Open Access

Risk factors for intra-abdominal hypertension and abdominal compartment syndrome among adult intensive care unit patients: a systematic review and meta-analysis

  • Jessalyn K Holodinsky1,
  • Derek J Roberts2Email author,
  • Chad G Ball3,
  • Annika Reintam Blaser4,
  • Joel Starkopf4,
  • David A Zygun5,
  • Henry Thomas Stelfox6,
  • Manu L Malbrain7,
  • Roman C Jaeschke8 and
  • Andrew W Kirkpatrick9
Critical Care201317:R249

DOI: 10.1186/cc13075

Received: 10 June 2013

Accepted: 25 September 2013

Published: 21 October 2013

Abstract

Introduction

Although intra-abdominal hypertension (IAH) and abdominal compartment syndrome (ACS) are associated with substantial morbidity and mortality among critically ill adults, it remains unknown if prevention or treatment of these conditions improves patient outcomes. We sought to identify evidence-based risk factors for IAH and ACS in order to guide identification of the source population for future IAH/ACS treatment trials and to stratify patients into risk groups based on prognosis.

Methods

We searched electronic bibliographic databases (MEDLINE, EMBASE, PubMed, and the Cochrane Database from 1950 until January 21, 2013) and reference lists of included articles for observational studies reporting risk factors for IAH or ACS among adult ICU patients. Identified risk factors were summarized using formal narrative synthesis techniques alongside a random effects meta-analysis.

Results

Among 1,224 citations identified, 14 studies enrolling 2,500 patients were included. The 38 identified risk factors for IAH and 24 for ACS could be clustered into three themes and eight subthemes. Large volume crystalloid resuscitation, the respiratory status of the patient, and shock/hypotension were common risk factors for IAH and ACS that transcended across presenting patient populations. Risk factors with pooled evidence supporting an increased risk for IAH among mixed ICU patients included obesity (four studies; odds ratio (OR) 5.10; 95% confidence interval (CI), 1.92 to 13.58), sepsis (two studies; OR 2.38; 95% CI, 1.34 to 4.23), abdominal surgery (four studies; OR 1.93; 95% CI, 1.30 to 2.85), ileus (two studies; OR 2.05; 95% CI, 1.40 to 2.98), and large volume fluid resuscitation (two studies; OR 2.17; 95% CI, 1.30 to 3.63). Among trauma and surgical patients, large volume crystalloid resuscitation and markers of shock/hypotension and metabolic derangement/organ failure were risk factors for IAH and ACS while increased disease severity scores and elevated creatinine were risk factors for ACS in severe acute pancreatitis patients.

Conclusions

Although several IAH/ACS risk factors transcend across presenting patient diagnoses, some appear specific to the population under study. As our findings were somewhat limited by included study methodology, the risk factors reported in this study should be considered candidate risk factors until confirmed by a large prospective multi-centre observational study.

Introduction

Intra-abdominal hypertension (IAH) and abdominal compartment syndrome (ACS) are common and associated with substantial morbidity and mortality among critically ill adults [14]. These conditions have been linked with acute and chronic renal failure [59], multi-organ dysfunction syndrome (MODS) [10], increased lengths of intensive care unit (ICU) and hospital stay [10], and elevated mortality [5, 7, 10]. Unfortunately, it remains unknown if prevention or treatment (either surgical or medical) of IAH/ACS among these patients improves patient-important outcomes. Identifying critically ill patients at risk for IAH/ACS is therefore important in order to guide identification of the source population for future treatment trials and to stratify patients into risk groups based on prognosis [11].

As clinical examination is likely inadequate for diagnosis of elevated intra-abdominal pressure (IAP) [12, 13], trans-bladder pressure monitoring is frequently used to more accurately identify IAH and ACS [14]. The World Society of the Abdominal Compartment Syndrome (WSACS) recommends measuring IAP via the bladder when one or more risk factors for IAH or ACS are present [14]. However, as the risk factors proposed in the latest WSACS guideline were reported to be largely opinion- or pathophysiology-based and occur among nearly all of the patients admitted to the ICU, identifying evidence-based risk factors may better inform IAP screening practices [15].

Although a number of studies of IAH/ACS risk factors have been published, interpretation of their reported estimates of risk is difficult due to significant between-study clinical heterogeneity [1, 2, 9, 10, 1523]. Many of these studies included varying patient populations, ranging from purely medical [1, 2, 9, 15, 18, 19] to post-operative trauma and other surgical patients [16, 17, 20, 21, 23]. Several also used somewhat ambiguous descriptions (for example, blood glucose level [10] and fluid [1, 24] or crystalloid resuscitation [1, 2, 16, 17]) or varying thresholds or cutoffs (for example, crystalloid resuscitation >3 L or >7.5 L [17]) to define their proposed candidate risk factors. Finally, some of the studies defined IAH or ACS differently, and adjusted their estimates of risk for potential confounding factors to varying degrees.

In order to assist clinicians in comparing the risk of IAH or ACS development across varying patient populations, risk factor definitions, and study methodologies, we conducted a systematic review of IAH/ACS risk factors among adult ICU patients that utilized a formal narrative synthesis alongside a meta-analysis. As we sought to increase the awareness, dissemination, and use of the findings of this systematic review, we invited international members of the WSACS and WSACS Clinical Trials Working Group to be engaged across all phases of this study.

Materials and methods

Methods for inclusion of articles and analysis and reporting of their results were specified a priori in a protocol developed according to recommendations from the preferred reporting items for systematic reviews and meta-analyses (PRISMA) [25] and the meta-analysis of observational studies in epidemiology (MOOSE) [26] statements. We did not request ethical review of the study as this is not required by the University of Calgary Conjoint Health Research Ethics Board for systematic reviews and meta-analyses.

