Effect of cholecalciferol supplementation on CVD, inflammation and bone metabolism markers in CKD: results of feasibility phase of randomized double blind controlled placebo trial

Effect of cholecalciferol supplementation on CVD, inflammation and bone metabolism markers in CKD: results of feasibility phase of randomized double blind controlled placebo trial | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effect of cholecalciferol supplementation on CVD, inflammation and bone metabolism markers in CKD: results of feasibility phase of randomized double blind controlled placebo trial Kajal Kamboj, Karthikeyan Manoharan, Shubham Sharma, Himanshi Khera, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5276044/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Vitamin D deficiency is common in chronic kidney disease (CKD) and associated with cardiovascular disease (CVD) and bone mineral metabolism. Despite short term favourable effects, long term impact of cholecalciferol supplementation is unknown. We tested the effects of cholecalciferol supplementation on CVD outcome [major adverse cardiovascular events (MACE)], progression of CKD and markers of bone-mineral metabolism and inflammation in patients with pre-dialysis CKD. Methods: The study was a single centre, prospective, randomized (1:1), placebo controlled, double blind clinical trial. Inclusion criteria were ages between 18-75 years, estimated glomerular filtration rate 10-45 ml/min/1.73m 2 , serum 25(OH)D levels 20-50 ng/ml and clinically stable course for last 3 months. After 2 weeks run-in phase, participants received either cholecalciferol 60000 IU once/2 weeks or matching placebo and followed up at every 3 months till 36 months after enrolment. All clinical, demographic characters and biomarkers were analysed at baseline and annual follow up. Results: 692 participants were screened, out of which 126 were enrolled. However, 37 participants dropped out before randomization on account of COVID-19 related lockdowns or other reasons. The pilot phase was stopped in April 2023. Follow up course of 89 participants were available till that time: 46 participants were in the cholecalciferol group whereas 43 were in the placebo group. Both the groups were similar with respect to MACE events, need of renal replacement therapy and all-cause mortality. Over one year, serum 25 (OH)D increased in the cholecalciferol group [Mean diff between groups: 31.89, 95% CI: 20.46 to 43.32, P<0.001]. Serum calcium increased whereas C-reactive protein and bone specific alkaline phosphatase levels decreased in the cholecalciferol group. Conclusions: Cholecalciferol treatment did not affect CVD outcome or progression of CKD in vitamin D insufficient patients with stage G3-G4 CKD, however it favourably affected markers of inflammation and bone metabolism in these patients. Trial Registration: The trial was prospectively registered at the Clinical Trials Registry of India (www.ctri.nic.in, trial registration number CTRI/2019/05/019211 dated 20 May 2019). CKD CVD vitamin D deficiency cholecalciferol inflammation biomarkers Figures Figure 1 Introduction Cardiovascular disease (CVD) is a global health concern that caused 20.5 million deaths in 2021, with a surge of about 60% globally over the last 30 years [ 1 ]. As compared to individuals with normal renal function, the risk of cardiovascular mortality is two and three times increased in patients with chronic kidney disease (CKD) stages G3 and 4, respectively [ 2 , 3 ]. In 2021, 1.87 million cardiovascular deaths and 3.47 million overall deaths were attributable to reduced kidney function [ 4 ]. Vitamin D deficiency have been linked with CVD and mortality in both general population and in individuals with CKD. In CKD, the targets of vitamin D supplementation is correcting its deficiency, enhancing mineral balance along with reducing the risk and progression of secondary hyperparathyroidism (SHPT). Vitamin D derivatives or its analogs in the treatment of CKD have focused on biochemical markers [25(OH)D3, or 1,25(OH)2D3 levels, parathyroid hormone (PTH), calcium, phosphorus, and intermediate outcomes (vascular calcifications, bone density and histology) and major clinical end points (CVD, mortality etc.). Based on evidence from observational studies suggesting association of vitamin D deficiency with CVD associated mortality in CKD, impact of vitamin D supplementation on surrogate endpoints for CVD in pre-dialysis CKD has been investigated in a number of randomized controlled trials (RCTs) in the recent past [ 5 – 11 ]. Overall, the findings from these clinical trials suggest that supplementation with vitamin D favorably modify endothelial and vascular function in CKD. Recently, we have also shown improvement in endothelial function and vascular stiffness, which are surrogates of future CVD, and markers of inflammation and bone metabolism with cholecalciferol supplementation in a RCT in patients with stage G3-4 CKD [ 7 , 12 ]. This study showed that cholecalciferol supplementation significantly decreased the circulating interleukin-6 (IL-6), serum C-terminal cross-linked collagen type I telopeptides (CTX-1), serum total and bone-specific alkaline phosphatase (SAP, BAP)[ 12 ]. Kidney Disease Improving Global Outcomes (KDIGO) has recommended BAP as a bone biomarker for the diagnosis and management of renal osteodystrophy [ 13 ]. Also, it has been shown to be an effective indicator for distinguishing low bone turnover [ 14 ]. In CKD, the impact of native vitamin D forms (cholecalciferol) might be mediated through conversion to 1,25(OH) 2 D but limited data suggest that different effector mechanisms might be present that can be inferred from our work suggesting opposing effects on fibroblast growth factor 23 (FGF-23) when compared to calcitriol [ 15 ]. The native forms might be important for paracrine and autocrine effects, and higher circulating levels might be required for extra-skeletal effects including favorable modulation of vascular function and inflammatory state [ 16 ]. In fact, the lack of favorable effects of vitamin D supplementation on extra-skeletal effects in studies could also be due to the fact that majority of clinical trials were never designed to look at extra- skeletal effects as primary outcome parameters[ 17 ]. These data suggest that cholecalciferol supplementation targeted to higher circulating vitamin D levels would be the most appropriate intervention when extra-skeletal effect like modulation of vascular function is the primary endpoint of clinical trial. In this feasibility study, we evaluated the effect of cholecalciferol supplementation on CVD, inflammation and bone metabolism markers in CKD in a randomized double-blind placebo-controlled trial. Materials and Methods Study design: The study was a feasibility phase clinical trial conducted at the Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India. It was a single center, prospective, randomized, placebo controlled, double blind clinical trial. The trial was prospectively registered at the Clinical Trials Registry of India ( www.ctri.nic.in , trial registration number CTRI/2019/05/019211 dated 20 May 2019). The study was approved by the Institute Ethics Committee of PGIMER, Chandigarh. Study Population: Adult patients (≥ 18 years) with pre-dialysis CKD [as defined KDIGO; CKD definition] who were attending the outpatient clinic in the Department of Nephrology were screened. Inclusion criteria were ages between18-75 years, estimated glomerular filtration rate (eGFR) ranging from 10–45 ml/min/1.73m 2 by creatinine based Chronic Kidney Disease -Epidemiology Collaboration (CKD-EPI) Eq. 2009, serum 25-hydroxy vitamin D [25(OH)D] levels 20–50 ng/ml and clinically stable course for last 3 months. Exclusion criteria were patients receiving long-term maintenance dialysis or immunosuppressive therapy, those with diagnosis of chronic liver disease, primary hyperparathyroidism, sarcoidosis, malignancy, history of having been treated for hypercalcemia due to any cause, anticipated need of long-term kidney replacement therapy within 6 months, poor functional status, life expectancy < 1 year, pregnancy in case of females, blood hemoglobin 9.5 mg/dL, history of having received any type of organ transplant, history of allergy to the interventional drug (cholecalciferol), having received vitamin D supplementation in last 30 days or participation in another interventional clinical trial. Patients satisfying all of the inclusion criteria and none of the exclusion criteria were enrolled after informed consent. Enrolment, randomization and intervention: At enrolment, all participants entered a run-in phase of 2 weeks. At the end of run-in phase, they were randomized in 1:1 ratio. An adaptive allocation algorithm based on OxMaR. [ 18 ] was used to minimize imbalance across treatment groups in the stage of CKD and presence of diabetes. The treatment boxes were neutrally coded and centrally masked. The boxes were identical, sequentially numbered, sealed and traceable. The allocation sequence was concealed from participants, investigators, and outcome assessors. Participants received either cholecalciferol 60000 IU once/2 weeks or matching placebo. Follow up: Follow up visits were scheduled at 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33 and 36 months after enrolment. Serum levels of 25(OH)D, calcium, and intact parathyroid hormone (iPTH) were assessed at every scheduled follow up visit. Cholecalciferol/placebo intervention were stopped at follow up if serum 25(OH)D were > 70 ng/ml or serum calcium were > 10 mg/dL. It was re-started on subsequent follow up visit when serum 25(OH)D levels was ≤50 ng/ml and serum calcium was ≤9.5 mg/dL. 10 ml each of fasting blood and second morning urine samples were collected and stored at -80 o C at baseline and annually thereafter. This was required for measurement of biomarkers as outlined in secondary objectives. During any acute clinical event or hospitalization, the treating physicians could withdraw study interventions at their discretion. The decision to start interventions again after recovery or discharge was also at the sole discretion of treating physician. The study intervention was permanently withdrawn in an index participant under these circumstances: Suspicion of drug related hypersensitivity after administration, new diagnosis of malignancy, pregnancy in case of female participant, participant’s or physician’s request for the same or drug related adverse event necessitating hospitalization. The concurrent clinical care continued as per prevailing standards of care. Any adverse reaction that resulted in death, was life-threatening, required hospitalisation or prolongation of existing hospitalisation, resulted in persistent or significant disability or incapacity was treated as serious adverse event. Treatment of secondary hyperparathyroidism and/or vitamin D deficiency were allowed with use of activated forms of vitamin D (e.g. calcitriol) as felt necessary by treating physician. Use of native forms of vitamin D (cholecalciferol or ergocalciferol) was forbidden. Compliance to the study drug was checked by comparing the actual number of tablets taken by a participant with the total number of tablets should have been taken by a participant over the study duration. Objectives and outcomes: Primary outcome measures were a composite of major adverse cardiac events (MACE) that included new onset heart failure, CAD, PVD, cerebrovascular accident (transient ischemic attack or stroke), any coronary or peripheral arterial revascularization procedure and death due to CVD. Secondary outcome measures were: all-cause mortality, need for renal replacement therapy (RRT), change in high sensitivity C-reactive protein (hsCRP), Interleukin-6 (IL-6), intact parathyroid hormone (iPTH), fibroblast growth factor-23 (FGF-23), bone specific alkaline phosphatase (BAP), and C-terminal telopeptide (CTX-1). Measurements: All measurements were done in fasting blood samples. Serum levels of 25(OH)D and iPTH were analyzed using Cobas ® 8000 modular analyzer (Roche Diagnostics, Mannheim, Germany). All biochemical investigations were done using Cobas ® c702 auto-analyzer (Roche Diagnostic Limited, Rotkreuz, Switzerland). Serum IL-6 (Quantikine soild phase sandwich ELISA; R&D Systems ® , Minneapolis, MN, USA), serum hs-CRP (Calbiotech Inc., CA, USA), human plasma FGF-23 (Immutopics, Inc., Athens, Ohio), serum BAP (MicroVue ™ BAP EIA; Quidel Corporation San Diego, CA, USA), serum CTX-1 [Serum Crosslaps ® (CTX-1) ELISA; IDS, Boldon, UK] were measured in stored samples at baseline and 12 months follow up. Statistical analysis: There was no formal sample size calculation for the feasibility phase of the study. We planned to enroll at least 125 participants. All participants with non-missing outcome data were included in the analysis. Descriptive statistics were used to describe characteristics of study participants. Categorical data were presented as frequencies and continuous variables were presented as mean ± SD or median (IQ range) as appropriate. Continuous variables were compared by independent sample t test if normally distributed, or Mann-Whitney U test if distribution were skewed. Categorical variables were analyzed by Chi-squared test or Fisher exact test as appropriate. Hemoglobin, calcium, phosphorus, creatinine, eGFR, alkaline phosphatase and other biomarker measurements were reported and compared between groups at baseline and 12 months. Other outcome data were reported descriptively for the study duration completed by participants. Results A total of 692 patients were screened between August 2019 to October 2021, out of which 126 were enrolled. 