MD, MSc Mohammed A Almekhlafi
email: mohammed.almekhlafi1@ucalgary.ca

Diederik Mayank Goyal

MD W J Dippel

L M Majoie

V Campbell

MD Keith W Muir

MD; Andrew M Demchuk

MD Serge Bracard

MD Francis Guillemin

MD, PhD Tudor G Jovin

PhD ; Diederik

MD Charles B L M Majoie

PhD Bruce C V Campbell

MD Peter Mitchell

MD Philip White

MD Michael D Hill

MD, MSc Scott Brown

PhD Jeffrey L Saver

Almekhlafi

Goyal

Demchuk

Healthy Life-Year Costs of Treatment Speed From Arrival to Endovascular Thrombectomy in Patients With Ischemic Stroke

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

E

ndovascular thrombectomy (EVT) has produced substantial changes in the outcomes associated with acute ischemic stroke due to large-vessel occlusions. 1 Evidence from multiple randomized clinical trials has demonstrated substantial EVT benefit, establishing thrombectomy as a standard of care treatment and encouraging efforts to improve its delivery. 2 One of the most important determinants of outcome after acute ischemic stroke is rapid reperfusion via intravenous thrombolysis, EVT, or both, reducing total brain ischemia time. [3][4][5] Previous analyses of the association of faster treatment delivery with improved patient outcomes have been limited. Ischemic stroke is a disease that can produce multiple gradations of functional impairment. For almost a decade, the preponderance of time-benefit studies focused on binary functional outcomes, counting only a single transition among disability states as important instead of all the transitions valued by patients, families, and practitioners. Even multilevel outcome analyses have generally analyzed disability level as an ordinal outcome, neglecting to weight outcome states using health utilities to capture health-related quality of life in a patient-centric manner.

Most analyses of EVT time-benefit associations have emphasized the time interval from onset/last known well (LKW) time to last known well/onset-to-puncture (LKWTP) time. 6 The analyses of time-benefit associations using LKWTP time are imprecise and systematically biased toward the null. The imprecision arises because, even in patients with stroke starting while awake, the exact moment of symptom onset may have been incorrectly perceived or reported, especially in patients who were not with witnesses at time of onset, owing to strokeinduced deficits such as neglect or aphasia. A systematic bias toward the null occurs when patients with wake-up or unwitnessed-onset strokes are included in analyses. Among these patients, the last known well time precedes actual stroke start time, yielding artificially long LKWTP values and causing systematic underestimation of the association between speed of treatment delivery and amount of treatment benefit. In addition, the differential selection for EVT of only those latearriving patients who have limited extent of ischemic changes on imaging results in overrepresentation of patients with reduced speed of infarct growth also biasing toward undervaluing the time-benefit association.

To address these limitations, we undertook a series of analyses minimizing these sources of imprecision and bias toward the null, including by evaluating outcomes along the full health-related quality of life range, with lead analyses focused on onset-to-treatment times in patients arriving early, among whom patients with fast progression are likely to be fully represented, and door-to-treatment times, as their intervals begin with precisely known time of emergency department arrival rather than imprecisely known last known well time.

Methods

Study Design and Inclusion Criteria

We analyzed individual patient-level data included in the Highly Effective Reperfusion Evaluated in Multiple Endovas-cular Stroke (HERMES) trials collaboration. The collaboration includes all randomized clinical trials of stent retriever thrombectomy devices (entirely or predominantly) vs medical therapy in patients with anterior circulation LVO within 12 hours of last known well time and for which a peerreviewed, complete primary results article was published by August 1, 2020. PubMed search and inquiry among collaborators and colleagues was performed to confirm that the 7 included represented all those eligible. [7][8][9][10][11][12][13] These trials were approved by the respective local ethics boards and enrolled patients using prospective (6 trials) or prospective and deferred (1 trial) written informed consent. The details of the HERMES collaboration initiation and the method of the meta-analysis search strategy and data gathering have been previously reported. 2,14 A full list of investigators in the HERMES collaboration is included in the Supplement.

Analyses were performed in 3 patient populations (all patients, early-treated patients, and late-treated patients). The early-treated population was defined as patients with an interval from last known well time to arterial puncture (LKWTP) of less than or equal to 4 hours. The 4-hour cutoff was selected based on spline analyses of both the HERMES clinical trial data set and the large Get With the Guideline-Stroke national registry indicating that the first inflection point of change in time-benefit associations from linear to nonlinear occurs at an LKWTP of 240 minutes. 4,5 This morphologic change was deemed to potentially indicate the transition point at which substantial numbers of unwitnessedonset patients, patients with symptoms first observed on awakening, and patients with fast progression begin to not be included in the EVT population.

The late-treated population was analyzed as an explanatory analysis, to probe a cohort likely to be more greatly biased by increased inclusion of unwitnessed onset and symptoms first observed on awakening and by a decreased inclusion of patients with fast progression. The late-treated population was defined as patients with LKWTP of greater than 4 hours and less than or equal to 12 hours.

All analyses were confined to directly arriving patients, excluding interfacility transfer patients. Transfer patients were identified in all trials and excluded because they often have paradoxically short emergency department to puncture (doorto-puncture [DTP]) times at the thrombectomy center, having undergone preliminary workup at outside facilities.

Outcomes

The leading outcome was gain or loss of healthy life, quantified using the disability-adjusted life-years (DALY) metric. The World Health Organization developed the DALY to measure the relative and total global burden of all diseases with a common metric. 15 One DALY is 1 year of healthy life, free of disability. The DALY metric integrates both mortality (years of life lost [YLL] because of premature death) and functional outcome (years of healthy life lost because of living with disability [YLD]). DALYs were calculated as the sum of YLL plus YLD. DALY values for each patient were calculated based on their age at time of stroke, their global disability outcome level at 3 months after stroke, as measured by the modified Rankin Scale (mRS) (scale from 0 indicating no residual symptoms to 6 indicating death), and their resulting projected life expectance and health-related quality of life.