Search strategy

We searched Ovid MEDLINE and EMBASE, PubMed, the Cochrane Central Register of Controlled Trials (CENTRAL), and the Cochrane Database of Systematic Reviews from their first available date until January 21, 2013 without restrictions. Two investigators (DJR, AWK) created the initial MEDLINE search strategy. This strategy was then piloted and refined by another investigator (JKH) by adding additional thesaurus/indexing search terms when new and relevant citations were located [27]. Using a combination of Medical Subject Heading (MeSH)/Emtree terms and keywords, we constructed search filters covering the themes IAH/ACS, risk factors, and critical care (see Additional file 1: Table S1 for our final electronic search strategies). In order to identify additional citations, we also used the PubMed 'related articles’ feature, contacted content experts (including members of the WSACS), and manually searched bibliographies of included studies and relevant review articles. Finally, we wrote to the first or corresponding author of nine articles in order to clarify study procedures or obtain additional study data [1, 2, 9, 10, 17, 2023].

Study selection

Two investigators (JKH, DJR) independently screened the titles and abstracts of all identified citations. We used the following inclusion criteria: (1) study participants were adult (≥16 years old) ICU patients; (2) the study reported patient-level characteristics considered candidate risk factors for IAH or ACS; (3) IAH was reported to be diagnosed using trans-bladder pressure measurements [14, 28]; (4) odds ratios (ORs) or relative risks (RRs) (either adjusted or unadjusted for potential confounding factors) relating the candidate risk factor with the development of IAH or ACS were provided or could be calculated; and (5) the study design was observational. Although we defined and graded IAH and ACS according to the definitions developed by the WSACS [14], studies using alternate definitions or grading schemes for these conditions were also included. As outlined by the WSACS, primary ACS was considered to be ACS associated with injury or disease in the abdominopelvic region while secondary ACS included that not originating from the abdominopelvic region [14]. Disagreements between investigators regarding study inclusion were resolved by consensus.

Data extraction

The same two investigators extracted data independently using a pre-designed electronic data extraction spreadsheet piloted on a representative sample of five included studies. We extracted the following data from included studies: (1) design and setting, including ICU type; (2) study participant characteristics, including age, primary patient diagnosis (for example, trauma, intra-abdominal sepsis, or pancreatitis), and severity of illness (for example acute physiology and chronic health evaluation II (APACHE-II) [29], sequential organ failure assessment (SOFA) [30], and injury severity score (ISS) [31]); (3) indications used for IAP measurement; (4) whether the method of trans-bladder IAP measurement followed the recommendations of the WSACS (that is measurement via the bladder at end-expiration in the completely supine position with a maximal instillation volume of 25 mL and the transducer zeroed at the midaxillary line) [14]; (5) whether the patient was mechanically ventilated or breathing unassisted; (6) reported candidate risk factors for IAH or ACS and their exact definitions; and (7) the definition of IAH and ACS.

Risk of bias assessment

Risk of bias was assessed independently and in duplicate by two investigators (JKH, DJR) using the guidelines proposed by Hayden and colleagues for the evaluation of the quality of prognostic studies [32]. These guidelines assist in evaluating study patient participation and attrition; prognostic factor, outcome, and confounding factor measurement; and the conducted statistical analyses using a four-point ordinal scale (yes/partly/no/unsure) [32]. As the method of statistical data analysis may substantially influence the reported results of an observational study, we also examined whether each of the included observational studies met the more detailed recommendations developed by Moss and colleagues for reporting multivariable logistic regression analyses in the pulmonary and critical care literature [33]. These authors recommend that study investigators report the logistic regression equation developed for the analysis, name the statistical package utilized, identify the selected variables for inclusion in the model, and explain whether attempts were made to assess for inter-variable collinearity, effect measure modification, and model validity [33]. Several other study items of interest were also assessed, including study temporality (prospective versus retrospective), patient enrollment (consecutive versus non-consecutive), the definition of IAH and ACS, and the method of bladder pressure measurement (WSACS versus other) [14]. We also examined whether studies reported the ventilatory status of included patients and whether the patient was calm and/or abdominal muscular contractions were absent during IAP measurements.

Analysis

Following recommendations provided by Rogers and colleagues and Popay and coworkers on the conduct of narrative synthesis in systematic reviews [34, 35], we conducted a staged formal narrative synthesis of candidate risk factors alongside a random-effects meta-analysis.

We began by clustering the identified candidate risk factors for IAH and ACS separately into themes (for example, patient characteristics) and subthemes (for example, the disease severity of the patient as measured by a validated scale) without consideration of presenting patient diagnosis in order to identify those that transcended across patient populations [33]. Within subthemes, we then used vote counting [33] to summarize the direction (that is hazardous or protective) and strength of statistical evidence against the null hypothesis of no risk using a simple ordinal scale. This three-level ordinal scale summarized all identified patient-level characteristics as either a: (1) risk factor (OR point estimate and confidence interval (CI) >1), (2) an exposure that was neither hazardous nor protective (CI included 1), or (3) an exposure that was protective (OR and CI <1) [33].

Vote counting is a relatively novel narrative synthesis tool that can be used to identify patterns across heterogeneous data. It involves pre-determining categories (in this case subthemes) and then assigning 'data points’ (in this case a value of one for each risk factor from a study within a subtheme) to these categories [34, 35]. This type of descriptive tool subsequently allows for the creation of simple stacked bar charts, which provide a simple visual representation of how many reported potential risk factors were reported to have a hazardous, null, or protective effect across all of the identified observational studies.

Within subthemes, we then stratified each of the identified candidate risk factors into groupings according to presenting patient diagnosis (for example, trauma, pancreatitis, or mixed ICU patients) [33]. As only a few of the adjusted ORs for the reported risk factors had similar enough definitions (and were estimated from similar populations), only a select number of risk factor estimates could be combined through meta-analysis. However, where appropriate, adjusted risk factor ORs were pooled using random-effects models according to the method proposed by DerSimonian and Laird [36]. As only RRs were available in one study [2], we converted these measures into ORs using the method proposed by Deeks and colleagues [37].