32 enrolled participants dropped out before randomization on account of COVID-19 related lockdowns and restrictions and other reasons. 89 participants were randomized till end of October 2021 (Fig. 1 ). The following data analysis pertains to baseline measurements of 89 participants and follow up comparative measurements of 80 participants who have completed one year of follow up. Baseline characteristics: Till October 2021, 89 participants were randomized. 46 participants were in the cholecalciferol group whereas 43 were in the placebo group. Table 1 shows the baseline characteristics of study population. Mean age of the overall participants was 50.84±12.68 years with 38% being female. At baseline, the cholecalciferol and placebo groups were similar with respect to demographic characteristics, distribution of causes of CKD, risk factors, presence of CVD and use of medications. Similarly, there were no significant differences between the two groups with respect to baseline biochemical and biomarker measurements (Table 2 ). eGFR, serum 25(OH)D and iPTH levels were similar between the groups at baseline (Table 2 ). Table 1 Baseline characteristics of study population Characteristic or parameter Cholecalciferol group (n = 46) Placebo group (n = 43) Male 30 (65.2) 24(55.8) Female 16 (34.8) 19 (44.2) Age (years) 50.4± 12.4 50.74±12.73 BMI (kg/m 2 ) 24.4 ± 5.6 26.5±4.6 Waist/Hip ratio 0.9 (0.9 ,1.0) 0.9 (0.9, 1.0) SBP (mmHg) 144.0± 22.9 135.7±22.6 DBP (mmHg) 89± 12.2 83.7±15.5 Duration of kidney disease (months) 44 (22, 80) 60 (30.8, 87.8) Cause of CKD Diabetic kidney disease 8 (17.4) 6 (14) Chronic interstitial nephritis 16 (34.8) 12 (27.9) CAKUT 1(2.2) 1 (2.3) Unknown kidney disease 12(26.1) 15 (34.9) PKD 4 (8.7) 2 (4.7) Biopsy proven GN 1 (2.2) 3 (7) Other kidney diseases 4 (8.7) 4 (9.3) Presence/history of Hypertension 43 (93.5) 36 (83.7) Diabetes mellitus 12 (23.9) 10 (23.3) Renal stone disease 11(23.9) 4 (9.3) CAD 2 (4.3) 4 (9.3) PVD 0 1 (2.3) CVA 0 0 Any other form of atherosclerotic vascular disease 0 0 Coronary angiography 3 (6.5) 4 (9.3) Heart failure 0 1 (2.3) Medications use ACE inhibitor/ARB 15 (32.6) 18 (41.9) Statin 23 (50) 30 (69.8) Beta blocker 21 (45.7) 24 (55.8) SGLT-2 inhibitor 40 (87) 37 (86) Nitrates 1 (2.2) 1 (2.3) Hypouricemic drugs 6 (13) 8 (18.6) Bicarbonates 37 (80.4) 31 (72.1) Erythropoietin 3 (6.5) 4 (9.3) Antiplatelet (Aspirin/Clopidogrel) 7 (15.2) 8 (18.6) Data presented as mean ± standard deviation, median (25th -75th percentile) or frequency (percentage) as appropriate. ACE: angiotensin-converting enzyme, ARB: angiotensin II receptor blocker, BMI: body mass index, CAD: coronary artery disease, CAKUT: congenital anomalies of kidney and urinary tract, CKD: chronic kidney disease, CVA: cerebrovascular accident, DBP: diastolic blood pressure, GN: glomerulonephritis, PKD: polycystic kidney disease, PVD: peripheral vascular disease, SBP: systolic blood pressure, SGLT-2: sodium-glucose cotransporter-2. Table 2 Baseline investigations and biomarkers in the study population Characteristic or parameter Cholecalciferol group (n = 46) Placebo group (n = 43) Hemoglobin (g/dL) 11.52 ± 1.96 11.87 ± 1.64 Serum creatinine (mg/dL) 2.97 ± 1.11 2.66 ± 1.18 eGFR (CKD-EPI Cr 2009) 22.58(15.51, 33.58) 29.56 (18.89, 36.62) Blood urea (mg/dL) 76.00 (49.53, 103.10) 63.00(51.20, 95.10) Serum calcium (mg/dL) 9.20 (8.69, 9.37) 9.23 (8.95, 9.45) Serum inorganic phosphorous (mg/dL) 3.77 (3.16, 4.09) 3.83 (3.20, 4.22) Serum uric acid (mg/dL) 7.10 (6.15, 8.30) 7.20 (5.80, 8.95) Serum alkaline phosphatase (U/L) 92.00 (77.00, 116.00) 101.50 (83.50, 116.50) Serum total cholesterol (mg/dL) 148.95 (120.30 ,165.35) 140.30 (118.90,159.15) Serum triglycerides (mg/dL) 136.40 (104.18, 169.75) 126.30 (98.45, 171.30) Serum LDL-C (mg/dL) 83.45 (62.28, 105.15) 75.50 (56.00, 97.40) Serum HDL-C (mg/dL) 42.65 (37.28, 51.65) 42.20 (37.25, 50.90) Serum iPTH (pg/mL) 192.00 (125.00, 321.75) 166.80 (81.48, 317.63) Serum 25(OH)D (ng/mL) 29.40 (24.29, 39.97) 28.51 (22.75, 38.03) Spot urine protein/creatinine ratio (mg/g) 739.90 (303.10, 2141.93) 1012.36 (302.33, 1679.57) Serum BAP (U/L) 27.56 (21.04, 37.40) 29.41 (23.53, 42.98) Serum intact FGF-23 (pg/mL) 131.03 (30.02, 143.96) 131.03 (34.91, 143.96) Serum CRP (ng/mL) 4.06 (1.94 ,7.26) 2.20 (1.22, 6.80) Serum IL-6 (pg/mL) 5.40 (3.50, 10.40) 4.88(2.47, 10.57) Serum CTX (ng/mL) 1.41 (0.81, 2.14) 1.52 (0.84, 2.07) Data presented as mean ± standard deviation or median (25th -75th percentile) as appropriate. 25(OH)D: 25-hydroxyvitamin D3, BAP: bone alkaline phosphatase, CRP: C-reactive protein, CTX: carboxy terminal telopeptide, eGFR: estimated glomerular filtration rate, FGF-23: fibroblast growth factor-23, HDL-C: high density lipoprotein cholesterol, iPTH: intact parathyroid hormone, IL-6: interleukin-6, LDL-C: low density lipoprotein cholesterol. Outcome parameters: Table 3 represents the outcome parameters of the study groups. Total of 23 adverse events were recorded in cholecalciferol group and 31 adverse events were recorded in placebo group. Out of which 9 and 10 participants reported serious adverse events in cholecalciferol and placebo group respectively. One participant in placebo group was reported for CVA. Seven participants in cholecalciferol group reached the end stage renal disease (ESRD)/ need of renal replacement therapy (RRT) while eleven participants in placebo group reached ESRD. In addition to this, four deaths in each group were recorded. These were reported to Clinical Trials Data Safety Board at PGIMER and finally, concluded to be unrelated to study intervention. Table 3 Outcome parameters in the study population till last follow up visit Parameter Cholecalciferol (n = 46) Placebo (n = 43) Duration of follow up (months) 27 (15, 36) 30 (21, 36) Number of total adverse events records 23 31 Total number of patients who experienced at least one adverse event 15 17 Serious Adverse Events 9 10 Number of patients who experienced SAE at least once 7 9 Total number of hospitalizations 9 10 Total number of patients who experienced at least one hospitalization 7 9 MACE New onset heart failure 0 0 CAD 0 0 PVD 0 0 CVA 0 1 Any coronary or peripheral arterial revascularization procedure 0 0 Death due to CVD 0 0 Need for RRT 7 11 Time to start of RRT (months) 16 (11, 27 19 (11, 24) Composite of 40% decline in GFR or need for RRT 17 18 Overall Mortality 4 4 Composite of all-cause death and non-fatal MACE 4 5 Data presented as number or median (25th -75th percentile) as appropriate CAD: coronary artery disease, CVA: cerebrovascular accident, CVD: cardiovascular disease, MACE: major adverse cardiovascular event, GFR: glomerular filtration rate, PVD: peripheral vascular disease, RRT: renal replacement therapy, SAE: serious adverse events Biochemical and biomarkers at follow up: The biochemical and biomarker characteristics of these participants were compared at annual follow up visit. Table 4 shows the within group and between group differences with respect to biochemical and biomarker characteristics. Table 4 Within group and between group differences in biochemical and biomarker measurements at 12 months in the study population who completed at least one year follow up Parameters Cholecalciferol (n = Mean difference (95%CI) P value N (number of patients) Placebo Mean difference (95% CI) P value N (number of patients) Between group difference P value Serum 25(OH)D (ng/mL) 31.15 (21.37 to 40.92) < 0.001 31 -0.75 (-7.43 to 5.94) 0.510 34 31.89 (20.46 to 43.32) < 0.001 Serum iPTH (pg/mL) 35.51 (-24.19 to 95.94) 0.329 30 58.39 (-17.92 to 134.69) 0.081 33 -22.87 (-119.56 to 73.81) 0.660 Hemoglobin (g/dL) -0.21 (-0.89 to 0.48) 0.642 34 -0.37 (-0.75 to 0.020) 0.07 35 0.160 (-0.61 to 0.93) 0.442 Serum Cr (mg/dL) 0.46 (0.12 to 0.81) 0.029 34 0.44 (0.071 to 0.81) 0.010 35 0.022 (-0.47 to 0.52) 0.871 eGFR (CKD-EPIcr) -1.72 (-3.80 to 0.37) 0.07 34 -2.54 (-4.71 to -0.38) 0.021 35 0.82 (-2.13 to 3.78) 0.848 Serum calcium (mg/dL) 0.72 (-0.14 to 0.29) 0.817 34 -0.49 (-0.82 to -0.15) 0.001 33 0.558 (0.17 to 0.95) 0.024 Serum inorganic phosphorous (mg/dL) 0.80 (0.006 to 1.59) 0.010 34 0.29 (-0.088 to 0.658) 0.238 33 0.517 (-0.35 to 1.39) 0.270 Serum alkaline phosphatase (U/L) 8.26 (-12.11 to 28.62) 0.648 27 15.28 (1.19 to 29.37) 0.023 25 -7.02 (-31.56 to 17.52) 0.197 UPCR (mg/g) 215.11 (-878.61 to 1308.83 0.690 28 -49.12 (-523.19 to 425.67) 0.264 25 264.23 (-950.39 to 1478.85) 0.664 Serum IL-6 (pg/mL) -0.244 (-22.75 to 22.26) 0.694 35 -4.56 (-14.69 to 5.57) 0.081 39 4.315 (-19.08 to 27.72) 0.221 Serum intact FGF-23 (pg/mL) 101.74 (21.72 to 181.76) 0.001 35 82.08 (15.74 to 148.43) 0.015 39 19.66 (-81.75 to 121.06) 0.335 Serum CRP (ng/mL) -0.105 (-1.65 to 1.44) 0.909 35 1.86 (0.51 to 3.23) 0.004 39 -1.97 (-3.99 to 0.04) 0.042 Serum CTX (ng/mL) -0.395 (-0.68 to -0.112) 0.020 35 -0.185 (-0.53 to 0.16) 0.288 39 -0.215 (-0.655 to 0.23) 0.452 Serum BAP (U/L) -4.61 (-9.90 to 0.68) 0.074 35 0.471 (-5.25 to 6.20) 0.085 39 -5.08 (-12.80 to 2.64) 0.019 Data presented as mean difference (95% confidence interval). 25(OH)D: 25-hydroxyvitamin D3, BAP: bone alkaline phosphatase, CRP: C-reactive protein, CTX: carboxy terminal telopeptide, eGFR: estimated glomerular filtration rate, FGF-23: fibroblast growth factor-23, iPTH: intact parathyroid hormone, IL-6: interleukin-6, UPCR: urine protein creatinine ratio Cholecalciferol group: Serum 25(OH)D and inorganic phosphorous (Pi) levels significantly increased at annual follow up in the cholecalciferol group [25 (OH) vitamin D, Mean diff: 31.15 (95% CI: 21.37 to 40.92), P < 0.001; Pi, Mean diff: 0.80 (95% CI: 0.006 to 1.59), P = 0.010]. (Table 4 ). Cholecalciferol group also showed a significant increase in serum creatinine levels at follow up [Mean diff: 0.46 (95% CI: 0.12 to 0.81), P = 0.029]. Serum intact fibroblast growth factor-23 (FGF-23) significantly increased in the cholecalciferol group [Mean diff: 101.74 (95% CI: 21.72 to 181.76), P = 0.001]. Serum CTX levels significantly decreased in cholecalciferol group [Mean diff: -0.395 (95% CI: -0.68 to -0.112), P = 0.020] at 12 months follow up. Placebo group: Serum creatinine levels significantly increased in the placebo group [Mean diff: 0.44 (95%CI: 0.071 to 0.81), P = 0.01]. eGFR levels significantly decreased in the placebo group [Mean diff:-0.254 (95% CI: -4.71 to -0.38), P = 0.021] while there was no between group difference. Serum calcium levels significantly decreased at follow up [mean diff: -0.49 (95% CI: -0.82 to -0.15), P = 0.001). FGF-23 significantly increased in the placebo group also [Mean diff: 82.08 (95% CI: 15.74 to 148.43), P = 0.015]. Serum C-reactive protein (CRP) levels significantly increased in placebo group [Mean diff: 1.86 (95% CI: 0.51 to 3.23), P = 0.004]. Levels of serum alkaline phosphatase (ALP) showed significant increase in placebo group [Mean change: 15.28, 95% CI: 1.19 to 29.37, P = 0.023] but the difference was not significant between groups (Table 4 ). Between group difference: Between group difference showed a significant change in 25 (OH) vitamin D [Mean diff: 31.89, 95% CI: 20.46 to 43.32, P < 0.001 while no significant change in Pi [Mean diff: 0.517, 95% CI: -0.35 to 1.39, P = 0.270]. CRP showed a significant between group difference [Mean diff: -1.97 (95% CI: -3.99 to 0.04), P = 0.042]. Bone alkaline phosphatase (BAP) levels showed no significant change in both the groups however there was a significant between group difference [Mean change: -5.08, 95% CI: -12.80 to 2.64, P = 0.019] (Table 4 ). Drug compliance, safety and protocol violations: As shown in