Download - Effect of ionized serum calcium on outcomes in acute kidney injury needing renal replacement therapy: secondary analysis of the acute renal failure trial network study

Effect of ionized serum calcium on outcomes in acute kidneyinjury needing renal replacement therapy: Secondary analysis ofthe Acute Renal Failure Trial Network Study

Farsad Afshinnia, MD, MS,Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor VAMedical Center, Michigan

Karen Belanger, MS,University of Michigan, Ann Arbor VA Medical Center, Michigan

Paul M. Palevsky, MD [Chief], andRenal Section, VA Pittsburgh Healthcare System; Professor of Medicine and Clinical &Translational Science, University of Pittsburgh School of Medicine

Eric W. Young, MD, MS [Professor]Medicine, Department of Internal Medicine, Division of Nephrology, University of Michigan, AnnArbor VA Medical Center, Michigan

Farsad Afshinnia: [email protected]; Karen Belanger: [email protected]; Paul M. Palevsky:[email protected]; Eric W. Young: [email protected]

Abstract

Background—Hypocalcemia is very common in critically ill patients. While the effect of

ionized calcium (iCa) on outcome is not well understood, manipulation of iCa in critically ill

patients is a common practice. We analyzed all-cause mortality and several secondary outcomes in

patients with acute kidney injury (AKI) by categories of serum iCa among participants in the

Acute Renal Failure Trial Network (ATN) Study.

Methods—This is a post hoc secondary analysis of the ATN Study which was not preplanned in

the original trial. Risk of mortality and renal recovery by categories of iCa were compared using

multiple fixed and adjusted time-varying Cox regression models. Multiple linear regression

models were used to explore the impact of baseline iCa on days free from ICU and hospital.

Results—A total of 685 patients were included in the analysis. Mean age was 60 (SD=15) years.

There were 502 male patients (73.3%). Sixty-day all-cause mortality was 57.0%, 54.8%, and

54.4%, in patients with an iCa <1, 1–1.14, and ≥1.15 mmol/L, respectively (P=0.87). Mean of

days free from ICU or hospital in all patients and the 28-day renal recovery in survivors to day 28

were not significantly different by categories of iCa. The hazard for death in a fully adjusted time-

varying Cox regression survival model was 1.7 (95% CI: 1.3–2.4) comparing iCa <1 to iCa ≥1.15

mmol/L. No outcome was different for levels of iCa >1 mmol/L.

Corresponding Author: Farsad Afshinnia, Address: 3914 Taubman Center, 1500 E. Medical Center Dr., SPC 5364, Ann Arbor, MI48109-5364, Office: 734-764-3469, Fax: 734-936-9621, [email protected].

NIH Public AccessAuthor ManuscriptRen Fail. Author manuscript; available in PMC 2014 November 01.

Published in final edited form as:Ren Fail. 2013 ; 35(10): 1310–1318. doi:10.3109/0886022X.2013.828258.

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Conclusion—Severe hypocalcemia with iCa <1 mmol/L independently predicted mortality in

patients with AKI needing renal replacement therapy.

Keywords

Acute kidney injury; Mortality; Renal replacement therapy; Hypocalcemia; Renal recovery;Length of stay

Introduction

The serum ionized calcium (iCa) is directly associated with smooth muscle and left

ventricular contractility.1–3 These observations have been confirmed in chronic stable

hemodialysis patients4,5 with a mechanistic underpinning6 that has been used to justify

targeting higher serum iCa levels in critically ill patients with multi-organ failure.

Particularly in patients receiving continuous renal replacement therapy, regional citrate

anticoagulation allows targeting a desired serum iCa level through changes in the calcium

and citrate infusion rates. However, the theoretical concept of achieving a better

hemodynamic status in critically ill patients receiving renal replacement therapy by targeting

a high-normal range of iCa is primarily an extrapolation of observations in chronic stable

dialysis patients. In fact there are no randomized controlled clinical trials that show a

survival benefit by targeting a specific level of serum iCa in critically ill patients with acute

kidney injury (AKI). On the other hand, there could even be harm associated with excessive

utilization of calcium supplementation by targeting high-normal or high levels of serum iCa

in AKI including cardiac arrhythmias, metastatic calcification, nephrolithiasis, and renal

tubular acidosis.7–12 This study is aimed to investigate the association between different

levels of serum iCa concentrations with several clinical outcomes including 60-day all-cause

mortality (primary outcome), 28-day renal recovery, days free from the ICU, days free from

the hospital and mean arterial pressure (MAP), in critically ill ICU patients with AKI

needing renal replacement therapy.

