Article Text
Abstract
Objectives To evaluate whether nephrotic syndrome (NS) and further corticosteroid (CS) use increase the risk of osteoporosis in Asian population during the period January 2000–December 2010.
Design Nationwide population-based retrospective cohort study.
Setting All healthcare facilities in Taiwan.
Participants A total of 28 772 individuals were enrolled.
Interventions 26 614 individuals with newly diagnosed NS between 2000 and 2010 were identified and included in out study. 26 614 individuals with no NS diagnosis prior to the index date were age matched as controls. Diagnosis of osteoporosis prior to the diagnosis of NS or the same index date was identified, age, sex and NS-associated comorbidities were adjusted.
Primary outcome measure To identify risk differences in developing osteoporosis among patients with a medical history of NS.
Results After adjusting for covariates, osteoporosis risk was found to be 3.279 times greater in the NS cohort than in the non-NS cohort, when measured over 11 years after NS diagnosis. Stratification revealed that age older than 18 years, congestive heart failure, hyperlipidaemia, chronic kidney disease, liver cirrhosis and NS-related disease including diabetes mellitus, hepatitis B infection, hepatitis C infection, lymphoma and hypothyroidism, increased the risk of osteoporosis in the NS cohort, compared with the non-NS cohort. Additionally, osteoporosis risk was significantly higher in NS patients with CS use (adjusted HR (aHR)=3.397). The risk of osteoporosis in NS patients was positively associated with risk of hip and vertebral fracture (aHR=2.130 and 2.268, respectively). A significant association exists between NS and subsequent risk for osteoporosis.
Conclusion NS patients, particularly those treated with CS, should be evaluated for subsequent risk of osteoporosis.
- case-control studies
- diabetic nephropathy & vascular disease
- diabetes & endocrinology
- nephrology
- bone diseases
Data availability statement
Data may be obtained from a third party and are not publicly available. All data and related metadata were deposited in an appropriate public repository. The data on the study population that were obtained from the NHIRD (http://w3.nhri.org.tw/nhird//date_01.html) are maintained in the NHIRD (http://nhird.nhri.org.tw/). The NHRI is a nonprofit foundation established by the government. The use of the data needs the assessment and agreement by NHRI.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Statistics from Altmetric.com
- case-control studies
- diabetic nephropathy & vascular disease
- diabetes & endocrinology
- nephrology
- bone diseases
STRENGTHS AND LIMITATIONS OF THIS STUDY
To our knowledge, this is the largest Asian population study to explore the impact of nephrotic syndrome (NS) on osteoporosis.
The main strength of this study is the large population-based dataset, which minimised the selection bias.
The most important limitation of this study is the characteristic of the database. Since it is a National Health Insurance Claims Database, detailed body mass index, dietary habits, laboratory data and histopathological changes involved in NS and bone densitometry results are unavailable for further stratification and analysis.
Supplementary calcium and vitamin D for the older group were not investigated.
Introduction
Nephrotic syndrome (NS) is defined on the basis of heavy proteinuria, accompanied by hypoalbuminaemia, hyperlipidaemia and oedema. The mechanism of NS can be idiopathic and comprise kidney disease such as minimal-change disease, membranous nephropathy and focal glomerulosclerosis. Secondary causes include systemic diseases such as diabetes mellitus (DM), systemic lupus erythematosus (SLE), amyloidosis, and cancers, drugs, and infections.1 2 The complications of NS are divided into two categories, namely: disease-associated and drug-related complications. Both the disease-associated and drug-related complications of NS could be susceptible to osteoporosis.3
Controversy remained as to whether people with NS have an increased risk of developing osteoporotic fractures. The reported prevalence ranges from 9% to 60% of osteoporosis among patients with NS.4–7 Some studies have elucidated that NS is correlated with increased risk of osteoporosis,6 and that the risk of osteoporosis also increases with increasing age,8 notwithstanding, others have not.9 It is unclear that the association between osteoporosis prevalence and NS progression.6 Data on the risk of osteoporosis in patients with NS and corticosteroids (CS) use are scarce.6 Therefore, this study used the National Health Insurance Research Database (NHIRD) to determine whether NS is a risk factor for osteoporosis and fracture. Further risk in NS patients and non-NS patients who do and do not use CS is additionally evaluated.