The YLL for each patient is the difference between the patient's age-specific life expectancy without stroke and the patient's age-specific life expectancy given the particular level of poststroke disability present at 3 months. Following current World Health Organization recommendations, age weighting and discount rates were not applied. Each patient's age-specific life expectancy without stroke was taken from 2017 US National Vital Statistics. The degree of life expectancy curtailment associated with poststroke mRS global disability level was based on 2 poststroke long-term cohort studies, the UK Lothian Cohort Study and the Swedish Risk-Stroke Cohort Study. [16][17][18] The YLD for each patient was their years of expected life multiplied by a disability weight that reflected the degree of reduced value of each year owing to reduced health-related quality of life. Disability weights for each of the 7 mRS global disability levels were assigned using the utility-weighted modified Rankin Scale (UW-mRS). For each mRS level, the disability weight was calculated as 1 minus the UW-mRS utility weight. The UW-mRS health-related quality of life weightings for each mRS level were derived by averaging findings from 2 studies, including a large population-based stroke patient study in Great Britain and an international stroke clinician study with US, European, and Asian participants. 19,20 Accordingly, in the current study, for each mRS level, the disability weights were 0.0 for mRS level 0; 0.09 for mRS level 1; 0.24 for mRS level 2; 0.35 for mRS level 3; 0.67 for mRS level 4; 1.0 for mRS level 5; and 1.0 for mRS level 6. 21 An additional outcome analyzed was health-related quality of life exactly at 3 months after stroke, as reflected in 3-month UW-mRS scores. Utility measures are preference values that patients attach to their overall health status and integrate both positive and negative effects of an intervention into a single score between 0 (equal to death) and 1 (equal to perfect health).

Time Intervals

A total of 5 time intervals were analyzed: (1) LKW to door (LKWTD), (2) LKW to puncture (LKWTP), (3) LKW to reperfu-sion (LKWTR), (4) door to puncture (DTP), and (5) door to reperfusion (DTR). Substantial reperfusion was scored centrally by the HERMES collaboration central core laboratory and was defined as a score of 2b-3 (successful reperfusion) on the modified Thrombolysis in Cerebral Infarction (mTICI) scale (scores range from 0 indicating no perfusion to 3 indicating complete perfusion). Analyses of LKWTD, LKWTP, and DTP were performed in all patients meeting the entry LKWTP time criterion, regardless of whether substantial reperfusion was achieved. Analyses of LKWTR and DTR were performed in the subset of patients in whom substantial reperfusion was achieved.

Statistical Analysis

Probability of each outcome as a function of time was analyzed using mixed-method ordinal logistic regression, with trial and trial-by-treatment interaction as random-effects variables. In the main analyses, models were constructed of the linear dependence of the log odds of a particular outcome on time duration of care processes. Six patient feature variables were used as covariates in adjusted analyses: age (a linear variable), sex (binary variable), baseline stroke severity (National Institutes of Health Stroke Scale [NIHSS] score, with a range of 0-42; the higher the score, the greater the stroke severity, with 0 indicating no signs of stroke and 42 indicating coma), target occlusion location (a 3-level categorical variableinternal carotid artery [ICA], M1 middle cerebral artery [MCA], M2 MCA), entry Alberta Stroke Program Early Computed Tomography Score (ASPECTS; linear variable), and pretreatment intravenous alteplase; binary variable). Race/ethnicity was not included because collection of race data was legally prohibited in some countries where studies were performed and because race/ethnicity is not a known major independent factor associated with outcome from large-vessel ischemic stroke.

All effect size estimates are provided with their 95% CIs. All P values presented are 2-sided, with values less than .05 indicating statistical significance, without adjustment for multiple comparisons. Statistical analyses were performed in SAS software, version 9.4 (SAS Institute Inc), and R, version 3.3 (R Foundation for Statistical Computing).

Results

Among the 871 patients allocated to EVT across the 7 trials, 781 patients (89.7%) underwent EVT and 90 did not, most often because of reperfusion before EVT or tortuous vessels precluding navigation to the target occlusion. Among the 781 EVT-treated patients, 406 patients (52.0%) were in the earlytreated (LKWTP ≤4 hours) population and 375 patients (48.0%) were within the late-treated (LKWTP >4-12 hours) population.

The presenting features of early-treated and late-treated EVT patients are shown in Table 1. In the early-treated population, the mean (SD) age was 66.2 (13.4) years, 46.6% were women, and the median pretreatment NIH Stroke Scale score was 18 (interquartile range [IQR], 14-21). Patients in the latetreated group were generally comparable, although substan- The association of care process durations with functional outcomes is shown in Table 2 and the Figure . With regard to time intervals from LKW time to intervention, there was a difference between the early-treatment and late-treatment populations for the presence of a time-benefit association. In the early-treatment population, onset-to-puncture and onset-toreperfusion time intervals both showed substantial rates of benefit decrease with time, and the late-treatment population showed no significant change in benefit with longer onset-topuncture and onset-to-reperfusion time intervals. For example, in the early-treated population, every 1 hour of delay in LKW-to-puncture time was associated with a loss of 0.81 (95% CI, 0.08-1.55) healthy life-years, and in the late-treated population no statistically significant association of LKW-topuncture time and DALYs was present. The early-treated population effect size is substantial. Considering more granular time intervals, the loss of 0.81 healthy years per hour delay in the early-treated patients is equivalent to a loss of 1.6 months per 10-minute 4.9 days per 1-minute delay, and 2.0 hours per 1-second delay.