Table 5 , non-compliance for > 3 months with the study drug was recorded in 6 participants out of 89; 4 in cholecalciferol group and 2 in placebo group. No reasons for the same were given by the participants. No serious drug related adverse events were recorded in either of the groups. Similarly, there were no protocol violations except for drug non-compliance as mentioned before. However, 4 participants in cholecalciferol group and 3 participants were taking cholecalciferol. Activated vitamin D was started in 5 participants in cholecalciferol group and 5 participants in placebo group during different durations of follow up. Table 5 Drug compliance, safety and protocol violations Characteristic or parameter Cholecalciferol group (n = 46) Placebo group (n = 43) Duration of follow up (months) 27 (15,36) 30 (21,36) Compliance Number of times participant received drug refill 9 (5,11) 10 (7,11) Non-compliance for > 3 months at any time during the study (number of patients) 4 2 Drug compliance less than 75% 1 4 Participants who received cholecalciferol supplementation 4 3 Participants who received activated form of vitamin D (as per protocol according to discretion of the treating physician) 5 5 Safety Permanent discontinuation 0 0 Suspicion of drug related hypersensitivity after administration 0 0 New diagnosis of malignancy 0 0 Pregnancy in case of female participant 0 0 Drug related adverse event necessitating hospitalization 0 0 Other protocol violations Randomisation of ineligible patient 0 0 Adverse Events 23 31 Data presented as number or median (25th -75th percentile) as appropriate Discussion In this study, cholecalciferol supplementation significantly increased the levels of 25(OH)D levels in cholecalciferol group and a significant between group difference was observed. Most randomized controlled clinical trials has shown effective increase in 25(OH)D levels after supplementation with most common forms of vitamin D[ 5 , 19 , 20 ]. We did not observed any significant effect of cholecalciferol treatment on MACE, need of RRT and mortality, however, markers of inflammation and bone metabolism were favourably changed. The data of this study indicating no effect of vitamin D on CVD outcome or progression of CKD are consistent with the previously reported data. Studies including low daily dose of Vitamin D (VITAL) or monthly high dose of vitamin D (ViDA) did not have any effect on cardiovascular outcome [ 21 , 22 ]. A recent meta-analysis of RCTs including the VITAL and ViDA studies, confirm these findings and suggest that supplementation with vitamin D does not prevent cardiovascular events (risk ratios, 1.00 [95% CI, 0.95–1.06]), CVD mortality (risk ratios, 0.98 [95% CI, 0.90–1.07]) or all-cause mortality (risk ratios, 0.97 [95% CI, 0.93–1.02]) [ 23 ]. Similarity, meta-analysis of RCTs of different vitamin D supplements, with or without calcium, did not show any positive impact on preventing CVD risk [ 24 ]. Additionally, vitamin D supplementation in patients receiving haemodialysis has been found to be ineffective in improving CVD[ 25 ]. D-Health randomised trial, however, showed a reduction in the incidence of major cardiovascular events like myocardial infarction and coronary revascularisation when given monthly dose of 60000IU of vitamin D 3 for five years [ 26 ]. Other observational studies have also reported the beneficial effects of vitamin D supplementation on CVD and mortality in patients with CKD. Third National Health and Nutrition Examination Survey which followed cohort of CKD patients (n = 3011) for 9 years reported a higher risk for all-cause mortality in patients with serum 25(OH)D levels 30 ng/ml [ 27 ]. For both cardiovascular and non-cardiovascular mortality, the magnitude of the effect size was similar and remained consistent across various subgroups[ 27 ]. Another meta-analysis of 20 observational studies observed the association of vitamin D with reduced risk of overall and cardiovascular mortality[ 28 ]. This study reported that individuals receiving vitamin D had a lower mortality rate in comparison to those who did not receive vitamin D (hazard ratio (HR) of 0.74 with a 95% confidence interval (CI) of 0.67–0.82). Both calcitriol and paricalcitol treatment reduced cardiovascular mortality, however, participant on paricalcitol treatment had better survival than calcitriol (HR, 0.95; 95% CI, 0.91–0.99) [ 28 ]. These variations in outcomes across all these studies could be attributed to the observed heterogeneity among them in various aspects, including differences in study design, vitamin D analogues and dosage, variations in baseline vitamin D levels of study participants, cardiovascular disease prevalence, and variations in study duration, among other factors. We also analysed the levels of biomarkers of bone turnover as vitamin D has been reported to play a beneficial role in bone mineral metabolism. Among these, FGF-23 significantly increased in the cholecalciferol group as well as placebo group while serum CTX levels significantly decreased in cholecalciferol group at 12 months follow up. FGF-23 plays a significant role in regulating phosphorus and vitamin D metabolism. Its levels gradually rise, starting in the early stages of CKD. This increase is believed to be a physiological adaptation aimed at preserving normal serum phosphate levels and overall phosphorus balance [ 29 ]. It suppresses the synthesis of calcitriol in the kidney and promotes the breakdown of active vitamin D sterols. Conversely, calcitriol encourages the expression of FGF23 [ 30 ]. Our findings suggest that vitamin D therapy may boost FGF-23 levels. In individuals with CKD, this elevation can be attributed to the increase in early osteocytes induced by active vitamin D sterols leading to the expression of FGF-23 [ 31 ]. In a recent randomized controlled trial of 127 patients with CKD stage 3 and type 2 diabetes mellitus, calcitriol was shown to significantly decrease CTX levels [Between group difference: 0.12 µg/l; 95% CI (− 0.19 to − 0.06); (p < 0.001] and increase in FGF-23 levels [Between group difference: 30.6 pg/ml; 95% CI (14.8 to 46.3); p < 0.001] [ 32 ]. CTX is a bone turnover marker that is directly released during bone-resorption. Hence decreased levels of CTX are an indicator of decrease in bone resorption due to cholecalciferol. We observed a significant between group difference in BAP, a specific marker of bone formation and remodeling. Similar results were reported in a study conducted on children with CKD by Lerch et al. [ 33 ]. These data indicate the effectiveness of Vitamin D in markers of bone metabolism. Continuous accumulation of inflammatory factors like IL-6 and CRP leads to microinflammation in kidneys. Higher the content of inflammatory factors, more is the severity of CKD [ 34 ]. In this context, our study results showed no significant effect of vitamin D on IL-6 levels whereas CRP levels significantly decreased. Although a recent metal analysis of randomized controlled trials in CKD indicate no effect of vitamin D on inframammary markers (IL-6 and CRP) [ 35 ], however, our data suggest that vitamin D is effective in reducing the inflammation in CKD. Vitamin D deficiency is nearly ubiquitous among individuals with CKD. It is of utmost importance to evaluate whether interventions aimed at intermediate outcomes, such as vitamin D supplementation or other treatments in CKD, lead to enhancements in clinical outcomes like CVD, mortality, need of RRT. The precise procedure for addressing vitamin D deficiency is not clearly defined. We administered 60,000 IU of cholecalciferol once every two weeks, which successfully restored 25(OH)D levels and improved markers of bone turnover. However, this approach did not impact the occurrence of CVD, all-cause mortality, or the necessity of RRT. Our study, however, was not specifically structured to explore the long-term effects of cholecalciferol on bone turnover in these patients. Hence, it is essential to monitor the long-term effects of this strategy. There are few limitations of our study. We studied a protective effect of vitamin D among CKD patients with insufficient levels of vitamin D at baseline, which may vary in patients with deficient levels. We did not assess intermediate cardiovascular outcomes like pulse wave velocity, bone health markers like bone biopsy and dual energy X ray absorptiometry (DXA). We did not consider cardiovascular health at baseline. We did not exclude CKD patients with type 2 diabetes mellitus which is a contributing factor in CVD and disruptions in bone metabolism. We exclusively examined a single form of vitamin D, which may not always be the most efficient option. Conclusion In conclusion, cholecalciferol treatment did not affected MACE, need of RRT and mortality in participants with CKD, however it improved vitamin D levels and favourably affected markers of inflammation and bone metabolism in vitamin D insufficient patients with stage G3-G4 CKD. Declarations Author’s Contribution Conceived and designed the work: VK, AKY, VJ; data acquisition (screening, enrolment, and follow-up of patients): KK,KM, SS, VK and HSK; subject randomisation and drug dispensing: HK, NS; laboratory measurements: KK and AKY; data analysis: KK, AKY and VK; manuscript: KK, AKY, VK and VJ. All authors have read and approved the manuscript. Funding This study was funded by grant received by VK from Department of Biotechnology, Ministry of Science and Technology, India (Grant No. BT/PR29764/PFN/20/1417/2018) and Department of Biotechnology -Wellcome Trust, India Alliance (Grant No. IA/CPHI/18/1/503954). The funding agency had no role in design and conduct of this study. Conflict of interest VJ has research grants from Baxter, GSK and reports Consultancy and Advisory Board honoraria from Baxter Healthcare, and AstraZeneca, outside the published work. All other authors reported no conflict of interest. Ethical approval statement The study was approved by institutional ethics committee, Postgraduate Institute of Medical Education and Research (No. PGI/IEC/2019/000042 dated: 07- 01- 2019). Data sharing statement The datasets analysed during this study are available from the corresponding author on reasonable request. References WHR: Confronting the World’s Number One Killer. Geneva, Switzerland. World Heart Fedration. 2023. 2023. Chronic Kidney Disease Prognosis C, Matsushita K, van der Velde M, Astor BC, Woodward M, Levey AS, de Jong PE, Coresh J, Gansevoort RT: Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis . Lancet 2010, 375 (9731):2073-2081. van der Velde M, Matsushita K, Coresh J, Astor BC, Woodward M, Levey A, de Jong P, Gansevoort RT, Chronic Kidney Disease Prognosis C, van der Velde M et al : Lower estimated glomerular filtration rate and higher albuminuria are associated with all-cause and cardiovascular mortality. A collaborative meta-analysis of high-risk population cohorts . Kidney Int 2011, 79 (12):1341-1352. Vaduganathan M, Mensah GA, Turco JV, Fuster V, Roth GA: The Global Burden of Cardiovascular Diseases and Risk: A Compass for Future Health . J Am Coll Cardiol 2022, 80 (25):2361-2371. Dreyer G, Tucker AT, Harwood SM, Pearse RM, Raftery MJ, Yaqoob MM: Ergocalciferol and microcirculatory function in chronic kidney disease and concomitant vitamin d deficiency: an exploratory, double blind, randomised controlled trial . PLoS One 2014, 9 (7):e99461. Kendrick J, Andrews E, You Z, Moreau K, Nowak KL, Farmer-Bailey H, Seals DR, Chonchol M: Cholecalciferol, Calcitriol, and Vascular Function in CKD: A Randomized, Double-Blind Trial . Clin J Am Soc Nephrol 2017, 12 (9):1438-1446. Kumar V, Yadav AK, Lal A, Kumar V, Singhal M, Billot L, Gupta KL, Banerjee D, Jha V: A Randomized Trial of Vitamin D Supplementation on Vascular Function in CKD . J Am Soc Nephrol 2017, 28 (10):3100-3108. Levin A, Tang M, Perry T, Zalunardo N, Beaulieu M, Dubland JA, Zerr K, Djurdjev O: Randomized Controlled Trial for the Effect of Vitamin D Supplementation on Vascular Stiffness in CKD . Clin J Am Soc Nephrol 2017, 12 (9):1447-1460. Lundwall K, Jorneskog G, Jacobson SH, Spaak J: Paricalcitol, Microvascular and Endothelial Function in Non-Diabetic Chronic Kidney Disease: A Randomized Trial . Am J Nephrol 2015, 42 (4):265-273. Thethi TK, Bajwa MA, Ghanim H, Jo C, Weir M, Goldfine AB, Umpierrez G, Desouza C, Dandona P, Fang-Hollingsworth Y et al : Effect of paricalcitol on endothelial function and inflammation in type 2 diabetes and chronic kidney disease . J Diabetes Complications 2015, 29 (3):433-437. Zoccali C, Curatola G, Panuccio V, Tripepi R, Pizzini P, Versace M, Bolignano D, Cutrupi S, Politi