Exploratory and Confirmatory Factor Analyses Support the Unidimensionality of the Arabic Quick Disabilities of the Arm, Shoulder and Hand

Abstract

The objective of this investigation was to assess the structural validity of the Arabic Quick Disabilities of the Arm, Shoulder and Hand (QuickDASH) in individuals suffering from upper extremity musculoskeletal disorders, utilizing both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). A group of participants with upper extremity musculoskeletal disorders attending physical therapy clinics were recruited. Upon their initial visit to physical therapy, participants were requested to complete the Arabic versions of the QuickDASH, as well as the Numeric Pain Rating Scale. In order to determine the number of factors, parallel analysis was employed in the EFA, while maximum likelihood was utilized for extraction. The fit of the model identified using EFA was subsequently examined using CFA, incorporating multiple fit indices. The outcomes of the EFA indicated the existence of a one-factor structure, accounting for a considerable 50.22% of the total variance. It was observed that all of the QuickDASH items displayed loadings on the single factor, with values ranging from 0.35 to 0.77. However, the multiple fit indices obtained from the CFA did not provide sufficient support for the fit of the initially proposed unidimensional structure. The data showed good fit to the unidimensional model after adding error covariance: chi-square = 100.52 [degrees of freedom (df) = 40, P < 0.001], chi-square/df = 2.51, Tucker–Lewis index = 0.94, comparative fit index = 0.95, root mean square error of approximation = 0.077 [90% confidence interval (CI) = 0.058-0.096], and standardized root mean residual = 0.048. Ultimately, the findings from the EFA provided evidence supporting the unidimensionality of the Arabic QuickDASH, while the CFA supported the unidimensionality of the QuickDASH after addressing the issue of local dependency between some scale items.

Main article text

INTRODUCTION

Musculoskeletal disorders affecting the upper limbs are common ( Huisstede et al., 2006; Lucas et al., 2022). Those who suffer from such disorders often encounter restrictions in their daily activities that involve the upper limbs ( Røe et al., 2021; van Kooij et al., 2021; Vincent et al., 2021). These limitations, as perceived by the patients themselves, hold great significance in their overall functionality ( Røe et al., 2021; van Kooij et al., 2021; Vincent et al., 2021). Consequently, it is imperative to utilize a patient-reported outcome measure (PROM) in order to evaluate the functioning of the upper limbs and determine the extent of limitations in these crucial activities for individuals within this particular population.

The short edition of the Disabilities of the Arm, Shoulder and Hand (QuickDASH) is a commonly utilized PROM for evaluating both symptoms and activity limitations in the upper extremities ( Beaton et al., 2005). Studies have shown that the QuickDASH exhibits satisfactory internal consistency, test–retest reliability, and construct validity ( Kennedy et al., 2013). On the contrary, the QuickDASH exhibited contradictory results regarding its structural validity ( Kennedy et al., 2013). Recent studies have also reported factor structure other than the assumed unidimensional structure of the QuickDASH ( Fayad et al., 2009; Gabel et al., 2009; Hong et al., 2018; da Silva et al., 2020; Stirling et al., 2023). The systematic review by Kennedy et al. (2013) also indicated that most translated versions of the QuickDASH lack a proper assessment of the adapted scale structural validity.

According to the consensus-based standards for the selection of health measurement instruments (COSMIN), structural validity refers to “the degree to which the scores of a health-related patient-reported outcome instrument are an adequate reflection of the dimensionality of the construct to be measured” ( Aldaihan and Alnahdi, 2023). Establishing a PROM structural validity requires item-level analysis to determine the number of latent constructs measured by the scale items and pattern of relationship between the items and the latent constructs ( de Vet et al., 2011). Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) are the most commonly used analysis techniques for the formal examination of a PROM structural validity. The COSMIN suggested both techniques for establishing structural validity with a preference of the CFA given its ability to examine a pre-defined hypothesis regarding the underlying structure ( Mokkink et al., 2018; Prinsen et al., 2018).

