%)	<.001
Blood transfusion	455 (10.6%)	469 (11.0%)	.62

To assess the potential improvement in quality of surgery associated with the newer da Vinci Xi robot system, a propensity matched subgroup analysis was performed comparing Xi Robot-L and VATS-L using ICD-10-CM procedure coding as a surrogate for Xi robot use (Supplemental Table 2, Supplemental Figure 1). Patient outcomes are represented in Supplemental Table 3. Like the larger cohort, in-hospital mortality was similar between the 2 groups; however, Xi Robot-L was associated with a shorter LOS but increased patient charge. Multivariable Cox analysis showed equivalent in-hospital mortality for both groups (HR 1.00, P = 1.00, data not shown).

Comment

In this study, there was a substantial increase in the use of robotic approach for lung cancer lobectomy over a 10-year span. From 2009 to 2019, the annual rate of minimally invasive lobectomies performed by robotic approach increased by almost 15-fold. Robotic approach is now the most common minimally invasive technique used for cancer lobectomy in the United States. The robust sample size and recent timeframe of our study provides an accurate comparison of outcomes and charges between robotic and thoracoscopic cancer lobectomy while comprehensively representing the patient population of the country.

Prior to this study, the most recent nationally representative study was published in 2017 by Oh et al. which also used the PHD to compare outcomes of robotic, thoracoscopic and open lobectomy using data from 2011 to 2015.¹⁴ Similar to our study, when compared to thoracoscopic lobectomy, patients who underwent robotic lobectomy had a shorter hospital stay and similar postoperative mortality rates. When looking at other outcomes, robotic approach was associated with a lower conversion rate to thoracotomy, lower overall postoperative complication rate, and an increased likelihood of patients being discharged home rather than to a transitional healthcare facility. Although postoperative outcomes investigated in both studies were similar, one of the main differences in our study was that a charge analysis was performed for robotic vs thoracoscopic approach. Another study published in 2014 by Swanson and colleagues used PHD data from 2009 to 2011 to show that robotic lung resection had higher hospital costs and longer operating times without any differences in adverse events compared to thoracoscopic lobectomy.¹⁵

A key difference between our study and prior studies is that our more recent timeframe allowed the inclusion of patients who underwent robotic surgery using the da Vinci Xi robot system. The Xi robot was first introduced in April 2015 and since that time there have been no studies looking at the effect of the Xi system on lung cancer lobectomy outcomes. With advancement in technology, the Xi system is thought to offer technical improvements which may lead to improved surgical outcomes. One study looking at patients who underwent radical prostatectomy suggested better outcomes with the Xi robot compared to the Si robot.¹⁶ Our study is the first to include national data as well as data from the Xi platform. In our subgroup analysis comparing Xi Robot-L to VATS-L, we found similar outcomes as the larger cohort. Compared to VATS-L, Xi Robot-L had equivalent in-hospital mortality, similar complication rates, shorter LOS, and higher patient charges. Although the Xi robot is thought to offer technical advantages compared to the Si system, the lack of differences observed in patient outcomes may be due to evolution in techniques within the Xi system itself such as staplers, which could not be accounted for in this study.

Other studies comparing Robot-L and VATS-L have shown similar outcomes between these two approaches.^5-7,10-12 These studies include systemic reviews, meta-analyses, and single institution retrospective reviews which use data mainly collected from high-volume, specialty centers. This differs from our study which used a nationally representative database and may be more generalizable to the current patient population. Furthermore, national data regarding this topic has not been published in more than 5 years. Adoption of robotic technique for any operation requires surgeon frequency and volume to become proficient, making it important to reanalyze this data in a more recent timeframe to determine if outcomes have changed over time.

In addition to safety and efficacy, other important considerations include resource allocation and total cost to the patient. This is especially relevant when outcomes have been shown to be equivalent between approaches. Like our study, literature has shown that the cost of robotic lobectomy greatly exceeds that of thoracoscopic lobectomy.^17-19 Although some believe that robotic surgery may prove to be cost effective over time, this was not appreciated over our 10-year study period. In a recent study published by Heiden et al, the authors suggest that factors such as lower conversion rates, shorter operating times, and higher hospital volumes may lead to robotic lobectomy being the most cost-effective approach in the future.¹⁸ Now that robotic approach has been widely accepted and is the most common approach for lung cancer lobectomy, we expected the charge difference to have resolved in our study period, but instead it remained persistent. One hypothesis for the excess charges associated with robotic lobectomy includes increased intraoperative resource utilization of consumables and other equipment such as instruments.²⁰ This lends itself to further discussion surrounding the benefits and cost of robotic lobectomy.

In contrast, other studies have shown similar cost for robotic surgery compared to more traditional approaches such as VATS and open thoracotomy.^21,22 Nguyen et al. used the PHD to evaluate the cost of robotic, thoracoscopic, and open malignant lobectomy from 2008 to 2015 and found that when annual hospital volume was >25 cases, there was no significant cost difference between the 3 approaches.²¹ Another study by Kneuertz et al. demonstrated that Robot-L and VATS-L had improved patient outcomes compared to open thoracotomy approach and similar cost.²² This study, performed at a single tertiary referral center, suggests that robotic surgery may be more likely to be cost effective when performed by specialty trained surgeons at high adoption centers. This is consistent with data demonstrating that a learning curve exists before being able to achieve robotic thoracic surgery competency.^23,24

Limitations of this study include that this is a retrospective analysis of a national database. The PHD does not contain data regarding neoadjuvant treatment or clinical stage which may have affected decisions regarding surgical approach and may have impacted outcomes such as in-hospital mortality and length of stay. The PHD also lacks data regarding patient characteristics such as comorbidities and pulmonary function status. However, we do not believe that there is a significant bias between which patients are offered a robotic vs thoracoscopic approach to lung lobectomy based on these clinical factors. Furthermore, studies have shown that patients with significant comorbidities can still safely undergo a minimally invasive approach to lung lobectomy.²⁵ Since billing data was used to determine surgical approach with an intention to treat model, we are unable to verify that the procedure performed is what was billed. Another important limitation of our study is that we did not have data relating to patient-centered outcomes. Lastly, although total patient charges were analyzed in our study, details of the charge analysis (including individual components of the total charge) are unknown making it difficult to draw conclusions regarding cost effectiveness of either approach.

In conclusion, this study of a nationally representative database demonstrates that robotic lobectomy is now the most common approach for lung cancer lobectomy. Although Robot-L had similar in-hospital mortality compared to VATS-L, patients who underwent robotic approach had reduced LOS but significantly increased patient charges. Further research with emphasis on patient-centered outcomes is warranted to determine the relationship between cost and benefit for patients undergoing robotic lobectomy for lung cancer.

Supplemental Material

Supplemental Material - Comparing Thoracoscopic and Robotic Lobectomy Using a Nationally Representative Database

Supplemental Material for Comparing Thoracoscopic and Robotic Lobectomy Using a Nationally Representative Database by Christine E. Alvarado, MD, Stephanie G. Worrell, MD, Anuja L. Sarode, MPH, Boxiang Jiang, MD, Sean J. Halloran, BS, Luis M. Argote-Greene, MD, Philip A. Linden, MD, and Christopher W. Towe, MD in The American Surgeon

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Disclosures

Dr. Towe is a consultant and recipient of a grant for Zimmer Biomet. He is also a consultant for SigMedical, Atricure, and Medtronic. Dr. Worrell is a consultant for Intuitive and Bristol Meyer Squibbs. None of these relationships have affected this manuscript or the accuracy of the data analysis.

ORCID iD

Boxiang Jiang

Supplemental Material

Supplementary material for this article is available on the Online.

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