With regard to time intervals from ED arrival to intervention, the early-treatment and late-treatment populations both showed similar and substantial time-benefit associations for both door-to-puncture and door-to-reperfusion time intervals. For example, every 1 hour of delay in door-to-puncture was associated with a loss of 0.92 (95% CI, 0.16-1.68) healthy life-years in the early-treated population and with a loss of 0.86 (95% CI, 0.43-1.28) healthy life years in the late-treated population. Considering more granular time intervals, the loss of 0.92 healthy years per hour delay in early-treated patients is equivalent to a loss of 1.8 months per 10-minute delay, 5.6 days per 1-minute delay, and 2.2 hours per 1-second delay (Table 3).

In contrast to the time-benefit associations for door-tointervention time intervals, for the onset-to-door time interval, no statistically significant time-benefit association was pre-sent for either the early-treatment or the late-treatment population (Table 2).

Discussion

In this individual patient data pooled meta-analysis, substantial reductions in years of healthy life were associated in earlytreated patients with delays from last known well time to start of EVT procedures and to achievement of successful reperfusion and in both early-treated and late-treated patients with delays from door to procedure start and to reperfusion. Similar findings were noted for health-related quality of life at 3 months after stroke, as indexed by the UW-mRS. The timebenefit decrease was substantial: among early-treated patients, in the door-to-puncture time interval, each 1 hour of delay was associated with 0.92 healthy life-years lost and each 1 second of delay with 2.2 healthy life-hours lost.

In contrast, no association of treatment delay with outcomes was noted for several care process intervals that have less precision of temporal measurement, less representation of fast as well as slow progressors, or both. Of these, imprecision in recording timing of actual stroke onset likely is the greater factor. That time delays in the LKW-to-door interval were not associated with benefit decline in late-treated patients and in early-treated patients accords with the clinical recognition that times of stroke onset elicited by history are imprecise even in early-arriving patients who have reduced representation of wake-up and unwitnessed-onset strokes. Conversely, that time delays in the door-to-intervention interval were associated with benefit decrease in early-treated patients and in late-treated patients indicates that when time measures are fully reliable, as is the case with ED arrival, a substantial benefit decrease will be associated with time passage even fairly late after stroke onset. a The early-treatment population was defined as LKWTP Յ4 hours and the late-treatment population was defined as LKWTP >4 hours. b The UW-mRS is stated here in the conventional units of health utility, which range in value from 0 (death) to 1.00 (optimum health). For example, in the first row, the UW-mRS of -0.02 indicates that a patient's 90-day UW-mRS will be 0.02 points worse with every 1-hour delay in LKW-to-puncture time. c For example, in the second row, the DALY of 0.24 indicates that a patient will lose 0.24 years (2.9 months) of healthy life with every 1-hour delay in LKW-to-puncture time.

Healthy The association between EVT care delay and DALYs lost using an analysis confined to actual treatment times, actual patient ages, and actual outcomes among EVT-treated patients frames the analysis of the temporal dependency of benefit in unambiguous epochs of time. Prior studies estimated the effect of care delays on DALYs by applying patterns of mRS outcomes observed in clinical trials to an observational cohort not treated with EVT [START_REF] Meretoja | Endovascular therapy for ischemic stroke: save a minute-save a week[END_REF] and a theoretical patient group with an imputed fixed rate of loss of eligibility for EVT throughout the first 6 hours after onset. 6 Compared with these prior studies, the current investigation found moderately higher point estimates for the time-benefit decrease with treatment delay in EVT patients. The higher values may in part reflect the use of more reliably determined time points in the current study.

The current study is consonant with and extends prior studies that have reported much steeper decreases in benefit in dichotomous and ordinal mRS outcomes with postarrival care delays than with prearrival care days. 4,5,[START_REF] Menon | Analysis of workflow and time to treatment on thrombectomy outcome in the endovascular treatment for small core and proximal occlusion ischemic stroke (ESCAPE) randomized, controlled trial[END_REF][START_REF] Ribo | Association between time to reperfusion and outcome is primarily driven by the time from imaging to reperfusion[END_REF] This phenomenon has at least 3 potential sources. 5 First is the application of imaging criteria after emergency department arrival to exclude patients who have already developed large core infarcts from endovascular treatment. Thus, imaging removes patients with wake-up onset and unwitnessed onset in whom symptoms' first observed time was long after actual stroke onset with interval advanced infarct progression. Passing through this process is a population to be treated with EVT, all of whom have clinical-core, perfusion-core, or collateral-core mismatch. The resulting selected patients are physiologically homogeneous, all having a propensity for rapid infarct growth in postarrival minutes. This phenomenon has been termed the time-reset effect by Fiehler. [START_REF] Fiehler | The time-reset effect[END_REF] Second is the differential greater reliability of documented times in emergency department vs those for both unwitnessed and even witnessed stroke onset. Third is the possibility that human cerebral ischemic injury may follow an exponential or sigmoid growth trajectory, with more rapid progression at intermediate than very early aftersymptom onset times. The similarity of door-to-intervention time-benefit measures in early-arriving vs late-arriving patients suggests this third mechanism may be unlikely to be a major factor, as it would be expected to magnify early more than late associations.