In order to assess for inter-study heterogeneity in our pooled ORs, we calculated Cochran’s Q homogeneity [38] and I2 inconsistency statistics [39]. As suggested by Higgins and colleagues, we considered an I2 statistic of >25%, >50%, and >75% to represent low, moderate, and high degrees of heterogeneity, respectively [40]. Although we planned to conduct sensitivity or stratified analyses in the presence of inter-study heterogeneity (in order to determine whether our pooled estimates varied across a number of a priori-identified covariates), these analyses were only able to be conducted based on patient respiratory status (that is mechanically ventilated versus breathing unassisted) and diagnosis (for example, trauma or severe acute pancreatitis). All analyses were performed using Stata version 12.0 (Stata Corp., College Station, TX, USA).

Results

Study selection and characteristics

Among 1,224 unique citations, a total of 14 studies enrolling 2,500 critically ill adults met the inclusion criteria (Figure 1) [1, 2, 9, 10, 1524]. Among the 14 included studies, 11 were cohort studies [2, 9, 10, 1519, 2224], two were case–control studies [20, 21], and one was a cross-sectional study [1]. Seven studies included mixed ICU patients [1, 2, 9, 15, 18, 19, 24], one included surgical ICU patients [21], two included severe acute pancreatitis patients [10, 22], and four included trauma patients, including those who were in shock [17] or who presented with torso [16], a variety of blunt [23], and severe extremity injuries [20]. Two studies included only mechanically ventilated patients [15, 18]. Eight authors [1, 9, 17, 2023] responded to our requests for supplementary study data, and one [1] provided us with their original dataset and regression modeling strategy such that we could calculate an adjusted OR for a candidate risk factor that was only reported in the manuscript as an adjusted P value. The characteristics of the included studies are shown in Table 1.
https://static-content.springer.com/image/art%3A10.1186%2Fcc13075/MediaObjects/13054_2013_Article_3022_Fig1_HTML.jpg
Figure 1

Flow chart of steps in systematic review.

Table 1

Characteristics of studies included in systematic review

Study, Year

Patients (n)

Design

ICU type

Patient population

Mechanically ventilated, (%)

Reports risk factors for

Illness severitya

Balogh et al., 2003 [16]

188

Prospective cohort

Trauma

Trauma patients in shock

Not reported

ACS

ISS: 1° ACSb 29 (3)

2° ACSb: 28 (2)

Normal IAP: 27 (1)

Balogh et al., 2011 [17]

81

Prospective cohort

General

Trauma patients in shock

Not reported

IAH

ISS: 29 (1)

Dalfino et al., 2008 [9]

123

Prospective cohort

General

Mixed

Not reported

IAH

IAH, median (IQR): 24 (20–28)

Normal IAP, median (IQR): 21.5 (18–26)

De Keuleaner et al., 2011 [18]

149

Prospective cohort

General

Mixed mechanically ventilated

100

IAH and ACS

22 (10)

Davis et al., 2013 [22]

45

Retrospective cohort

General

Severe acute pancreatitis

62

ACS

20.3 (6.4)

Ke et al., 2012 [10]

58

Prospective cohort

Surgical

Severe acute pancreatitis

21

IAH

9 (range 8–11)

Kim et al., 2012 [19]

100

Prospective cohort

General

Mixed

81

IAH

19.4 (8.4)

Madigan et al., 2008 [20]

96

Case–control

Trauma

Extremity injury AIS score >3

66

ACS

ISS: ACS 25.6 (9.06)

Normal IAP: 21.4 (11.02)

Malbrain et al., 2004 [1]

97

Cross-sectional

General

Mixed

Not reported

IAH

SOFA: 6.5 (4)

Malbrain et al., 2005 [24]

265

Prospective cohort

General and specialized

Mixed

Not reported

IAH

17.4 (8.3)

McNelis et al., 2002 [21]

44

Case–control

Surgical

Surgical

100

ACS

ACS: 20.3 (6.5)

Non-ACS: 11.0 (3.2)

Neal et al., 2012 [23]

452

Prospective cohort

General

Blunt trauma

Not reported

ACS

ISS, median (IQR): 34 (25–43)

Reintam Blaser et al., 2011 [15]

563

Prospective cohort

General

Mixed mechanically ventilated

100

IAH

15.2 (7.4)

Vidal et al., 2008 [2]

83

Prospective cohort

Medical/surgical

Mixed

Not reported

IAH

19 (8)

aAPACHE II mean (standard deviation) unless otherwise stated; bprimary ACS was defined as ACS associated with injury or disease in the abdominopelvic region, secondary ACS was defined as ACS not originating from the abdominopelvic region [14]. ACS, abdominal compartment syndrome; ISS, injury severity score; IAP, intra-abdominal pressure; IAH, intra-abdominal hypertension; IQR, interquartile range; SOFA, s equential organ failure assessment; AIS, abbreviated injury scale.

Risk of bias assessment

While the methodological quality of the included studies was variable, seven satisfied most or all of the criteria proposed by Hayden and colleagues (Table 2) [32]. Although 13 did not report whether abdominal muscular contractions were absent during IAP measurement, one study targeted a Richmond Agitation Sedation Scale score of -5 (unarousable) in all patients undergoing IAP monitoring [18]. Ten studies used the WSACS criteria to define IAH and ACS [1, 2, 9, 10, 15, 18, 19, 22],[24, 41] while four used alternate criteria to define ACS (including the need for abdominal decompression due to IAP ≥25 mmHg with organ dysfunction, pulmonary/renal/cardiovascular dysfunction, or oliguria/increased peak airway pressure) among some of the included ICU patients (see Additional file 1: Tables S2 and S3) [16, 20, 21, 23]. Further, three studies included a small number of patients diagnosed with IAH/ACS using physical examination alone [20, 22, 23]. In two of the included 14 studies [15, 16], it was unclear if some of the included trauma patients may have been diagnosed with ACS while having an open abdomen as they were reported to have undergone damage control laparotomy.
Table 2

Risk of bias assessment for the included studies[32]

Study

Participation

Attrition

Prognostic factor (Risk factors)

Outcome measurement (IAH/ACS)

Confounding

Analysis

Balogh et al., 2003 [16]