Methods

This study is a post hoc secondary analysis of the Acute Renal Failure Trial Network (ATN)

Study. The primary study results have been previously published.13,14 The ATN Study was

a multicenter, randomized, clinical trial aimed at comparing the outcomes of different

intensities of renal replacement therapy in critically ill patients with AKI due to acute

tubular necrosis (ATN), conducted in 27 centers across the United States. Eligible patients

were 18 years of age or older, critically ill with AKI consistent with ATN needing renal

replacement therapy and accompanied by sepsis or failure of at least one non-renal organ

system. After screening, enrolled eligible patients were randomly assigned to two different

intensities of renal replacement therapy using a centralized computer-generated adaptive

randomization scheme. Assigned interventions were delivered for up to 28 days after

randomization or until renal recovery, discharge from the ICU, withdrawal of care, or death.

Patients were followed for up to 60 days to ascertain the primary end point of all-cause

mortality.

Afshinnia et al. Page 2

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After obtaining local institutional review board approval, we requested and received the

study dataset from the NIDDK central repository. All data files were reviewed and all

patients with valid measurements of serum iCa at baseline were included. Ionized calcium

was categorized to less than 1 mmol/L (severe hypocalcemia), 1 to 1.14 mmol/L (mild

hypocalcemia), and 1.15 mmol/L or more according to existing classification.15 The same

cut-points were applied to categorize iCa in subsequent days, as well as for the classification

of the time-averaged iCa during ICU stay. Pressor support was defined as use of any type of

pressor (epinephrine, norepinephrine, phenylephrine, dopamine, dobutamine, vasopressin) at

any point throughout the study from baseline to post-randomization days of 1 to 14, 21, and

28. Renal recovery among survivors to day 28 was defined as being off dialysis by day 28.

Days free from the ICU/hospital was defined as the number of days from ICU/hospital

discharge until 60 days after randomization or death, whichever occurred first. MAP was

calculated from systolic and diastolic blood pressures throughout the study from baseline to

days 1 to 14, 21 and 28 after randomization. In this cohort 1124 patients were randomized.

Five patients were excluded due to erroneous levels of iCa at baseline and 434 others were

excluded due to unmeasured serum iCa at baseline. The final analysis included 685 patients.

Statistical analysis

Mean ± standard deviation or counts and percentages were used to describe the distribution

of continuous and categorical variables, respectively. Median values and interquartile range

were used when the distribution of variables was skewed. The Chi-square test was used to

compare categorical variables across categories of iCa. Analysis of variance was used to

compare the mean of continuous variables across the categories of iCa. Bonferroni

correction with post hoc analysis was used to identify statistically significant differences

among iCa groups, correcting for multiple measurements. We took two different approaches

to assess mortality and renal recovery outcomes. First, Cox regression survival models were

applied to test the prognostic value of baseline as well as time-varying iCa on 60-day

mortality and 28-day renal recovery. As iCa was measured at irregular intervals and with

various frequencies, the last measured iCa was used and carried forward to next

measurement or to outcome, in the construct of time-varying survival models. The

covariates in the fully adjusted survival models included age, gender, race, baseline

components of ATN study predictive risk model for 60-day mortality16, and time varying

covariates during study including number of pressor agents per day, system Sequential

Organ Failure Assessment (SOFA) scores, MAP, and mechanical ventilation. In an

alternative approach, time-averaged iCa during ICU stay for each patient was calculated

assuming a linear trend between subsequent measurements, weighted by the number of days

between the observations. For example, an iCa of 1.2 mmol/L followed by an iCa of 1.3 in

two days, yields a value of 1.25 mmol/L weighted by two days. The sums of such weighted

values were then divided by the number of days between the first and last measured iCa

during ICU stay to result in the time-averaged iCa for a given individual during the study

period. Then, different subgroups of the time-averaged iCa during ICU stay were used to

compare their mortality odds ratio versus reference category (time-averaged iCa≥1.15

mmol/l), using multiple logistic regression models. To study the effect of the change in iCa

on mortality over time by change from below 1 to ≥1 mmol/L, in addition to testing in Cox

models, we categorized the patients in to four subgroups: A)- patients whose serum iCa



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remained 1 mmol/L or above throughout the study; B)- patients with an initial iCa less than

1 mmol/L but with subsequent levels of ≥1mmol/L; C)- patients with an initial iCa≥1

mmol/L but with subsequent level <1 mmol/L; D)- and patients whose serum iCa remained

<1 mmol/L throughout the study. Then multiple logistic regression models were used to

explore the mortality odds ratio of subgroups versus group A as the reference category.