The decline in EVT benefit with delay in door-topuncture and door-to-reperfusion time intervals in the current study supports ongoing quality efforts to shorten doorto-procedure times worldwide. The American Heart/ American Stroke Association Target: Stroke III program [START_REF]Target: Stroke Phase III Guide[END_REF] recommends 12 specific best practice strategies to accelerate door-to-device times, including prearrival notification of the neurointerventional team, rapid availability around the clock of the neurointerventional team, transfer directly from the brain imaging suite to the angiography suite, prereadied EVT equipment sets, rapid anesthesia protocols, and prompt workflow data feedback after every case. A particularly notable finding from the current investigation is the similarity of door-tointervention delays in worsening outcome between patients treated late (>4-12 hours) and patients treated early (≤4 hours) after last known well time. Among all patients who qualify for EVT based on imaging, regardless of time within the first 12 hours from onset, speedy postarrival workflow is necessary to maximize patient benefit. [START_REF] Goyal | Rapid alteplase administration improves functional outcomes in patients with stroke due to large vessel occlusions: meta-analysis of the noninterventional arm from the HERMES collaboration[END_REF]

Limitations

This study has limitations. The patient data come from randomized clinical trials with strict inclusion criteria that excluded patients with preexisting disability. Therefore, the outcomes of this analysis may not accurately reflect the changes of DALYs associated with EVT when applied to broader populations in routine practice, but they are fully applicable to patients who meet the highest level of guideline-endorsed eligibility for treatment, as these criteria reflect the clinical trial populations. 1 In addition, the analyzed trials had heterogeneous entry criteria and imaging methods. However, all pa- tients had disabling strokes with LVO and limited extent of early ischemic changes on baseline imaging. The utility scores used here were not directly collected from patients in each trial. Therefore, the DALYs lost may vary when applied to different populations. However, the utility weights were derived from 2 studies, 1 of a broad stroke patient population 19 and the other of international stroke health professionals 20 ; the similar weights identified in these studies with contrasting methods suggest a broadly applicable weighting. This study analyzed mostly patients enrolled in trials of relatively early EVT with limited imaging selection. Findings are not directly applicable to patients treated in late time windows up to 24 hours after onset after sophisticated imaging selection. [START_REF] Albers | DEFUSE 3 Investigators. Thrombectomy for stroke at 6 to 16 hours with selection by perfusion imaging[END_REF][START_REF] Nogueira | Thrombectomy 6 to 24 hours after stroke with a mismatch between deficit and infarct[END_REF] Finally, we projected lifetime disability status based on 90-day outcomes. Up to 25% of stroke patients may experience improvement in mRS scores between 3 months and 1 year after stroke. [START_REF] Ganesh | Late functional improvement and 5-year poststroke outcomes: a population-based cohort study[END_REF] This finding indicates that our estimates of the magnitude of DALYs lost with care process delays are likely conservative, as some patients will have lateoutcome time periods characterized by reduced disability.

Conclusions

Results of this study suggest that timely successful reperfusion is an important factor associated with EVT outcome. Delays, particularly after arrival to the hospital until reperfusion is achieved, may result in substantial losses in years of healthy life for patients. Efforts to optimize workflow and eliminate barriers preventing timely patient evaluation and treatment within health care systems are warranted.

Figure .

 . Figure. Association Between Postarrival Treatment Time and Disability-Adjusted Life-Years (DALYs) Lost After Endovascular Thrombectomy (EVT)

Table 1 .

 1 Healthy Life-Year Costs From Arrival to Endovascular Thrombectomy in Patients With Ischemic Stroke Original Investigation Research Patient Characteristics and Care Process Times According to LKWTP Time

		No./total No. (%)
		All	LKWTP ≤4 h	LKWTP >4 h
	Characteristic	(n = 781)	(n = 406)	(n = 375)
	Age, y
	Mean (SD) [No.]	65.5 (13.5) [781]	66.2 (13.4) [406]	64.7 (13.5) [375]
	Median (IQR)	67.0 (57.0-76.0)	68.0 (58.0-76.9)	66.0 (55.0-75.5)
	Female sex	367/781 (47.0)	189/406 (46.6)	177/375 (47.2)
	Atrial fibrillation	217/640 (33.9)	121/343 (35.3)	96/297 (32.3)
	Hypertension	426/779 (54.7)	238/405 (58.8)	188/374 (50.3)
	Hyperlipidemia	264/766 (34.5)	137/400 (34.3)	127/366 (34.7)
	Diabetes	120/780 (15.4)	69/405 (17.0)	51/375 (13.6)
	Prior stroke	89/777 (11.5)	49/403 (12.2)	40/374 (10.7)
	Glucose level, mg/dL
	Mean (SD) [No.]	133.5 (79.6) [755]	131.7 (62.3) [394]	135.5 (95.1) [361]
	Median (IQR)	120.0 (106.2-140.4)	118.8 (105.6-140.0)	121.0 (107.3-141.8)
	Prestroke mRS
	0	501/605 (82.8)	255/314 (81.2)	246/291 (84.5)
	1	76/605 (12.6)	49/314 (15.6)	27/291 (9.3)
	≥2	28/605 (4.6)	10/314 (3.2)	18/291 (6.2)
	NIHSS at baseline
	Mean (SD) [No.]	17.0 (4.8) [777]	17.2 (4.9) [403]	16.9 (4.7) [374]
	Median (IQR)	17.0 (14.0-21.0)	18.0 (14.0-21.0)	17.0 (14.0-20.0)
	tPA delivered	678/781 (86.8)	366/406 (90.1)	312/375 (83.2)
	Occlusion location
	ICA	198/733 (27.0)	103/387 (26.6)	95/346 (27.5)
	M1-segment middle	473/733 (64.5)	247/387 (63.8)	226/346 (65.3)
	cerebral artery
	M2-segment middle	61/733 (8.3)	37/387 (9.6)	24/346 (6.9)
	cerebral artery
	Other	1/733 (0.1)	0/387 (0.0)	1/346 (0.3)
	ASPECTS at baseline
	Mean (SD) [No.]	7.6 (1.8) [773]	7.9 (1.7) [401]	7.3 (1.9) [372]
	Median (IQR)	8.0 (7.0-9.0)	8.0 (7.0-9.0)	7.0 (6.0-9.0)	Abbreviations: ASPECTS, Alberta Stroke Program Early Computed
	TICI 2b/3	536/728 (73.6)	298/380 (78.4)	238/348 (68.4)	Tomography Score; ED, emergency
	LKW to randomization				department; ICA, internal carotid
	Mean (SD) [No.]	204.3 (95.3) [779]	144.6 (37.9) [406]	269.2 (96.6) [373]	artery; IQR, interquartile range; LKW, last known well; LKWTP, last
	Median (IQR)	183.0 (141.0-243.0)	146.0 (118.0-171.0)	248.0 (211.0-308.0)	known well/onset to puncture;
	LKW to puncture				mRS, modified Rankin Scale (scale
	Mean (SD) [No.]	249.4 (94.0) [781]	182.2 (40.5) [406]	322.3 (80.3) [375]	from 0 indicating no residual symptoms to 6 indicating death);
	Median (IQR)	240.0 (185.0-299.0)	188.0 (151.3-214.8)	300.0 (270.0-346.5)	NIHSS, National Institutes of Health
	LKW to reperfusion				Stroke Scale (with a range of 0-42;
	Mean (SD) [No.]	303.1 (106.7) [520]	233.9 (63.7) [271]	378.5 (92.1) [249]	the higher the score, the greater the stroke severity, with 0 indicating no
	Median (IQR)	291.5 (230.8-358.3)	234.0 (190.5-274.0)	358.0 (315.0-410.0)	signs of stroke and 42 indicating
	ED to puncture				coma); TICI, thrombolysis in cerebral
	Mean (SD) [No.]	121.2 (57.0) [743]	109.3 (41.4) [376]	133.5 (67.3) [368]	infarction (scores range from 0 indicating no perfusion to
	Median (IQR)	110.0 (78.0-150.5)	105.0 (76.0-135.0)	120.0 (80.8-175.0)	3 indicating complete perfusion);
	ED to reperfusion				tPA, tissue plasminogen activator.
	Mean (SD) [No.]	161.0 (69.2) [383]	152.9 (57.6) [211]	170.8 (80.3) [172]	SI conversion factor: To convert
	Median (IQR)	148.0 (112.5-197.0)	145.0 (111.5-185.5)	154.0 (113.8-205.5)	glucose to millimoles per liter, multiply by 0.0555.

