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Erratum to: Strong predictive value of mannose-binding lectin levels for cardiovascular risk of hemodialysis patients.

Felix Poppelaars1, Mariana Gaya da Costa2, Stefan P Berger2, Solmaz Assa3, Anita H Meter-Arkema2, Mohamed R Daha2,4, Willem J van Son2, Casper F M Franssen2, Marc A J Seelen2.   

Abstract

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Year:  2016        PMID: 27557787      PMCID: PMC4997692          DOI: 10.1186/s12967-016-1004-8

Source DB:  PubMed          Journal:  J Transl Med        ISSN: 1479-5876            Impact factor:   5.531


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Erratum to: J Transl Med (2016) 14:236 DOI:10.1186/s12967-016-0995-5

Unfortunately, the original version of this article [1] contained errors in the main text and in Tables 2 and 3. Tables 2 and 3 were included incorrectly. The correct Tables 2 and 3 have been updated in the original article and are also included correctly in this erratum.
Table 2

Baseline characteristics of hemodialysis patients presented as groups according to MBL levels

PatientsP* < 0.001RP#
All (n = 107)MBL low 319 < ng/mL (n = 26)MBL high 319 ≥ ng/mL (n = 81)
MBL range (ng/mL)821 [319–1477]98 [33–146]1290 [671–1848]
Demographics
Age, years62.5 ± 15.665.3 ± 12.161.56 ± 16.60.3−0.26 0.007
Male gender, n (%)71 (66)17 (65)54 (67)1.0
Current diabetes, n (%)25 (24)9 (35)16 (20)0.2
Hypertension, n (%)85 (84)22 (88)63 (83)0.8
Cardiovascular history, n (%)26 (25)9 (35)15 (19)0.1
BMI, kg/m2 25.8 ± 4.427.0 ± 4.525.4 ± 4.40.1−0.030.8
Hemodialysis
Dialysis vintage, months25.5 [8.5–52.3]18.2 [7.0–47.7]32.8 [9.1–53.3]0.2−0.010.9
Primary renal disease, n (%)
Hypertension18 (17)4 (15)14 (17)1.0
Diabetes14 (13)5 (19)9 (11)0.3
ADPKD13 (12)3 (12)10 (12)1.0
FSGS9 (8)4 (15)5 (6)0.2
IgA nephropathy4 (4)0 (0)4 (5)0.6
Chronic pyelonephritis3 (3)0 (0)3 (4)1.0
Glomerulonephritis13 (12)2 (8)11 (14)0.7
Other diagnoses16 (16)6 (23)10 (12)0.2
Unknown17 (16)2 (8)15 (19)0.2
Ultrafiltration volume, L2.55 ± 0.782.54 ± 0.822.56 ± 0.780.9−0.010.9
Ultrafiltration rate, mL/kg/h8.56 ± 2.637.81 ± 2.398.80 ± 2.670.10.040.7
Systolic blood pressure
Predialysis, mmHg140.4 ± 25.1144.7 ± 26.4139.1 ± 24.70.3−0.170.08
Postdialysis, mmHg131.8 ± 25.6136 ± 24.3130.4 ± 26.00.4−0.24 0.02
Heart rate
Predialysis, bpm73 [63–82]71 [62–82]74 [64–82]0.30.110.3
Postdialysis, bpm79 [69–87]75 [65–86]79 [69–88]0.40.130.2
Kidney transplant, n (%)21 (20)4 (15)17 (21) 0.8
Laboratory measurements
Hematocrit, %34.9 ± 3.834.5 ± 4.135.0 ± 3.70.60.040.7
HbAlc, mmol/mol5.68 ± 0.985.80 ± 0.975.63 ± 0.980.5−0.150.2
Albumin, g/L39 [37–42]39 [37–42]39 [37–42]0.90.010.9
pH7.37 [7.34–7.39]7.37 [7.32–7.39]7.37 [7.34–7.39]0.70.050.6
Calcium, mmol/L2.31 ± 0.162.31 ± 0.152.32 ± 0.160.90.030.7
Phosphate, mmol/L1.67 ± 0.531.82 ± 0.471.65 ± 0.540.2−0.000.9
hsCRP, mg/L6.7 [2.8–10.9]6.1 [1.4–12.0]6.7 [3.0–10.9]0.70.100.3
Medication
Aspirin, n (%)57 (54)11 (42)46 (64)0.3
Calcium channel blockers, n (%)14 (13)3 (12)11 (14)1.0
β-Blocker, n (%)61 (57)18 (69)43 (53)0.2
ACE inhibitor, n (%)10 (10)3 (12)7 (9)0.7
AT2-receptor antagonists, n (%)14 (13)2 (8)12 (15)0.5
Statin, n (%)20 (19)5 (19)15 (19)1.0
Diuretics, n (%)8 (8)3 (12)5 (6)0.4

Italic values used to show which statistical testing was significant (below 0.05)

Data are presented as mean ± SD or median [IQR]

BMI body mass index, ADPKD autosomal dominant polycystic kidney disease, FSGS focal segmental glomerulosclerosis, HDA1c hemoglobin A1c, pH potential hydrogen, hsCRP high sensitive C-relative protein, ACE inhibitor angiotensin-converting-enzyme inhibitor, AT2 receptor antagonists Angiotensin II receptor antagonists