R, Tripepi G et al : Paricalcitol and endothelial function in chronic kidney disease trial . Hypertension 2014, 64 (5):1005-1011. Yadav AK, Kumar V, Kumar V, Banerjee D, Gupta KL, Jha V: The Effect of Vitamin D Supplementation on Bone Metabolic Markers in Chronic Kidney Disease . J Bone Miner Res 2018, 33 (3):404-409. Chapter 3: Management of progression and complications of CKD . Kidney Int Suppl (2011) 2013, 3 (1):73-90. Salam S, Gallagher O, Gossiel F, Paggiosi M, Khwaja A, Eastell R: Diagnostic Accuracy of Biomarkers and Imaging for Bone Turnover in Renal Osteodystrophy . J Am Soc Nephrol 2018, 29 (5):1557-1565. Kumar V, Yadav AK, Singhal M, Kumar V, Lal A, Banerjee D, Gupta KL, Jha V: Vascular function and cholecalciferol supplementation in CKD: A self-controlled case series . J Steroid Biochem Mol Biol 2018, 180 :19-22. Wimalawansa SJ: Non-musculoskeletal benefits of vitamin D . J Steroid Biochem Mol Biol 2018, 175 :60-81. Rejnmark L, Bislev LS, Cashman KD, Eiriksdottir G, Gaksch M, Grubler M, Grimnes G, Gudnason V, Lips P, Pilz S et al : Non-skeletal health effects of vitamin D supplementation: A systematic review on findings from meta-analyses summarizing trial data . PLoS One 2017, 12 (7):e0180512. O'Callaghan CA: OxMaR: open source free software for online minimization and randomization for clinical trials . PLoS One 2014, 9 (10):e110761. Chandra P, Binongo JN, Ziegler TR, Schlanger LE, Wang W, Someren JT, Tangpricha V: Cholecalciferol (vitamin D3) therapy and vitamin D insufficiency in patients with chronic kidney disease: a randomized controlled pilot study . Endocr Pract 2008, 14 (1):10-17. Marckmann P, Agerskov H, Thineshkumar S, Bladbjerg EM, Sidelmann JJ, Jespersen J, Nybo M, Rasmussen LM, Hansen D, Scholze A: Randomized controlled trial of cholecalciferol supplementation in chronic kidney disease patients with hypovitaminosis D . Nephrol Dial Transplant 2012, 27 (9):3523-3531. Manson JE, Cook NR, Lee IM, Christen W, Bassuk SS, Mora S, Gibson H, Gordon D, Copeland T, D'Agostino D et al : Vitamin D Supplements and Prevention of Cancer and Cardiovascular Disease . N Engl J Med 2019, 380 (1):33-44. Scragg R, Stewart AW, Waayer D, Lawes CMM, Toop L, Sluyter J, Murphy J, Khaw KT, Camargo CA, Jr.: Effect of Monthly High-Dose Vitamin D Supplementation on Cardiovascular Disease in the Vitamin D Assessment Study : A Randomized Clinical Trial . JAMA Cardiol 2017, 2 (6):608-616. Barbarawi M, Kheiri B, Zayed Y, Barbarawi O, Dhillon H, Swaid B, Yelangi A, Sundus S, Bachuwa G, Alkotob ML et al : Vitamin D Supplementation and Cardiovascular Disease Risks in More Than 83 000 Individuals in 21 Randomized Clinical Trials: A Meta-analysis . JAMA Cardiol 2019, 4 (8):765-776. Bolland MJ, Grey A, Gamble GD, Reid IR: The effect of vitamin D supplementation on skeletal, vascular, or cancer outcomes: a trial sequential meta-analysis . Lancet Diabetes Endocrinol 2014, 2 (4):307-320. Investigators JD, Shoji T, Inaba M, Fukagawa M, Ando R, Emoto M, Fujii H, Fujimori A, Fukui M, Hase H et al : Effect of Oral Alfacalcidol on Clinical Outcomes in Patients Without Secondary Hyperparathyroidism Receiving Maintenance Hemodialysis: The J-DAVID Randomized Clinical Trial . JAMA 2018, 320 (22):2325-2334. Thompson B, Waterhouse M, English DR, McLeod DS, Armstrong BK, Baxter C, Duarte Romero B, Ebeling PR, Hartel G, Kimlin MG et al : Vitamin D supplementation and major cardiovascular events: D-Health randomised controlled trial . BMJ 2023, 381 :e075230. Mehrotra R, Kermah DA, Salusky IB, Wolf MS, Thadhani RI, Chiu YW, Martins D, Adler SG, Norris KC: Chronic kidney disease, hypovitaminosis D, and mortality in the United States . Kidney Int 2009, 76 (9):977-983. Zheng Z, Shi H, Jia J, Li D, Lin S: Vitamin D supplementation and mortality risk in chronic kidney disease: a meta-analysis of 20 observational studies . BMC Nephrol 2013, 14 :199. Wolf M: Fibroblast growth factor 23 and the future of phosphorus management . Curr Opin Nephrol Hypertens 2009, 18 (6):463-468. Quarles LD: Role of FGF23 in vitamin D and phosphate metabolism: implications in chronic kidney disease . Exp Cell Res 2012, 318 (9):1040-1048. Zou D, Wu W, He Y, Ma S, Gao J: The role of klotho in chronic kidney disease . BMC Nephrol 2018, 19 (1):285. Stathi D, Fountoulakis N, Panagiotou A, Maltese G, Corcillo A, Mangelis A, Ayis S, Gnudi L, Karalliedde J: Impact of treatment with active vitamin D calcitriol on bone turnover markers in people with type 2 diabetes and stage 3 chronic kidney disease . Bone 2023, 166 :116581. Lerch C, Shroff R, Wan M, Rees L, Aitkenhead H, Kaplan Bulut I, Thurn D, Karabay Bayazit A, Niemirska A, Canpolat N et al : Effects of nutritional vitamin D supplementation on markers of bone and mineral metabolism in children with chronic kidney disease . Nephrol Dial Transplant 2018, 33 (12):2208-2217. Liu C, Li H: Correlation of the severity of chronic kidney disease with serum inflammation, osteoporosis and vitamin D deficiency . Exp Ther Med 2019, 17 (1):368-372. Zhao L, Zhu G, Wu L, Xie D: Effects of vitamin D on inflammatory state in patients with chronic kidney disease: A controversial issue . Ther Apher Dial 2023, 27 (3):383-393. Additional Declarations Competing interest reported. VJ has research grants from Baxter, GSK and reports Consultancy and Advisory Board honoraria from Baxter Healthcare, and AstraZeneca, outside the published work. All other authors reported no conflict of interest. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5276044","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":371102801,"identity":"6e3146d4-a26c-4fe6-972b-06abc7102ada","order_by":0,"name":"Kajal Kamboj","email":"","orcid":"","institution":"Post graduate Institute of Medical Education and Research, Chandigarh","correspondingAuthor":false,"prefix":"","firstName":"Kajal","middleName":"","lastName":"Kamboj","suffix":""},{"id":371102802,"identity":"8c4ef9c3-72af-420e-b098-a565e86965aa","order_by":1,"name":"Karthikeyan Manoharan","email":"","orcid":"","institution":"Post graduate Institute of Medical Education and Research, Chandigarh","correspondingAuthor":false,"prefix":"","firstName":"Karthikeyan","middleName":"","lastName":"Manoharan","suffix":""},{"id":371102804,"identity":"5ec86613-50f9-4f91-8f10-1be78b6f3220","order_by":2,"name":"Shubham Sharma","email":"","orcid":"","institution":"Post graduate Institute of Medical Education and Research, Chandigarh","correspondingAuthor":false,"prefix":"","firstName":"Shubham","middleName":"","lastName":"Sharma","suffix":""},{"id":371102805,"identity":"eb5daf2b-1e32-4966-9bb1-9956b9a7003c","order_by":3,"name":"Himanshi Khera","email":"","orcid":"","institution":"Post graduate Institute of Medical Education and Research, Chandigarh","correspondingAuthor":false,"prefix":"","firstName":"Himanshi","middleName":"","lastName":"Khera","suffix":""},{"id":371102807,"identity":"3d4ff032-eac1-402e-be51-f07b12da39b9","order_by":4,"name":"Nusrat Shafiq","email":"","orcid":"","institution":"Post graduate Institute of Medical 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Chandigarh","correspondingAuthor":false,"prefix":"","firstName":"Vivek","middleName":"","lastName":"Kumar","suffix":""},{"id":371102814,"identity":"947bff54-1cc5-4dd4-8371-103bdc40e211","order_by":8,"name":"Vivekanand Jha","email":"","orcid":"","institution":"Post graduate Institute of Medical Education and Research, Chandigarh","correspondingAuthor":false,"prefix":"","firstName":"Vivekanand","middleName":"","lastName":"Jha","suffix":""}],"badges":[],"createdAt":"2024-10-16 13:08:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5276044/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5276044/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":69080012,"identity":"7adfa8b5-1082-4945-a717-b088e04a733b","added_by":"auto","created_at":"2024-11-15 11:46:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":152268,"visible":true,"origin":"","legend":"\u003cp\u003eCONSORT flow diagram of the study\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5276044/v1/a66d262f29cd07f5b445a244.png"},{"id":78463304,"identity":"15247873-cd02-4845-ac52-4a03d9bf5961","added_by":"auto","created_at":"2025-03-13 14:01:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3089749,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5276044/v1/d94dc4c1-a067-4cbb-88ac-86457e5f2c47.pdf"}],"financialInterests":"Competing interest reported. VJ has research grants from Baxter, GSK and reports Consultancy and Advisory Board honoraria from Baxter Healthcare, and AstraZeneca, outside the published work. All other authors reported no conflict of interest.","formattedTitle":"Effect of cholecalciferol supplementation on CVD, inflammation and bone metabolism markers in CKD: results of feasibility phase of randomized double blind controlled placebo trial","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCardiovascular disease (CVD) is a global health concern that caused 20.5\u0026nbsp;million deaths in 2021, with a surge of about 60% globally over the last 30 years [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. As compared to individuals with normal renal function, the risk of cardiovascular mortality is two and three times increased in patients with chronic kidney disease (CKD) stages G3 and 4, respectively [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In 2021, 1.87\u0026nbsp;million cardiovascular deaths and 3.47\u0026nbsp;million overall deaths were attributable to reduced kidney function [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVitamin D deficiency have been linked with CVD and mortality in both general population and in individuals with CKD. In CKD, the targets of vitamin D supplementation is correcting its deficiency, enhancing mineral balance along with reducing the risk and progression of secondary hyperparathyroidism (SHPT). Vitamin D derivatives or its analogs in the treatment of CKD have focused on biochemical markers [25(OH)D3, or 1,25(OH)2D3 levels, parathyroid hormone (PTH), calcium, phosphorus, and intermediate outcomes (vascular calcifications, bone density and histology) and major clinical end points (CVD, mortality etc.). Based on evidence from observational studies suggesting association of vitamin D deficiency with CVD associated mortality in CKD, impact of vitamin D supplementation on surrogate endpoints for CVD in pre-dialysis CKD has been investigated in a number of randomized controlled trials (RCTs) in the recent past [\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9 CR10\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Overall, the findings from these clinical trials suggest that supplementation with vitamin D favorably modify endothelial and vascular function in CKD. Recently, we have also shown improvement in endothelial function and vascular stiffness, which are surrogates of future CVD, and markers of inflammation and bone metabolism with cholecalciferol supplementation in a RCT in patients with stage G3-4 CKD [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This study showed that cholecalciferol supplementation significantly decreased the circulating interleukin-6 (IL-6), serum C-terminal cross-linked collagen type I telopeptides (CTX-1), serum total and bone-specific alkaline phosphatase (SAP, BAP)[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Kidney Disease Improving Global Outcomes (KDIGO) has recommended BAP as a bone biomarker for the diagnosis and management of renal osteodystrophy [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Also, it has been shown to be an effective indicator for distinguishing low bone turnover [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn CKD, the impact of native vitamin D forms (cholecalciferol) might be mediated through conversion to 1,25(OH)\u003csub\u003e2\u003c/sub\u003eD but limited data suggest that different effector mechanisms might be present that can be inferred from our work suggesting opposing effects on fibroblast growth factor 23 (FGF-23) when compared to calcitriol [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The native forms might be important for paracrine and autocrine effects, and higher circulating levels might be required for extra-skeletal effects including favorable modulation of vascular function and inflammatory state [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In fact, the lack of favorable effects of vitamin D supplementation on extra-skeletal effects in studies could also be due to the fact that majority of clinical trials were never designed to look at extra- skeletal effects as primary outcome parameters[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These data suggest that cholecalciferol supplementation targeted to higher circulating vitamin D levels would be the most appropriate intervention when extra-skeletal effect like modulation of vascular function is the primary endpoint of clinical trial. In this feasibility study, we evaluated the effect of cholecalciferol supplementation on CVD, inflammation and bone metabolism markers in CKD in a randomized double-blind placebo-controlled trial.