jamaneurology.com (Reprinted) JAMA Neurology Published online May 3, 2021 E3 tial reperfusion was achieved more often in early than in late patients (298 of 380 [78.4%] vs 238 of 348 [68.4%]). Care process times in the patient treatment time window groups are shown in Table 1. In the early-treated population, the median LKWTD time was 188 minutes (IQR, 151.3-214.8 minutes) and median DTP time 105 minutes (IQR, 76-135 minutes). Among early-window patients in whom substantial reperfusion was achieved, median LKWTR time was 234 minutes (IQR, 190.5-274 minutes) and median DTR time 145 minutes (IQR, 111.5-185.5 minutes). Research Original Investigation Healthy Life-Year Costs From Arrival to Endovascular Thrombectomy in Patients With Ischemic Stroke E4 JAMA Neurology Published online May 3, 2021 (Reprinted) jamaneurology.com

Table 2 .

 2 Outcomes Measured According to DALYs Lost and UW-mRS in the EVT Arm According to Various Epochs in the Early-Treatment or the Late-Treatment Population a

			EVT arm, effect per 1-h delay (95% CI)
	Time interval	Outcome	Full cohort	LKWTP ≤4 h	LKWTP >4 h
	LKW to puncture	UW-mRS b	-0.02 (-0.04 to -0.009)	-0.06 (-0.11 to -0.005)	-0.03 (-0.06 to -0.004)
		DALY c	0.24 (0.02 to 0.46)	0.81 (0.08 to 1.55)	0.19 (-0.22 to 0.60)
	LKW to reperfusion	UW-mRS	-0.03 (-0.05 to -0.01)	-0.07 (-0.11 to -0.02)	-0.04 (-0.07 to -0.01)
		DALY	0.33 (0.09 to 0.57)	0.84 (0.28 to 1.39)	0.50 (0.07 to 0.92)
	ED arrival to puncture	UW-mRS	-0.08 (-0.11 to -0.06)	-0.10 (-0.15 to -0.05)	-0.08 (-0.11 to -0.05)
		DALY	0.93 (0.56 to 1.30)	0.92 (0.16 to 1.68)	0.86 (0.43 to 1.28)
	ED arrival to reperfusion	UW-mRS	-0.09 (-0.12 to -0.07)	-0.10 (-0.15 to -0.05)	-0.08 (-0.11 to -0.05)
		DALY	1.00 (0.67 to 1.33)	0.84 (0.26 to 1.42)	1.00 (0.60 to 1.41)
	LKW to door	UW-mRS	0.002 (-0.01 to 0.02)	0.04 (-0.01 to 0.09)	0.02 (-0.002 to 0.04)
		DALY	-0.04 (-0.25 to 0.16)	0.02 (-0.69 to 0.73)	-0.27 (-0.57 to 0.02)
	Abbreviations: DALY, disability-adjusted life-year; ED, emergency department;
	EVT, endovascular thrombosis; LKW, last known well; LKWTP, last known
	well/onset to puncture; UW-mRS, utility-weighted modified Rankin Scale.

  Life-Year Costs From Arrival to Endovascular Thrombectomy in Patients With Ischemic Stroke Original Investigation Research

jamaneurology.com (Reprinted) JAMA Neurology Published online May 3, 2021 E5

Table 3 .

