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Keywords:

  • Ankylosing spondylitis;
  • Fatigue;
  • Vitality;
  • Disease activity;
  • Physical function

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Objective

To investigate 1) levels of fatigue in patients with ankylosing spondylitis (AS) compared with the general population; 2) the relationships between fatigue and demographic, self-reported, and clinical measures; and 3) the performance of both a generic and a disease-specific measure of fatigue.

Methods

Patients with AS (n = 152) were compared with people from the general population (n = 2,323). Fatigue was assessed by the Short Form 36 (SF-36) vitality scale and the fatigue item of the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI). Other measures of self-reported health included BASDAI for disease activity, Bath Ankylosing Spondylitis Functional Index for functional abilities, and the SF-36 for mental health. Clinical measures comprised Bath Ankylosing Spondylitis Metrology Index for joint mobility and erythrocyte sedimentation rate and C-reactive protein as inflammatory markers. The explanatory power of demographic, self-reported, and clinical measures was examined in a block regression model.

Results

The mean ± SD SF-36 vitality score was 43 ± 24 in the patients and 60 ± 21 in the general population (P < 0.001). The SF-36 vitality and the BASDAI fatigue scores were consistently associated with measures of mental health and disease activity. Clinical measures did not show explanatory power. A cutoff at 70 mm on the BASDAI fatigue item implied specificity of 0.77 and sensitivity of 0.82.

Conclusion

Self-reported measures of disease activity and mental health contributed significantly to explain fatigue, whereas clinical measures of inflammation and joint mobility did not. The BASDAI fatigue item reached acceptable sensitivity and specificity with a cutoff at 70 mm when using the low vitality scores of SF-36 as an external indicator.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Ankylosing spondylitis (AS) is a rheumatic disease characterized by inflammation and radiographic changes, mainly localized to the spinal column. Therapies are aimed at reducing inflammatory responses, spinal stiffness, and pain (1–4). Additionally, fatigue is reported to be a common complaint among patients with AS (5–7); according to Calin et al, this complaint should be emphasized more in clinical practice (5). The importance and relevance of fatigue as an outcome measure is also highlighted by different research groups working on outcome measure consensus, including the Patient Perspective Workshop at Outcome Measures in Arthritis Clinical Trials 6 (8) and the Assessment in Ankylosing Spondylitis Working Group (9).

Fatigue in healthy persons occurs as a normal and temporary phenomenon, whereas disease-related fatigue may persist despite adequate amounts of rest and sleep, and is considered long lasting or chronic (10–12). Although the acute form of fatigue is regarded to be purposeful and protective against overexertion, chronic disease-related fatigue is recognized as unrelenting and dysfunctional, and its symptoms may be attributed to an underlying somatic condition (10, 13). Fatigue is frequently reported in ill people as well as in the general population (12, 14–16). Group comparisons of fatigue severity levels by appropriate instruments, as well as examination of associations with other variables, may elucidate fatigue as a disease-related symptom or as a normally occurring phenomenon.

In a group of patients with AS, van Tubergen et al found that the degree of fatigue varied greatly, covering almost the entire range of a scale from 0 (none) to 100 (severe) on the disease-specific Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) fatigue item (17). Additionally, female patients reported higher fatigue scores than male patients. However, sex differences in fatigue levels are also reported in the general population (16, 18, 19), and the sex differences among patients may thus not necessarily reflect a disease-related problem.

Previous studies have shown that fatigue in AS patients is associated with limitations in daily life functioning (5, 6, 17), pain, and stiffness (6), as well as with global wellbeing and mental health (17). Possible associations between fatigue and biologic signs of inflammation in AS are, to our knowledge, scarcely reported. Fatigue has been measured by the fatigue item of the BASDAI, dichotomized with a cutoff at 50 mm (scores ≥50 mm indicate fatigue as a major symptom) (17, 20). To our knowledge, this cutoff is not based upon comparisons with fatigue levels in the general population. The use of reference data for comparisons is an accepted standard for assessment of health status (21), and the generic health status measure Short Form 36 (SF-36) is regarded as a useful instrument for estimating the relative burden of disease (22). Thus, using the SF-36 vitality scores of the general population as reference data (external indicator) could be a valid approach for establishing cutoff values on the disease-specific measure of fatigue.

