Safety and efficacy of routine diagnostic test reduction interventions in patients admitted to the intensive care unit: A systematic review and meta-analysis

Abstract

Reducing unnecessary routine diagnostic testing has been identified as a strategy to curb wasteful healthcare. However, the safety and efficacy of targeted diagnostic testing strategies are uncertain. The aim of this study was to systematically review interventions designed to reduce pathology and chest radiograph testing in patients admitted to the intensive care unit (ICU). A predetermined protocol and search strategy included OVID MEDLINE, OVID EMBASE and the Cochrane Central Register of Controlled Trials from inception until 20 November 2019. Eligible publications included interventional studies of patients admitted to an ICU. There were no language restrictions. The primary outcomes were in-hospital mortality and test reduction. Key secondary outcomes included ICU mortality, length of stay, costs and adverse events. This systematic review analysed 26 studies (with more than 44,00 patients) reporting an intervention to reduce one or more diagnostic tests. No studies were at low risk of bias. In-hospital mortality, reported in seven studies, was not significantly different in the post-implementation group (829 of 9815 patients, 8.4%) compared with the pre-intervention group (1007 of 9848 patients, 10.2%), (relative risk 0.89, 95% confidence intervals 0.79 to 1.01, P = 0.06, I² 39%). Of the 18 studies reporting a difference in testing rates, all reported a decrease associated with targeted testing (range 6%–72%), with 14 (82%) studies reporting >20% reduction in one or more tests. Studies of ICU targeted test interventions are generally of low quality. The majority report substantial decreases in testing without evidence of a significant difference in hospital mortality.

Keywords

Diagnostic tests intensive care units X-rays haematologic tests

Introduction

Ordering routine, daily diagnostic tests, including pathology tests and chest radiographs (CXRs), is common in the intensive care unit (ICU). This occurs despite evidence that such testing may lead to harmful over-investigation, may contribute to iatrogenic anaemia, and is costly; and that a substantial proportion of these tests are normal or unchanged on repeat testing.^1–4 Targeted diagnostic testing, in which clinicians order tests in response to specific clinical questions, may reduce unnecessary diagnostic test ordering by up to 50% and has been identified as a priority area to decrease waste by both clinicians and consumers.^5,6 However, concern has been raised that targeted testing may increase the risk of missed diagnoses, and high-quality evidence of the safety and effectiveness of targeted compared with routine diagnostic testing is lacking.^7,8 The primary aim of this systematic review was to evaluate interventional studies reporting on the implementation of a targeted diagnostic testing strategy in adult patients admitted to the ICU.

Methods

The study was conducted according to a predetermined protocol (PROSPERO registration number: CRD42018115218) and is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (Supplementary Appendix eFigure 1).⁹

Search strategy

The search strategy included OVID MEDLINE, OVID EMBASE and the Cochrane Central Register of Controlled Trials from inception until 20 November 2019. We searched for interventional studies describing the implementation of an intervention designed to reduce routine pathology and/or CXR use in patients admitted to the ICU. The search strategies included the terms “critical care”, “investigation”, “pathology test” and “chest radiograph”. A full list of the search terms is provided in the supplementary appendix. There were no date or language limitations. Conference proceedings were not searched. Two authors (EL and KH) independently searched, screened and determined study eligibility, with any disagreement resolved by consensus. Study quality was assessed using the Cochrane Collaboration’s Risk-of-Bias in Non-Randomized Studies of Interventions and the revised Cochrane Risk-of-Bias Tool for Randomized Trials.^10,11

Eligibility criteria

Publications were eligible for inclusion if they were an interventional study (pre- and post-implementation or randomised clinical trial (RCT)), included an adult patient population admitted to an ICU and reported the numbers of at least one routine diagnostic test in the pre- and post-implementation periods. Studies that were presented only in abstract and publications that did not report any outcomes of interest were excluded.

Data collection

A case report form was piloted and refined by the study authors. Study data were then extracted from eligible studies onto a final pre-specified case report form independently, in duplicate, by two authors (EL and KH). Disagreement was resolved by consensus. Where relevant, requests were made to the corresponding authors for data not reported in the primary manuscripts.