 3 Healthy Life-Time Lost Associated With Delays in the DTP Time in the Early-Treated Population a Jovin TG, Chamorro A, Cobo E, et al; REVASCAT Trial Investigators. Thrombectomy within 8 hours after symptom onset in ischemic stroke. N Engl J Med. 2015;372(24):2296-2306. Campbell BCV, van Zwam WH, Goyal M, et al; HERMES Collaborators. Effect of general anaesthesia on functional outcome in patients with anterior circulation ischaemic stroke having endovascular thrombectomy versus standard care: a meta-analysis of individual patient data. Lancet Neurol. 2018;17(1):47-53. doi:10.1016/S1474-4422(17) 30407-6 15. Murray CJL, Lopez AD; World Health Organization; World Bank & Harvard School of Public Health. The global burden of disease: a comprehensive assessment of mortality and disability from diseases, injuries, and risk factors in 1990 and projected to 2020: summary. Published 1996. Accessed March 29, 2021. https://apps. who.int/iris/handle/10665/41864 16. Slot KB, Berge E, Dorman P, Lewis S, Dennis M, Sandercock P; Oxfordshire Community Stroke Project, the International Stroke Trial (UK); Lothian Stroke Register. Impact of functional status at six months on long term survival in patients with ischaemic stroke: prospective cohort studies. BMJ. Hong K-S, Saver JL. Quantifying the value of stroke disability outcomes: WHO global burden of disease project disability weights for each level of the modified Rankin Scale. Stroke. 2009;40(12): 3828-3833. doi:10.1161/STROKEAHA.109.561365 21. Chaisinanunkul N, Adeoye O, Lewis RJ, et al; DAWN Trial and MOST Trial Steering Committees; Additional contributors from DAWN Trial Steering Committee. Adopting a patient-centered approach to primary outcome analysis of acute stroke trials using a utility-weighted modified Rankin scale. Stroke. Research Original Investigation Healthy Life-Year Costs From Arrival to Endovascular Thrombectomy in Patients With Ischemic Stroke

	Healthy Life-Year Costs From Arrival to Endovascular Thrombectomy in Patients With Ischemic Stroke	Original Investigation Research
		Amount of healthy life-time lost
	Variable	Hours	Days	Months	Years
	Amount of delay in DTP time interval
	1 s	2.2	0.09	0.003	0.00026
	1 min	134.0	5.6	0.18	0.015
	10 min	1340.3	55.8	1.8	0.15
	1 h	8041.7	335.1	11.0	0.92
	Amount of delay in DTR time interval
	1 s	2.4	0.10	0.003	0.00028	Abbreviations: DTP, door-to-puncture;
	1 min	146.4	6.2	0.20	0.017	DTR, door-to-reperfusion.
	10 min	1464.4	61.0	2.0	0.17	a The early-treated population was
	1 h	8786.3	366.1	12.0	1.00	defined as onset to puncture Յ4 hours.

N Engl J Med. 2015;372(11):1009-1018. doi:10.1056/ NEJMoa1414792 10. Saver JL, Goyal M, Bonafe A, et al; SWIFT PRIME Investigators. Stent-retriever thrombectomy after intravenous t-PA vs t-PA alone in stroke. E8 JAMA Neurology Published online May 3, 2021 (Reprinted) jamaneurology.com

© 2021 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ by a Alberta Health Services User on 05/06/2021

Author Contributions: Drs Almekhlafi and Saver had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: Almekhlafi, Goyal, Jovin, Mitchell, Hill, Saver.


Jason Gauci

John De Carlo

Alessia Golfetti

Paola Tomasello

Linda Napoletano

Uğur Turhan

Suat Uslu

Birsen Yörük

Musa Güngören

Joao Gomes-Mota

Nadine Matton

Elpidio Romano

Sabrina Feletig

Daniela Geraldes

Filipa Manaia

Maria Macedo

Ana Ribeiro

Fabrice Drogoul

From education and training to the workplace: Gaps and challenges in aviation

Keywords: Aviation, education and training, future workplace

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The nature of work is constantly changing, and the aviation sector is no exception. In order to cope with these changes, it is necessary to equip workers with the skills and competences required to adapt to their workplace environment. This includes the upskilling and reskilling of workers. A recent survey found that private-sector organisations are increasingly considering investments in retraining and upskilling of existing workers as an urgent business priority [START_REF] Illanes | Retraining and reskilling workers in the age of automation[END_REF].

Several European research projects, such as Mobility4EU and SKILLFUL, have sought to predict what the future workplace will look like in a bid to understand what skills and competences will be required by future workers. The Mobility4EU project developed a vision for the European transport system in 2030, as well as an action plan to implement that vision. On the other hand, SKILLFUL identified the skills and competences that will be required by the transport workforce at various future milestones (up to 2050) and defined training methods and tools to meet those requirements. This paper presents and discusses the results of a study which was carried within the framework of the Skill-UP research project (Skill-UP, 2020. The study, which was conducted by means of an online survey and structured interviews, examined the transition from education and training to the workplace in the context of the aviation sector (both now and in the near future) and focussed on four main groups of Vocational Education and Training (VET) users, namely: flight crew, Air Traffic Control Officers (ATCOs), airport operators, and Unmanned Aircraft System (UAS) operators. The study also considered three target groups within each group of VET users: employees (new entrants and experienced professionals), employers and external training providers.

Method

Survey and interview design

Google Forms was used as the platform to design and conduct the survey. The survey consisted primarily of Likert scale rating questions; however, some open-ended questions were also included. The first section of the survey focussed on the participants' background (and was common to all participants) whereas the second section was tailored to each target group. The survey was designed to take approximately 15 minutes to complete and was disseminated to various stakeholders via email and social media channels.

The structured interviews were conducted with participants from each target group, with a different set of questions for each group. Participants within each target group were selected in such a way that the four groups of VET users were represented. The interview questions were mostly openended; however, some closed-ended questions, using rating scales, were also used. Each interview lasted approximately one hour.

In order to reach a wide audience, the surveyoriginally designed in Englishwas translated into Italian, Portuguese and Turkish. Similarly, the interviews were conducted in four different languages. The survey and interviews were carried out over a period of approximately six weeks and participation was completely voluntary.

Participant profile

The nationality and age of the survey and interview participants is shown in Figure 1. As can be observed, 79% of the participants were in their 30s, 40s and 50s which suggests that, probably, most of the participants were fairly experienced in their respective role. The gender distribution of survey participants was: 74% male, 25% female and 1% other. The number of participants in each target group and in each group of VET users is shown in Table 1.