Evaluations of the measurement properties of the Arabic version of QuickDASH were conducted among patients with upper extremity musculoskeletal disorders ( Alnahdi, 2021; Aldaihan and Alnahdi, 2023). These evaluations demonstrated adequate internal consistency, test–retest reliability, construct validity, and responsiveness of the Arabic QuickDASH ( Alnahdi, 2021; Aldaihan and Alnahdi, 2023). The structural validity of the Arabic QuickDASH has only been examined with exploratory techniques using EFA that suggested a unidimensional structure for the Arabic QuickDASH ( Alnahdi, 2021). Structural validity of the Arabic QuickDASH has not been established previously using the preferred method of CFA. The original contribution of the current study lies in the assessment of the Arabic QuickDASH using a hypothesis-driven CFA. Thus, the current study aimed to use EFA and CFA to examine the structural validity of the Arabic QuickDASH in patients with upper extremity musculoskeletal disorders. The hypothesis proposed is that the Arabic QuickDASH would exhibit a one-factor structure indicative of upper extremity function.

MATERIALS AND METHODS

Study design

This research study was structured as a cross-sectional study, involving the evaluation of participants at a single time point.

Setting and participants

Participants for this current research were recruited through convenience sampling from various physical therapy departments. These were the outpatient physical therapy clinics at the King Abdulaziz Medical City, Security Forces Hospital, and PhysioTrio, in Riyadh, Saudi Arabia. Ethical approval was obtained from the Institutional Review Board of the Security Forces Hospital (H-01-R-069) and the study adhered to the principles of the Declaration of Helsinki. Prior to participation, individuals provided consent by signing informed consent documents. Individuals who were 18 years of age or older with upper extremity musculoskeletal disorders were recruited in the current study. Individuals who were unable to read and understand the Arabic language had spinal, cardiovascular, neurological, or pulmonary disorders causing functional limitations were excluded from participation in the study.

Procedure

During the participants’ first encounter with the outpatient physical therapy departments, they were requested to fill out the Arabic versions of both QuickDASH ( Alnahdi, 2021) and the Numeric Pain Rating Scale (NPRS) ( Alghadir et al., 2016), as part of the initial assessment for their upper extremity musculoskeletal disorders. In addition to these questionnaires, a comprehensive set of general information pertaining to the participants was gathered during the same assessment session. This information encompassed various anthropometric data, including the participants’ height and weight.

Outcome measures

Quick Disabilities of the Arm, Shoulder and Hand short version

The QuickDASH, which is an 11-item PROM, serves as an important tool for assessing upper extremity activity limitation and symptoms ( Beaton et al., 2005). In this regard, the items within the QuickDASH were assigned scores ranging from 1 to 5, reflecting the degree of functional limitation and symptom severity experienced by individuals. A score of 1 signifies the absence of any functional limitation or symptoms, while a score of 5 denotes the presence of significant functional inability and extreme symptoms. Consequently, the total score derived from the QuickDASH was calculated by transforming the average score obtained across all items into a scale that ranges from 0 to 100. A score of 0 on this scale indicates the optimal level of upper extremity function and the absence of any symptoms. Pertaining to the Arabic version of the QuickDASH implemented in the present study, it has been validated and demonstrated to exhibit excellent reliability and responsiveness when utilized among patients afflicted with upper extremity musculoskeletal disorders ( Alnahdi, 2021; Aldaihan and Alnahdi, 2023).

Numeric Pain Rating Scale

The NPRS was utilized in order to evaluate and determine the average level of pain intensity that the participant experienced specifically in relation to the area of dysfunction in their upper extremities ( Hawker et al., 2011). The scores on this particular scale ranged from 0, which was indicative of the absence of any pain, all the way up to 10, which represented the most severe pain that one could possibly imagine. In previous research studies, the measurement properties of the Arabic version of the NPRS have been thoroughly examined and validated, demonstrating its reliability and validity as a means of assessing pain intensity ( Alghadir et al., 2016; Alnahdi, 2021). The NPRS was not directly relevant to the study’s objective; however, it was documented to offer a more comprehensive understanding of the clinical condition of the participants.

Statistical analysis

The present investigation sought to assess the structural validity of the Arabic QuickDASH, employing both exploratory and CFA. In the initial stage of the EFA, the extraction of factors was carried out utilizing the maximum likelihood method. Furthermore, the determination of the number of factors, latent constructs, was accomplished through the implementation of parallel analysis, wherein only factors exhibiting an eigenvalue greater than the 95th percentile of the simulated random data eigenvalue were extracted ( O’Connor, 2000). The EFA and parallel analysis were conducted in the current research study employing the statistical software of IBM SPSS Statistics 28 (IBM Corp, Armonk, NY, USA) and JASP (version 0.18.1.0).