Statistical analysis

Eligible studies were pooled for meta-analysis using a random effects model. The primary safety outcome was hospital mortality. The primary efficacy outcome was aggregated tests per patient bed-day. Key secondary outcomes included ICU and hospital length of stay (LOS), duration of mechanical ventilation and individual test numbers. For categorical data, the number of participants with an event was compared with the total number of participants with and without an event. For continuous data, the participant number, mean and standard deviation (SD) were used. Where outcome data were only reported as number, median and range, and where author contact failed to provide means and SD, these were imputed for inclusion in the meta-analysis using validated methods.¹² Weighted mean difference (WMD) and relative risk (RR) with 95% confidence intervals (CI) were calculated for continuous and categorical data respectively. A P <0.05 was considered significant. Heterogeneity was measured using the I² statistic with an I²>40% considered significant heterogeneity. A pre-specified sensitivity analysis was conducted excluding those studies with a high risk of bias in any domain. Publication bias was measured with a funnel plot with the odds ratio (OR) for the primary outcome plotted against the standard error of the log OR. To provide comparative estimates of cost savings, the reported currency was adjusted for inflation using the gross domestic product deflator from the International Monetary Fund: World Economic Outlook Database and then exchanged to US dollars.^13,14 The statistical analysis was conducted using Stata (Intercooled Version 11.2, StataCorp, College Station, TX, USA).

Results

The search identified 94 potentially relevant studies. Of these, 26 studies with more than 44,000 patients were included in the systematic review.^15–40 There were three studies that did not report the total number of patients.^21,32,33 The process of identifying eligible studies is provided in Figure 1.

Figure 1.

Preferred Reporting Items for Systematic Reviews and Meta-analyses study screening, inclusion and meta-analysis.

Characteristics of the included trials

The included trials were published between 1993 and 2018. They were conducted in Europe, North America and Australasia. Additional data for the primary outcome were received from two authors.^20,30 There was substantial variation in the intervention design and tests targeted for reduction (Table 1). Overall, the quality of the included studies was low, with all included studies having at least one domain of greater than low risk of bias (Table 2). A description of the rationale for each bias assessment is provided in the supplementary appendix eTable 1.

Table 1.