To test the independent effect of iCa on days-free from the ICU and hospital, multiple linear

regression models with multivariable adjustments were applied. A mixed model with iCa as

a repeated measure was applied to show its variability throughout the study and to test its

independent effect on MAP. The baseline components of ATN Study predictive risk model

for 60-day mortality were imputed by application of highly interrelated variables using

multiple linear regression models. The survival models were calculated with and without

imputation. P values of less than 0.01 for differences in the baseline variables are declared.

Analyses were performed using SAS version 9.2, and SPSS version 20.

Results

Among the 685 patients entered into this study, the mean age was 60 years (SD = 15) and

502 were male (73.3%). The median number of measurements of iCa after randomization

was four with an interquartile range of 2 to 9. As shown in Table 1, there was a graded

increase in proportion of post-surgical AKI from the lowest to the highest category of

baseline iCa (p<0.001). Nephrotoxic ATN had the lowest proportion in the first category as

compared to other categories (p=0.009). There was also a graded decrease in severity of

cardiovascular SOFA score from the lowest to the highest baseline iCa (p=0.002). Other

variables were not significantly different among the categories of baseline iCa. Table 2

shows the management of renal replacement therapy using different modalities of dialysis

by categories of iCa. The delivered KT/V with IHD and the effluent flow with CVVHDF

were not significantly different across the categories of iCa. Figure 1 shows the patterns of

change in level of iCa during the ICU stay by baseline categories of iCa. Overall, mean of

iCa in patients with the baseline iCa< 1 mmol/L increased to more than 1.05 mmol/L after 3

days in survivors to day 3 and beyond.

Table 3 shows that there were no significant differences in the outcomes of 60-day

mortality, days free from ICU or hospital in all patients as well as in 28-day renal recovery

among survivors to day 28 by categories of baseline iCa. Figure 2, panel A (supplement

Table 2) shows the Cox regression survival modeled hazard ratio (HR) of 60-day mortality

by categories of baseline iCa as well as iCa as a time varying variable, with increasing

degrees of adjustment, using iCa ≥ 1.15 mmol/L as the reference group (HR=1).

Accordingly, when categories of iCa at baseline were compared, there was no difference in

the risk of mortality across the categories (Model 1). However, when iCa was entered as a

time-varying variable either in an unadjusted manner (Model 2) or in partially to fully

adjusted models (Models 3 and 4), iCa less than 1 mmol/L as compared to level ≥ 1.15 was

an independent predictor of 60-day all-cause mortality. Similar approach did not show any

difference in outcome of renal recovery by 28 day (panel B, Models 1 to 4, and supplement

Table 2). Similarly, days free from ICU and Hospital were not associated with categories of

serum iCa according to multiple linear regression models (supplement Table 3). Application



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of a mixed model revealed no association between MAP and the level of iCa during ICU

stay (supplement Table 4). Figure 3 shows the adjusted HR of mortality in the lowest versus

the highest category of iCa by clinical subgroups. A low iCa was associated with increased

mortality risk in all subgroups although statistical significance was not reached for age ≤ 60,

black and other races, baseline total SOFA score < 15, Cleveland ICU Acute Renal Failure

score < 13, age adjusted Charlson score < 4, and baseline albumin < 2.3 g/dL.