Material and methods
Patients and study design
The nationwide population study retrieved data from the 2000 to 2010 NHIRD which is a compulsory single-payer programme delineating practically 99.9% population of the country.
NHIRD contains inpatient and outpatient dataset regarding details of diagnoses based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, gender, prescriptions assigned at contracted pharmacies. Researchers can get relevant claims information with scrambled patient identification numbers. All methods were performed in accordance with the relevant guidelines and regulations.
Ethics statement
Patient consent was not required for us to access the NHIRD because of encrypted patient personal information system to protect patient privacy. Institutional Review Board of the Kaohsiung armed forces general hospital approved the study (KAFGHIRB 113-008).
Figure 1 depicts the details of study design and specific patient characteristics including inclusion and exclusion criteria. During 2000–2010, 26 614 patients who had been diagnosed with NS (ICD-9-CM code 581) during 2000–2010 were selected in our study. The cohort was confined to at least two NS diagnoses during ambulatory visits or patients who had received at least one NS diagnosis during an inpatient visit. Furthermore, the cohort was circumscribed to patients with ICD-9 codes assigned by a nephrologist with appropriate validation. To ensure the accuracy of the data, we only included cases if they received two osteoporosis diagnoses for ambulatory visits in outpatient clinics or one diagnosis in inpatient care and the ICD-9 code was assigned by orthopedists and receiving at least one BMD (bone mass density) examination were included in the osteoporotic group. The index date was selected as the date of the first clinical visit for NS. Exclusion criteria were as follows: diagnosis with NS before 2000, osteoporosis (ICD-9-CM code 733) before the index date, incomplete data and unknown gender. Stratification analysis employed with the ratio of NS to non-NS patients maintained at 1:4 according to age, sex and index date using the propensity score matching method to control covariates that produce selection bias. Using these criteria, 106 456 non-NS patients were identified.
The flow chart of study sample selection from National Health Insurance Research Database in Taiwan. ICD-9-CM 581. Osteoporosis: ICD-9-CM 733. ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification; NS, nephrotic syndrome.
Data collection and definition
The main outcome was a discharge diagnostic claim of osteoporosis (ICD-9-CM code 733) after at least one BMD examination and orthopedist validation. For each participant, follow-up duration was estimated from the index date of osteoporosis diagnosis of uncensored subjects and until date of health insurance policy termination (mostly due to death) or 31 December 2010 for those who were censored. Aside from analysis of baseline comorbidities, baseline sociodemographic characteristics, we also adjusted environmental factors according to urbanisation level and the use of CS. We defined a comorbidity of NS-related disease with ICD-9 codes. All the ICD codes of the comorbidities are as listed in online supplemental table S1.
Supplemental material
The urbanisation level of residence was characterised with population density, various indicators including political, economic, cultural and metropolitan development. Despite a specific designation of significant above mention condition, level 1 was defined as a population of more than 1 250 000. Level 2 was defined as a population between 500 000 and 1 249 999. Urbanisation levels 3 and 4 were defined as a population between 149 999 and 499 999, and <149 999, respectively.
Patient and public involvement
No patients or members of the public were directly involved in the study. Owing to the nature of this study and data privacy constraints, no patients or members of the public were involved in the study design, analysis, interpretation of data or revision of the manuscript.
Statistical analysis
We first compared distribution of age, sex, urbanisation, comorbidities and CS use between NS and non-NS cohorts, which were examined using χ2 test. We then calculated the incidence density of osteoporosis (per 105 person-years). NS versus non-NS incidence rate ratio of osteoporosis was examined. We used the univariate and multivariate Cox proportional hazards regression models with adjustment for age, sex, urbanisation, hypertension (HTN), DM, congestive heart failure (CHF), stroke, coronary artery disease, hyperlipidaemia, chronic kidney disease (CKD), liver cirrhosis (LC), obesity, chronic obstructive pulmonary disease (COPD), dementia, postmenopause, hyperparathyroidism, alcohol-attributed disease, NS-related disease (including hepatitis B virus (HBV), hepatitis C virus (HCV), HIV infection, syphilis, herpes zoster, IgA nephropathy, lymphoma, leukaemia, multiple myeloma, neoplasm, amyloidosis, sarcoidosis, SLE, rheumatoid arthritis (RA), Sjögren’s syndrome, hyperthyroidism, hypothyroidism and gestational proteinuria), medication including steroid use, relevant fractures(including hip, wrist, vertebral and rib fracture), season, city location, urbanisation and level of care to calculate HR with a 95% CI. Kaplan-Meier curves were used to calculate the cumulative proportion of osteoporosis incidence for both groups, and log-rank test was then employed to test differences between curves. We performed statistical analyses with SAS (V.9.3 for Windows), and a two-tailed p<0.05 was considered statistically significant.
