Critical Care

Adverse events during intrahospital transport of critically ill patients: A systematic review and meta-analysis

a b s t r a c t

Introduction: intrahospital transport of critically ill patients is often necessary for Diagnostic procedures, thera- peutic procedures, or admission to the intensive care unit. The aim of this study was to investigate and describe safety and adverse events during intrahospital transport of critically ill patients.

Material and methods: A systematic search was performed of MEDLINE and the Cochrane Central Register of Con- trolled Trials for studies published up to June 3, 2020, and of the International Clinical Trials Platform Search Por- tal and ClinicalTrials.gov for ongoing trials. We selected prospective and retrospective cohort studies published in English on intrahospital transport of critically ill patients, and then performed a meta-analysis. The primary out- come was the incidence of all adverse events that occurred during intrahospital transport. The secondary out- comes were death due to intrahospital transport or life-threatening adverse events, minor events in vital signs, adverse events related to equipment, durations of ICU and hospital stay, and costs.

Results: A total of 12,313 intrahospital transports and 1898 patients from 24 studies were included in the meta- analysis. Among 24 studies that evaluated the primary outcome, the pooled frequency of all adverse events was 26.2% (95% CI: 15.0-39.2) and the heterogeneity among these studies was high (I2 = 99.5%). The pooled fre- quency of death due to intrahospital transport and life-threatening adverse events was 0% and 1.47% each, but heterogeneity was also high.

Conclusions: Our findings suggest that adverse events can occur during intrahospital transport of critically ill pa- tients, and that the frequency of critical adverse events is relatively low. The results of this meta-analysis could assist in risk-benefit analysis of diagnostic or therapeutic procedures requiring intrahospital transport of critically ill patients.

Trial registration: UMIN000040963.

(C) 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://

creativecommons.org/licenses/by-nc-nd/4.0/).

  1. Introduction

Bedside Diagnostic procedures and therapeutic procedures, such as portable chest X-ray, echography, or minor surgery in the intensive

Abbreviations: CI, Confidence interval; ECLS, Extracorporeal life support; ICTRP, International Clinical Trials Platform Search Portal; ICU, intensive care unit.

* Corresponding author at: Department of Respiratory Medicine, The University of Tokyo Hospital, Bunkyo-ward, Tokyo 113-8655, Japan.

E-mail address: [email protected] (N. Nakagawa).

care unit (ICU), may be available at some hospitals [1]. However, intrahospital transport is still necessary for many diagnostic procedures such as computed tomography or for treatment in the operating room or angiography room. In clinical practice, intrahospital transport for ra- diographic diagnoses is common and the results often change the course of care [2]. Intrahospital transport is also necessary for admission to ICU from the emergency department.

Critically ill patients who are admitted to the ICU are at higher risk of adverse events associated with intrahospital transports [2-4]. Adverse events can occur for various reasons, including unstable hemodynamics,

https://doi.org/10.1016/j.ajem.2021.11.021

0735-6757/(C) 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Selection process“>the need for many devices such as a ventilator, and miscommunication between healthcare providers [4-6].

Several observational studies have reported on the frequency or types of adverse events associated with intrahospital transport. Adverse events during intrahospital transport have been reported to occur in 6%-70% of cases, and changes in vital signs, accidental extubation, and cardiopulmonary arrest have been reported to occur in 8% of cases [2- 4,7,8]. The number of intrahospital transports has been associated with delirium, length of hospitalization, and death [9,10]. Some narra- tive reviews have focused on adverse events during intrahospital trans- port [2-4], but to our knowledge, there has been only one systematic review, which did not include a meta-analysis [11]. Therefore, we con- ducted a systematic review and meta-analysis with the aim of investi- gating and describing safety and adverse events during intrahospital transport of critically ill patients.

  1. Material and methods

This systematic review and meta-analysis followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta- Analyses (PRISMA) Statement [12], and the protocol was registered in the University Hospital Medical Information Network Clinical Trials Registry (UMIN000040963; July 1, 2020). Ethical approval and in- formed consent were waived because of the nature of this systematic review and meta-analysis.

    1. Data sources and searches

In this systematic review and meta-analysis, our aim was to investi- gate and describe safety and adverse events during intrahospital trans- port of critically ill patients. We searched the MEDLINE database via PubMed and the Cochrane Central Register of Controlled Trials for stud- ies published up to June 3, 2020. We also searched the International Clinical Trials Platform Search Portal (ICTRP) and ClinicalTrials.gov for ongoing trials. The search strategy is detailed in Table S1.