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy design:\u003c/h2\u003e\n \u003cp\u003eThe study was a feasibility phase clinical trial conducted at the Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India. It was a single center, prospective, randomized, placebo controlled, double blind clinical trial. The trial was prospectively registered at the Clinical Trials Registry of India (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.ctri.nic.in\u003c/span\u003e\u003c/span\u003e, trial registration number CTRI/2019/05/019211 dated 20 May 2019). The study was approved by the Institute Ethics Committee of PGIMER, Chandigarh.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eStudy Population:\u003c/h3\u003e\n\u003cp\u003eAdult patients (\u0026ge;\u0026thinsp;18 years) with pre-dialysis CKD [as defined KDIGO; CKD definition] who were attending the outpatient clinic in the Department of Nephrology were screened. Inclusion criteria were ages between18-75 years, estimated glomerular filtration rate (eGFR) ranging from 10\u0026ndash;45 ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e by creatinine based Chronic Kidney Disease -Epidemiology Collaboration (CKD-EPI) Eq.\u0026nbsp;2009, serum 25-hydroxy vitamin D [25(OH)D] levels 20\u0026ndash;50 ng/ml and clinically stable course for last 3 months. Exclusion criteria were patients receiving long-term maintenance dialysis or immunosuppressive therapy, those with diagnosis of chronic liver disease, primary hyperparathyroidism, sarcoidosis, malignancy, history of having been treated for hypercalcemia due to any cause, anticipated need of long-term kidney replacement therapy within 6 months, poor functional status, life expectancy\u0026thinsp;\u0026lt;\u0026thinsp;1 year, pregnancy in case of females, blood hemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;8 g/dL, serum calcium\u0026thinsp;\u0026gt;\u0026thinsp;9.5 mg/dL, history of having received any type of organ transplant, history of allergy to the interventional drug (cholecalciferol), having received vitamin D supplementation in last 30 days or participation in another interventional clinical trial. Patients satisfying all of the inclusion criteria and none of the exclusion criteria were enrolled after informed consent.\u003c/p\u003e\n\u003ch3\u003eEnrolment, randomization and intervention:\u003c/h3\u003e\n\u003cp\u003eAt enrolment, all participants entered a run-in phase of 2 weeks. At the end of run-in phase, they were randomized in 1:1 ratio. An adaptive allocation algorithm based on OxMaR. [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e] was used to minimize imbalance across treatment groups in the stage of CKD and presence of diabetes. The treatment boxes were neutrally coded and centrally masked. The boxes were identical, sequentially numbered, sealed and traceable. The allocation sequence was concealed from participants, investigators, and outcome assessors. Participants received either cholecalciferol 60000 IU once/2 weeks or matching placebo.\u003c/p\u003e\n\u003ch3\u003eFollow up:\u003c/h3\u003e\n\u003cp\u003eFollow up visits were scheduled at 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33 and 36 months after enrolment. Serum levels of 25(OH)D, calcium, and intact parathyroid hormone (iPTH) were assessed at every scheduled follow up visit. Cholecalciferol/placebo intervention were stopped at follow up if serum 25(OH)D were \u0026gt;\u0026thinsp;70 ng/ml or serum calcium were \u0026gt;\u0026thinsp;10 mg/dL. It was re-started on subsequent follow up visit when serum 25(OH)D levels was \u0026le;50 ng/ml and serum calcium was \u0026le;9.5 mg/dL. 10 ml each of fasting blood and second morning urine samples were collected and stored at -80 \u003csup\u003eo\u003c/sup\u003eC at baseline and annually thereafter. This was required for measurement of biomarkers as outlined in secondary objectives. During any acute clinical event or hospitalization, the treating physicians could withdraw study interventions at their discretion. The decision to start interventions again after recovery or discharge was also at the sole discretion of treating physician. The study intervention was permanently withdrawn in an index participant under these circumstances: Suspicion of drug related hypersensitivity after administration, new diagnosis of malignancy, pregnancy in case of female participant, participant\u0026rsquo;s or physician\u0026rsquo;s request for the same or drug related adverse event necessitating hospitalization. The concurrent clinical care continued as per prevailing standards of care. Any adverse reaction that resulted in death, was life-threatening, required hospitalisation or prolongation of existing hospitalisation, resulted in persistent or significant disability or incapacity was treated as serious adverse event. Treatment of secondary hyperparathyroidism and/or vitamin D deficiency were allowed with use of activated forms of vitamin D (e.g. calcitriol) as felt necessary by treating physician. Use of native forms of vitamin D (cholecalciferol or ergocalciferol) was forbidden. Compliance to the study drug was checked by comparing the actual number of tablets taken by a participant with the total number of tablets should have been taken by a participant over the study duration.\u003c/p\u003e\n\u003ch3\u003eObjectives and outcomes:\u003c/h3\u003e\n\u003cp\u003ePrimary outcome measures were a composite of major adverse cardiac events (MACE) that included new onset heart failure, CAD, PVD, cerebrovascular accident (transient ischemic attack or stroke), any coronary or peripheral arterial revascularization procedure and death due to CVD. Secondary outcome measures were: all-cause mortality, need for renal replacement therapy (RRT), change in high sensitivity C-reactive protein (hsCRP), Interleukin-6 (IL-6), intact parathyroid hormone (iPTH), fibroblast growth factor-23 (FGF-23), bone specific alkaline phosphatase (BAP), and C-terminal telopeptide (CTX-1).\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eMeasurements:\u003c/h2\u003e\n \u003cp\u003eAll measurements were done in fasting blood samples. Serum levels of 25(OH)D and iPTH were analyzed using Cobas\u003csup\u003e\u0026reg;\u003c/sup\u003e 8000 modular analyzer (Roche Diagnostics, Mannheim, Germany). All biochemical investigations were done using Cobas\u003csup\u003e\u0026reg;\u003c/sup\u003e c702 auto-analyzer (Roche Diagnostic Limited, Rotkreuz, Switzerland). Serum IL-6 (Quantikine soild phase sandwich ELISA; R\u0026amp;D Systems\u003csup\u003e\u0026reg;\u003c/sup\u003e, Minneapolis, MN, USA), serum hs-CRP (Calbiotech Inc., CA, USA), human plasma FGF-23 (Immutopics, Inc., Athens, Ohio), serum BAP (MicroVue\u003csup\u003e\u0026trade;\u003c/sup\u003e BAP EIA; Quidel Corporation San Diego, CA, USA), serum CTX-1 [Serum Crosslaps\u003csup\u003e\u0026reg;\u003c/sup\u003e (CTX-1) ELISA; IDS, Boldon, UK] were measured in stored samples at baseline and 12 months follow up.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical analysis:\u003c/h2\u003e\n \u003cp\u003eThere was no formal sample size calculation for the feasibility phase of the study. We planned to enroll at least 125 participants. All participants with non-missing outcome data were included in the analysis. Descriptive statistics were used to describe characteristics of study participants. Categorical data were presented as frequencies and continuous variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or median (IQ range) as appropriate. Continuous variables were compared by independent sample t test if normally distributed, or Mann-Whitney U test if distribution were skewed. Categorical variables were analyzed by Chi-squared test or Fisher exact test as appropriate. Hemoglobin, calcium, phosphorus, creatinine, eGFR, alkaline phosphatase and other biomarker measurements were reported and compared between groups at baseline and 12 months. Other outcome data were reported descriptively for the study duration completed by participants.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 692 patients were screened between August 2019 to October 2021, out of which 126 were enrolled. 32 enrolled participants dropped out before randomization on account of COVID-19 related lockdowns and restrictions and other reasons. 89 participants were randomized till end of October 2021 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The following data analysis pertains to baseline measurements of 89 participants and follow up comparative measurements of 80 participants who have completed one year of follow up.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics:\u003c/h2\u003e \u003cp\u003eTill October 2021, 89 participants were randomized. 46 participants were in the cholecalciferol group whereas 43 were in the placebo group. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the baseline characteristics of study population. Mean age of the overall participants was 50.84\u0026plusmn;12.68 years with 38% being female. At baseline, the cholecalciferol and placebo groups were similar with respect to demographic characteristics, distribution of causes of CKD, risk factors, presence of CVD and use of medications. Similarly, there were no significant differences between the two groups with respect to baseline biochemical and biomarker measurements (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). eGFR, serum 25(OH)D and iPTH levels were similar between the groups at baseline (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of study population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic or parameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCholecalciferol group (n\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePlacebo group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;43)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (65.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(55.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (34.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (44.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.4\u0026plusmn; 12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.74\u0026plusmn;12.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.4 \u0026plusmn; 5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.5\u0026plusmn;4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist/Hip ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9 (0.9 ,1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.9, 1.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e144.0\u0026plusmn; 22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135.7\u0026plusmn;22.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89\u0026plusmn; 12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.7\u0026plusmn;15.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of kidney disease (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (22, 80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (30.8, 87.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCause of CKD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic interstitial nephritis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (34.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (27.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAKUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12(26.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (34.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePKD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (4.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiopsy proven GN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther kidney diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (9.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePresence/history of\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (93.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (83.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (23.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (23.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal stone disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11(23.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (9.