Partly

Unsure

Yes

Partly

Unsure

Yes

Balogh et al., 2011 [17]

Partly

Unsure

No

Partly

Unsure

Partly

Reintam Blaser et al., 2011 [15]

Yes

Unsure

Yes

Yes

Unsure

Yes

Dalfino et al., 2008 [9]

Yes

Unsure

No

Yes

Partly

Yes

De Keuleaner et al., 2011 [18]

Yes

Unsure

Yes

Partly

Unsure

Yes

Davis et al., 2013 [22]

Yes

Unsure

Partly

No

Unsure

Yes

Ke et al., 2012 [10]

Yes

Unsure

No

Yes

Partly

Yes

Kim et al., 2012 [19]

Yes

Unsure

Yes

Yes

Unsure

Yes

Madigan et al., 2008 [20]

Yes

Unsure

No

No

Partly

Yes

Malbrain et al., 2004 [1]

Yes

N/A – cross-sectional

Partly

Yes

Unsure

Yes

Malbrain et al., 2005 [24]

Yes

Unsure

Yes

Yes

Partly

Yes

McNelis et al., 2002 [21]

Yes

Unsure

No

Yes

Unsure

Yes

Neal et al., 2012 [23]

Partly

Unsure

Yes

No

Yes

Yes

Vidal et al., 2008 [2]

Yes

Unsure

No

Yes

Unsure

Yes

Where participation was defined as the study sample being representative of the patient population of interest, attrition was defined as loss to follow-up being described and not associated with key participant characteristics (that is, selection bias), prognostic factor indicated that risk factors were adequately defined and measured within the text of the paper (the authors of any studies not satisfying this criteria completely were contacted for definition clarification), outcome measurement indicated that intra-abdominal hypertension/abdominal compartment syndrome (IAH/ACS) is defined and adequately measured (for this category, 'yes’ specifically indicated that the WSACS consensus definitions and guidelines for intra-abdominal pressure (IAP) measurement were used by the studies whereas 'partly’ indicated IAH/ACS that the study used either the WSACS consensus definitions or IAP measurement guidelines (but not both), and 'no’ indicated that either the WSACS consensus definitions or measurement guidelines were both not used, or that some patients had their IAH or ACS diagnosed by physical examination) [42], confounding indicated that potential confounders were appropriately accounted for, and analysis indicated the statistical analysis is appropriate for the study design. In general, for each of the above categories, 'yes’ indicated conditions were satisfied, 'no’ indicated conditions were not satisfied, 'partly’ indicated conditions were partly satisfied, and 'unsure’ indicated it was unclear whether or not conditions were satisfied.

While the quality of reporting of multivariable analyses appeared adequate when assessed using the guidelines proposed by Hayden and colleagues [32] (Table 2), when assessed in more detail using those suggested by Moss et al. [33] several methodological limitations became apparent (Additional file 1: Table S4). Eight of the studies failed to provide clearly operational definitions of their reported candidate risk factors (for example, large volume fluid resuscitation) [1, 2, 9, 10, 17, 2022]. Moreover, although in all of the included studies except three [10, 18, 22] the reported ORs were adjusted for potential confounding factors, only two studies specifically reported which covariates were included in the regression model [20, 23]. Finally, eight studies [1, 9, 10, 15, 16, 19, 21, 22] appeared to select variables for inclusion in the model using stepwise selection procedures (which may have tended to eliminate non-significant factors), none mentioned whether investigators assessed for effect measure modification, and only three reported using a goodness-of-fit test for model validation [2, 9, 16].

Risk factors for IAH and ACS

Of the 14 included studies, nine reported candidate risk factors for IAH [1, 2, 9, 10, 15, 1719, 24] while six reported candidate risk factors for ACS [16, 18, 2023]. Using narrative synthesis techniques, we clustered the 62 identified candidate risk factors, including 38 for IAH and 24 for ACS, into three themes, including baseline patient characteristics, systemic physiology, and fluid resuscitation, and eight subthemes (Table 3). The direction of 'risk’ associated with the factors included in each subtheme, and the strength of evidence against the null hypothesis of no risk of IAH/ACS, is summarized in Figure 2. Large-volume crystalloid resuscitation, the respiratory status of the patient, and shock/hypotension were observed to be the most common risk factors for IAH and ACS that transcended across presenting patient populations.
Table 3

Narrative synthesis tabulation of candidate risk factor theme and subtheme clusters

Theme

Risk factors included

Subthemes

Patient characteristics

Baseline demographics

Age

Gender

Obesity

Emergent/surgical status

Presenting diagnosis

Etiology

Cirrhosis

Liver dysfunction

Gastrointestinal bleed

Ileus

Sepsis/infections

White blood cell count

Abdominal surgery

Pancreatitis

Amylase level

Calcium level

C-reactive protein level

Albumin

Disease severity

APACHE-II score

SOFA score

Glasgow Coma Scale score

Revised trauma score

Injury severity score

Charlson comorbidity score

Ranson score

Glasgow-Imrie score

Systemic physiology

Shock/hypotension

Mean arterial pressure

Systolic blood pressure

Shock

Hypotension

Vasopressor use

Capillary leak index

Central venous pressure

GAPCO2

Urine output

Cardiac index

Hematocrit

Hemoglobin

Metabolic derangement/organ failure

Base deficit

Blood glucose

International normalized ratio

Hypothermia

Acidosis

Serum creatinine

Respiratory status/failure

Respiratory failure

Acute respiratory distress syndrome

Mechanical ventilation

Positive end-expiratory pressure

Peak airway pressure

Respiratory rate

Fluid resuscitation

Crystalloid resuscitation

Pre-ICU crystalloid

Pre-hospital crystalloid

Emergency department fluid

24-hour fluid balance

Fluid balance

Fluid resuscitation

Fluid collections

Non-crystalloid resuscitation

Poly-transfusion

Packed red blood cell units

Crystalloid: packed red blood cell ratio

APACHE, acute physiology and chronic health evaluation; SOFA, sequential organ failure assessment; GAPCO2, gastric mucosal CO2 minus end tidal CO2.