P* indicates P value for the difference in baseline characteristics between the MBL groups, tested by Student’s t test or Mann–Whitney U test for continuous variables and with χ2 test for categorical variables; R indicates Spearman correlation coefficient between MBL levels and the baseline characteristic; P# indicates the corresponding P value

Table 3

Associations of MBL levels with cardiovascular events and cardiac events in 107 chronic hemodialysis patients

Low MBLLog MBL continuous
HR95 % CI P HR (per SD)95 % CI P
Cardiovascular events
 Model 12.641.36–5.13 0.004 0.640.46–0.90 0.01
 Model 22.751.39–5.44 0.004 0.610.43–0.88 0.008
 Model 32.941.45–5.94 0.003 0.610.42–0.89 0.01
 Model 43.551.70–7.40 0.001 0.580.40–0.84 0.004
 Model 53.981.88–8.42<0.001 0.560.38–0.81 0.002
Cardiac events
 Model 12.601.10–6.18 0.03 0.710.46–1.100.1
 Model 22.491.04–5.96 0.04 0.730.46–1.160.2
 Model 32.651.08–6.55 0.03 0.740.47–1.180.2
 Model 43.821.48–9.87 0.006 0.620.38–1.010.06
 Model 53.961.49–10.54 0.006 0.590.35–0.98 0.04

Model 1: crude

Model 2: adjusted for age and gender

Model 3: adjusted for model 2 plus ultrafiltration volume and dialysis vintage

Model 4: adjusted for model 3 plus cardiovascular history, diabetes and post-HD systolic blood pressure

Model 5: adjusted for model 4 plus hsCRP

Data are presented as hazard ratio (HR) plus 95 % confidence interval (CI) according to the cut-off of MBL and per standard deviation (SD) MBL increase

Italic values used to show which statistical testing was significant (below 0.05)

MBL mannose-binding lectin, HD hemodialysis, hsCRP high sensitive C-reactive protein

Baseline characteristics of hemodialysis patients presented as groups according to MBL levels Italic values used to show which statistical testing was significant (below 0.05) Data are presented as mean ± SD or median [IQR] BMI body mass index, ADPKD autosomal dominant polycystic kidney disease, FSGS focal segmental glomerulosclerosis, HDA1c hemoglobin A1c, pH potential hydrogen, hsCRP high sensitive C-relative protein, ACE inhibitor angiotensin-converting-enzyme inhibitor, AT2 receptor antagonists Angiotensin II receptor antagonists P* indicates P value for the difference in baseline characteristics between the MBL groups, tested by Student’s t test or Mann–Whitney U test for continuous variables and with χ2 test for categorical variables; R indicates Spearman correlation coefficient between MBL levels and the baseline characteristic; P# indicates the corresponding P value Associations of MBL levels with cardiovascular events and cardiac events in 107 chronic hemodialysis patients Model 1: crude Model 2: adjusted for age and gender Model 3: adjusted for model 2 plus ultrafiltration volume and dialysis vintage Model 4: adjusted for model 3 plus cardiovascular history, diabetes and post-HD systolic blood pressure Model 5: adjusted for model 4 plus hsCRP Data are presented as hazard ratio (HR) plus 95 % confidence interval (CI) according to the cut-off of MBL and per standard deviation (SD) MBL increase Italic values used to show which statistical testing was significant (below 0.05) MBL mannose-binding lectin, HD hemodialysis, hsCRP high sensitive C-reactive protein Additionally, the following section has been corrected: However, after adjustment MBL for these confounders levels remained associated with cardiovascular events, indicating a direct and independent effect of MBL on cardiovascular risk. Should read: However, after adjustment for these confounders, MBL levels remained associated with cardiovascular events, indicating a direct and independent effect of MBL on cardiovascular risk.
  1 in total

1.  Strong predictive value of mannose-binding lectin levels for cardiovascular risk of hemodialysis patients.

Authors:  Felix Poppelaars; Mariana Gaya da Costa; Stefan P Berger; Solmaz Assa; Anita H Meter-Arkema; Mohamed R Daha; Willem J van Son; Casper F M Franssen; Marc A J Seelen
Journal:  J Transl Med       Date:  2016-08-05       Impact factor: 5.531

  1 in total
  2 in total

1.  Soluble CD59 in peritoneal dialysis: a potential biomarker for peritoneal membrane function.

Authors:  Bernardo Faria; Mariana Gaya da Costa; Carla Lima; Loek Willems; Ricardo Brandwijk; Stefan P Berger; Mohamed R Daha; Manuel Pestana; Marc A Seelen; Felix Poppelaars
Journal:  J Nephrol       Date:  2020-12-11       Impact factor: 3.902

2.  Intradialytic Complement Activation Precedes the Development of Cardiovascular Events in Hemodialysis Patients.

Authors:  Felix Poppelaars; Mariana Gaya da Costa; Bernardo Faria; Stefan P Berger; Solmaz Assa; Mohamed R Daha; José Osmar Medina Pestana; Willem J van Son; Casper F M Franssen; Marc A Seelen
Journal:  Front Immunol       Date:  2018-09-13       Impact factor: 7.561

  2 in total

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