Following the completion of EFA, the researchers proceeded to evaluate the adequacy of the underlying structure that was identified through the use of EFA by utilizing CFA. In order to ensure the validity of the CFA, a series of preliminary assessments were conducted, including evaluations for multivariate normality as well as detection of outliers. The chi-square statistic (χ ²) was used as a means to assess the model fit, whereby a non-significant result would indicate a perfect fit. It is important to note, however, that the interpretation of the χ ² statistic must take into account its known sensitivity to large sample sizes, which can lead to an indication of poor fit even when the data reasonably conforms to the proposed measurement model ( Byrne, 2010; Cappelleri et al., 2013). In addition to the χ ² statistic, several other fit indices were used to evaluate the model fit, including the χ ²/degrees of freedom (df) ratio, the Tucker–Lewis index (TLI), the comparative fit index (CFI), the standardized root mean residual (SRMR), and the root mean square error of approximation (RMSEA). The subsequent cutoff values were employed to indicate good model fit: a χ ²/df value <3, a CFI and TLI value ≥0.90, a RMSEA value ≤0.06, and an SRMR value ≤0.08 ( Hu and Bentler, 1999; Jackson et al., 2009). The CFA was carried out using the maximum likelihood estimation method through the use of IBM SPSS AMOS software (version 26; IBM Corp, Armonk, NY, USA). In order to identify any potential model misspecifications, modification indices and standardized residuals were thoroughly examined ( Byrne, 2010; Brown, 2015).

Sample size estimation

According to the COSMIN guidelines, it has been determined that a sample size including seven participants for each item within the scale, with a minimum sample size of 100 participants, is considered to be highly suitable for assessing the structural validity of a PROM ( Mokkink et al., 2018). Therefore, in line with these recommendations, it was determined that a sample size of 100 participants constitutes the minimum required sample size for our study given that seven participants for each of the 11 QuickDASH items are lower than the minimum of 100 participants ( Mokkink et al., 2018).

RESULTS

This research study comprised the involvement of 255 participants who were affected by musculoskeletal disorders in their upper extremities ( Table 1). Musculoskeletal disorders in the shoulder and arm region were the most prevalent disorders in our sample, followed by issues in the wrist and hand, and lastly, disorders in the elbow and forearm. All the participants in the current study completed the QuickDASH with no missing items; thus, no imputations were performed. The descriptive statistics of the QuickDASH items are provided in Table 2.

Table 1:

Characteristics of participants ( N = 255).

Variable	Mean ± SD or N (%)
Age (year)	39.25 ± 14.05
Sex
Male	145 (56.9)
Female	110 (43.1)
Height (m)	1.67 ± 0.09
Mass (kg)	76.19 ± 16.49
Body mass index (kg/m 2)	27.44 ± 5.64
Site of dysfunction
Shoulder and arm	135 (52.9)
Elbow and forearm	37 (14.5)
Wrist and hand	83 (32.5)
Upper extremity surgery
Yes	100 (39.2)
Time after surgery (months)	1.84 (2.07) a
No	155 (60.8)
Duration of symptoms (months)	2.99 (8.74) a
QuickDASH (0-100)	48.20 ± 21.46
NPRS (0-10)	4.79 ± 2.35

Abbreviations: N, number of participants; NPRS, Numeric Pain Rating Scale; QuickDASH, Quick Disabilities of the Arm, Shoulder and Hand; SD, standard deviation.

^aMedian (interquartile range).

Table 2:

Descriptive statistics and EFA factor loading for QuickDASH items.

Item		Mean	SD	Factor loading
1.	Open a tight or new jar.	3.15	1.28	0.69
2.	Do heavy household chores (e.g. wash walls, floors).	3.75	1.19	0.77
3.	Carry a shopping bag or briefcase.	2.88	1.20	0.77
4.	Wash your back.	3.36	1.37	0.70
5.	Use a knife to cut food.	2.56	1.32	0.77
6.	Recreational activities in which you take some force or impact through your arm, shoulder or hand (e.g. golf, hammering, tennis, etc.).	3.53	1.26	0.74
7.	During the past week, to what extent has your arm, shoulder or hand problem interfered with your normal social activities with family, friends, neighbors or groups?	2.36	1.20	0.65
8.	During the past week, were you limited in your work or other regular daily activities as a result of your arm, shoulder or hand problem?	2.70	1.17	0.70
9.	Arm, shoulder or hand pain.	3.08	1.05	0.61
10.	Tingling (pins and needles) in your arm, shoulder or hand.	2.29	1.21	0.35
11.	During the past week, how much difficulty have you had sleeping because of the pain in your arm, shoulder or hand?	2.54	1.17	0.56

Abbreviations: EFA, exploratory factor analysis; QuickDASH, Quick Disabilities of the Arm, Shoulder and Hand; SD, standard deviation.