    1. Study selection

We included studies with adults aged 16 years or older that investi- gated safety and adverse events during intrahospital transport of critically ill patients, defined here as patients admitted to an ICU. Bias assessment“>Intrahospital transports during an ICU stay or to the ICU from other units, including the emergency room, operating room, and general ward, were eligible. We did not include studies about transport between hospitals and transport to another bed in the ICU. We included prospec- tive and retrospective cohort studies published in English, and excluded case reports, case series, Case-control studies, randomized controlled studies, and studies that did not report adverse events during transport. The primary outcome was the incidence of all adverse events that occurred during intrahospital transport. The secondary outcomes were death due to intrahospital transport or life-threatening adverse events (cardiopulmonary arrest, adverse events considered life-threatening by the author of each article, or airway problems such as accidental extubation and obstruction), minor events in vital signs (e.g., transient changes in respiratory rate, oxygenation, heart rate, blood pressure, and level of consciousness), adverse events related to equipment (e.g., loss of battery power, disconnection of the oxygen supply tube, catheter dislodgement), duration of ICU or hospital stay, and costs. The definition or classification of adverse events in each included study was used as-is in the present analysis even though they varied. In the case of multiple intrahospital transports per person, the adverse events during each intrahospital transport were extracted and, if there were no data for each intrahospital transport, the adverse events per

person was extracted.

    1. Selection process

Two reviewers (MM and NN) independently assessed the titles and abstracts of all studies identified by the search strategy in order to ascer- tain whether each study met the inclusion criteria. Full texts of eligible articles were evaluated to determine whether they should be included in the analysis. For abstract-only studies, we contacted the original au- thor. Any disagreements between the two reviewers were resolved through discussion. If disagreements remained unresolved, a third re- viewer (TK or SY) was included in the discussion and consensus was reached.

    1. Data extraction

In the included studies, two review authors (MM and NN) indepen- dently extracted data on study characteristics (first author, Publication year, country, study design, setting, and the number of intrahospital transports) and participant characteristics (age, sex, severity score, use of mechanical ventilation, use of vasopressors, use of sedation, kinds of devices used, and reason for intrahospital transport). If the number of intrahospital transports was not available, we extracted the number of participants. In cohort studies comparing patients with IHTs with those without intrahospital transports, only the data of patients with intrahospital transports were extracted.

    1. Data analysis

We analyzed adverse events during intrahospital transport as fre- quency and 95% confidence intervals (CIs). Quantitative analysis using a random effects model was performed to pool measured effects. We used STATA/SE version 16.1 (Stata Corp. LLC, College Station, TX) and Review Manager (RevMan) software version 5.4 (Copenhagen: The Nordic Cochrane Center, The Cochrane Collaboration) for statistical analysis.

    1. Assessment of heterogeneity and reporting bias

We assessed heterogeneity among the studies using the I2 statistic. The I2 statistic was developed to measure the consistency between trials in a meta-analysis [13]. We considered that there was heterogeneity if I2 was greater than 50%. We investigated heterogeneity by performing subgroup analysis. We planned to assess reporting bias using funnel plot analysis if 10 or more studies were included in the analysis.

    1. Risk of bias assessment

Two reviewers (MM and NN) evaluated risk of bias using the Newcastle-Ottawa quality assessment scale [14]. This scale consists of three domains (selection domain, comparability domain, outcome do- main). In the selection domain, we considered a study as low risk if the target patients in the study were patients in the ICU or Mechanically ventilated patients, while studies with patients who had community- acquired pneumonia were considered as high risk. We did not evaluate any studies in the comparability domain because our focus was not on comparability. In the outcome domain, we considered the study as low risk if it analyzed all the patients who underwent intrahospital transport. We resolved any disagreements between the two reviewers by discussion. If disagreements remained unresolved, a third reviewer (TK or SY) was included in the discussion and consensus was reached.

    1. Subgroup and sensitivity analysis

We planned to perform the following subgroup analysis pre- specified in the study protocol, if available, in order to investigate whether the frequency of each adverse event was different among the following subgroups: 1) age, younger than 65 years and 65 years or

older; 2) use of a mechanical ventilator; 3) use of Extracorporeal life support ; 4) reason for intrahospital transport; and 5) causative disease. We also planned to perform a sensitivity analysis in which stud- ies identified as having a high risk of bias were excluded from the meta- analysis.