Study characteristics.⁴⁰

First author (year)ref	Location	Population	Study type	Intervention	Duration^#	N	Primary outcome	Secondary outcome
Brogi (2017)¹⁵	Italy	Mixed ICU	Before and after	Process change	5 years C: 29 months I: 31 months	4134 C = 1869 I = 2265	Number of CXRs	Cost
Clec’h (2008)¹⁶	France	Mixed ICU	Individual RCT	Process change	6 months	165 C = 84 I = 81	Rate of new findings on CXR	Findings that prompted intervention, delayed diagnosis, mortality
Dhanani (2018)¹⁷	Australia	Mixed ICU	Interrupted time series	Process change Education Guideline Feedback	3 years C: 6 months I: 6 months PI: 6 months	3250 C = 1141 I = 1067 PI = 1042	Cost of laboratory tests, number of laboratory tests	Abnormal test proportion, mortality
Graat (2007)¹⁸	Netherlands	Mixed ICU	Before and after	Process change	10 months C: 5 months I: 5 months	1376 C = 754 I = 622	Number of CXRs	Diagnostic and therapeutic efficacy, ICU LOS, re-admission rate, mortality
Hejblum (2009)¹⁹	France	21 ICUs in 18 hospitals	Cluster RCT	Process change	8 months	849 C = 424 I = 425	Number of CXRs	Duration of MV, LOS, mortality
Hendrikse (2007)²⁰	Netherlands	Mixed ICU	Before and after	Process change	18 months C: 12 months I: 6 months	736 C = 486 I = 250	CXR diagnostic and therapeutic efficacy	Number of CXRs, ICU LOS, re-admission rate, mortality
Keveson (2017)²¹	USA	Mixed ICU	Before and after	Process change Education	NR	NR	Number of CXRs	Cost
Krinsley (2003)²²	USA	Mixed ICU	Before and after	Process change	35 months C: 17 months I: 18 months	2564 C = 1297 I = 1267	Number of CXRs	Cost
Krivopal (2003)²³	USA	Medical ICU	Individual RCT	Process change/RCT	10 months	94 C = 43 I = 51	CXR diagnostic and therapeutic efficacy	Duration of MV, ICU LOS, hospital LOS, mortality
Kumwilaisak (2008)²⁴	USA	Surgical ICU	Before and after	Guideline Process change Education Audit Feedback	12 months C: 6 months I: 6 months	1117 C = 558 I = 559	Number of laboratory tests, number of laboratory tests ordered through electronic provider order entry	Abnormal values, blood transfusion, ICU LOS, duration of MV, ICU mortality, ICU re-admission, adverse events
Leong (2000)²⁵	USA	Cardiac ICU	Interrupted time series	Process change Guideline	5 years C: 4 months I: 4 months PI: 3 months	300 C = 100 I = 100 PI = 100	Number of CXRs	Hospital LOS, ICU LOS, duration of MV
Mehari (1997)²⁶	New Zealand	Mixed ICU	Before and after	Guideline Education	5 months C: 1 month I: 1 month	199 C = 99 I = 100	Number of laboratory tests	Cost
Mehari (2001)²⁷	New Zealand	Mixed ICU	Follow-up	Guideline	NR	95	Number of laboratory tests	Number of tests per ventilation time
Merkeley (2016)²⁸	Canada	Mixed ICU	Before and after	Guideline Education Process change	24 months C: 12 months I: 12 months	1440 C = 709 I = 731	Number of laboratory tests	Cost
Merlani (2001)⁴⁰	UK	Surgical ICU	Before and after	Guideline Education Feedback	10 months C: 10 months I: 10	2679 C = 1276 PI = 1403	Number of ABGs per patient bed-day	ICU LOS and mortality, cost, cost-effectiveness, nursing time, patient blood saved
Murphy (2016)²⁹	USA	7 ICUs in 2 hospitals	Before and after	Education Audit Feedback Financial incentives	36 months C: 12 months I: 12 months PI: 12 months	C = 7357 I = 7553 F/U = 7657	Number of ABGs, CXRs and blood transfusions	Cost, mortality
Musca (2016)³⁰	Australia	Mixed ICU	Before and after	Education Guideline Process change Audit Feedback	5 months C: 2 months I: 2 months	253 C = 100 I = 153	Number of coagulation tests, cost	Other pathology tests, blood volume and adverse events
Prat (2009)³¹	France	Medical ICU	Before and after	Guideline Education Feedback	24 months C: 12 months I: 12 months	1175 C = 541 I = 634	Number of laboratory tests and CXRs	Cost
Raad (2017)³²	USA	Medical ICU	Before and after	Process change Education	13 months C: 3 monthsI: 9 months	NR	Number of laboratory tests, cost	Blood transfusions, hospital mortality, central line utilisation, CLABSI
Rachakonda (2017)³³	Australia	Mixed ICU	Before and after	Process change Education	18 months C: 6 months I: 6 months	NR	Cost	Adverse events
Rao (1997)³⁴	UK	Cardiac ICU	Before and after	Process change Guideline	NR	200* C = 100 I = 100	CXR diagnostic and therapeutic efficacy	Number of CXRs, mortality
Resnick (2017)³⁵	USA	Surgical ICU	Before and after	Process Guideline	25 months C: 1 month I: 1 month	197 C = 107 I = 90	Number of CXRs	CXR diagnostic and therapeutic efficacy
Roberts (1993)³⁶	Canada	Mixed ICU	Before and after	Process Guideline	19 months C: 7 months I: 12 months	1883 C = 647 I = 1236	Number of laboratory tests and CXRs	Costs, difference in reduction between targeted and non-targeted tests
Seguin (2002)³⁷	France	Surgical ICU	Before and after	Education	4 months C: 2 months I: 2 months	287 C = 128 I = 159	Number of laboratory tests and CXRs	Cost
Wang (2002)³⁸	USA	CCU	Before and after	Guideline Education	15 months C: 3 months I: 3 months	471 C = 246 I = 225	Frequency of laboratory tests and CXRs	Cost
Yorkgitis (2018)³⁹	USA	Surgical ICU	Before and after	Process change	7 months C: 3.5 months I: 3.5 months	307 C = 155 I = 152	Frequency of laboratory tests and CXRs	Red blood cell transfusion

N: number of participants; ICU: intensive care unit; LOS: length of stay; CXR: chest radiograph; C: control; I: intervention; PI: post-intervention; MV: mechanical ventilation; NR: not reported; ABG: arterial blood gas; CLABSI: central line–associated bloodstream infection; CCU: coronary care unit; F/U: follow-up; #: duration of study defined from date of control group data to date of intervention or post-intervention data. A period of intervention or absence of data collection between these two points is represented when overall duration is greater than stated period of control, intervention and post-intervention.*Group A and C included from reported study. Group A was pre-intervention, Group C was post intervention post-intervention, Group B was an intermediate group that occurred temporarily between A and C and so was excluded.