Results
Figure 1 shows that the 28 772 patients enrolled between January 2000 and December 2010 as inclusion criteria. Osteoporosis was observed in 1299 of 26 614 NS patients and in 4094 of 106 456 non-NS patients.
Table 1 compares demographic characteristics and baseline comorbidities between the two cohorts. In the study cohorts, approximately 38% of patients were more than 60 years of age, 17% were 50–59 years and 55% were male; the age and sex proportions of the cohorts were similar.
Demographic characteristics and comorbidities in NS and non-NS cohorts
The following comorbidities were significantly more likely in the NS cohort than in the baseline non-NS cohort: HTN (32.12% vs 13.42%;p<0.001), DM (36.01% vs 10.99%; p<0.001), CHF (7.18% vs 2.08%; p<0.001), hyperlipidaemia (10.17% vs 2.15%; p<0.001), CKD (22.34% vs 3.66%; p<0.001), LC (2.22% vs 1.93%; p=0.001), obesity (0.12% vs 0.03%; p<0.001), HBV (1.98% vs 0.62%; p<0.001), HCV (1.45% vs 0.54%; p<0.001), syphilis (0.07% vs 0.03%; p=0.002), IgA nephropathy (1.10% vs 0.04%; p<0.001), leukaemia (0.33% vs 0.13%; p<0.001), multiple myeloma (0.26% vs 0.03%;p<0.001), amyloidosis (0.23% vs 0.01%; p<0.001), SLE (6.81% vs 0.09%; p<0.001), RA (0.33% vs 0.24%; p<0.001), Sjögren’s syndrome (0.32% vs 0.05%; p<0.001), hyperthyroidism (0.25% vs 0.15%; p<0.001), hypothyroidism (0.57% vs 0.11%; p<0.001) and gestational proteinuria(0.17% vs 0.00%; p<0.001). Steroid use was predominant in the NS cohort (23.75% vs 22.57%; p<0.001). The NS cohort compared with the non-NS cohort had both higher non-osteoporosis related fracture and osteoporosis-related fracture . The NS cohort had higher proportion of individuals diagnosed in winter (28.46% vs 27.25%; NS vs non-NS cohort; p<0.001), higher proportion of individuals living in northern Taiwan (44.06% vs 39.53%; NS vs non-NS cohort; p<0.001), a higher proportion of individuals living in higher urban areas (39.04% vs 33.66%; NS vs non-NS cohort; p<0.001) and a higher proportion of individuals diagnosed in medical centre (50.23% vs 33.34%; NS vs non-NS cohort; p<0.001).
Osteoporosis incidence and risk
The results revealed that NS cohorts had a 3.279 times (95% CI 3.054 to 3.520) higher risk to develop osteoporosis compared with non-NS cohorts with adjustments for age, sex and comorbidities. (table 2) During the follow-up period, 1299 patients in the NS cohorts (4.88%) and 4094 non-NS participants (3.84%) developed osteoporosis (table 3). Males in the NS cohort were at a lower risk for osteoporosis development than females in that cohort (adjusted HR (aHR) 0.727; 95% CI 0.688 to 0.768; p<0.001). Using age of less than 18 years as reference, the 18–29, 30–39, 40–49, 50–59 and ≥60 age groups had a higher risk of osteoporosis (aHR=4.974, 3.552, 5.839, 6.356 and 10.264, respectively). Additionally, compared with patients without comorbidities, we observed that the risk of osteoporosis was higher in patients who were postmenopausal (aHR 5.719; 95% CI 2.775 to 9.665; p<0.001), and who had alcohol-attributed disease (aHR 1.870; 95% CI 1.175 to 2.976; p=0.008), multiple myeloma (aHR 5.219; 95% CI 2.358 to 11.551; p<0.001), SLE (aHR 1.729; 95% CI 1.449 to 2.063; p<0.001), RA (aHR 2.538; 95% CI 2.027 to 3.178; p<0.001) and gestational proteinuria (aHR 2.344; 95% CI 2.011 to 2.731; p<0.001). Use of CS was associated with a higher risk of osteoporosis compared with non-use of CS (aHR 1.264; 95% CI 1.102 to 1.578; p=0.041). Osteoporosis was highly associated with hip and vertebral fracture (aHR 2.343; 95% CI 2.011 to 2.731; p<0.001 and 6.816; 95% CI 6.095 to 7.622; p<0.001, respectively).