  1. Results
    1. Search results and study selection

In total, 1540 articles were identified and screened, of which 24 were excluded as duplicates and 1479 were excluded after screening. The re- maining 36 articles were subjected to full-text analysis, resulting in the inclusion of 24 articles (12,313 intrahospital transports and 1898 pa- tients) (Fig. 1, Table 1). The characteristics of the included articles are shown in Table 1 and S2. The mean or median age of the patients in the selected studies ranged from 46 to 72 years, with most studies in- cluding patients in their 50s and 60s, and 51% to 71% were men. About 60% of the studies were conducted in teaching hospitals or university hospitals, and half were in mixed ICUs. Seven studies included only mechanically ventilated patients, none included only patients on ECLS, and only 3 studies included patients on ECLS (1.1% to 5.8% of study population).

    1. Quality of included studies

Details of risk of bias in the included studies as assessed by the Newcastle-Ottawa quality assessment scale are shown in Fig. S1. Most included studies had a low risk of bias in the selection domain and out- come domain. We did not assess the comparability domain because here we focused on adverse events, not comparison between studies with and without intrahospital transports. A few included studies

Fig. 1. Flow diagram of the search strategy and study selection.

were considered to have a high risk of bias because they included self- reported outcome measurements.

    1. Safety and adverse events
      1. Primary outcome

In 3 of the 24 included studies, the incidence of all the adverse events was not extracted. The pooled frequency of all the adverse events was 26.2% (95% CI: 15.0-39.2) and the heterogeneity among the studies was high (I2 = 99.5%) (Fig. 2). Common types of adverse events were respiratory, cardiovascular, neurological, and equipment problems. Sev- eral studies included delays to transfer as an adverse event [6,8,5,17,18, 24,34]. Frequently reported adverse events related to physical condition were desaturation, hypotension, hypertension, arrythmia including car- diac arrest and agitation. Notably, adverse events related to medical de- vice occurred frequently, which included equipment malfunction, accidentally dislodgement, oxygen tank empty, and transport ventilator switch accidentally knocked into off. It was hard to show the range of re- ported frequency of each adverse event because the definition and clas- sification of adverse events were various in each study as shown in Table S2.

      1. Secondary outcome

Death due to intrahospital transport or life-threatening adverse events was less frequent. The pooled frequency was 1.47% (95% CI 0.43-2.95), and heterogeneity among the studies was high (I2 = 92.6%) (Fig. 3). The pooled frequency of death due to intrahospital transport was 0%. The pooled frequency of minor events in vital signs and equipment was 20.7% (95% CI 11.8-31.4) and 8.97% (95% CI 3.97-15.6), respectively, and there was high heterogeneity (I2 = 99.2% and 97.2%, respectively) (Fig. 4-5).

      1. Subgroup analysis and sensitivity analysis

For the incidence of all adverse events, which was highly heteroge- neous, we conducted subgroup analysis between studies with patients aged younger than 65 years and those with patients aged 65 years or older (Fig. S2), and between studies with and studies without mechan- ically ventilated patients (Fig. S3). In both subgroup analyses, heteroge- neity remained high. We could not conduct subgroup analysis of the use of ECLS, the reason for intrahospital transport, and causative disease, due to lack of data.

We had planned to perform sensitivity analysis, but found that the data were insufficient because only two studies were applicable.

  1. Discussion

The results of the present study showed that the pooled frequency of all adverse events, life-threatening adverse events, and death was 26.2%, 1.47%, and 0%, respectively. The pooled frequency of all adverse events appeared to be substantial and is consistent with previous literature re- views [2-4,7,8], while the frequency was inconsistent between each study included in the meta-analysis. Also, I2 statistics of nearly 100% reflected the heterogeneity of the studies included in the meta- analysis. There are three reasons for this inconsistency. First, the patient characteristics of each study varied. In two studies included in the meta- analysis, severity of illness was associated with incidence of adverse events during intrahospital transport [15,19]. Critically ill patients are likely to be more unstable or attached to more medical equipment, which may cause more adverse events. Here, meta-regression between severity of illness and frequency of adverse events was difficult because the indicators of severity, such as APACHE II, SOFA, and SAPS II, differed among the studies and were not mentioned in several studies. Mechan- ical ventilation may be a potential risk factor for adverse events during intrahospital transport, but no significant association was seen between mechanical ventilation and adverse events in our exploratory subgroup analysis.