The Kaiser–Meyer–Olkin measure of sampling adequacy, which is a statistical measure used to assess the appropriateness of a sample for factor analysis, yielded a value of 0.90, indicating a high level of adequacy in the sample. Additionally, Bartlett’s test of sphericity, a statistical test that examines whether the correlation matrix of the variables is significantly different from an identity matrix, demonstrated significance with a P value of <0.001. This significant result further confirms the suitability of the data for factor analysis. The findings from the parallel analysis revealed that only a single factor had an eigenvalue that exceeded the eigenvalues obtained from random data ( Fig. 1) ( Table 3). This observation suggests that the Arabic QuickDASH possesses a singular underlying factor structure related to upper extremity function. As a result, this endorses the structural validity of the scale as a unidimensional measure. In line with the outcomes of the parallel analysis, a single factor was extracted, accounting for a substantial portion of the total variance, specifically 50.22%. Furthermore, when examining the loadings of the QuickDASH items it was found that all items displayed meaningful loadings ranging from 0.35 for item 10 to 0.77 for items 2, 3, and 5 ( Table 2).

Figure 1:

Scree plot of the QuickDASH including actual and simulated eigenvalues from the parallel analysis. Abbreviation: QuickDASH, Quick Disabilities of the Arm, Shoulder and Hand.

Table 3:

Factor structure of the QuickDASH.

Factor	Initial eigenvalues
	Total	% of Variance	Cumulative %
1	5.52	50.22	50.22
2	1.25	11.39	61.61
3	0.81	7.37	68.98
4	0.63	5.72	74.71
5	0.61	5.53	80.24
6	0.46	4.22	84.46
7	0.43	3.95	88.41
8	0.37	3.40	91.81
9	0.34	3.07	94.88
10	0.30	2.72	97.60
11	0.26	2.40	100.00

Abbreviation: QuickDASH, Quick Disabilities of the Arm, Shoulder and Hand.

The initial CFA model that was examined encompassed the inclusion of a single latent variable, upper extremity function, and a total of 11 indicators representing the QuickDASH items. The analysis yielded a set of fit indices that were as follows: χ ² = 224.92 (df = 44, P < 0.001), χ ²/df = 5.11, TLI = 0.83, CFI = 0.86, RMSEA = 0.13 (90% CI = 0.11-0.14), and SRMR = 0.072. These fit indices did not provide adequate support for the alignment of the data with the proposed model. Upon further investigation, certain areas of model misfit were identified, specifically in relation to the high residual covariance and high error covariance indicating local dependency between some items. Such instances of high error covariances were observed between the following items: items 7 and 8, items 9 and 11, items 10 and 11, and items 9 and 10. In an attempt to address this model misfit, the decision was made to allow these error terms to covary, as depicted in Figure 2. The incorporation of this modification led to an improvement in the fit of the model, which in turn resulted in the following revised set of fit indices: χ ² = 100.52 (df = 40, P < 0.001), χ ²/df = 2.51, TLI = 0.94, CFI = 0.95, RMSEA = 0.077 (90% CI = 0.058-0.096), and SRMR = 0.048. As indicated by these fit indices, the modified model now displayed a good level of fit with the data, as depicted in Figure 2. The final CFA model parameter estimates can be found in Table 4. Significant positive loadings were observed for all QuickDASH items ( Table 4).

Figure 2:

QuickDASH final CFA model showing good model fit. Abbreviations: CFA, confirmatory factor analysis; QuickDASH, Quick Disabilities of the Arm, Shoulder and Hand.

Table 4:

Parameter estimates in the confirmatory factor analysis.