In an alternative approach baseline characteristics of the patients were compared by

categories of time-averaged iCa during ICU stay (supplement Table 1) which showed no

significant differences in distribution of baseline variables as compared to Table 1. Using

multiple logistic regression analysis, a time-averaged iCa of less than 1 mmol/L, and not iCa

of 1 to 1.14 mmol/L throughout stay in ICU as compared to iCa of 1.15 or above was

associated with higher odds of 60-day mortality in different models from unadjusted to fully

adjusted (supplement Table 5). Similar table shows that the 28-day renal recovery has not

been different by levels of the time-averaged iCa during ICU stay. Supplement Figure 1

shows the change in the level and direction of iCa during the ICU stay by subgroups of

patients defined by iCa trend. Supplement table 6 shows that patients who continued to have

an iCa below 1 mmol/L during ICU stay had a significantly higher odds of 60-day mortality

as compared to those who had iCa above 1 mmol/L, in several unadjusted to fully adjusted

models. Similarly those with a low iCa (<1 mmol/L) who achieved iCa>1 mmol/L in

subsequent days had a mortality similar to patient with iCa>1 mmol/L at all times.

Discussion

In this study, the 60-day all-cause mortality, 28-day renal recovery, days free from ICU and

hospital were not significantly different by the levels of baseline iCa. MAP during ICU stay

was not dependent on absolute values of iCa, and multivariable models did not show any

relationship between iCa with renal recovery, days free from hospital or ICU. However,

survival models using iCa as a time-varying variable suggest that serum iCa<1 mmol/L

compared to iCa≥1.15 mmol/L independently predicts short-term mortality. This is

consistent with results from logistic regression models which have used categories of a time-

averaged iCa during ICU stay.

Chernow et al17 reported a study of 259 ICU patients, finding that those with hypocalcemia

had a higher mortality, a longer duration of stay in the ICU, and higher likelihoods of sepsis,

renal failure and blood transfusion as compared to the normocalcemic group. Desai et a18

studied 108 critically ill patients admitted to the ICU and found mortality rates of 44% in

patients with hypocalcemia compared to 17% in patients without hypocalcemia. In a study

of 199 patients, Zivin et al19 demonstrated that iCa was inversely correlated with the

APACHE score and, therefore, suggested that higher mortality observed with hypocalcemia

might be a reflection of severity of disease. In a larger study from the Helsinki University

Hospital, Hastbacka et al reported the hypocalcemia rate of up to 85% in 993 critically ill

patients defined as iCa less than 1.16 mmol/L.20 Although the investigators showed a higher

risk of mortality among patients with hypocalcemia, hypocalcemia did not appear to be an

independent risk factor for mortality after multivariable adjustment for severity of disease at

baseline as measured by the APACHE score. Their analysis, however, was limited to use of



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a single baseline measurement of iCa per patient and therefore did not take into account the

impact of changes in serum iCa over time or the duration of time at each level of iCa. In a

cohort of 7024 critically ill patients from four medical centers, Egi et al15 used a time

weighted approach to account for the level of iCa during critical care and found a graded

inverse relationship between mortality and serum iCa even after multivariable adjustments.

This approach has allowed the investigators to capture worse outcome attributable to

changes of iCa over time. In our study, other than use of time-varying Cox survival models,

we also calculated a time-averaged iCa during ICU stay and compared risk of mortality

across its categories using logistic regression models, and found similar higher mortality risk

with iCa<1 mmol (Supplement table 5). Similar results from the two approaches suggest that

the latter has been able to capture the higher mortality attributed to change of iCa over time,

a phenomenon which was captured similarly with Cox models. Our findings are in

agreement with previous observations15,17–22 and can be considered as reconciling the

seemingly contradictory results of the studies by Hastbacka and Egi. Although the mortality

was not different by baseline level of iCa after adjusting for severity of disease, the time-

varying analysis accounting for change of iCa throughout ICU stay unmasked its prognostic

value to predict mortality. The reason that a time-varying Cox model and not the fixed

model has unmasked the prognostic value of iCa is that a significant number of patients with

a baseline iCa of above 1 mmol/L who subsequently died, dropped their iCa to a level of <1

mmol/L in later days prior to their death. On the other hand, significant number of other

patients with iCa<1 mmol/L at baseline who eventually survived, improved their iCa to a

level of ≥1 mmol/L in subsequent days, a phenomenon which could be unmasked by

application of a time-varying approach taking into account change of iCa in subsequent

days. Consistent with these findings, in an alternative approach, patients who continuously

had iCa<1 mmol/L throughout ICU stay had a significantly higher mortality odds ratio (OR)

as compared to patients who kept their iCa≥1 mmol/L at all time, while those severely

hypocalcemic patients at baseline with increased iCa to ≥1mmo/L in subsequent days didn’t

have different mortality OR as compared to those with iCa≥1 mmol/L at all times

(Supplement table 6).