https://static-content.springer.com/image/art%3A10.1186%2Fcc13075/MediaObjects/13054_2013_Article_3022_Fig2_HTML.jpg
Figure 2

Vote counting descriptive analysis of candidate risk factors for IAH/ACS. Vote counting is a descriptive tool that can be used to identify patterns across heterogeneous data. All candidate risk factors from the included studies were first grouped into a subtheme (which is reported along the vertical axis of each of the displayed graphs) and then categorized as to whether they were a: (1) risk factor (odds ratio (OR) point estimate and confidence interval (CI) >1), (2) an exposure that was neither hazardous nor protective (CI included 1), or (3) an exposure that was protective (OR and CI <1) by arbitrarily assigning each of these three categories a representative color (shown in the legend). Subsequently, studies reporting candidate risk factors were assigned a value of one within each of the above-named categories and then summed in order to display the stacked horizontal bar charts shown in each of the vote-counting summary plots. IAH/ACS, intra-abdominal hypertension/abdominal compartment syndrome.

Risk factors for IAH

Significant risk factors for IAH (stratified by narrative synthesis subtheme), including those pooled in meta-analysis, are reported in Table 4. In contrast, all IAH risk factors, regardless of their significance level, are reported in (Additional file 1: Table S2).
Table 4

Significant risk factors for intra-abdominal hypertension among intensive care unit patients, including pooled estimates where appropriate

Risk factor

Systematic review and/or meta-analysis

Number

Patient population

Odds ratio (95% CI)

Heterogeneity

Studies

Patients

I2, %

P value

Demographics

Obesity [1, 15, 18, 19]

4

909

Mixed ICU patients

5.10 (1.92 to 13.58)

60.2

0.06

Age (per year increase) [9]

1

123

Mixed ICU patients

2.75 (1.01 to 3.09)

  

Presenting diagnosis

Sepsis [9, 19]

2

223

Mixed ICU patients

2.38 (1.34 to 4.23)

0.0

0.47

Abdominal infection [2, 19]

2

183

Mixed ICU patients

2.49 (0.48 to 13.0)

82.7

0.02

Abdominal surgery [2, 9, 15, 24]

4

1034

Mixed ICU patients

1.93 (1.30 to 2.85)

57.1

0.07

Post-laparotomy [17]

1

81

Trauma patients

5.72 (1.50 to 21.43)

  

Pancreatitis [15]

1

563

Mechanically ventilated mixed ICU patients

4.73 (1.96 to 11.41)

  

Hepatic failure/cirrhosis [15]

1

563

Mechanically ventilated mixed ICU patients

2.07 (2.07 to 28.81)

  

GI bleeding [15]

1

563

Mechanically ventilated mixed ICU patients

3.37 (1.43 to 7.94)

  

Ileus [2, 24]

2

348

Mixed ICU patients

2.05 (1.40 to 2.98)

0.0

0.96

Liver dysfunction [24]

1

265

Mixed ICU patients

2.25 (1.1 to 4.58)

  

Disease severity

APACHE II score (per point increase) [10]

1

58

Pancreatitis patients

1.652 (1.131 to 2.414)*

  

Metabolic derangement/organ failure

Base deficit [17]

1

81

Trauma patients

1.15 (1.01 to 1.33)

  

Acidosis [2]

1

83

Mixed ICU patients

1.93 (1.12 to 3.45)

  

Shock/hypotension

Vasopressor use [15]

1

563

Mechanically ventilated mixed ICU patients

2.33 (1.02 to 5.35)

  

Shock [9]

1

123

Mixed ICU patients

4.68 (1.93 to 6.44)

  

Hypotension [2]

1

83

Mixed ICU patients

2.12 (1.05 to 4.50)

  

CVP (per mmHg) [19]

1

100

Mixed ICU patients

1.3 (1.1 to 1.6)

  

Respiratory status/failure

PEEP >10cm H20 [15]

1

563

Mechanically ventilated mixed ICU patients

2.41 (1.57 to 3.70)

  

Respiratory failure [15]

1

563

Mechanically ventilated mixed ICU patients

1.87 (1.22 to 2.87)

  

ARDS [2]

1

83

Mixed ICU patients

3.61 (1.60 to 9.06)

  

Mechanical ventilation [2]

1

83

Mixed ICU patients

6.78 (1.94 to 59.03)

  

Crystalloid resuscitation

Pre-ICU crystalloid [17]†,‡

1

81

Trauma patients

1.40 (1.00 to 1.96)

  

Fluid balance [9]†,‡

1

563

Mixed ICU patients

5.22 (2.03 to 7.45)

  

24hr fluid balance [10]†,‡

1

58

Pancreatitis patients

1.004 (1.001 to 1.006)*

  

Fluid collections [10]

1

58

Pancreatitis patients

2.015 (1.298 to 3.129)*

  

Non-crystalloid resuscitation

Fluid resuscitation (>3.5 L crystalloid or colloid) [1, 24]

2

362

Mixed ICU patients

2.17 (1.30 to 3.63)

0.0

0.35

*Unadjusted; indicative of a risk factor that was not clearly defined; although the odds ratio in these studies appeared to increase per liter of fluid, this was unclear in the manuscript. Where abdominal infection was defined as infection of the peritoneal cavity confirmed by radiology or microbiology [19], or pancreatitis, abscess, or other [2]; sepsis was defined according to consensus definitions [9, 19]; and respiratory failure was defined as PaO2/FiO2 <300 mmHg [15]. APACHE II, acute physiology and chronic health evaluation II, CVP, central venous pressure; PEEP, positive end-expiratory pressure; ARDS, acute respiratory distress syndrome.

Mixed patients

Among mixed ICU patients, common risk factors for IAH included obesity, sepsis/infection, the presenting diagnosis of the patient, abdominal surgery, acidosis, hypotension, mechanical ventilation/acute respiratory distress syndrome (ARDS), and crystalloid and non-crystalloid resuscitation.