QuickDASH items		Standardized loading	Unstandardized loading	SE	CR	P
1.	Open a tight or new jar	0.71	1.00 a	—	—	—
2.	Do heavy household chores (e.g. wash walls, floors)	0.79	1.04	0.09	11.90	<0.001
3.	Carry a shopping bag or briefcase	0.77	1.02	0.09	11.56	<0.001
4.	Wash your back	0.71	1.07	0.10	10.66	<0.001
5.	Use a knife to cut food	0.78	1.12	0.10	11.69	<0.001
6.	Recreational activities in which you take some force or impact through your arm, shoulder or hand (e.g. golf, hammering, tennis, etc.)	0.76	1.05	0.09	11.34	<0.001
7.	During the past week, to what extent has your arm, shoulder, or hand problem interfered with your normal social activities with family, friends, neighbors, or groups?	0.60	0.79	0.09	8.99	<0.001
8.	During the past week, were you limited in your work or other regular daily activities as a result of your arm, shoulder, or hand problem?	0.65	0.84	0.09	9.83	<0.001
9.	Arm, shoulder or hand pain	0.56	0.65	0.08	8.50	<0.001
10.	Tingling (pins and needles) in your arm, shoulder, or hand	0.30	0.40	0.09	4.49	<0.001
11.	During the past week, how much difficulty have you had sleeping because of the pain in your arm, shoulder, or hand?	0.51	0.66	0.09	7.71	<0.001

Abbreviations: CR, critical ratio; SE, standard error; QuickDASH, Quick Disabilities of the Arm, Shoulder and Hand.

^aFixed to 1 (no associated SE, CR, or P value).

DISCUSSION

This research study was specifically undertaken in order to thoroughly examine the structural validity of the Arabic QuickDASH within a specific population of individuals who were diagnosed with upper extremity musculoskeletal disorders. It was hypothesized that the Arabic QuickDASH would successfully demonstrate a unidimensional structure, thereby reflecting one single latent variable that pertains to upper extremity function. Upon analyzing the results obtained from the EFA, it was found that these findings indeed supported the hypothesized unidimensional structure. Furthermore, the CFA also provided additional support for this hypothesized unidimensional structure, taking into consideration the local dependency that exists among certain items in the scale.

The results of the EFA conducted in the current study supported our hypothesized unidimensionality of the QuickDASH. This one-factor structure is believed to represent upper extremity function. The results reported here are in line with our previous study ( Alnahdi, 2021). Both studies used an objective method for determining the number of factors and parallel analysis, and this method suggested an underlying unidimensional structure for the Arabic QuickDASH. Using the similar method for determining the number of factors, Franchignoni et al. (2011) supported the unidimensionality of the QuickDASH. Additional reports in the literature have also reported using EFA that the QuickDASH has a unidimensional structure ( Imaeda et al., 2006; Varjú et al., 2008; LeBlanc et al., 2014).

On the other hand, Stirling et al. (2023) used parallel analysis for determining the number of factors and reported that the QuickDASH has two-factor structure. It is worth noting that the authors did not provide details regarding the results of parallel analysis and that the study was conducted in patients with one specific upper extremity disorder that is carpal tunnel syndrome. This difference in the characteristics of the participants between our study and that of Stirling et al. might explain the difference in the underlying structure reported. Number of other studies in the literature examined the underlying structure of the QuickDASH and used other less optimal methods for determining the number of underlying factors and these studies reported a two-factor structure ( Fayad et al., 2009; Gabel et al., 2009; da Silva et al., 2020) and a three-factor structure ( Hong et al., 2018). The methods used for determining the number of factors in these studies such as eigenvalue >1, reliance on visual observation of scree plot, are known to be less optimal compared to the parallel analysis method employed in the current study ( Cappelleri et al., 2013).

All the items within the Arabic QuickDASH seem to be good indicators of upper extremity function as manifested by the magnitude of factor loadings. Despite having a factor loading that is considered acceptable ( Tabachnick and Fidell, 2013), item 10 showed distinctly lower factor loading compared to the other items. This relatively low loading for item 10 suggests lower level of correlation between the latent construct representing upper extremity function and item 10 representing arm tingling and that this item might not be a good indicator of the underlying construct. This relatively low factor loading for item 10 has been reported previously for the Arabic QuickDASH and other versions ( Franchignoni et al., 2011; Alnahdi, 2021).