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (9.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny other form of atherosclerotic vascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary angiography\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (9.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedications use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACE inhibitor/ARB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (32.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (41.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (69.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta blocker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (45.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (55.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGLT-2 inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNitrates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypouricemic drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (18.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBicarbonates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (80.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (72.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErythropoietin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (9.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntiplatelet (Aspirin/Clopidogrel)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (18.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eData presented as mean \u0026plusmn; standard deviation, median (25th -75th percentile) or frequency (percentage) as appropriate. ACE: angiotensin-converting enzyme, ARB: angiotensin II receptor blocker, BMI: body mass index, CAD: coronary artery disease, CAKUT: congenital anomalies of kidney and urinary tract, CKD: chronic kidney disease, CVA: cerebrovascular accident, DBP: diastolic blood pressure, GN: glomerulonephritis, PKD: polycystic kidney disease, PVD: peripheral vascular disease, SBP: systolic blood pressure, SGLT-2: sodium-glucose cotransporter-2.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline investigations and biomarkers in the study population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic or parameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCholecalciferol group (n\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePlacebo group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;43)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.87\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum creatinine (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.97\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eeGFR (CKD-EPI\u003csub\u003eCr\u003c/sub\u003e 2009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.58(15.51, 33.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.56 (18.89, 36.62)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood urea (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.00 (49.53, 103.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.00(51.20, 95.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum calcium (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.20 (8.69, 9.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.23 (8.95, 9.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum inorganic phosphorous (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.77 (3.16, 4.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.83 (3.20, 4.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum uric acid (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.10 (6.15, 8.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.20 (5.80, 8.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum alkaline phosphatase (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92.00 (77.00, 116.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101.50 (83.50, 116.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum total cholesterol (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148.95 (120.30 ,165.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140.30 (118.90,159.15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum triglycerides (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e136.40 (104.18, 169.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126.30 (98.45, 171.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum LDL-C (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83.45 (62.28, 105.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.50 (56.00, 97.40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum HDL-C (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.65 (37.28, 51.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.20 (37.25, 50.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum iPTH (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e192.00 (125.00, 321.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e166.80 (81.48, 317.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum 25(OH)D (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.40 (24.29, 39.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.51 (22.75, 38.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpot urine protein/creatinine ratio (mg/g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e739.90 (303.10, 2141.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1012.36 (302.33, 1679.57)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum BAP (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.56 (21.04, 37.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.41 (23.53, 42.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum intact FGF-23 (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131.03 (30.02, 143.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131.03 (34.91, 143.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum CRP (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.06 (1.94 ,7.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.20 (1.22, 6.80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum IL-6 (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.40 (3.50, 10.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.88(2.47, 10.57)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum CTX (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.41 (0.81, 2.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.52 (0.84, 2.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eData presented as mean \u0026plusmn; standard deviation or median (25th -75th percentile) as appropriate. 25(OH)D: 25-hydroxyvitamin D3, BAP: bone alkaline phosphatase, CRP: C-reactive protein, CTX: carboxy terminal telopeptide, eGFR: estimated glomerular filtration rate, FGF-23: fibroblast growth factor-23, HDL-C: high density lipoprotein cholesterol, iPTH: intact parathyroid hormone, IL-6: interleukin-6, LDL-C: low density lipoprotein cholesterol.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eOutcome parameters:\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e represents the outcome parameters of the study groups. Total of 23 adverse events were recorded in cholecalciferol group and 31 adverse events were recorded in placebo group. Out of which 9 and 10 participants reported serious adverse events in cholecalciferol and placebo group respectively. One participant in placebo group was reported for CVA. Seven participants in cholecalciferol group reached the end stage renal disease (ESRD)/ need of renal replacement therapy (RRT) while eleven participants in placebo group reached ESRD. In addition to this, four deaths in each group were recorded. These were reported to Clinical Trials Data Safety Board at PGIMER and finally, concluded to be unrelated to study intervention.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOutcome parameters in the study population till last follow up visit\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCholecalciferol (n\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePlacebo (n\u0026thinsp;=\u0026thinsp;43)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of follow up (months)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (15, 36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (21, 36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of total adverse events records\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal number of patients who experienced at least one adverse event\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSerious Adverse Events\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of patients who experienced SAE at least once\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal number of hospitalizations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal number of patients who experienced at least one hospitalization\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMACE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNew onset heart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny coronary or peripheral arterial revascularization procedure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath due to CVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNeed for RRT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTime to start of RRT (months)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (11, 27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (11, 24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComposite of 40% decline in GFR or need for RRT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall Mortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComposite of all-cause death and non-fatal MACE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eData presented as number or median (25th -75th percentile) as appropriate\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eCAD: coronary artery disease, CVA: cerebrovascular accident, CVD: cardiovascular disease, MACE: major adverse cardiovascular event, GFR: glomerular filtration rate, PVD: peripheral vascular disease, RRT: renal replacement therapy, SAE: serious adverse events\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eBiochemical and biomarkers at follow up:\u003c/h2\u003e \u003cp\u003eThe biochemical and biomarker characteristics of these participants were compared at annual follow up visit. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the within group and between group differences with respect to biochemical and biomarker characteristics.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWithin group and between group differences in biochemical and biomarker measurements at 12 months in the study population who completed at least one year follow up\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCholecalciferol\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;Mean difference (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN (number of patients)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePlacebo Mean difference (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN (number of patients)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eBetween group difference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum 25(OH)D (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.15\u003c/p\u003e \u003cp\u003e(21.37 to 40.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.75\u003c/p\u003e \u003cp\u003e(-7.43 to 5.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31.89\u003c/p\u003e \u003cp\u003e(20.46 to 43.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum iPTH (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.51\u003c/p\u003e \u003cp\u003e(-24.19 to 95.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.39\u003c/p\u003e \u003cp\u003e(-17.92 to 134.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-22.87\u003c/p\u003e \u003cp\u003e(-119.56 to 73.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.660\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.21\u003c/p\u003e \u003cp\u003e(-0.89 to 0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.37\u003c/p\u003e \u003cp\u003e(-0.75 to 0.020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003cp\u003e(-0.61 to 0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum Cr (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003cp\u003e(0.12 to 0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003cp\u003e(0.071 to 0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003cp\u003e(-0.47 to 0.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.871\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eeGFR (CKD-EPIcr)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.72\u003c/p\u003e \u003cp\u003e(-3.80 to 0.