Four studies reported that obesity (defined as body mass index (BMI) >30 kg/m2) was a risk factor for IAH in mixed ICU patients [1, 15, 18, 19]. Among these studies, the pooled OR for IAH was 5.10 (95% CI, 1.91 to 13.58; I2 = 60.2%; P = 0.057). Although this estimate was associated with moderate heterogeneity, one of the four studies included only mechanically ventilated patients [15]. In a sensitivity analysis excluding the results of this study, the pooled OR increased to 8.80 (95% CI, 3.66 to 21.19), and this estimate was homogenous across studies (I2 = 0.0%; P = 0.945).

Sepsis was also observed to be a risk factor for IAH among mixed populations of ICU patients. Among two studies of mixed ICU patients [9, 19], the pooled OR of IAH among those with sepsis was 2.38 (95% CI, 1.34 to 4.23). This estimate was homogeneous across studies (I2 = 0.0%; P = 0.465).

Four studies reported abdominal surgery as a risk factor for IAH among mixed ICU patients [2, 9, 15, 24]. The pooled odds of IAH among those undergoing abdominal surgery was 1.93 (95% CI, 1.30 to 2.85) times the odds of IAH among patients not undergoing abdominal surgery in these studies. There was a moderate amount of heterogeneity in this estimate (I2 = 57.1%; P = 0.072), which could not be explained in a sensitivity analysis excluding the results of a single study that included only mechanically ventilated patients.

Two studies [2, 24] reported development of ileus to be a risk factor for IAH among mixed ICU patients while two others [1, 24] reported large volume fluid resuscitation to be a risk factor (>3.5 L of crystalloid or colloid in the last 24 hours). The pooled OR of IAH associated with ileus development was 2.05 (95% CI, 1.40 to 2.98), which was homogeneous (I2 = 0.0%; P = 0.960) across studies. The pooled odds of IAH among those who received large volume fluid resuscitation was 2.17 (95% CI, 1.30 to 3.63) times the odds of IAH among those who did not received fluid resuscitation. This estimate was also homogeneous across studies (I2 = 0.0%; P = 0.350).

Trauma and severe acute pancreatitis patients

Among trauma patients, common risk factors for IAH included abdominal surgery, increased plasma base deficit, and pre-ICU crystalloid resuscitation. Among pancreatitis patients, common risk factors included age, gender, disease severity (higher APACHE II and Glasgow-Imrie scores), and large volume crystalloid resuscitation. These risk factors were too clinically heterogeneous to pool through meta-analysis.

Risk factors for ACS

Significant risk factors for ACS are listed in Table 5. These could often be classified across studies according to location of care (pre-ICU or ICU). All reported risk factors for ACS, regardless of significance level, including those for primary and secondary ACS, are shown in (Additional file 1: Table S3).
Table 5

Significant risk factors for abdominal compartment syndrome among intensive care unit patients

Risk factor

Systematic review and meta-analysis

Number

Patient population

Odds ratio (95% CI)

Studies

Patients

Demographics

Patient to OR within 75 mins of ED admission [16]

1

188

Trauma patients

102.7 (9.65 to 999.9)

Disease severity

APACHE II score > sample mean of 20.3 [22]

1

45

Severe acute pancreatitis

1.143 (1.012 to 1.292)

Glasgow-Imrie score > sample mean of 9.1 [22]

1

45

Severe acute pancreatitis

1.221 (1.000 to 1.493)

Metabolic derangement/organ failure

Temperature ≤34°C [16]

1

188

Trauma patients

22.9 (1.39 to 378.25)

Hemoglobin ≤80 g/L [16]

1

188

Trauma patients

252.2 (9.89 to 999.9)

Hemoglobin ≤80 g/L [16] (primary ACS)

1

188

Trauma patients

206.1 (7.41 to 999.9)

Base deficit ≥12 [16]

1

188

Trauma patients

3.5 (1.37 to 839.50)

Urine output ≤150 ml in 24 hrs [16]

1

188

Trauma patients

64.1 (5.48 to 749.68)

Serum creatinine > sample mean of 217.7 μmol/L [22]

1

45

Severe acute pancreatitis

1.115 (1.02 to 1.219)*

Shock/hypotension

Systolic blood pressure <86 in ED [16]

1

188

Trauma patients

4.9 (1.78 to 13.99)

GAPCO2 ≥16 [16]

1

188

Trauma patients

>999.9 (22.1 to 999.9)

GAPCO2 ≥16 [16] (primary ACS)

1

188

Trauma patients

54.3 (2.15 to 999.9)

Urine output ≤150 ml in 24 hrs [16]

1

188

Trauma patients

89.8 (4.49 to 999.9)

Cardiac index <2.6 L/min/m2[16]

1

188

Trauma patients

12.5 (1.02 to 153.64)

Respiratory status/failure

Respiratory rate > sample mean of 19.7 breaths/min [22]

1

45

Severe acute pancreatitis

1.004 (1 to 1.008)*

Crystalloid resuscitation

Crystalloid ≥3 L in ED [16]

1

188

Trauma patients

23 (6.38 to 83.10)

Crystalloid ≥3 L in ED [16] (primary ACS)

1

188

Trauma patients

69.8 (10.21 to 477.7)

Crystalloid ≥3 L in ED [16] (secondary ACS)

1

188

Trauma patients

15.8 (1.74 to 143.85)

Crystalloid ≥7.5 L [16]

1

188

Trauma patients

166.2 (4.76 to 999.9)

Crystalloid ≥7.5 L [16] (secondary ACS)

1

188

Trauma patients

38.7 (3.19 to 469.55)

Pre-hospital crystalloid [20]

1

96

Extremity injury patients

1.99 (1.07 to 3.73)

ED crystalloid [20]

1

96

Extremity injury patients

1.85 (1.08 to 3.15)

Non-crystalloid resuscitation

PRBC ≥3 units in ED [16]

1

188

Trauma patients

5.6 (1.03 to 30.83)

Crystalloid:PRBC ratio [23]

1

452

Blunt trauma patients

2.3 (1.4 to 3.8)

Crystalloid (L):PRBCs (units) >1.5:1 [23]

1

452

Blunt trauma patients

3.6 (1.3 to 9.7)

*Unadjusted; where more risk factors for ACS and primary and/or secondary ACS were reported in a single study, this was indicated in brackets. OR, operating room; ED, emergency department; APACHE II, acute physiology and chronic health evaluation II; ACS, abdominal compartment syndrome; GAPCO2, gastric mucosal CO2 minus end tidal CO2; PRBC, packed red blood cells.