Findings

Training gaps and issues

The survey participants were asked whether they followed any training programme prior to employment. Whilst the majority of flight crew and air traffic controllers (95% and 70% respectively) claimed to have followed a training programme, only 52% of those involved in airport operations and 50% of those involved in UAS operations claimed that they did. The participants were also asked to rate the quality of the training which they received prior to employment with respect to several key indicators (Figure 2). When considering all VET users, knowledge and experience of the instructors was rated highest, followed by delivery of training sessions and relationship between the trainer and trainees. Exposure to the workplace rated lowest. Table 2 highlights the main training gaps and issues identified by each group of VET users.

Workplace knowledge/skill gaps and challenges

The participants were asked to identify any knowledge/skill gaps and challenges which they experienced in the workplace at the beginning of their job, as well as methods which they used to approach them (Table 3).

Foreseen changes in the workplace

The participants were asked to identify changes which are expected to occur in the workplace in the near future (2030 and beyond) and any external factors which can impact the workplace (Table 4).

Impact of changes on jobs and roles

The participants were asked to state how much they agree with the statement that their jobs will change significantly in the near future, by giving a score from 1 (strongly disagree) to 6 agree). The overall average score was 4.6, with the highest average score (5.3) given by those involved in UAS operations. The participants were then asked to explain how their jobs and roles would be impacted by foreseen changes in the workplace (Table 5). The participants were also asked whether the importance of different competency areas will change in the future workplace. The top three competency areas which are expected to increase in importance for each group of VET users are given in Table 6.

Table 5: Impact of changes on jobs and roles

VET users Impact

Flight crew

The role of an airline pilot will continue to change, partly due to automation and AI The pilot's role will become more about managing equipment and people The level of threats caused by human factor issues will decrease Technology and AI will affect how pilot training and assessment are carried out Certain manned flights will become unmanned (coastal surveillance, inspections, etc.) In a single pilot cockpit, the pilot will be more isolated and will need to be more self-reliant

Air Traffic Control

ATCOs will transition from a purely operational role to one of managing complex systems Controllers will need to accept new technology, learn about it and learn how to use it Regulations will probably add more and more constraints The increase in air traffic will affect procedures and working methods With the introduction of remote towers, the controller will need to have a broader set of skills as he/she will have to do everything

Airport operations

Certain airport jobs will become obsolete whereas other jobs will be unaffected Some jobs may also be created as a result of technology and automation Operators will need much more automation training Operators will need to gain more expertise in managing health emergencies

UAS operations

• The role of the drone pilot may become redundant since it will be replaced by that of an operator who monitors and supervises the mission of a drone flying autonomously • The ability to fly a drone manually will remain important because a human operator will need to be able to override the "autonomous" mode of operation • Certain jobs in the area of unmanned aviation will become obsolete but new jobs will be created, including jobs related to planning, forecasting, maintenance, and management. • Pilots with a mix of manned and unmanned aircraft experience may be more employable

Discussion

As mentioned in the results, the majority of flight crew and ATCOs claimed to have followed a training programme prior to employment, whereas only around half of those involved in airport operations and UAS operations claimed that they did. This considerable difference can be explained by the fact that the training of flight crew and ATCOs is highly regulated and structured, whereas this is not necessarily the case for airport and UAS operations. For flight crew and ATCOs, the job requires a licence which is only obtained after completing a formal training programme which normally takes 18 to 24 months to complete. On the other hand, the majority of new airport employees are given on-the-job training, without having been formally trained beforehand. In the case of UAS operations, training has been neither well-regulated nor harmonised between countries (until now).

Some of the training gaps and issues were pointed out by multiple categories of VET users. For instance, the limited amount of human factors training and the lack of exposure to the workplace were both mentioned by flight crew and ATCOs. On the other hand, some training issues are specific to a particular group of VET users. For instance, airport operators mentioned the lack of training on immigration issues and document control, whereas UAS operators stated that current training programmes do not address real-world operations and rarely address specific drone applications (e.g. surveying and agriculture).

A closer look at the gaps and challenges associated with the workplace shows that some of them are clearly linked to training deficiencies, such as: differences between training and real-life; lack of knowledge of technical systems and regulations; and English speaking and writing. For instance, differences between training and real-life are partly due to limitations in the fidelity of simulator training e.g. static weather is used during training, whereas weather is dynamic in real life. Furthermore, simulator trainingespecially in the case of flight crewstill focuses on failures (e.g. single engine failure on takeoff) which have become extremely rare as aircraft systems have become more reliable. Instead, the participants stated that it should focus on more essential areas such as Upset Prevention and Recovery Training (UPRT).

Other gaps and challenges associated with the workplace are primarily due to the lack of experience of new employees and/or the unique characteristics of the work environment, implying that certain challenges are unavoidable. For instance, all groups of VET users mentioned challenges related to human factor issues. This is not surprising given that employees in each group work in a team, or have to deal with customers or with their own limitations. For example, ATCOs stated that new employees may be influenced by existing employees who may tell them to forget everything they learnt. Some controllers also said that there exists an unofficial hierarchy where the First Controller is always right even if he/she is wrong. Other gaps and challenges due to the specific nature of the workplace are: dealing with practicalities of the job; adapting to a commercial environment; and handling changes in company SOPs.

As observed from the results, technology and innovation are the key drivers of change. Technologyrelated changes are expected to be disruptive in the case of UAS operations, and incremental elsewhere. Nevertheless, changes in UAS operations are expected to affect the other groups of VET users as well. Regulation will also have to change, partly due to new technology; however, it will still lag behind technological advancements. In the case of UAS operations, a stronger and more harmonised regulatory framework will be required. In fact, a common EU drone regulatory framework has only recently come into force (primarily through EU Implementing Regulation 2019/947 and Commission Delegated Regulation 2019/945), replacing national rules (European Aviation Safety Agency, 2020). Apart from specific changes in the workplace, the participants also identified various external factors which could affect the work environment (and which are not specific to a particular group of users) such as climate change, contagious diseases (such as the COVID-19 pandemic) and the economy.