Table 1

Studies included in the systematic review (n = 24)

Study

Year

Design

n

Setting Hospital, ICU type

Agea

Severity of illnessa

Reason for intrahospital transport

1 Aliaga et al. [15]

2015

Prospective

533

Teaching hospital,

56 +- 16

SAPS2 49 +- 18

CT

mixed

2 Bercault et al. [16]

2005

Prospective

158

Teaching hospital,

57 +- 18

SAPS2 40 +- 12

CT, angiography

mixed

3 Brunsveld-Reinders et al.

2015

Prospective

503

University hospital,

Unknown

Unknown

CT, angiography

[17]

mixed

4 Gillman et al. [18]

2006

Prospective,

290

Tertiary hospitals,

46 [15-96]

Unknown

Unknown

retrospective

unknown

5 Gimenez et al. [5]

2017

Prospective

143

Tertiary hospitals,

62.2 +- 18.2

SOFA 5 +- 3.5

CT, MRI, angiography, operating room

mixed

SAPS2 46.8

+- 14.5

6 Harish et al. [19]

2016

Prospective

120

Tertiary hospitals,

50.1

SOFA 11.8

CT, MRI, angiography, operating room

unknown

APACHE2 14.1

7 Ignatyeva et al. [20]

2018

Prospective

200

Unknown,

59

SOFA 6.1

Unknown

cardiovascular

8 Jia et al. [6]

2016

Prospective

441

Unknown, mixed

58.8 +- 18.0

APACHE2 15.4

CT, MRI, angiography

+- 8.1

9 Kollef et al. [21]

1997

Prospective

993

University hospital,

57.6 +- 19.4

APACHE2 19.1

CT, MRI, operating room

mixed

+- 6.7

10 Kue et al. [7]

2011

Retrospective

3383

University hospital,

Unknown

Unknown

Unknown

mixed

11 Kwack et al. [22]

2018

Retrospective

184

Tertiary hospital,

72 (62-75)

APACHE2 33.2

CT, MRI, angiography

12 Lahner et al. [23]

2007

Prospective

452b

medical

University hospital,

Children 2.9

APACHE2 18.5

CT, MRI, operating room

surgical

[1-13]

+- 8.5

Adults 49

[16-86]

13 Lin [24]

2020

Unknown

1019

University hospital,

Unknown

Unknown

Unknown

unknown

14 Marquet et al. [25]

2015

Retrospective

830

Acute hospital, mixed

Unknown

APACHE2 17.8

Unknown

+- 8.7

15 Matsumura [26]

2015

Prospective

20

University hospital,

62.5 +- 19.7

SOFA 9.1 +- 3.7

CT

unknown

APACHE2 31.9

+- 8.2

16 Parmentier-Decrucq

2013

Prospective

262

Teaching hospital,

58 (48-71)

SOFA 5 (3-8)

CT

et al. [27]

medical

SAPS2 48

17 Schwebel et al. [28]

2013

Prospective

1659c

Unknown, mixed

63 (52-75)

(34-62)

SOFA 8 (5-11)

CT, MRI, angiography

SAPS2 51

(39-64)

18 Solano et al. [29]

2017

Prospective

921

Tertiary hospital,

64 +- 17

Unknown

Unknown

unknown

19 Stankiewicz et al. [30]

2019

Retrospective

21

Tertiary hospitals,

Unknown

Unknown

Unknown

20 Stearley et al. [31]

1998

Unknown

219c

surgical

University hospital,

60

Unknown

CT, MRI, angiography

mixed

21 Szem et al. [32]

1995

Prospective

203

University hospital,

64.7

APACHE2 17.6

CT, operating room

surgical

22 Veiga et al. [8]

2019

Retrospective

1559

Unknown, mixed

66 +- 17

Unknown

Unknown

23 Waddell. [33]

1975

Prospective

20c

Unknown, unclear

Unclear

Unknown

Unknown

24 Zuchelo et al. [34]

2009

Prospective

58

Tertiary hospital, mixed

52.7 +- 18.9

APACHE2 18.4

CT, echocardiography,

+- 5.4

endoscopy/bronchoscopy

CT, computed tomography; ICU, intensive care unit; MRI, magnetic resonance imaging; SAPS2, Simplified Acute Physiology Score 2; SOFA, sequential organ failure assessment; APACHEII, Acute Physiology and Chronic Health Evaluation II.

a Age and Severity of illness reported as mean +- SD, median (interquartile range) or median [range].

b Included children.

c Number of patients.