Hypocalcemia is a common electrolyte abnormality in critically ill patients and in ICU

settings17,19,20. Although the etiology of hypocalcemia is unclear in the majority of critically

ill patients, proposed mechanisms include the effect of sepsis, impairment of parathyroid

hormone secretion, resistance of end-organs to the function of parathyroid hormone,

alterations in calcium-sensing receptor gene transcription via proinflammatory cytokines,

and intracellular accumulation of calcium.21–26 Other less frequent causes of hypocalcemia

in this patient population include acute pancreatitis, massive transfusions and vitamin D

deficiency. Calcium has numerous crucial roles in the cellular function of almost every

system. It is part of signal transduction pathways, contributes to cell membrane potential and

nerve conduction, triggers muscle contraction, is a cofactor of many enzymes and acts as the

second messenger of many hormones that regulate metabolism and gene expression.3,27

Although, it is not yet clear, whether or not the association between hypocalcemia with

higher mortality reflects a cause and effect relationship, the increase from a low iCa along

with improvement in severity of disease, and weakening of mortality hazard ratio by further

adjustment for surrogates of severity (Figure 2, Panel A, model 4 compared to model 3)



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suggest that hypocalcemia itself may be a surrogate for disease severity rather than a

therapeutic target. Carlon et al28 showed no significant improvement in patient

hemodynamic variables with calcium supplementation in sepsis and trauma settings. Several

model systems have also shown worse outcomes with calcium supplementation, and

alleviation of cellular injury with lowering of the extracellular calcium concentration.29–33 A

systematic review of clinical trials reveals that no randomized controlled clinical trial has

ever evaluated the effect of calcium supplementation on mortality, multiple organ

dysfunction, length of stay in the ICU or hospital.34 In spite of that, given the crucial role of

calcium in metabolism and cellular function, recommendations have been made in favor of

supplementation to normalize the serum calcium in critically ill patients.19,21 However,

there is absolutely no evidence to suggest that within physiologic range any level of serum

iCa is associated with a better outcome. Given the lack of clinical trial evidence for a

beneficial effect of calcium supplementation on outcomes within physiologic and normal

limits, the intensity of calcium supplementation to target a pre-defined high-normal or high

level of iCa remains speculative.

Subgroup analysis revealed a consistent pattern of higher mortality risk in the lowest

category of iCa as compared to the highest category for most subgroups. The subgroup

exceptions were likely attributable to insufficient statistical power (for black race and other

races) as well as to the potential impact of additional comorbidities acting as competing risk

factors for death even at higher levels of iCa in younger patients and in those with less

severe illness such as the subgroups with total SOFA<15, CCFARF<13, and Charlson<4.

This study has several strengths. This is the second largest multicenter study of the

relationship between iCa and short term mortality and the analyses of main outcomes had

sufficient power. It also has highly accurate ascertainment of outcomes due to the clinical

trial origins of the study.13 Collection of severity of illness by multiple scoring systems as

well as comorbid conditions at baseline provided a unique opportunity to test the effect of

iCa after extensive adjustment for the most important prognostic variables. This study also

has several important limitations. Although this is a secondary analysis of a well-designed

clinical trial, it was not primarily designed to assess the effect of different levels of iCa

during the ICU stay on the outcomes. As a consequence, serum iCa was not measured

uniformly or consistently for everybody. Comparison of patients with and without iCa

measurement shows that the former group was sicker overall and had higher mortality

compared to the latter group (55.7% vs, 47.7%; supplement Table 7). Thus, differences in

patterns of measurement between patients may have introduced ascertainment bias,

characterized by a higher likelihood of measuring iCa in patients with more severe illness

with a magnitude corresponding to 7% higher mortality in the measurement group, and a

direction toward the sicker patients. However, as the median number of iCa measurements

was identical in all categories of baseline iCa (n=4, P=0.767), the patients’ characteristics

and outcomes were not significantly different by these categories, and as the differences in

risk of mortality manifested with follow up, we infer that the association of iCa with

mortality has not been impacted by ascertainment bias, and although the iCa measurements

were not protocol based, evidence for their randomness argues in favor of unbiased

estimations and therefore the derived conclusions. There were also up to 15% missing in a

few of the baseline covariates posing a significant attrition in sample size in multivariable



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models without imputation. However, as the results of survival models with and without

imputation were not significantly different, we chose to apply the dataset after imputation.