Table 2a.

Studies assessed using ROBINS-I: Risk of Bias in Non-randomized Studies of Interventions assessment.

Hospital mortality

In-hospital mortality, reported in seven studies (n = 19,663), occurred in 828/9815 patients (8.4%) in the targeted testing group and 1007/9848 patients (10.2%) in the comparator group, (relative risk (RR) 0.89, 95% CI 0.79 to 1.01, P = 0.006, I² 38.5%) (Figure 2). There was no evidence of publication bias on funnel plot (eFigure 2).

Figure 2.

Forest plot for the association between targeted test reduction interventions and hospital mortality.

Targeted test reduction

Of the 18 studies reporting a difference in testing between the two groups, all reported a decrease associated with targeted testing (range 6%–72%), with 14 (82%) studies reporting >20% reduction in one or more tests and 11 (65%) studies reporting >30% reduction in one or more tests. Of the 23 studies reporting whether testing reduction was statistically significant, reduction was significant for 19 (83%) studies. Heterogeneity in reporting (e.g. reporting ICU admission number rather than bed days) and missing data (e.g. lack of estimated variance) precluded meta-analysis of the diagnostic tests per patient bed-day. Overall, there was a consistent reduction in proportion of tests conducted, ranging from 6% to 64%. A summary of the effect of targeted testing on testing frequency is provided in Table 3.

Table 3.

Targeted test reduction.

First author (year)ref	Test type	Reported measure of effect	Statistically significant reduction (yes/no)	Reduction proportion
Brogi (2017)¹⁵	CXR	Mean number of CXRs/admission	Yes	57%
Clec’h (2008)¹⁶	CXR	Diagnostic and therapeutic efficacy of routine vs. clinically indicated CXRs	Yes	NR
Dhanani (2018)¹⁷	Pathology	Cost reduction	Yes	28%
Graat (2007)¹⁸	CXR	Mean number of CXRs/patient day	Yes	NR
Hejblum (2009)¹⁹	CXR	Mean number of CXRs/patient day of mechanical ventilation	Yes	32%
Hendrikse (2007)²⁰	CXR	Diagnostic and therapeutic efficacy of routine vs. clinically indicated CXRs	Yes	35%
Keveson (2017)²¹	CXR	Mean number of CXRs/month	Yes	64%
Krinsley (2003)²²	CXR	Mean number of CXRs/patient day	Yes	22.5%
Krivopal (2003)²³	CXR	Mean number of CXRs/admission	Yes	NR
Kumwilaisak (2008)²⁴	Pathology	Mean number of tests/patient day	Yes	37%
Leong (2000)²⁵	CXR	Mean number of CXRs/admission	No	N/A
Mehari (1997)²⁶	Pathology	Mean number of tests/admission	NR	Pathology tests: 6%-58.6%
Mehari (2001)^27*	Pathology	N/A	N/A	N/A
Merkeley (2016)²⁸	Pathology	Mean number of complete blood count (CBC) and electrolyte-renal panel (UEC)/patient day	Yes	CBC: 9% UEC: 7%
Merlani (2001)⁴⁰	Pathology	ABGs per patient day	Yes	41%
Murphy (2016)²⁹	CXR and pathology	Mean number of CXRs and ABGs/admission	Yes	CXR: 26% ABG: 42%
Musca (2016)³⁰	Pathology	Mean number of coagulation tests/patient day	Yes	63.68%^#
Prat (2009)³¹	CXR and pathology	Mean number of CXRs and multiple individual pathology tests/patient day	Yes	CXR: 40.8%Pathology tests: 38%-72%
Raad (2017)³²	Pathology	Mean number of tests/patient day	Yes	32%
Rachakonda (2017)³³	Pathology	Cost reduction	Yes	12%
Rao (1997)³⁴	CXR	Total number of CXRs/100 patient cohort	No^{^}	N/A
Resnick (2017)³⁵	CXR	Percentage of patient-days CXRs performed on	Yes	29%
Roberts (1993)³⁶	CXR and pathology	Mean number of tests/admission	Yes	18%
Seguin (2002)³⁷	CXR and pathology	Mean number of tests/admission	No	NR
Wang (2002)³⁸	CXR and pathology	Mean number of CXRs and multiple individual pathology tests/patient day	CXR: NoPathology: potassium, glucose, calcium, magnesium and phosphorus were significant	CXR: N/APathology tests: 7%-40%
Yorkgitis (2018)³⁹	CXR and pathology	Mean number of CXRs and multiple individual pathology tests/patient day	No	N/A

NR: not reported; N/A: not applicable; CXR: chest radiograph; ABG: arterial blood gas.