The second reason for inconsistency between studies included in the meta-analysis is differences in potential beneficial interventions, such as a checklist for intrahospital transport [4,18,35,36], a training program for medical staff [4], or a specialized team for intrahospital transport [7]. Careful preparation, checking, and training could lead to the preven- tion of some types of adverse events. In the studies included in the meta-analysis, the frequency of equipment-related adverse events ranged between 10.4% and 44% [5,15,23,37]. In these studies, equipment malfunction or battery failure were included as equipment-related ad- verse events, so a checklist for intrahospital transport may be beneficial for preventing these types of adverse events. Other adverse events re- lated to equipment include dislodgment or disconnection of lines, tubes, or catheters. In another study included in the meta-analysis, the

number of equipment and the occurrence of adverse events were found to be associated [15]. For the transport of critically ill patients with a lot of medical equipment, medical staff with knowledge, corre- sponding skills, good communication, and teamwork could be useful. A specialized transport team would be useful not only for reducing the number of adverse events [31], but also for educating medical staff [38]. However, subgroup analysis was impossible because the existence of these interventions was not described in many studies included in the meta-analysis.

The third reason for inconsistency among the studies included in the meta-analysis is differences in the definition of adverse events. Some of the studies considered only predetermined adverse events [6,7,16,21, 31,34], while others included any adverse events recognized by medical

Image of Fig. 4

Image of Fig. 2Fig. 4. Forest plot of minor events in vital signs.

Image of Fig. 5Fig. 2. Forest plot of all adverse events.

staff. The definition of adverse events in vital signs also differed among the studies. For example, one study included desaturation defined as pulse oximetry less than 95% as an adverse event [27], while another study defined more than 5% change in pulse oximetry as an adverse event [34], and another study included frequency of hypoxia as an ad- verse event without any definition [17]. The lack of a clear definition of adverse events is also pointed out in a previous review [2]. Therefore, the clinical significance of adverse events was different in each included study.

The pooled frequency of life-threatening adverse events and death was low in our meta-analysis. In addition to the lack of a clear definition of adverse events, categories of severity of adverse events were also lacking a clear definition, which led to the observed inconsistency among studies included in the meta-analysis [2]. Although the confi- dence intervals were wide, point estimates were less than 10% for seri- ous adverse events in 15 of 16 studies. The remaining one study was a prospective study with 120 patients, of whom 16.7% required cardiopul- monary resuscitation [19]. In this study, multivariate analysis showed a significant correlation between severity of illness and cardiac arrest. The severity of illness of patients was not notably higher rather than that of patients in the other studies included in meta-analysis, and the reason

Image of Fig. 3

Fig. 3. Forest plot of death or life-threatening adverse events.

Fig. 5. Forest plot of minor events in equipment.

why the incidence of severe adverse events was so high was not de- scribed. The high rate might be the result of local factors at the tertiary care center in India where that prospective study was conducted.

There are several limitations to our study. First, because of the high risk of bias, the internal validity of the results was low. Second, judge- ments about life-threatening adverse events could be subjective and may have low reproducibility because many studies included in the meta-analysis did not define life-threatening adverse events and the studies assessed the frequency of life-threatening events based on dis- cussion between authors. Third, it was impossible to perform subgroup analysis according to severity of illness, potential beneficial intervention such as checklists, or the destination of intrahospital transports because of various criteria for severity of illness, the small sample size, and the lack of data. The differences of patient characteristics between each study also made subgroup analysis impossible.

  1. Conclusions

Overall, our findings suggest that adverse events can occur during intrahospital transport of critically ill patients, while the frequency of critical adverse events is relatively low. The results of this meta- analysis could assist in risk-benefit analysis of diagnostic or therapeutic procedures requiring intrahospital transport of critically ill patients.

Further studies are warranted for verification of the several factors which may contribute to adverse events during intrahospital transports.

Ethics approval and consent to participate

Ethical approval and informed consent were waived by because this was a systematic review and meta-analysis of published literature.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Funding

This research did not receive any specific grant from funding agents in the public, commercial, or not-for-profit sectors.

Authors’ contributions

All authors were involved in the study design. MM, NN, TK, SY, TY, KA, SO, and YO identified the studies included in the meta-analysis and analyzed the data. MM and NN drafted the manuscript and YO su- pervised the drafting of the manuscript. All authors were involved in the Data interpretation and discussion. All authors read and approved the final manuscript.

Declaration of Competing Interest

The authors declare that they have no competing interests.

Acknowledgements

We thank all the members of the Japanese Acute respiratory distress syndrome clinical practice guideline committee from the Japanese Society of Respiratory Care Medicine, the Japanese Respiratory Society and the Japanese Society of Intensive Care Medicine. We also ap- preciate the librarian at Kyoto Prefectural University of Medicine Library for developing the search strategy.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi. org/10.1016/j.ajem.2021.11.021.

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