The CFA analysis indicated misfit of the data to the proposed unidimensional structure. The results of the follow-up diagnostics including residual covariance and modification indices suggested that the primary reason for the deviation from the unidimensional model is the presence of local item dependence among some items. The presence of the local item dependency is suggestive of either response dependency among the items or multidimensionality ( Tennant and Conaghan, 2007; Hagquist et al., 2009).

The high error covariance detected between item 7 and item 8 could be argued to be mainly caused by response dependency between the items. The content of both items seems to be general covering social activities and daily activities which could be interpreted similarly by patients completing the scale. This general nature of these items and the potential similarity of the content could make the response of one of the two items to determine the response of the other item. This presence of response dependency between items violates the requirement of unidimensionality where the responses to items are only driven by one factor that is the level of upper extremity function ( Tennant and Conaghan, 2007; Hagquist et al., 2009).

High error covariance among the items 9, 10, and 11 constituted local dependency among the items and presented deviation from the unidimensional model. These items represent upper extremity impairments rather than upper extremity function as the rest of the items. These items represent upper extremity pain (item 9), tingling (item 10), and difficulty sleeping because of the pain (item 11). The content of these items seems to raise the suspicion of the presence of another dimension in the QuickDASH, thus violating the requirement of unidimensionality ( Tennant and Conaghan, 2007; Hagquist et al., 2009). Response dependency might also explain some of the observed high error covariance among these items especially between items 9 and 11. Both of these items enquire about upper extremity pain; thus, the response to one item would determine the response to the other item given that both items have similar content.

Despite some suggestions of the presence of another dimension representing upper extremity impairment, addressing the issue of local dependency resulted in satisfactory fit suggesting the presence of one general factor representing upper extremity function. The issue of local dependency was reported previously among the DASH and QuickDASH item analyses ( Prodinger et al., 2019). Similar to that reported in the current study but within the Rasch model framework, impairment-related and function-related QuickDASH items have shown residual correlation beyond what is explained by the main underlying factor analysis ( Prodinger et al., 2019). This local dependency was accounted for by the creation of two super items: impairment-related and function-related. After accounting for local dependency, the authors reported the QuickDASH satisfied the requirement of unidimensionality similar to the good fit in our study to the unidimensional model after the local dependency was accounted for by allowing error terms to covary.

Based on COSMIN, PROM score should reflect the dimensionality of the construct to be measured by the PROM ( Aldaihan and Alnahdi, 2023).The good fit of the data to the unidimensional CFA model reported in the current study supports the validity of using one total score for the Arabic QuickDASH representing one underlying construct that is upper extremity function. Transforming the QuickDASH total score from an ordinal-level to interval-level score would require the use of advanced techniques such as Rasch measurement model ( Tennant and Conaghan, 2007; Hagquist et al., 2009). It is interesting to note that number of research studies that reported the QuickDASH to have more than one dimension still scored the scale and analyzed its remaining measurement properties using one total score, which assume that the scale is unidimensional ( Fayad et al., 2009; da Silva et al., 2020).

This research study has certain limitations that must be acknowledged. It is important to note that the number of participants suffering from elbow and forearm disorders in this study is relatively small, which means that the findings should be interpreted with caution when it comes to individuals with similar disorders in this specific anatomical region. In order to further enhance our understanding of the Arabic QuickDASH, it is recommended that additional analyses be conducted to explore the internal structure of the instrument. These analyses could include an assessment of the response options validity, an examination of measurement invariance using the Rasch measurement model. Conversely, it is worth noting that the current study did benefit from a robust sample size, which greatly surpassed the number of participants recommended by the COSMIN guidelines for examining the structural validity of a PROM. The fact that the study had a complete data set with no imputations further adds to the confidence one can have in the results obtained.

CONCLUSION

By utilizing both EFA and CFA techniques on a sample of individuals suffering from musculoskeletal disorders in the upper extremities, this study sought to assess the structural validity of the Arabic QuickDASH. The results of the EFA indicated that the Arabic QuickDASH is a unidimensional outcome measure, while the CFA confirmed this unidimensionality after accounting for local dependency issues among certain scale items.

COMPETING INTERESTS

The authors declare no conflict of interest.

INSTITUTIONAL REVIEW BOARD STATEMENT

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of the Security Forces Hospital (H-01-R-069).

INFORMED CONSENT STATEMENT

Informed consent was obtained from all subjects involved in the study.

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