*: follow-up study demonstrating sustained reduction; ^#: % reduction/patient bed-day; ^: no significant reduction between pre- and two-month post-pathway group.

Secondary outcomes

ICU mortality was reported in 15 studies (n = 31,446) and occurred in 1153/16,052 patients (7.2%) in the targeted testing group and 1288/15,394 (8.4%) patients in the comparator group, (RR 0.91, 95% CI 0.81 to 1.02, P = 0.10, I² 45%), (Supplementary Appendix eFigure 3).

ICU LOS was reported in 17 studies (n = 32,127). Diagnostic test reduction was associated with a WMD in ICU LOS of –0.28 (95% CI –0.48 to –0.07, P = 0.01, I² 95.6%; see Supplementary Appendix eFigure 4). Hospital LOS was reported in five studies, all investigating CXR reduction only (n = 654). Diagnostic test reduction resulted in a WMD in hospital LOS of –0.14 (95% CI –0.51 to 0.23, P = 0.46, I² 9%; see Supplementary Appendix eFigure 5).

Adverse events

Of the 11 studies reporting adverse events, 9 (82%) found no adverse events or no statistically significant difference in adverse events (Table 4).

Table 4.

Adverse events.

First author (year)ref	Test type	Adverse event monitoring	Control	Intervention	Difference
Clec’h (2008)¹⁶	CXR	Rate of delayed diagnoses between clinically indicated and routine CXRs.	Multiple indices	Multiple indices	0.7% rate of delayed diagnoses (6 out of 849). These 6 patients had minor atelectasis, which did not prompt any therapeutic intervention.
Graat (2007)¹⁸	CXR	Total number of patients with CXR abnormalities.	6.4% (n=48)	9.5% (n=59)	Statistically significant increase in total number of patients with CXR abnormalities. This finding was unable to be explained. No difference in re-admission rates or hospital mortality.
Hendrikse (2007)²⁰	CXR	Monitored adjustment of oropharyngeal tube, bronchoscopy, change in medication, adjustment of IV line, adjustment of thorax tube, placement of thorax tube, change in respiratory settings and other.	Multiple indices	Multiple indices	No statistically significant difference.
Keveson (2017)²¹	CXR	Review of internal patient safety event system.	Nil	Nil	No adverse patient outcomes found.
Krinsley (2003)²²	CXR	Monitored ventilation duration, inadvertent extubation, rate of reintubation within 48 h of planned extubation.	Multiple indices	Multiple indices	No statistically significant difference.
Kumwilaisak (2008)²⁴	Pathology	Monitored rate of re-admission within 48 h, myocardial infarction, cardiac arrhythmia, bleeding, reintubation and ICU mortality.	Multiple indices	Multiple indices	No statistically significant increase.
Leong (2000)²⁵	CXR	Monitored tube insertion for pleural effusion/haemothorax, persistent pneumothoraces or increasing pneumothoraces, significant morbidity requiring re-admission and/or reoperation, and death.	Multiple indices	Multiple indices	No statistically significant change between pre-pathway and 2-month post-pathway group.
Murphy (2016)²⁹	CXR and pathology	Review of reports to internal patient safety event system and ICU leadership group.	Nil	Nil	No adverse patient outcomes found.
Musca (2016)³⁰	Pathology	Monitored reporting of adverse events relating to bleeding or morbidity from a missed coagulation test.	Nil	Nil	No adverse patient outcomes found.
Rachakonda (2017)³³	Pathology	Adverse events related to not performing blood tests were prospectively recorded.	Nil	2 minor events (minor delays in daily plans)	No adverse patient outcomes found.
Resnick (2017)³⁵	CXR	Rates of pneumonia, acute respiratory distress syndrome, pulmonary embolism, deep vein thrombosis, bacteraemia/sepsis, urinary tract infection, acute renal failure, cardiovascular incident, surgical site infections, ileus.	50.4%	56%	No statistically significant difference.