Another limitation is presumption of constancy of last measurement for subsequent

unmeasured iCa with the “last observation carried-forward” method in Cox survival models

which may not be true in every individual case and may have overestimated the effect of

hypocalcemia in some patients who have had a rapid correction. In another approach,

application of time-weighted averaged values between subsequent measures was an

alternative approach which has eliminated the effect of constancy of the pre-missing-value

measurements. As the results from the two approaches were similar, we infer that on

average the method of handling unmeasured iCa between subsequent measurements have

not impacted its relationship with mortality. This study is also unable to assess outcomes in

the hypercalcemic range because of the low prevalence of hypercalcemia. This study is

neither designed nor aimed to identify the impact of calcium supplementation on outcome.

Therefore, it cannot be inferred from the data how much calcium supplementation was used

for each patient. We believe that the safety and efficacy of calcium supplementation on hard

outcomes are best determined by randomized controlled clinical trials, but even in such trials

serum iCa can be and should be used as a reasonable monitoring index to separate arms of

the trials targeting different ranges of serum iCa using different intensities of calcium

supplementation. In this context this study which aimed testing the effect of different ranges

of serum iCa on the defined outcomes has successfully reached to its aims, irrespective of

how the level was achieved.

Conclusion

Cox survival models as well as analysis of time-averaged iCa with use of logistic regression

models suggested that hypocalcemia with iCa < 1.0 mmol/L was independent predictor of

higher mortality in critically ill patients with acute renal failure in need of renal replacement

therapy in the studied cohort. There is no evidence to suggest that above this level, different

values of iCa are necessarily associated with better outcome including better survival,

shorter ICU or hospital stay, better preservation of blood pressure independent of pressor

support, or a higher rate of renal recovery. Randomized controlled clinical trials are needed

to confirm the independent beneficial effect of calcium supplementation as well as to

determine the optimal serum iCa target in critically ill patients.

Supplementary Material

Refer to Web version on PubMed Central for supplementary material.

Acknowledgments

• The ATN Study was conducted by the ATN Investigators and supported by the Cooperative StudiesProgram of the Department of Veterans Affairs Office of Research and Development (VA) and theNIDDK. The data from the ATN study were supplied by the NIDDK Central Repositories. Thismanuscript was not prepared in collaboration with Investigators of the ATN study and does notnecessarily reflect the opinions or views of the ATN study, the VA, the NIDDK Central Repositories, orthe NIDDK. The authors also would like to thank Mallika Kommareddi for her remarks.

• F.A. is supported by grant 5T32DK7378-32.



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Key Messages

• Outcomes of 60-day all-cause mortality, renal recovery, days free from ICU,

days free from hospital and MAP during ICU stay in mild hypocalcemia (iCa of

1.0 to 1.14 mmol/L) were not different from normocalcemia (iCa≥1.15 mmol/L)

in critically ill patients with AKI needing renal replacement therapy.

• Outcomes of renal recovery, days free from ICU, days free from hospital, and

MAP during ICU stay in severe hypocalcemia (iCa<1.0 mmol/L) were not

different from normocalcemia (iCa≥1.15 mmol/L) in critically ill patients with

AKI needing renal replacement therapy.

• Severe hypocalcemia (iCa<1.0 mmol/L) appeared an independent predictor of

60-day all-cause mortality as compared to normocalcemia in critically ill

patients with AKI needing renal replacement therapy.

• Hypocalcemia may be a surrogate marker for severity of illness and not

necessarily a therapeutic target.

• Randomized controlled clinical trials are needed to determine the optimum level

of serum iCa and optimal supplementation in critically ill patients.



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Figure 1.Change of mean ionized calcium ± standard error during course of stay in ICU by categories

of baseline ionized calcium (mmol/L). Number of measurements per category per day is

shown in the table.



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Figure 2.Hazard ratio (95% confidence interval) of mortality and renal recovery outcomes:

Model 1: Unadjusted, using categories of baseline ionized calcium, Model 2: Unadjusted,

using ionized calcium as a time-varying variable, Model 3: Model 2, plus gender, race, and

baseline elements of ATN study predictive risk model for 60-day mortality, Model 4: Model

3, plus “mechanical ventilation, mean arterial pressure, number of pressor agents per day,

and SOFA system (coagulation, cardiovascular, liver, central nervous system, respiratory)

during ICU stay” all as time-varying covariates.



