G Abuelo

LH Lehman

M Maclure

M Ostermann

RL Mehta

S Bagshaw

Li-wei H. Lehman

Mengling Feng

Yijun Yang

Roger G. Mark

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Blood Pressure and the Risk of Acute Kidney Injury in the ICU: Case-Control Versus Case-Crossover Designs

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Chapter 25
Blood Pressure and the Risk of Acute
Kidney Injury in the ICU: Case-Control
Versus Case-Crossover Designs
Li-wei H. Lehman, Mengling Feng, Yijun Yang and Roger G. Mark
Learning Objectives
Introduce two different approaches, a case-control and a case-crossover design, to
study the effect of transient exposure of hypotension on the risk of acute kidney
injury (AKI) development in intensive care unit (ICU) patients.
25.1 Introduction
Acute kidney injury (AKI) refers to a rapid decrease in kidney function, occurring
over a period of days. The presence of AKI can be detected using well-established
deﬁnitions based on serum creatinine rise or urine output reduction [1]. Acute
kidney injury has been reported in 36 % of all patients admitted to the intensive
care unit ICU [2, 3]. A prior study showed that hospital patients with even very
small increases in their serum creatinine (0.3–0.4 mg/dL) have 70 % greater risk of
death than patients without creatinine increase [4]. Although the relationship
between low blood pressure and kidney function is well documented in an
experimental setting based on animal data [5], the association between hypotension
and acute kidney injury in a critical care setting is not completely understood.
This chapter describes two different approaches for studying blood pressure and
the risk of AKI development in ICU patients using the MIMIC II database [6]. In
our ﬁrst study, we adopted a traditional case-control approach and examined the
association between hypotension and AKI by comparing blood pressure measure-
ments of patients who had AKI (case) with patients without AKI (control) [7, 8].
Blood pressure measurements immediately prior to patients’ AKI onset were
compared with blood pressure measurements of the controls sampled from a similar
time window.
In the second study, we adopted a case-crossover design in which each patient
serves as his or her own control. Blood pressure measurements immediately prior to
each patient’s AKI onset were compared with the same patient’s blood pressure
© The Author(s) 2016
MIT Critical Data, Secondary Analysis of Electronic Health Records,
DOI 10.1007/978-3-319-43742-2_25
369
measurements sampled from an earlier time window while that patient’s kidney
functions were still stable. In the remainder of the chapter, we highlight the key
differences and the design rationale of these two approaches. We applied these
analysis techniques to study the relationship between hypotension and AKI
development using the MIMIC II database, and present our preliminary ﬁndings.
25.2 Methods
25.2.1 Data Pre-processing
Nurse-veriﬁed mean arterial blood pressure (MAP) samples, recorded on an hourly
basis were used for the analysis. Blood pressure measurements from both invasive
arterial line and automated, non-invasive oscillometric methods were included in
the study. Our choice of MAP (rather than systolic blood pressure) for blood
pressure measurement was motivated by prior work [8] which demonstrated that
MAP provided more consistent readings across different measurement modalities in
the ICU. Blood pressure measurements were ﬁltered to remove values outside of
reasonable physiological bounds (MAP between 20 and 200 mmHg).
25.2.2 A Case-Control Study
In the case-control approach [7], we examined the effect of transient exposure to
hypotension (deﬁned as blood pressure falling below speciﬁed thresholds) and the
risk of AKI development by comparing blood pressure measurements of patients
who experienced AKI (case) with patients who never developed AKI in the ICU
(control). AKI was deﬁned as an acute increase in serum creatinine  0.3 mg/dL,
or an increase of  50 % in serum creatinine within 48 h, based on the Acute
Kidney Injury Network (AKIN) deﬁnition [1]. Blood pressure measurements (from
up to a 48 h window) prior to patients’ AKI onset were compared with blood
pressure measurements of the controls from a time window prior to the last crea-
tinine measurement time.
Patients were selected from among the adult ICU stays in the MIMIC II [8]
database. We examined adult ICU stays (patients  15 years of age) with at least 2
serum creatinine values. Patients with fewer than 2 serum creatine values in their
ICU stay or evidence of end-stage renal disease (ESRD) were excluded.
Among the remaining 16,728 adult ICU stays that had at least 2 creatinine
measurements without evidence of end-stage renal disease, AKI occurred in 5207
(31 %). The remaining 11,521 cases were identiﬁed as the controls. The average
AKI onset time was 2.34 days after ICU admission. For the controls, the last
creatinine sample time was, on average, 2.76 days after ICU admission. Figure 25.1
370 25 Blood Pressure and the Risk of Acute Kidney Injury …
plots the population mean and standard error of median MAP up to 3 days prior to
the AKI onset for the AKI cohort, or prior to the last creatinine measurement time
for the controls. Note that mean arterial blood pressure of the AKI cohort diverged
from that of the controls prior to the AKI onset.
We studied the risk of AKI in ICU patients as a function of both the severity and
duration of hypotension. Blood pressure features extracted from the target 48-h
window were examined as primary predictors for AKI, including the minimum
MAP and maximum number of hours that MAP was continuously less than several
different thresholds (from 80 to 45 mmHg). Duration of hypotension below a
speciﬁc threshold was calculated based on linear interpolated blood pressure
samples. Hypotensive episodes were considered to begin and end when the inter-
polated blood pressure values intercepted the target threshold. Hypotensive epi-
sodes that were less than one hour apart were merged to form one continuous
episode.
Univariate and multivariable logistic regressions were performed to ﬁnd corre-
lations between hypotension and AKI. Age, SAPS-I, admission creatinine, and the
−3 −2.5 −2 −1.5 −1 −0.5 0
75
76
77
78
79
80
81
82
83
84
85
M
AP
 (m
mH
g)
Time Before AKI Onset (Days)
 