CXR: chest radiograph.

Costs

Estimated annual ICU cost savings were reported in 15 studies. The annual saving per ICU bed in US dollars and adjusted for inflation to 2018 ranged from $1027 to $24,163 (Supplementary Appendix eTable2).

Discussion

Our systematic review and meta-analysis included 25 studies, which were generally of low to moderate quality, of interventions for reduction in ICU CXR, pathology or a combination of the two. Meta-analysis of seven studies suggested that targeted testing interventions were not associated with a significant difference in hospital mortality (RR 0.89, 95% CI 0.79 to 1.01, P = 0.006). These findings were consistent with a point estimate for ICU mortality and ICU and hospital LOS that favoured targeted testing but was not statistically significant. Although meta-analysis of overall test reduction per patient bed-day was not feasible due to trial reporting heterogeneity, included studies consistently achieved a substantial reduction in testing.

Our findings have several important implications. Previous systematic reviews have only quantitatively summarised CXR interventions.^41,42 Our review demonstrated that several interventions include both pathology and radiology interventions, and that decrease in testing appears to be consistent across diagnostic testing type. Although no difference in hospital mortality associated with targeted testing is somewhat reassuring, this was reported in only a minority of included studies. Furthermore, the design and quality of these studies precluded definitive conclusions about the safety of targeted testing interventions. Future studies with robust designs, powered to exclude a clinically meaningful difference in mortality and conducted in multiple centres, are needed to provide high quality, generalisable evidence of safety.⁴³ Such studies appear warranted given that stakeholders consider unnecessary testing in ICU to be a highly prevalent problem, ICU care is extremely costly with pathology and radiology costs representing 5%–25% and 4%–10% of direct costs respectively, and we consistently found in this study that targeted testing interventions were associated with decreased test ordering and costs.^44–48

Our review found that adverse events were not increased in the majority of studies, and that in the two studies that did observe an increase in adverse events, these were minor and not associated with an increase in ICU LOS or mortality. These findings are reassuring given the concern that decreasing testing may increase the number of missed diagnoses.^7,8 However, adverse events were only reported in 11 (44%) studies and generalisability remains uncertain.

A wide range of cost savings were reported in the included studies, but the majority range in the order of the salary of a junior medical officer to a staff specialist. Recouping, or being able to redirect this amount of funding to equipment or staffing, has the potential to increase efficiency and safety, in an era in which the global health sector is growing faster than the economy.⁴⁹

There are several limitations to our systematic review. None of the included studies were of low risk of bias and the majority were before and after designs that are particularly vulnerable to bias resulting from secular trends. Although only seven studies contributed to the primary outcome, the direction of effect was consistent with the 15 studies included in the ICU mortality meta-analysis. Heterogeneity precluded an aggregate estimate of test reduction and few of the included studies described the process of developing the intervention or of assessing its sustainability.

Conclusion

Studies of ICU targeted test interventions are generally of low quality. The majority report a substantial decrease in testing and associated costs without evidence of significant differences in hospital mortality or adverse events.

Supplemental Material

sj-pdf-1-aic-10.1177_0310057X20962113 - Supplemental material for Safety and efficacy of routine diagnostic test reduction interventions in patients admitted to the intensive care unit: A systematic review and meta-analysis

Supplemental material, sj-pdf-1-aic-10.1177_0310057X20962113 for Safety and efficacy of routine diagnostic test reduction interventions in patients admitted to the intensive care unit: A systematic review and meta-analysis by Katherine P Hooper, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing original draft, Conceptualization, Formal analysis, Methodology, Supervision, Writing review editing, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Supervision, Writing review editing in Anaesthesia and Intensive Care

Footnotes

Author contribution(s)

Katherine P Hooper: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Project administration; Writing-original draft.

Matthew H Anstey: Conceptualization; Formal analysis; Methodology; Supervision; Writing-review & editing.

Edward Litton: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Project administration; Supervision; Writing-review & editing.

Acknowledgements

The investigators would like to thank all the authors of the primary research material and in particular Dr Steven Musca and Dr Peter Spronk who provided additional data or clarification of their work.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Edward Litton is supported by a National Health and Medical Research Foundation Early Career Fellowship.

ORCID iDs

Katherine P Hooper

Matthew H Anstey

Edward Litton

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