Multivariable analysis for osteoporosis at the end of follow-up by using Cox regression
Factors of osteoporosis at the end of the follow-up period stratified by Cox regression
Figure 2 shows the Kaplan-Meier curve for the cumulative incidence of osteoporosis between the NS cohort and non-NS cohort after 11 years of follow-up (log rank test; p<0.001). The 1-year, 5-year and 11-year actuarial rates of osteoporosis were 1.73%, 4.10% and 4.88% in the NS cohort and 0.88%, 2.62% and 3.84% in the non-NS cohort, respectively. Figure 2B shows the Kaplan-Meier for cumulative risk of osteoporosis over time stratified by NS and CS.
(A) Kaplan-Meier for cumulative risk of osteoporosis over stratified by NS with log-rank test. (B) Cumulative risk of osteoporosis over time stratified by NS and CS. CS, corticosteroid; NS, nephrotic syndrome.
After stratification, the risk of osteoporosis notably increased independent of age status, except in patients younger than 18 years (aHR was highest in the 30–39 years group and lowest in the ≧60 years group). The risk of osteoporosis also increased independent of CHF, hyperlipidaemia, CKD, LC. We further evaluated the risk of osteoporosis stratified by NS aetiology subtypes. A significantly higher risk of osteoporosis was observed in patients with DM, HBV, HCV, lymphoma and hypothyroidism. Additionally, osteoporosis risk was significantly higher in NS patients with CS use (aHR=3.397). The risk of osteoporosis in NS patients was positively associated with risk of hip and vertebral fracture (aHR=2.130 and 2.268, respectively) (table 3).
In table 3, we observed that the osteoporosis risk was not increased in our paediatric NS cohort (aged younger than 18 years) after stratification. We further evaluated the role of CS in paediatric NS (aged younger than 18 years), using non-NS and non-CS as a reference, and found that use of CS significantly increased the risk of osteoporosis in both the NS cohort (aHR 1.478; 95% CI 1.009 to 1.803; p=0.042) and the non-NS cohort (aHR 1.315; 95% CI 1.001 to 1.698; p=0.049) (figure 3A). The role of CS in aged older than 18 years also is shown in figure 3B.
(A) Forest plot of risk of osteoporosis stratified by NS and steroid aged less than 18. Adjusted HR: adjusted variables listed in table 3. (B) Forest plot of risk of osteoporosis stratified by NS and steroid aged more than 18. Adjusted HR: adjusted variables listed in table 3. NS, nephrotic syndrome.
Discussion
NS was associated with a 3.279-fold increase in the risk of osteoporosis, compared with a non-NS cohort after adjusting for a number of potentially confounding factors. The results of this study are compatible with those of previous studies in relation to the female predominance of osteoporosis (53.19%), but the proportion of the NS cohort in this study that progressed to osteoporosis (4.88% over the 11 years of follow-up) was lower compared with the proportions reported by previous studies.4–7 Patients with NS often demonstrate a number of calcium homoeostasis disturbances that attributed to abnormal bone histology, including hypocalcaemia, impaired intestinal absorption of calcium, reduced serum vitamin D metabolites such as 25-hydroxyvitamin D (25(OH)D), 1,25-dihydroxyvitamin D (1,25(OH)2D) and elevated levels of immunoreactive parathyroid hormone (PTH).