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.54\u003c/p\u003e \u003cp\u003e(-4.71 to -0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003cp\u003e(-2.13 to 3.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.848\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum calcium (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003cp\u003e(-0.14 to 0.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.49\u003c/p\u003e \u003cp\u003e(-0.82 to -0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.558\u003c/p\u003e \u003cp\u003e(0.17 to 0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum inorganic phosphorous (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003cp\u003e(0.006 to 1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003cp\u003e(-0.088 to 0.658)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.517\u003c/p\u003e \u003cp\u003e(-0.35 to 1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum alkaline phosphatase (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.26\u003c/p\u003e \u003cp\u003e(-12.11 to 28.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.28\u003c/p\u003e \u003cp\u003e(1.19 to 29.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-7.02\u003c/p\u003e \u003cp\u003e(-31.56 to 17.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUPCR (mg/g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e215.11\u003c/p\u003e \u003cp\u003e(-878.61 to 1308.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-49.12\u003c/p\u003e \u003cp\u003e(-523.19 to 425.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e264.23\u003c/p\u003e \u003cp\u003e(-950.39 to 1478.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.664\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum IL-6 (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.244\u003c/p\u003e \u003cp\u003e(-22.75 to 22.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.56\u003c/p\u003e \u003cp\u003e(-14.69 to 5.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.315\u003c/p\u003e \u003cp\u003e(-19.08 to 27.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum intact FGF-23 (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101.74\u003c/p\u003e \u003cp\u003e(21.72 to 181.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82.08\u003c/p\u003e \u003cp\u003e(15.74 to 148.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19.66\u003c/p\u003e \u003cp\u003e(-81.75 to 121.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.335\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum CRP (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.105\u003c/p\u003e \u003cp\u003e(-1.65 to 1.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.86\u003c/p\u003e \u003cp\u003e(0.51 to 3.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.97\u003c/p\u003e \u003cp\u003e(-3.99 to 0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum CTX (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.395\u003c/p\u003e \u003cp\u003e(-0.68 to -0.112)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.185\u003c/p\u003e \u003cp\u003e(-0.53 to 0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.215\u003c/p\u003e \u003cp\u003e(-0.655 to 0.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.452\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum BAP (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.61\u003c/p\u003e \u003cp\u003e(-9.90 to 0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.471\u003c/p\u003e \u003cp\u003e(-5.25 to 6.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-5.08\u003c/p\u003e \u003cp\u003e(-12.80 to 2.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eData presented as mean difference (95% confidence interval). 25(OH)D: 25-hydroxyvitamin D3, BAP: bone alkaline phosphatase, CRP: C-reactive protein, CTX: carboxy terminal telopeptide, eGFR: estimated glomerular filtration rate, FGF-23: fibroblast growth factor-23, iPTH: intact parathyroid hormone, IL-6: interleukin-6, UPCR: urine protein creatinine ratio\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCholecalciferol group:\u003c/h2\u003e \u003cp\u003eSerum 25(OH)D and inorganic phosphorous (Pi) levels significantly increased at annual follow up in the cholecalciferol group [25 (OH) vitamin D, Mean diff: 31.15 (95% CI: 21.37 to 40.92), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Pi, Mean diff: 0.80 (95% CI: 0.006 to 1.59), P\u0026thinsp;=\u0026thinsp;0.010]. (Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Cholecalciferol group also showed a significant increase in serum creatinine levels at follow up [Mean diff: 0.46 (95% CI: 0.12 to 0.81), P\u0026thinsp;=\u0026thinsp;0.029]. Serum intact fibroblast growth factor-23 (FGF-23) significantly increased in the cholecalciferol group [Mean diff: 101.74 (95% CI: 21.72 to 181.76), P\u0026thinsp;=\u0026thinsp;0.001]. Serum CTX levels significantly decreased in cholecalciferol group [Mean diff: -0.395 (95% CI: -0.68 to -0.112), P\u0026thinsp;=\u0026thinsp;0.020] at 12 months follow up.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePlacebo group:\u003c/h2\u003e \u003cp\u003eSerum creatinine levels significantly increased in the placebo group [Mean diff: 0.44 (95%CI: 0.071 to 0.81), P\u0026thinsp;=\u0026thinsp;0.01]. eGFR levels significantly decreased in the placebo group [Mean diff:-0.254 (95% CI: -4.71 to -0.38), P\u0026thinsp;=\u0026thinsp;0.021] while there was no between group difference. Serum calcium levels significantly decreased at follow up [mean diff: -0.49 (95% CI: -0.82 to -0.15), P\u0026thinsp;=\u0026thinsp;0.001). FGF-23 significantly increased in the placebo group also [Mean diff: 82.08 (95% CI: 15.74 to 148.43), P\u0026thinsp;=\u0026thinsp;0.015]. Serum C-reactive protein (CRP) levels significantly increased in placebo group [Mean diff: 1.86 (95% CI: 0.51 to 3.23), P\u0026thinsp;=\u0026thinsp;0.004]. Levels of serum alkaline phosphatase (ALP) showed significant increase in placebo group [Mean change: 15.28, 95% CI: 1.19 to 29.37, P\u0026thinsp;=\u0026thinsp;0.023] but the difference was not significant between groups (Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eBetween group difference:\u003c/h2\u003e \u003cp\u003eBetween group difference showed a significant change in 25 (OH) vitamin D [Mean diff: 31.89, 95% CI: 20.46 to 43.32, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 while no significant change in Pi [Mean diff: 0.517, 95% CI: -0.35 to 1.39, P\u0026thinsp;=\u0026thinsp;0.270]. CRP showed a significant between group difference [Mean diff: -1.97 (95% CI: -3.99 to 0.04), P\u0026thinsp;=\u0026thinsp;0.042]. Bone alkaline phosphatase (BAP) levels showed no significant change in both the groups however there was a significant between group difference [Mean change: -5.08, 95% CI: -12.80 to 2.64, P\u0026thinsp;=\u0026thinsp;0.019] (Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eDrug compliance, safety and protocol violations:\u003c/h2\u003e \u003cp\u003eAs shown in Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, non-compliance for \u0026gt;\u0026thinsp;3 months with the study drug was recorded in 6 participants out of 89; 4 in cholecalciferol group and 2 in placebo group. No reasons for the same were given by the participants. No serious drug related adverse events were recorded in either of the groups. Similarly, there were no protocol violations except for drug non-compliance as mentioned before. However, 4 participants in cholecalciferol group and 3 participants were taking cholecalciferol. Activated vitamin D was started in 5 participants in cholecalciferol group and 5 participants in placebo group during different durations of follow up.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDrug compliance, safety and protocol violations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic or parameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCholecalciferol group (n\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePlacebo group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;43)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of follow up (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (15,36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (21,36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCompliance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of times participant received drug refill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (5,11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (7,11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-compliance for \u0026gt;\u0026thinsp;3 months at any time during the study (number of patients)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrug compliance less than 75%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticipants who received cholecalciferol supplementation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticipants who received activated form of vitamin D (as per protocol according to discretion of the treating physician)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSafety\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePermanent discontinuation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuspicion of drug related hypersensitivity after administration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNew diagnosis of malignancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePregnancy in case of female participant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrug related adverse event necessitating hospitalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOther protocol violations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRandomisation of ineligible patient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdverse Events\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eData presented as number or median (25th -75th percentile) as appropriate\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, cholecalciferol supplementation significantly increased the levels of 25(OH)D levels in cholecalciferol group and a significant between group difference was observed. Most randomized controlled clinical trials has shown effective increase in 25(OH)D levels after supplementation with most common forms of vitamin D[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. We did not observed any significant effect of cholecalciferol treatment on MACE, need of RRT and mortality, however, markers of inflammation and bone metabolism were favourably changed.\u003c/p\u003e \u003cp\u003eThe data of this study indicating no effect of vitamin D on CVD outcome or progression of CKD are consistent with the previously reported data. Studies including low daily dose of Vitamin D (VITAL) or monthly high dose of vitamin D (ViDA) did not have any effect on cardiovascular outcome [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. A recent meta-analysis of RCTs including the VITAL and ViDA studies, confirm these findings and suggest that supplementation with vitamin D does not prevent cardiovascular events (risk ratios, 1.00 [95% CI, 0.95\u0026ndash;1.06]), CVD mortality (risk ratios, 0.98 [95% CI, 0.90\u0026ndash;1.07]) or all-cause mortality (risk ratios, 0.97 [95% CI, 0.93\u0026ndash;1.02]) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Similarity, meta-analysis of RCTs of different vitamin D supplements, with or without calcium, did not show any positive impact on preventing CVD risk [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Additionally, vitamin D supplementation in patients receiving haemodialysis has been found to be ineffective in improving CVD[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. D-Health randomised trial, however, showed a reduction in the incidence of major cardiovascular events like myocardial infarction and coronary revascularisation when given monthly dose of 60000IU of vitamin D\u003csub\u003e3\u003c/sub\u003e for five years [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Other observational studies have also reported the beneficial effects of vitamin D supplementation on CVD and mortality in patients with CKD. Third National Health and Nutrition Examination Survey which followed cohort of CKD patients (n\u0026thinsp;=\u0026thinsp;3011) for 9 years reported a higher risk for all-cause mortality in patients with serum 25(OH)D levels\u0026thinsp;\u0026lt;\u0026thinsp;15 ng/ml and 15\u0026ndash;30 ng/ml in comparison to patients with 25(OH)D\u0026thinsp;\u0026gt;\u0026thinsp;30 ng/ml [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. For both cardiovascular and non-cardiovascular mortality, the magnitude of the effect size was similar and remained consistent across various subgroups[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Another meta-analysis of 20 observational studies observed the association of vitamin D with reduced risk of overall and cardiovascular mortality[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This study reported that individuals receiving vitamin D had a lower mortality rate in comparison to those who did not receive vitamin D (hazard ratio (HR) of 0.74 with a 95% confidence interval (CI) of 0.67\u0026ndash;0.82). Both calcitriol and paricalcitol treatment reduced cardiovascular mortality, however, participant on paricalcitol treatment had better survival than calcitriol (HR, 0.95; 95% CI, 0.91\u0026ndash;0.99) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. These variations in outcomes across all these studies could be attributed to the observed heterogeneity among them in various aspects, including differences in study design, vitamin D analogues and dosage, variations in baseline vitamin D levels of study participants, cardiovascular disease prevalence, and variations in study duration, among other factors.