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Figure 3.Hazard ratio of all-cause mortality in ionized calcium < 1 mmol/L compared to ionized

calcium ≥ 1.15 mmol/L by subgroups of patient’s characteristics and baseline study

variables, according to fully adjusted model (model 4)



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Table 1

Comparison of baseline characteristics in patients with acute kidney injury by level of baseline ionized serum

calcium, using analysis of variance with Bonferroni post hoc analysis for multiple comparisons

Variables < 1 mmol/L,n=186

1–1.14 mmol/L,n=343

≥ 1.15 mmol/L,n=156

Age (yrs) 57.7 ± 15.7 60.7 ± 15.0 61.3 ± 14.4

Sex

Male (%) 138 (74.2) 256 (74.6) 108 (69.2)

Female (%) 48 (25.8) 87 (25.4) 48 (30.8)

Race

White (%) 134 (72.0) 256 (74.6) 122 (78.2)

Black (%) 29 (15.6) 52 (15.2) 16 (10.3)

Others (%) 23 (12.7) 35 (10.2) 18 (11.5)

Post-open surgical AKI (%) * 69 (37.1) 193 (56.3) 98 (62.8)

Cause of AKI

Ischemic ATN (%) 151 (81.2) 281 (81.9) 136 (87.2)

Nephrotoxic ATN (%) * 32 (17.2) 103 (30.0) 37 (23.7)

Septic ATN (%) 105 (56.5) 168 (49.0) 62 (39.7)

Multifactorial ATN 111 (59.7) 194 (56.6) 83 (53.2)

Mechanical Ventilation (%) 160 (86.0) 280 (81.6) 131 (84.0)

MAP (mmHg) 74.4 ± 16.3 74.6 ± 15.0 76.3 ± 13.8

Baseline SOFA

Respiratory 2.5 ± 1.1 2.5 ± 1.1 2.2 ± 1.1

Coagulation 1.4 ± 1.1 1.4 ± 1.2 1.4 ± 1.2

Liver 1.6 ± 1.3 1.5 ± 1.3 1.6 ± 1.4

Cardiovascular * 2.8 ± 1.6 2.4 ± 1.7 2.2 ± 1.7

Central nervous system 2.7 ± 1.4 2.7 ± 1.4 2.4 ± 1.4

Age adjusted Charlson score! 4.0 ± 3.4 4.3 ± 2.7 4.3 ± 2.6

APACHE II score! 27.9 ± 7.6 26.6 ± 7.3 25.9 ± 7.2

Cleveland Clinic ICU Score! 12.5 ± 3.4 12.3 ± 3.2 12.3 ± 3.2

Pressor support

Epinephrine (%) 12 (6.5) 35 (10.2) 22 (14.1)

Norepinephrine (%) 98 (52.7) 155 (45.2) 63 (40.4)

Phenylephrine (%) 22 (11.8) 35 (10.2) 15 (9.6)

Dopamine (%) 23 (12.4) 54 (15.7) 18 (11.5)

Dobutamine (%) 22 (11.8) 32 (9.3) 13 (8.3)

Vasopressine (%) 51 (27.4) 60 (17.5) 30 (19.2)

Other pressors (%) 1 (0.5) 15 (4.4) 10 (6.4)

*p<0.01;


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!Sample size from the first to the third categories of ionized calcium for Charlson score is 163,322, 136; for APACHE score 177, 326, 149, and for

Cleveland score it is 153, 293, and 122, respectively.


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Table 2

Management of renal replacement therapy by levels of ionized serum calcium

Variables < 1 mmol/L 1–1.14 mmol/L ≥ 1.15 mmol/L

Intermittent Hemodialysis (IHD)

Treatment provided (no.) 784 1311 761

Days of therapy (no./patient) 8.0 ± 6.3 7.0 ± 5.9 8.0 ± 6.7

Duration of session (hr) 4 ± 1 4 ± 1 4 ± 2

Blood flow (mL/min) 365 ± 61 351 ± 60 357 ± 61

Dialysate flow (mL/min) 738 ± 113 693 ± 139 697 ± 134

Net ultrafiltration (liters/treatment) 1.7 ± 1.3 1.9 ± 1.3 1.7 ± 1.3

Predialysis BUN (mg/dL) 55 ± 29 57 ± 31 53 ± 30

Postdialysis BUN (mg/dL) 19 ± 13 21 ± 15 18 ± 13

Anticoagulant

None (%) 485 (62.8) 961 (73.6) 514 (68.1)