Loss of a variety of plasma proteins (vitamin D—binding protein) and minerals in the urine, as well as steroid therapy can have great impact on bone integrity.8–10
In a prospective study with 30 NS and 30 control patients conducted by Mohamed et al, compared with the control patients, the NS patients demonstrated a significantly lower level of serum OPG (osteoprotegerin) and parameters of bone formation (alkaline phosphatase and osteocalcin), conversely, a significantly higher 24-hour urinary Ca.11 The bone lesions in these patients can be attributed to vitamin D deficiency and elevated blood levels of PTH.
In the NS cohort, we observed that individuals at age older than 18 years, and especially within the 30–39 years group, had the highest risk of osteoporosis after stratification. The mean onset of osteoporosis in this age group is range from 0.98 to 8.93 years. There are two kinds of juvenile osteoporosis: secondary and idiopathic. Secondary juvenile osteoporosis is usually associated with underlying medical condition, medications used to treat the condition, or certain behaviours related to diet and exercise and idiopathic juvenile osteoporosis should be considered in rare circumstanced caused by unknown reason.12 In a prospective study by Gulati et al, the authors observed that only about 22% of children with idiopathic NS developed osteoporosis.6 The authors also concluded older age at onset, lower total calcium intake (p<0.0001) and greater cumulative steroid dose were the main predictive factor for a low BMD (p<0.0001), (p=0.005). A study by Hegarty et al found that adult survivors of childhood minimal change NS have significantly reduced forearm trabecular volumetric BMD, placing them at increased fracture risk at this site, indicating a delayed effect of osteoporosis in NS cohorts.8 In addition, because in the NHIRD we use BMD to define osteoporosis, which may be less accurate than bone mineral content measurements, especially in children, this could have led to an underestimation of the number of patients in the NS cohort who progressed to osteoporosis.11
Many epidemiological studies show a positive connection between hyperlipidaemia and risk of osteoporosis. The majority of the studies indicated a correlation between high cholesterol and high low-density lipoprotein (LDL-cholestrol level with low bone mineral density, a strong predictor of osteoporosis. Hyperlipidaemia increases the risk for generation of lipid oxidation products, which accumulate in the subendothelial spaces of vasculature and bone.13 Animal studies showed that hyperlipidaemia induces secondary hyperparathyroidism and impairs bone regeneration and mechanical strength.14 In addition, high cholesterol diet increases the risk of osteoporosis, possible via inhibiting the differentiation and proliferation of osteoblasts.15
DM is often associated with low levels of insulin, higher glucose levels with higher advanced glycation end-products which precipitate in collagen leading to reduce bone strength. The indirect effect of glycosuria with hypercalciuria leads to decreased levels of calcium in the body and poor bone quality, which hastens bone loss.16
Inflammatory cytokines such as interleukin-1, interleukin-6 and tumour necrosis factor-alpha induced by chronic HBV infection which increase receptor activator of nuclear factor kappa-B ligand (RANKL) to stimulate osteoclast formation and bone resorption. In addition, tumour necrosis factor-alpha can inhibit osteoblast differentiation and promote osteoblast apoptosis. Chronic HCV infection can also induce interleukin-6, which activates osteoclast to increase bone resorption. The combined effects of the aforementioned inflammatory cytokines can eventuate in coupling of decreased bone formation and increased bone resorption to diminish the BMD.17 18 Although the relationship between lymphoma and osteoporosis is unclear, osteopenia and osteoporosis in untreated Non-Hodgkin lymphoma (NHL) patients are regarded as a common finding.19 Mild hypothyroidism is usually observed in NS patients, and results from losses of T4, free T4, T3, free T3 and thyroxine binding globulin into the urine.20 It is proposed that hypothyroidism is correlated with increased risk of fractures with unknown mechanism. Hypothyroidism causes general hypometabolism, with subsequent lowering of bone formation and resorption. The subsequent reduced calciuria may lead to decreased serum osteocalcin and alkaline phosphatase, with elevated PTH, which may be a proposed mechanism for osteoporosis.21 In our study, we observed a prominent deleterious effect of CS on osteoporosis (aHR 3.397; 95% CI 3.101 to 3.623; p<0.001).