The aims of this study were to investigate the levels of fatigue in patients with AS compared with the general population and to examine how demographic, self-reported, and clinical measures were associated with fatigue. Furthermore, we wanted to explore the sensitivity and specificity of a disease-specific measure of fatigue using a generic measure as an external criterion.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Patients.

The patients participating in this cross-sectional study were recruited from a register of AS patients at the Department of Rheumatology, Diakonhjemmet Hospital, Oslo. The register included patients examined by rheumatologists and fulfilling the New York classification criteria (23), and totaled 465 patients 20–81 years of age. These patients received a postal questionnaire in 2002, and 314 (67%) completed questionnaires were returned. One year later, those responding in 2002 and still living at the same address (n = 283) were invited to undergo a clinical examination and to fill out questionnaires. One hundred fifty-two consented to participate and were included in the present study.

According to data from the 2002 survey, the participants in this study (n = 152) did not differ from the nonparticipants (n = 131) in terms of the BASDAI score (52 and 47, respectively; P = 0.08), the Bath Ankylosing Spondylitis Functional Index (BASFI) score (33 and 30, respectively; P = 0.30), and the SF-36 vitality score (42 and 44, respectively; P = 0.58). The mean ages were 42 and 47 years, respectively (P < 0.001). The study was approved by the Ethical Committee for Medical Research.

The patients' responses on the SF-36 were compared with the data obtained in a previous study of 2,323 individuals ages 19–80 years from the general population. This sample was randomly selected from the National Register of Norway, and reflected the general population in terms of sex and age distribution (15).

Self-reported measures.

Fatigue was measured by a generic (SF-36 vitality) and a disease-specific (BASDAI fatigue) measure. The SF-36 is a generic, valid, and reliable questionnaire examining different aspects of health in samples from the general population, as well as from patients with physical and mental conditions (24, 25). The SF-36 covers 8 domains of health. The use of single domains of the SF-36 is supported by the developers (25), and the vitality scale was applied in this study. The SF-36 vitality scale includes 4 items addressing energy level and fatigue (25). Vitality and fatigue can be regarded as inversely related constructs in this vitality scale, as vitality corresponds to estimation of energy and fatigue to reduced energy. The questions of the scales have 6 response choices that were summed, recalibrated, and converted into values ranging from the worst score (0) to the best score (100), according to standard guidelines (25). In the present study, the SF-36 vitality scale was dichotomized to perform a cutoff score between patients scoring above the 10th percentile of the general population (VTnormal), and patients scoring below the 10th percentile of the general population (VTlow). These cutoffs were 30 for men and 35 for women.

The fatigue item of the BASDAI was used as the disease-specific measure. The BASDAI has been developed to assess self-reported disease activity in AS (26). The severities of fatigue, spinal pain, joint pain, localized tenderness, morning stiffness, and duration of stiffness are measured by visual analog scales (VASs) that range from 0 = no problems to 100 = most severe problem. In accordance with previous studies (17, 20), the fatigue item was used to estimate fatigue (BASDAI fatigue in this study).

Measures of other dimensions of self-reported health included SF-36 for mental health (single domain), the BASDAI for disease activity, and the BASFI for physical functioning.

The SF-36 mental health scale includes 5 items addressing psychological distress and wellbeing (scale 0–100, 100 being best health) (25). Disease activity was, as in previous studies (17, 20), measured as the mean of the 5 BASDAI items about pain, stiffness, and tenderness (BASDAI in this study). The BASFI includes 8 items about the ability to perform specific functional activities (e.g., put on socks or stockings, pick up pen from floor, raise up from a supine lying position on floor) and 2 items about the ability to perform physical loaded work and fulfill working obligations at home or at work. The responses in the BASDAI and BASFI are given on VASs, and the mean scores of the items give the final scores (scale 0–100, 100 being worst) (5, 27).