 
No AKI
AKI
Fig. 25.1 The population mean (and standard error) of median MAP up to 3 days prior to the
AKI onset for the AKI cohort, or prior to the last creatinine measurement time for the controls.
Mean arterial blood pressure of the AKI cohort diverged from that of the controls during day two
prior to the AKI onset, and both cohorts exhibited prominent diurnal variation
25.2 Methods 371
presence (based on ICD-9) of chronic renal failure (585.9), hypertension (401.9),
diabetes (250.00), coronary atherosclerosis (414.01), congestive heart failure
(428.0), and septic shock (785.52) or sepsis (038) were added as potential con-
founding factors [9].
Our results indicate that the odds of AKI were related to the severity of
hypotension with an odds ratio (OR) of 1.03, 95 % conﬁdence interval (CI) 1.02–
1.04 (p < 0.0001) per 1 mmHg decrease in minimum MAP ≤ 80 mmHg.
Multivariable analysis on hypotension duration involved 3203 patients who had
SAPS-I scores and with at least 45 h of blood pressure samples in the target 48-h
window. Our results indicate that the duration of time that the patient’s MAP was
continuously less than or equal to 70, 65, 60, 55, and 50 mmHg were signiﬁcant
risk factors in AKI development. Further, as the extent of hypotension worsened,
the incremental risk for AKI from each additional hour of continuous hypotension
increased for each 10 mmHg drop in MAP below 80 mmHg. For each additional
hour MAP was less than 70, 60, 50 mmHg, the odds of AKI increased by 2 % (OR
1.02, 95 % CI 1.00–1.03, p = 0.0034), 5 % (OR 1.05, 95 % CI 1.02–1.08,
p = 0.0028), and 22 % (OR 1.22, 95 % CI 1.04–1.43, p = 0.0122) respectively. As
the degree of hypotension worsened, the increased odds for AKI from each addi-
tional hour of continuous hypotension more than doubled for each 10 mmHg drop
in MAP below 80 mmHg. Our results also suggest that the severity of hypotension
signiﬁcantly shortened the time to the onset of AKI.
25.2.3 A Case-Crossover Design
In the second study, we adopted a case-crossover cohort design to examine the
effect of transient exposure to hypotension and the risk of AKI. The case-crossover
design was devised to assess the relationship between transient exposures and acute
outcomes in situations where the control series of a case-control study is difﬁcult to
achieve. In the case-crossover design, subjects serve as their own matched controls
deﬁned by prior time periods in the same subject. Given a transient exposure with
stable prevalence over time, the case-crossover design uses the difference in
exposure rates just before an event (case) with those at other time points in the
subject’s history (controls) to estimate an odds ratio of the outcome associated with
exposure. The case-crossover design was ﬁrst proposed by Maclure et al. to study
the effects of transient changes on the risk of acute events [10]. One advantage of a
case-crossover design is that it avoids control selection bias and eliminates
between-patient confounding factors [10, 11]. In this study design, the AKI deﬁ-
nition is based on hourly urine output (instead of daily creatinine measurements) in
order to determine a more precise timing of the acute (oliguria) onset.
Adult patients with normal kidney function (i.e. urine output remaining at
0.5 ml/kg/h or above) during the ﬁrst 12 h in the ICU, who subsequently developed
372 25 Blood Pressure and the Risk of Acute Kidney Injury …
AKI/oliguria (urine output remains below 0.5 ml/kg/h for at least 6 h) in the ICU
were included in the study. The same patients, prior to developing AKI/oliguria,
were used as controls. The AKI/oliguria onset was deﬁned as the beginning of the
6-h period when urine output remained below 0.5 ml/kg/h.
The minimum MAP from the 3 h period prior to the AKI onset was used as
exposure for the cases. The minimum MAP from a 3-h control period during the
ﬁrst 12 h in the ICU, when the same patient’s renal function was still normal, was
used as exposure for the controls. Since the blood pressure measurements during
the ﬁrst 6 h patients were in the ICU can be sparse, we chose the control period to
be the 7th–9th hour from the beginning of the patients’ ICU stays. Blood pressure
measurements were ﬁltered to remove outliers as before.
Case-crossover designs are typically analyzed using conditional logistic
regression, as it accounts for the matched nature of the data. It is analogous to a
matched case-control study, where one compares a ‘case’ person-moment with a
series of ‘control’ person-moments from different subjects, while in the
case-crossover design, the ‘control’ person-moments are from the same subject. We
implemented the latter approach for analyzing case-crossover study data. In addi-
tion, time-varying confounding factors (mechanical ventilator, vasopressors, tem-
perature, heart rate, white blood cell count, SpO2) were included in the
multivariable conditional logistic regression model.
The total cohort included 911 adult ICU stays (29.86 % MICU, 21.73 % SICU,
22.94 % CCU, 25.47 % CSRU) from the MIMIC II database. The median time to
AKI/oliguria onset was 45 h. The population median of the minimum MAP mea-