Pre-ICU ACS risk factors

Two studies reported pre-ICU (pre-hospital and Emergency Department) risk factors for ACS [16, 20]. Pre-hospital crystalloid administration was observed to increase the odds of secondary ACS [20] as did development of a systolic blood pressure <86 mmHg or administration of >3 L of crystalloid in the Emergency Department [16]. Both Emergency Department crystalloid administration and resuscitation with >3 L of crystalloids significantly increased the odds of primary and secondary ACS, while surgical intervention within 75 minutes of Emergency Department admission increased the odds of primary ACS [16].

ICU ACS risk factors

Significant risk factors for ACS among those in the ICU included poor disease severity scores, markers of metabolic derangement/organ failure, shock/hypotension, and large volume crystalloid and non-crystalloid resuscitation (Table 5 and Additional file 1: Table S3) [16, 22, 23]. Among surgical patients, although positive fluid intake/fluid balance were the most common reported candidate risk factors for ACS, these were non-significant when adjusted for other covariates (Additional file 1: Table S3) [21]. In trauma patients, common risk factors similarly included crystalloid and non-crystalloid resuscitation, as well as markers of metabolic derangement/organ failure, and shock/hypotension [16, 20, 23]. In pancreatitis patients the most common risk factors included high APACHE II and Glasgow-Imrie scores [22]. The varying definitions of these risk factors precluded the production of pooled risk estimates.

Discussion

Although clinical practice guidelines recommend that IAP be measured via the bladder in all ICU patients with risk factors for IAH or ACS [14], intravesicular pressure measurement is time consuming and may not be required in many ICU patients. When performed at four-hour intervals, IAP measurements may take up to 30 to 42 minutes of nursing time per day [43]. Although controversy exists [44], some have also reported that instillation of saline into the bladder may increase risk of urinary tract infection [41, 43]. Thus, defining exactly which patients are at increased risk for IAH and/or ACS could prevent measurement of IAP when not indicated. Further, knowledge of which patient groups are at increased risk for these conditions is important for the design of future studies and to guide clinicians during IAH screening decisions.

This systematic review identified 25 unique significant risk factors for IAH and 16 for ACS. These risk factors could be clustered into three themes, including baseline patient characteristics, systemic physiology, and fluid resuscitation, and eight subthemes. Obesity, certain presenting patient diagnoses (sepsis, intra-abdominal infection, abdominal surgery, pancreatitis, cirrhosis, and gastrointestinal bleeding and ileus), acidemia and hypotension, and large volume crystalloid and non-crystalloid resuscitation were common risk factors for IAH among mixed ICU patients while abdominal surgery, base deficit, and pre-ICU crystalloid resuscitation were common risk factors for IAH among trauma patients. Crystalloid resuscitation was the most common risk factor for ACS in trauma and surgical patients as were indicators of metabolic derangement/organ failure and shock/hypotension. Finally, among patients with severe acute pancreatitis, higher APACHE II/Glasgow-Imrie scores and elevated serum creatinine were risk factors for ACS.

Crystalloid resuscitation prior to ICU admission was found to be a risk factor for both IAH and ACS among trauma patients [16, 17, 20]. Importantly, although we found that Emergency Department poly-transfusion with packed red blood cells (PRBCs) (≥3 units) was associated with ACS [16], a study by Cotton and colleagues suggests that this risk may be mitigated by use of a massive transfusion protocol that limits crystalloids and provides a larger ratio of plasma and platelets (that is more colloids) [45]. This suggestion is supported by the results of one of the included studies, which reported a graded increase in the odds of ACS as the crystalloid to PRBC ratio increased [23]. Although these findings suggest that there may be an association between the volume or type of administered resuscitation fluids and the incidence of IAH/ACS, the reason for this association remains somewhat unclear as it could be either fluid- or pathology-related. Thus, future studies are needed to determine optimal fluid resuscitation strategies for trauma patients, and IAH/ACS should be considered in these evaluations.

Although this study affords the first comprehensive description of evidence-informed risk factors for IAH/ACS, it has several limitations. First, heterogeneous risk factor definitions and the inclusion of varying patient populations among the included studies precluded the production of pooled OR estimates for many risk factors. Second, as some of the included studies failed to provide clear definitions of their reported risk factors, several likely cannot be readily operationalized in practice. Third, although the quality of reporting of multivariable analyses appeared adequate when assessed using the guidelines proposed by Hayden and colleagues [32], when assessed in more detail using those suggested by Moss et al. [33] several methodological limitations became apparent. For example, one study reported an OR upper CI limit that exceeded 1,000 as well as an OR point estimate that was higher than the upper CI limit [16], suggesting that either there were very few events in the logistic regression models used, or the models were highly unstable. Moreover, as stepwise model selection procedures were used by the majority of the included observational studies, some IAH/ACS risk factors may be underreported in this systematic review. Finally, as this study was interested in determining risk factors for IAH and ACS, we excluded studies that examined the effect of exposures on changes in IAP as a continuous measure. Thus, in addition to the risk factors reported in this study, clinicians may also need to consider the influence of other modifiable patient-level variables, including head of bed elevation [4648] and prone versus supine positioning [4953].

Conclusions

In summary, this systematic review and meta-analysis identified 25 unique evidence-informed risk factors for IAH and 16 for ACS. Although several of these risk factors appeared to transcend across patient populations (for example, large-volume crystalloid resuscitation and the presence of shock/hypotension), many were specific to the type of patient population under study. Among mixed ICU patients, certain specific presenting or admission diagnoses, the presence of shock or metabolic derangement, and the volume of crystalloids used in their initial resuscitation appear to be important considerations in determining risk of IAH and ACS. As our findings were partially limited by clinical heterogeneity and the quality of statistical analyses conducted in the included studies, the risk factors reported in this study should be considered candidate evidence-based risk factors until formally evaluated in a prospective multi-centre observational study, which is currently being planned.