Clinical measures.

The Bath Ankylosing Spondylitis Metrology Index (BASMI) includes 5 clinical examinations of spinal and hip mobility; i.e., the distance from tragus to wall, lumbar ventral and lateral flexion, cervical rotation, and intermalleolar distance (28). The ratings are classified in categories from 0 to 2, where 0 is normal mobility. The BASMI score is the sum of the scores recorded for each test (0–10, 10 being worst).

The erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) were measured and applied as biologic signs of inflammation. Because fatigue also is suggested to be associated with the level of hemoglobin in other diseases with immunopathologies (29), the hemoglobin concentration was examined. The normal references for hemoglobin were ≥11.5 gm/dl for women and ≥12.5 gm/dl for men.

Statistics.

Data were analyzed using SPSS for Windows, version 11 (SPSS Inc., Chicago, IL). Descriptive data are given as mean ± SD. Because of the large difference in number of respondents in the patient and the general population, the patients' SF-36 vitality score was analyzed by 1-sample t-tests against the mean of the general population. Other group differences were examined by the chi-square and the independent Student's t-tests.

Correlations between measures were examined by Pearson's correlation coefficients. Scales assumed to measure the same dimensions were expected to correlate 0.70 or higher (strong correlation). Correlations of 0.30–0.70 were considered moderate, and coefficients <0.30 were considered weak, expected to be found for unrelated measures (24).

The SF-36 vitality and the BASDAI fatigue scores were used as dependent variables in block regression models. The variables were entered into the models in 3 blocks including different categories of variables: the demographic variables (age, sex, and disease duration) were entered in block 1; the self-reported (subjective) variables of disease activity (BASDAI), physical function (BASFI), and mental health (SF-36 mental health) were entered in block 2; and the clinical (objective) variables inflammation (ESR, CRP) and joint mobility (BASMI) were entered in block 3. Scatterplots of the distribution of the residuals for the models were found acceptable.

A receiver operating characteristic (ROC) curve analysis was performed to calculate the level of specificity (proportion of negatives correctly identified by the test) and sensitivity (proportion of positives correctly identified by the test) (30) for the disease-specific fatigue item (BASDAI fatigue) when applying the VTlow versus the VTnormal as an external criterion.

In this study, P values ≤ 0.05 were considered statistically significant.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Patients with AS.

The patient sample comprised 88 men and 64 women between the ages of 24 and 81 years (Table 1). The mean ± SD symptom duration was 22 ± 12 years, and the time since diagnosis was 14 ± 12 years. Positive HLA–B27 test results were found in 94% of the patients.

Table 1. Characteristics of the patients with ankylosing spondylitis*
 All patients n = 152Men n = 88Women n = 64P
  • *

    Data presented as mean ± SD unless otherwise noted. ESR = erythrocyte sedimentation rate; CRP = C-reactive protein; BASDAI = Bath Ankylosing Spondylitis Disease Activity Index (0–100, 100 = worst score); BASFI = Bath Ankylosing Spondylitis Functional Index (0–100, 100 = worst score); BASMI = Bath Ankylosing Spondylitis Metrology Index (0–10, 10 = worst score); SF-36 = Short Form 36 (0–100, 100 = best score).