Heparin (%) 249 (32.2) 310 (23.8) 195 (25.8)

Others (%) 38 (5.0) 33 (2.6) 46 (6.1)

KT/Vurea

First treatment 1.11 ± 0.31 1.04 ± 0.29 1.15 ± 0.39

Subsequent treatments 1.30 ± 0.20 1.22 ± 0.29 1.30 ± 0.21

Percentage of therapies by IHD 40.0 ± 35.1 44.2 ± 39.0 43.3 ± 40.0

Continuous venovenous hemodiafiltration

Treatment provided (no.) 999 1901 1084


Daily duration of therapy/patient (hr) 17.6 ± 6.7 18.0 ± 6.7 18.0 ± 6.8

Blood flow (mL/min) 141 ± 32 143 ± 42 150 ± 36

Dialysate flow (mL/hr) 1134 ± 453 1091 ± 430 1177 ± 387

Replacement flow (mL/hr) 1145 ± 375 1094 ± 407 1130 ± 364

Net ultrafiltration (mL/hr)# 100 [17, 215] 110 [33, 201] 100 [18, 185]

24-hr effluent volume (Liters) 41 ± 21 41 ± 21 42 ± 20

Mean daily BUN (mg/dL) 42 ± 23 44 ± 23 40 ± 23

Effluent flow

Prescribed (mL/kg/hr) 29.6 ± 8.1 28.4 ± 8.0 29.5 ± 8.4

Delivered (mL/kg/hr) 29.7 ± 9.0 29.7 ± 8.9 29.8 ± 9.4

Anticoagulant

None (%) 72 (51.4) 272 (64.3) 323 (66.5)

Heparin (%) 54 (38.6) 87 (20.3) 85 (17.5)

Citrate (%) 14 (10.0) 55 (12.8) 20 (4.1)

Others (%) 3 (2.3) 15 (3.5) 58 (11.9)

Percentage of therapies by CVVHDF 56.6 ± 37.6 52.9 ± 40.3 55.7 ± 40.6


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Variables < 1 mmol/L 1–1.14 mmol/L ≥ 1.15 mmol/L

Sustained Low-efficiency dialysis

Treatments provided (no.) 62 92 23


Duration of session (hr) 8 ± 2 8± 4 10 ± 4

Blood flow (mL/min) 200 ± 0 226 ± 50 204 ± 30

Dialysate flow (mL/min) 252 ± 90 249 ± 124 230 ± 88

Net ultrafiltration (liters/treatment) 1.9 ± 1.6 1.4 ± 1.4 1.2 ± 1.1

Anticoagulant

None (%) 41 (66.1) 70 (76.9) 16 (76.2)

Heparin (%) 21 (33.9) 15 (16.5) 2 (9.5)

Others (%) 0 (0) 6 (6.6) 3 (14.3)

Percentage of therapies by SLED 3.4 ± 14.2 2.9 ± 14.4 1.0 ± 8.3

Isolated ultrafiltration

Treatments provided (no.) 28 50 39

Net ultrafiltration (Liters/treatment) 2.6 ± 1.4 2.5 ± 1.0 2.6 ± 1.0

#Median [Interquartile range]


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Table 3

Comparison of primary and secondary outcomes by base-line ionized calcium using analysis of variance with

Tukey post hoc correction for multiple comparisons; values are count (percentage) or mean ± standard error.

Variables < 1 mmol/L,n=186

1–1.14 mmol/L,n=343

≥ 1.15 mmol/L,n=156

Sixty-day mortality (%) 106 (57.0) 188 (54.8) 85 (54.5)

Renal recovery in survivors to day 28 (%)* 38 (39.6) 76 (41.5) 37 (43.0)

Days free from ICU by day 60 (days) 17 ± 1.6 19 ± 1.2 19 ± 1.8

Days free from hospital by day 60 (days) 10 ± 1.2 12 ± 1.0 12 ± 1.5

*Sample size in the first to the third category of ionized calcium for renal recovery is 109, 151, and 61, respectively.