\u003c/p\u003e \u003cp\u003eWe also analysed the levels of biomarkers of bone turnover as vitamin D has been reported to play a beneficial role in bone mineral metabolism. Among these, FGF-23 significantly increased in the cholecalciferol group as well as placebo group while serum CTX levels significantly decreased in cholecalciferol group at 12 months follow up. FGF-23 plays a significant role in regulating phosphorus and vitamin D metabolism. Its levels gradually rise, starting in the early stages of CKD. This increase is believed to be a physiological adaptation aimed at preserving normal serum phosphate levels and overall phosphorus balance [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. It suppresses the synthesis of calcitriol in the kidney and promotes the breakdown of active vitamin D sterols. Conversely, calcitriol encourages the expression of FGF23 [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Our findings suggest that vitamin D therapy may boost FGF-23 levels. In individuals with CKD, this elevation can be attributed to the increase in early osteocytes induced by active vitamin D sterols leading to the expression of FGF-23 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In a recent randomized controlled trial of 127 patients with CKD stage 3 and type 2 diabetes mellitus, calcitriol was shown to significantly decrease CTX levels [Between group difference: 0.12 \u0026micro;g/l; 95% CI (\u0026minus;\u0026thinsp;0.19 to \u0026minus;\u0026thinsp;0.06); (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001] and increase in FGF-23 levels [Between group difference: 30.6 pg/ml; 95% CI (14.8 to 46.3); p\u0026thinsp;\u0026lt;\u0026thinsp;0.001] [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. CTX is a bone turnover marker that is directly released during bone-resorption. Hence decreased levels of CTX are an indicator of decrease in bone resorption due to cholecalciferol. We observed a significant between group difference in BAP, a specific marker of bone formation and remodeling. Similar results were reported in a study conducted on children with CKD by Lerch \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. These data indicate the effectiveness of Vitamin D in markers of bone metabolism.\u003c/p\u003e \u003cp\u003eContinuous accumulation of inflammatory factors like IL-6 and CRP leads to microinflammation in kidneys. Higher the content of inflammatory factors, more is the severity of CKD [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In this context, our study results showed no significant effect of vitamin D on IL-6 levels whereas CRP levels significantly decreased. Although a recent metal analysis of randomized controlled trials in CKD indicate no effect of vitamin D on inframammary markers (IL-6 and CRP) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], however, our data suggest that vitamin D is effective in reducing the inflammation in CKD.\u003c/p\u003e \u003cp\u003eVitamin D deficiency is nearly ubiquitous among individuals with CKD. It is of utmost importance to evaluate whether interventions aimed at intermediate outcomes, such as vitamin D supplementation or other treatments in CKD, lead to enhancements in clinical outcomes like CVD, mortality, need of RRT. The precise procedure for addressing vitamin D deficiency is not clearly defined. We administered 60,000 IU of cholecalciferol once every two weeks, which successfully restored 25(OH)D levels and improved markers of bone turnover. However, this approach did not impact the occurrence of CVD, all-cause mortality, or the necessity of RRT. Our study, however, was not specifically structured to explore the long-term effects of cholecalciferol on bone turnover in these patients. Hence, it is essential to monitor the long-term effects of this strategy.\u003c/p\u003e \u003cp\u003eThere are few limitations of our study. We studied a protective effect of vitamin D among CKD patients with insufficient levels of vitamin D at baseline, which may vary in patients with deficient levels. We did not assess intermediate cardiovascular outcomes like pulse wave velocity, bone health markers like bone biopsy and dual energy X ray absorptiometry (DXA). We did not consider cardiovascular health at baseline. We did not exclude CKD patients with type 2 diabetes mellitus which is a contributing factor in CVD and disruptions in bone metabolism. We exclusively examined a single form of vitamin D, which may not always be the most efficient option.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, cholecalciferol treatment did not affected MACE, need of RRT and mortality in participants with CKD, however it improved vitamin D levels and favourably affected markers of inflammation and bone metabolism in vitamin D insufficient patients with stage G3-G4 CKD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor’s Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceived and designed the work: VK, AKY, VJ; data acquisition (screening, enrolment, and follow-up of patients): KK,KM, SS, VK and HSK; subject randomisation and drug dispensing: HK, NS; laboratory measurements: KK and AKY; data analysis: KK, AKY and VK; manuscript: KK, AKY, VK and VJ. All authors have read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by grant received by VK from Department of Biotechnology, Ministry of Science and Technology, India \u0026nbsp;(Grant No.\u0026nbsp;BT/PR29764/PFN/20/1417/2018) and Department of Biotechnology -Wellcome Trust, India Alliance (Grant No. IA/CPHI/18/1/503954). The funding agency had no role in design and conduct of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVJ has research grants from Baxter, GSK and reports Consultancy and Advisory Board honoraria from Baxter Healthcare, and AstraZeneca, outside the published work. All other authors reported no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by institutional ethics committee, Postgraduate Institute of Medical Education and Research (No. PGI/IEC/2019/000042 dated: 07- 01- 2019).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData sharing statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analysed during this study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWHR: \u003cstrong\u003eConfronting the World\u0026rsquo;s Number One Killer. Geneva, Switzerland. World Heart Fedration. 2023.\u003c/strong\u003e 2023.\u003c/li\u003e\n\u003cli\u003eChronic Kidney Disease Prognosis C, Matsushita K, van der Velde M, Astor BC, Woodward M, Levey AS, de Jong PE, Coresh J, Gansevoort RT: \u003cstrong\u003eAssociation of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis\u003c/strong\u003e. \u003cem\u003eLancet \u003c/em\u003e2010, \u003cstrong\u003e375\u003c/strong\u003e(9731):2073-2081.\u003c/li\u003e\n\u003cli\u003evan der Velde M, Matsushita K, Coresh J, Astor BC, Woodward M, Levey A, de Jong P, Gansevoort RT, Chronic Kidney Disease Prognosis C, van der Velde M\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eLower estimated glomerular filtration rate and higher albuminuria are associated with all-cause and cardiovascular mortality. 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\u003c/em\u003e2018, \u003cstrong\u003e33\u003c/strong\u003e(12):2208-2217.\u003c/li\u003e\n\u003cli\u003eLiu C, Li H: \u003cstrong\u003eCorrelation of the severity of chronic kidney disease with serum inflammation, osteoporosis and vitamin D deficiency\u003c/strong\u003e. \u003cem\u003eExp Ther Med \u003c/em\u003e2019, \u003cstrong\u003e17\u003c/strong\u003e(1):368-372.\u003c/li\u003e\n\u003cli\u003eZhao L, Zhu G, Wu L, Xie D: \u003cstrong\u003eEffects of vitamin D on inflammatory state in patients with chronic kidney disease: A controversial issue\u003c/strong\u003e. \u003cem\u003eTher Apher Dial \u003c/em\u003e2023, \u003cstrong\u003e27\u003c/strong\u003e(3):383-393.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"CKD, CVD, vitamin D deficiency, cholecalciferol, inflammation, biomarkers","lastPublishedDoi":"10.21203/rs.3.rs-5276044/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5276044/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u0026nbsp;\u003c/strong\u003eVitamin D deficiency is common in chronic kidney disease (CKD) and associated with cardiovascular disease (CVD) and bone mineral metabolism. Despite short term favourable effects, long term impact of cholecalciferol supplementation is unknown. We tested the effects of cholecalciferol supplementation on CVD outcome [major adverse cardiovascular events (MACE)], progression of CKD and markers of bone-mineral metabolism and inflammation in patients with pre-dialysis CKD.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u0026nbsp;The study was a single centre, prospective, randomized (1:1), placebo controlled, double blind clinical trial. Inclusion criteria were ages between 18-75 years, estimated glomerular filtration rate 10-45 ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e, serum 25(OH)D levels 20-50 ng/ml and clinically stable course for last 3 months. After 2 weeks run-in phase, participants received either cholecalciferol 60000 IU once/2 weeks or matching placebo and followed up at every 3 months till 36 months after enrolment. All clinical, demographic characters and biomarkers were analysed at baseline and annual follow up.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u0026nbsp;692 participants were screened, out of which 126 were enrolled. However, 37 participants dropped out before randomization on account of COVID-19 related lockdowns or other reasons. The pilot phase was stopped in April 2023. Follow up course of 89 participants were available till that time: 46 participants were in the cholecalciferol group whereas 43 were in the placebo group.\u0026nbsp;Both the groups were similar with respect to MACE events, need of renal replacement therapy and all-cause mortality. Over one year, serum 25 (OH)D increased in the cholecalciferol group [Mean diff between groups: 31.89, 95% CI: 20.46 to 43.32, P\u0026lt;0.001]. Serum calcium increased whereas C-reactive protein and bone specific alkaline phosphatase levels decreased in the cholecalciferol group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e\u0026nbsp;Cholecalciferol treatment did not affect\u0026nbsp;CVD outcome\u0026nbsp;or\u0026nbsp;progression of CKD\u0026nbsp;in vitamin D insufficient patients with stage G3-G4 CKD, however it favourably affected markers of inflammation and bone metabolism in these patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial Registration:\u0026nbsp;\u003c/strong\u003eThe trial was prospectively registered at the Clinical Trials Registry of India (www.ctri.nic.in, trial registration number CTRI/2019/05/019211 dated 20 May 2019).\u003c/p\u003e","manuscriptTitle":"Effect of cholecalciferol supplementation on CVD, inflammation and bone metabolism markers in CKD: results of feasibility phase of randomized double blind controlled placebo trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-15 11:46:10","doi":"10.21203/rs.3.rs-5276044/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9a6fca82-5fb3-4b04-90d7-5060d2211954","owner":[],"postedDate":"November 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-13T13:53:35+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-15 11:46:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5276044","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5276044","identity":"rs-5276044","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}