Age, years47 ± 1347 ± 1347 ± 130.97
Sex, % 5842 
Educational level >12 years, %6065540.18
Disease duration, years15 ± 1216 ± 1214 ± 120.34
Symptom duration, years22 ± 1222 ± 1321 ± 110.60
Laboratory tests    
 ESR18 ± 1717 ± 1719 ± 160.49
 CRP10 ± 1511 ± 179 ± 120.44
 Hemoglobin14 ± 1.214.5 ± 1.013.2 ± 1.1< 0.001
BASDAI44 ± 2338 ± 2153 ± 23< 0.001
 Fatigue55 ± 2848 ± 2865 ± 27< 0.001
 Spinal pain51 ± 2847 ± 2857 ± 280.03
 Joint pain32 ± 3027 ± 2640 ± 320.01
 Localized tenderness38 ± 3030 ± 2649 ± 31< 0.001
 Morning stiffness45 ± 2738 ± 2455 ± 28< 0.001
BASFI32 ± 2428 ± 2339 ± 240.004
BASMI2.7 ± 2.63.0 ± 3.02.2 ± 1.90.06
SF-36 mental health73 ± 1776 ± 1769 ± 170.01
SF-36 vitality43 ± 2449 ± 2333 ± 22< 0.001

Vitality and fatigue in AS.

The mean ± SD SF-36 vitality scores were 43 ± 24 in the patients and 60 ± 21 in the general population (P < 0.001). Men reported higher vitality than women in both the patient group (49 ± 23 and 33 ± 22, respectively; P < 0.001) and in the general population (63 ± 20 and 57 ± 21, respectively; P < 0.001). The distributions of vitality scores in patients and the general population for both sexes are visualized in Figure 1.

thumbnail image

Figure 1. The Short Form 36 (SF-36) vitality scores of women and men with ankylosing spondylitis (shaded boxes) and the general population (open boxes). The plot shows the median, quartiles, 10th percentile, and 90th percentile.

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The cutoff for low vitality (VTlow) was set at the 10th percentile of the general population (30 for men and 35 for women). Thirty-two percent of the patients were classified as having low vitality, and women were more likely than men to be classified in the VTlow group (relative risk [95% confidence interval] = 2.2 [1.6, 3.2], χ2 = 18.9, P < 0.001).

The mean ± SD score of the BASDAI fatigue item was 48 ± 28 and 65 ± 27 for men and women, respectively (P < 0.001).

Possible fatigue-associated factors.

More severe self-reported disease activity, limitations in physical function, and mental health were found in patients with VTlow compared with the VTnormal group (P < 0.001; additional data not shown). No statistically significant differences were found between patient groups with VTlow and VTnormal with respect to age, disease duration, BASMI score, or ESR and CRP (P > 0.4; data not shown).

The distribution of hemoglobin values was similar to the laboratory references, with few patients showing values below the lower limits. Hemoglobin levels were thus not included in subsequent analyses.

Tables 2 and 3 show 2 block regression models with the SF-36 vitality and the BASDAI fatigue scores as dependent variables, respectively. Block 1, the demographic variables (age, sex, and disease duration), contributed <10% to the variance in both models. The self-reported measures (block 2), covering disease activity, physical functioning, and mental health, contributed significantly with both vitality and BASDAI fatigue as dependent variables, accounting for an additional 49% (Table 2) and 41% (Table 3) of the variance, respectively. The clinical measures (block 3) did not contribute significantly in the models. In the final model (blocks 1–3), 58% of the variation was explained with the SF-36 vitality scale as the dependent variable (Table 2), whereas the final model accounted for 50% of the variation with the BASDAI fatigue item as the dependent variable (Table 3).

Table 2. Final model for the associations between the dependent variable SF-36 vitality and the independent variables entered in 3 blocks, in patients with ankylosing spondylitis*
VariablesPearson correlationUnstandardized β (95% CI)PR2 changeSignificant changeR2
  • *

    SF-36 = Short-Form 36 (0–100, 100 = best score); BASDAI = Bath Ankylosing Spondylitis Disease Activity Index (without fatigue item); BASFI = Bath Ankylosing Spondylitis Functional Index (0–100, 100 = worst score); BASMI = Bath Ankylosing Spondylitis Metrology Index (0–10, 10 = worst score); ESR = erythrocyte sedimentation rate; CRP = C-reactive protein.

  • Unstandardized coefficients (β) with 95% confidence intervals (95% CIs) and P values given for the final model.

  • P < 0.001.