surements during the control and case periods were 73 mmHg with an inter-quartile
range of [65, 83] mmHg, and 70 [62, 79] mmHg respectively. A paired signed
T-test indicates that the minimum MAP during the case period is statistically sig-
niﬁcantly lower than during the control period (p-value = 0.0001). Our results
indicate that the odds of AKI were related to the severity of hypotension with an
odds ratio (OR) of 1.035, 95 % conﬁdence interval (CI) 1.024–1.045 (p < 0.0001)
per 1 mmHg decrease in minimum MAP in multivariable conditional logistic
regression after adjusting for temperature, heart rate, SpO2, white blood cell count,
and the use of mechanical ventilation and vasopressors. Furthermore, we performed
a similar analysis to understand if the risk of developing AKI increases associated
with the worsened hypotension treating the minimum MAP at the binary variable
using cutoff of 70, 65, 60, 55, and 50 mmHg. The adjusted odds ratios and 95 % CI
for the minimum MAP < 70, MAP < 65, MAP < 60, MAP < 55, and MAP < 50
(vs. when MAP was greater than or equal to the respective thresholds) were 1.854
(1.44–2.38), 1.945 (1.502–2.519), 2.096 (1.532–2.869), 2.002 (1.307–3.065), and
2.107 (1.115–3.982), respectively. These ﬁndings are consistent with the results
described in the previous section using a case-control study design.
25.2 Methods 373
25.3 Discussion
In the study of the association of hypotension with AKI, the case-crossover design
is an efﬁcient alternative to the case-control approach. The case-crossover design,
based exclusively on the case series, performs within-subject comparisons of blood
pressure measurements from the case and the control periods to estimate the rate
ratio of the AKI outcome associated with hypotension. This design inherently
removes the biasing effects of unmeasured, time-invariant confounding factors from
the estimated rate ratio.
Many factors, (including chronic kidney disease, hypertension, diabetes) could
potentially contribute to the development of AKI in an ICU setting. In a traditional
case-control design, these time-invariant between-patient confounders (as well as
the time-varying confounders) would have to be included to adjust for the baseline
risk of AKI development. In some cases, these confounding variables can be dif-
ﬁcult to determine from a retrospective ICU database. In a case-crossover design,
each patient’s blood pressure during normal renal function is compared with the
same patient’s blood pressure immediately prior to AKI onset, so that
time-invariant patient characteristics and confounders are eliminated in the analysis.
A case-crossover design may be a more efﬁcient approach in investigating the
transient effect of exposure (e.g. low blood pressure) on the risk of an acute out-
come (e.g. AKI development), when the heterogeneity in the baseline risk may be
difﬁcult to account for in the conventional case-control design.
We acknowledge the following limitations in the current study. First, this was a
retrospective study, and as such, the incidence of hypotension prior to AKI does not
prove a causal mechanism. Second, we did not account for the presence of fluid and
several interventions (e.g. contrast agents, NSAIDs, aminoglycosides, ACEI, etc.)
that may impair renal function in our multivariable analysis. As part of future work,
additional time-varying confounders (such as, usage of Lasix within 6 h, IV fluid,
creatinine, time of AKI onset) could be included in the model.
25.4 Conclusions
We have presented two different approaches, a case-control and a case-crossover
design, to study the effect of transient exposure to hypotension on the risk of AKI
development in ICU patients. Results from multivariable analysis in both studies
indicate that hypotension is a statistically signiﬁcant risk factor in the development
of AKI in the ICU. This study serves as an example to illustrate the utility of
case-crossover designs to study the association between a risk factor and the sub-
sequent disease development in an EHR-based retrospective clinical analysis.
Open Access This chapter is distributed under the terms of the Creative Commons
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4.0/), which permits any noncommercial use, duplication, adaptation, distribution and reproduction
374 25 Blood Pressure and the Risk of Acute Kidney Injury …
in any medium or format, as long as you give appropriate credit to the original author(s) and the
source, a link is provided to the Creative Commons license and any changes made are indicated.
The images or other third party material in this chapter are included in the work’s Creative
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Code Appendix
The code used in this case study is available from the GitHub repository accom-
panying this book: https://github.com/MIT-LCP/critical-data-book. Further infor-
mation on the code is available from this website.
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25.4 Conclusions 375


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Blood Pressure and the Risk of Acute Kidney Injury in the ICU: Case-Control Versus Case-Crossover Designs

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