It is reported that after 12 months’ use of more than 7.5 mg/day of prednisone can lead to trabecular bone loss.22 Glucocorticoid-induced osteoporosis is caused by decreased bone formation and increased bone resorption through the coupling of bone resorption, gastrointestinal calcium absorption and renal tubule excretion imbalance.23 In NS, CS has been reported to disturb the function of osteoblasts by decreasing the expression of RANKL soluble decoy receptor OPG, and in contrast, activate the osteoclast by increasing the expression of macrophage colony stimulating factor (M-CSF) and RANKL.11 23 24
Several studies identified risk of increased risk of vertebral fracture and hip fracture in NS due to steroid use. Studies in adults have demonstrated that glucocorticoids cause rapid, dose-dependent bone loss and an increased risk of fracture.25–27 In addition, trabecular bone is more susceptible than cortical bone to the effects of glucocorticoids. Both vertebrae and femoral neck are mainly composed of trabecular bone which could be the explain of our results compared with rib and wrist bone fracture.28
There are several limitations to the present study despite the strength of this cohort study which comprise a large number of Asian patients. First, some adaptable risk factors such as body mass index, dietary habits and family history are not available in NHIRD. Supplementary calcium and vitamin D for the older group was not investigated. Laboratory results such as urine protein level, serum lipid and serum albumin are lacking. Histopathological changes involved in NS, specifically minimal change disease, membranous nephropathy and focal segmental glomerulosclerosis results are not accessible. Second, bone densitometry results were unavailable thus put validating the diagnosed of osteoporosis in a difficult situation. Nevertheless, diagnostic accuracy was strengthened by limiting the study population to patients with at last one BMD examination and medical care for osteoporosis for more than two separate visits. There are two common methods for testing BMD. One is quantitative ultrasound that measures the BMD in ankle, wrist or finger. The other method is using low-dose bone densitometry (Dual-Energy X-ray Absorptiometry (DEXA)) X-ray for spine or femur. Those physicians who enter the ICD-9 codes of osteoporosis were request to enter accurately subject according to BMD results because of big fines for incorrect entries. Finally, potential biases related to adjustment for confounding variables existed and resulted in a lower quality of statistical analysis of data derived from a retrospective cohort study.
Conclusions
NS patients are at high risk of osteoporosis. Prominent deleterious effect of CS on osteoporosis was observed even in paediatric NS cohort (aged younger than 18 years). Early identification of the NS related disease may alert clinical physician about the possible susceptible osteoporosis. Nevertheless, more precise large scale randomised control study needed to carry out to support the findings.
Data availability statement
Data may be obtained from a third party and are not publicly available. All data and related metadata were deposited in an appropriate public repository. The data on the study population that were obtained from the NHIRD (http://w3.nhri.org.tw/nhird//date_01.html) are maintained in the NHIRD (http://nhird.nhri.org.tw/). The NHRI is a nonprofit foundation established by the government. The use of the data needs the assessment and agreement by NHRI.
Ethics statements
Patient consent for publication
Ethics approval
Institutional Review Board of the Kaohsiung armed forces general hospital approved the study. (KAFGHIRB 113-008).
Acknowledgments
The authors would like to thank Enago and Editage for providing editing service of the manuscript including content, language, grammar and structure.
References
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
X @Chen-Yi Liao, @Min-Feng Tseng
Contributors C-YL had full access to all of the data in the study and took responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: C-YL, C-HC and W-CC. Acquisition, analysis and interpretation of data: K-YW, M-FT and F-HL. Drafting of the manuscript: C-YL. Critical revision of the manuscript for important intellectual content: C-YL, W-CC and C-CW. Statistical analysis: C-HC. Administrative, technical or material support: C-YL. Study supervision: C-HT. Substantial contributions to the conception or design of the work and/or to acquisition, analysis or interpretation of data for the work: C-YL, C-HC and PC. Drafting the work or revising it critically for important intellectual content: C-HC, W-CC and C-CW. Final approval of the version to be published: C-YL, C-CW and PC. Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved: C-YL, C-HC and W-CC. C-YL is responsibe for the overall content as the guarantor.
Funding From Ministry of Science and Technology MOST110-2314-B-016-014 and Tri-Service General Hospital TSGH-C04-111035.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.