Block 1: demographic variables   0.090.010.09
 Age−0.050.008 (−0.3, 0.3)0.96   
 Sex−0.33−3.6 (−10.5, 3.3)0.31   
 Disease duration−0.090.1 (−0.2, 0.5)0.50   
Block 2: self-reported variables   0.49< 0.0010.57
 BASDAI−0.56−0.2 (−0.4, 0.0)0.05   
 BASFI−0.53−0.3 (−0.5, −0.1)0.02   
 SF-36 mental health0.610.7 (0.5, 0.9)< 0.001   
Block 3: clinical variables   0.010.620.58
 BASMI−0.031.0 (−0.8, 2.9)0.28   
 ESR0.06−0.008 (−0.3, 0.3)0.96   
 CRP0.02−0.2 (−0.6, 0.3)0.50   
Table 3. Final model for the associations between the dependent variable BASDAI fatigue item and the independent variables entered in 3 blocks, in patients with ankylosing spondylitis*
VariablesPearson correlationUnstandardized β (95% CI)PR2 changeSignificant changeR2
  • *

    See Table 2 for acronym definitions.

  • Unstandardized coefficients (β) with 95% confidence intervals (95% CIs) and P values given for the final model.

  • P < 0.001.

Block 1: demographic variables   0.080.010.08
 Age0.07−0.02 (−0.4, 0.4)0.91   
 Sex0.293.3 (−5.5, 12)0.46   
 Disease duration0.110.2 (−0.3, 0.6)0.52   
Block 2: self-reported variables   0.41< 0.0010.49
 BASDAI0.690.6 (0.4, 0.9)< 0.001   
 BASFI0.530.08 (−0.2, 0.4)0.59   
 SF-36 mental health−0.42−0.4 (−0.6, −0.1)0.01   
Block 3: clinical variables   0.0020.910.50
 BASMI0.05−0.7 (−3.1, 1.7)0.55   
 ESR0.01−0.06 (−0.5, 0.4)0.77   
 CRP0.040.09 (−0.5, 0.7)0.75   

The BASDAI fatigue item and the SF-36 vitality scale.

Substantial correlation was found between the BASDAI fatigue item and the SF-36 vitality scores (r = −0.66, P < 0.001; data not shown). The level of 50 mm on the BASDAI fatigue item captures individuals with both high and low vitality scores, whereas the 10th percentile cutoff on the vitality scale (30 and 35 for men and women, respectively) captured few individuals with low BASDAI fatigue scores (Figure 2A). In an ROC curve analysis with the vitality cutoff score as the state variable, a proposed 50-mm cutoff at the BASDAI fatigue item classified VTlow with a sensitivity of 0.90 and a specificity of 0.54, whereas a 70-mm cutoff classified VTlow with a sensitivity of 0.82 and a specificity of 0.77.

thumbnail image

Figure 2. A, The association between the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) fatigue item and the Short Form 36 (SF-36) vitality scores in patients with ankylosing spondylitis. The horizontal lines indicate the 10th percentile value of the general population (women = 30, men = 35 [broken line]), and the vertical lines indicate 50 mm and 70 mm on the BASDAI fatigue item. B, The receiver operating characteristic curve shows sensitivity and specificity of different levels of the BASDAI fatigue item (low vitality [1] and normal vitality [0] serve as external indicators).

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DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

The AS patients in this study were significantly more affected by fatigue than the general population. The results of the study support the relevance of the initiatives that have been taken to put fatigue on the agenda for further research as an outcome measure in rheumatic diseases (9, 31, 32).

Self-reported health measures contributed in explaining about half of the variation in the generic and disease-specific fatigue measures, whereas clinical measures did not add significant explanation to the variation. Similar relationships between fatigue and measures of self-reported disease activity, limitations in functional abilities, and mental health have also been reported by others (5, 6, 17, 33). No differences were found in joint mobility or the inflammatory markers between the VTlow and the VTnormal groups. However, in accordance with other studies, moderate values of the inflammatory markers were found (20, 34), and the validity of ESR and CRP in AS have been discussed (34–36). A recent study by Dernis-Labous et al (20) showed that nonsteroidal antiinflammatory drug therapy strongly reduced pain and functional impairment in a group of AS patients, whereas the change in fatigue level was of lower magnitude. Thus, the relationship between fatigue and inflammatory markers is unclear, and more clinical trials are needed to explore whether interventions, such as disease-modifying drugs and physical activity, influence self-reported fatigue.