Key messages

  •  This systematic review and meta-analysis identified 25 unique evidence-informed risk factors for IAH and 16 for ACS

  •  Although several of these risk factors appeared to transcend across patient populations (for example, large-volume crystalloid resuscitation and the presence of shock/hypotension), many were specific to the type of patient population under study

  •  Among mixed ICU patients, their specific presenting or ICU admission diagnosis, the presence of shock or metabolic derangement, and the volume of crystalloids used in their initial resuscitation appear to be important considerations in determining risk of IAH and ACS

  •  Risk factors for IAH with pooled evidence supporting an increased risk among mixed ICU patients included obesity, sepsis, abdominal surgery, ileus development, and fluid resuscitation

  •  As our findings were partially limited by clinical heterogeneity and the quality of statistical analyses conducted in the included studies, the risk factors reported in this study should be considered candidate evidence-based risk factors until formally evaluated in a prospective multi-centre observational study.

Authors’ information

JKH is a Masters of Science (Health Services Research) student with a thesis on patient care rounds at the University of Calgary. DJR is a surgery and Clinician Investigator Program resident who is presently conducting a Doctor of Philosophy investigation study in epidemiology with a thesis on trauma damage control surgery at the University of Calgary. CGB and AWK are academic trauma and acute care surgeons while AWK is also an intensivist at the Foothills Medical Center. AWK is also the past President of the Trauma Association of Canada and a member of the Executive Committee of the World Society of the Abdominal Compartment Syndrome. ARB is a member of the World Society of the Abdominal Compartment Syndrome. DAZ is an academic intensivist at the University of Alberta Hospital as well as the Director of the Division of Critical Care Medicine, the Edmonton Zone Clinical Department Head, and a professor in the Department of Critical Care Medicine at the University of Alberta. HTS is an academic intensivist at the Foothills Medical Center and an Associate Professor in the Department of Community Health Sciences at the University of Calgary with expertise in health services research. MLM is the Director of the ICU and High Care Burn Unit at ZNA Stuivenberg Hospital in Belgium. He is also the Past President and Treasurer of the World Society of the Abdominal Compartment Syndrome and the Chairman of Working Group on Abdominal Problems within the European Society of Intensive Care Medicine. RJ is an intensivist and Professor in the Departments of Medicine and Clinical Epidemiology and Biostatistics at McMaster University.

Abbreviations

ACS: 

Abdominal compartment syndrome

APACHE II: 

Acute physiology and chronic health evaluation

BMI: 

Body mass index

CI: 

Confidence interval

IAH: 

Intra-abdominal hypertension

IAP: 

Intra-abdominal pressure

ICU: 

Intensive care unit

ISS: 

Injury severity score

MODS: 

Multiple organ dysfunction syndrome

MOOSE: 

Meta-analysis of observational studies in epidemiology

OR: 

Odds ratio

PRBC: 

Packed red blood cells

PRISMA: 

Preferred reporting items for systematic reviews and meta-analyses

RR: 

Risk ratio

SOFA: 

Sequential organ failure assessment

WSACS: 

World Society of the Abdominal Compartment Syndrome.

Declarations

Acknowledgments

We thank Zsolt Balogh, MD, PhD (Division of Surgery, Department of Traumatology, John Hunter Hospital and University of Newcastle, Newcastle, NSW, Australia); Nicola Brienza, MD, PhD (Emergency and Organ Transplantation Department, Anesthesia and Intensive Care Unit, University of Bari, Italy); Bryan Cotton, MD, MPH (Department of Surgery, University of Texas Medical School at Houston, Houston, TX, USA); Ke Lu, MD (Department of General Surgery, Jinling Hospital, Nanjing University School of Medicine, Nanjing, People’s Republic of China); John McNelis, MD (Chair of Surgery, Jacobi Medical Center/North Central Bronx Hospital, North Bronx Health Network, Bronx, NY, USA); Michele Molinari, MD (Department of Surgery, Dalhousie University, Halifax, Nova Scotia, Canada); and Jason Sperry, MD, MPH (Division of General Surgery and Trauma, Department of Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA) for answering specific queries and providing additional study data during the course of this study.

Dr. Roberts is supported by an Alberta Innovates - Health Solutions Clinician Fellowship Award, a Knowledge Translation Canada Strategic Training in Health Research Fellowship, and funding from the Canadian Institutes of Health Research and Clinician Investigator Program at the University of Calgary.

This work was presented in part at Trauma 2013: The Trauma Association of Canada and Australasian Trauma Society Joint Scientific Meeting in Whistler, British Columbia, Canada on April 11, 2013.

Authors’ Affiliations

(1)
Department of Community Health Sciences (Division of Health Services Research), University of Calgary Intensive Care Unit Administration, Foothills Medical Center
(2)
Departments of Surgery and Community Health Sciences (Division of Epidemiology), University of Calgary Intensive Care Unit Administration, Foothills Medical Center
(3)
Hepatobiliary and Pancreatic Surgery, Trauma and Acute Care Surgery University of Calgary Foothills Medical Center
(4)
Clinic of Anaesthesiology and Intensive Care, University of Tartu
(5)
Division of Critical Care Medicine Zone Clinical Department Department of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta, General Systems ICU, University of Alberta Hospital
(6)
Department of Community Health Sciences, University of Calgary
(7)
Intensive Care Unit and High Care Burn Unit, Ziekenhuis Netwerk Antwerpen ZNA Stuivenberg
(8)
Department of Medicine, Department of Clinical Epidemiology and Biostatistics, Critical Care Response Team St Joseph's Hospital McMaster University
(9)
The Departments of Surgery and Critical Care Medicine and Regional Trauma Services, Foothills Medical Centre

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