In the present study, women were more likely than men to be classified in the low vitality group, even if the cutoff score based on the normative data was made specific for each sex. Corresponding sex differences with respect to pain and fatigue are found in other studies (17, 37, 38). Although the effect of sex tended to be weaker in the multivariate analyses (Tables 2 and 3), women reported significantly worse scores on both the disease-specific and the generic measures, and the assumption was supported that, in clinical practice, special attention should be paid regarding women and fatigue (5).

In previous studies, the fatigued patients have been defined as those having BASDAI fatigue scores ≥50 mm (17, 20); according to this method, 53% and 63% (respectively) of their samples were classified as fatigued. When applying the same cutoff on the BASDAI fatigue item in the present study, 62% fulfilled this fatigue criterion. However, we made a cutoff between “affected” and “not affected” patients based on the normative data from the general population. The 10th percentile was chosen as cutoff, i.e., suggesting that low vitality normally occurs in 10% of the general population. Using this cutoff, about one-third of the patients in this study reported to suffer from low vitality. Because the proposed level of 50 mm on the BASDAI fatigue item seemed to capture nearly all patients with fatigue (sensitivity = 0.90), but also many without fatigue (specificity = 0.46) (Figure 2A and 2B), a more conservative cutoff should be considered. In an ROC curve analysis, we found an appropriate tradeoff between sensitivity and specificity (0.77 and 0.82, respectively) with a cutoff at 70 mm on the BASDAI fatigue item for classifying patients with low vitality. The use of this cutoff will avoid classifying too many false-positive individuals into a fatigue group.

Several factors have been suggested to cause or to associate with disease-related fatigue. Examples are bodily changes due to the disease processes itself, e.g., immunologic responses; drugs; or inability to get enough rest related to strong pain and disruptive sleep (29, 33). Fatigue can also be associated with deconditioning (11), and the presence of fatigue is one of the criteria of depression (39). Thus, fatigue is a multidimensional issue, and VASs provide information of only the patients' experienced level of disease-related fatigue. The vitality scale and the fatigue item had similar associations to other measures in multivariate analyses, and a substantial correlation to each other, suggesting that they measure similar constructs. Concomitant use of a domain-specific instrument would have provided additional information, but was not considered feasible due to the number of questionnaires to be completed by the patients in this study. Additional studies are needed to explore the different dimensions of fatigue. More specific information about fatigue might be important for the clinical management and for establishing valid outcome measures in clinical trials.

In the present sample, the demographic variables, the disease duration, and the measures of the self-reported disease severity are comparable with other studies (7, 17, 40, 41). In accordance with previous studies (6, 17), we applied a hospital register for identifying patients with AS. It may be questioned whether a sample based on a hospital register is representative for the patient group or if it includes those being most severely affected by disease. However, the clinical routine in Norway is that patients should have the diagnosis of AS confirmed by a rheumatologist. Thus, this patient cohort comprises both patients being seen by specialists and patients being seen by family physicians, indicating that the sample is representative. A possible shortcoming might be that all patients lived in a city area, but whether or how this may influence the results is unknown.

In this study, about one-third of the AS patients reported severe levels of fatigue. The phenomenon is associated with self-reported disease activity, physical functioning, and mental health, but not with objective clinical measures. The disease-specific BASDAI fatigue item reached an acceptable specificity and sensitivity with a cutoff at 70 mm. Further examinations of the different aspects of fatigue are needed to improve the accuracy of fatigue as an outcome measure in AS.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

We thank Petter Mowinckel, MSc, for expert statistical advice.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
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