The most controversial technological change is probably that related to SPO. Some of the participants felt certain that SPO will happen because the technology is already there, with some saying that SPO will start with cargo operations. Other participants were less convinced, stating that SPO will occur but only beyond 2030, partly because none of the aircraft currently in production are tailored for SPO. Other participants even went as far as saying that SPO will never occur, at least not in commercial airline operations, because it is essential to have two pilots in the cockpit.

All jobs will be impacted by changes in the workplace, albeit to different degrees. Some jobs will be completely replaced by automation. For instance, certain manned flights will be replaced by drones. On the flip side, new jobs will be created as a by-product of new technology and this will necessitate the reskilling and upskilling of workers. This is in line with the view of the World Development Report (World Bank Group, 2019). Furthermore, roles which require Emotional Intelligence (EQ)such as those that involve human interaction and coordinationare less likely to be affected by new technology. This observation is in line with the findings of [START_REF] Muro | Automation and Artificial Intelligence[END_REF].

In the future, workers will rely more on automation and will need to be able to interact with it and manage it effectively. Automation will reduce the level of threats caused by human factor issues, such as in the case of flight crew and ATCOs. At the same time, however, the human being will become the last safety defence and will need to be able to take over if the automation fails. Therefore, the human being (e.g. in a single-pilot cockpit) will need to be more vigilant.

As mentioned in the results, adaptability, IT/computer literacy and technical expertise are three competency areas whose importance is most likely to increase for three of the groups of VET users. The importance of technology-related skills is in line with the results of other studies such as that carried out by [START_REF] Pomonia | Future trends in transport workforce based on demographic, behavioural, cultural and socioeconomic factors[END_REF]. On the other hand, the ability to adapt to changes in the workplace will depend on factors such as age and attitude. In general, the participants felt that younger people are more likely to adapt than older people because they are more accepting of new technologies and are more exposed to them; they are more willing to take risks (and less afraid of making mistakes); and they have more energy and a desire to prove themselves. However, some participants stated that having the right attitude is more important than age i.e. being open-minded and not resistant to change; being flexible in one's approach; being motivated; and showing an innate interest in learning.

Conclusion

This paper presented the results of an online survey and structured interviews conducted with 204 participants across four groups of VET users in the aviation sector. The survey and interviews identified: deficiencies in training; challenges in the workplace; foreseen changes in the future workplace; and the impact of those changes on jobs and roles. The study highlighted the overlap between training deficiencies and workplace challenges and the similarities and differences between groups of VET users; the role of technology and innovation as drivers of change; and the importance of reskilling and upskilling workers to help them adapt to the future workplace, which will be characterised by a higher degree of automation while still requiring human monitoring and intervention in the event of an emergency.

The results of this work will be used to identify new job profiles (also known as personas) for each group of VET users, such as profiles for remote tower controllers and SPO. Then, study pathways will be created for each job profile, followed by the design of new training programmes and assessment tools. It is expected that these training programmes and assessment tools will address the issues identified in this work and assist aviation workers to adapt to the future workplace.

Figure 1 :

 1 Figure 1: Participant nationality distribution (left) and age distribution (right)

Figure

  Figure 2: Quality of training

Table 1 :

 1 Number of participants in each category

	13% Italy, 26,	Other, 14, 7%	France, 54, 26%	4% older, 8, 60 or	Not specified, 3,	31, 15% 20-29, <19, 2, 1%
	Portugal, 27, 13%			50-59, 44, 22%
						30-39,
	Turkey, 38, 19%	Malta, 45, 22%	40-49, 61, 30%		55, 27%

Table 2 : Training gaps and issues VET users Training gaps and issues Flight crew

 2

		• Human factors training is limited	• Basic flying skills are not given
		• Training focusses on single pilot skills	sufficient importance
		whereas pilots work in a multi-crew	• Flight instructor training is done with
		environment	another instructor (i.e. no students are
		• Simulator time is limited	involved)
		• Abnormal scenario training is	• Flight instructors are not necessarily
		repetitive/predictable	experienced in the industry
		• Training regulations are outdated,	• Lack of exposure to the workplace
		prescriptive and restrictive	• Imbalance between theory and practice
	Air Traffic	• Human factors training is limited	• Training should focus more on multi-
	Control	• Training programmes are too prescriptive	tasking and handover techniques and
		and repetitive	teamwork
		• Training should focus more on problem-	• Instructors should be practitioners
		solving scenarios	• Lack of exposure to the workplace
		• Imbalance between theory and practice	• Further harmonisation of training
		• Simulator time is limited and should be	requirements may reduce amount of
		more realistic	local training (i.e. by the employer)
	Airport	• Inadequate training on immigration issues,	• Lack of training on emergency
	operations	document checking and control	response and management
		• Inadequate training on handling of	• Training should focus more on essential
		passenger complaints/conflicts	tasks and individual deficiencies
		• Inadequate training on the use of manual	• More practical training for Aircraft
		procedures in the event of automated	Rescue and Fire Fighting (ARFF)
		system failures	personnel is required
	UAS	• Limited amount of instructors and of	• Training programmes do not address
	operations	approved training organisations for	real-world operations
		Remotely Piloted Aircraft Systems	• No adequate and harmonised regulatory
		(RPAS)	guidance exists
		• The quality of RPAS training	• Initial training is too focused on
		organisations is variable	technical aspects
		• Training should focus more on safety-	• Lack of interdisciplinarity in training
		related issues besides operational issues
		• Lack of training of 'soft' skills

Table 3 :

 3 Workplace knowledge/skill gaps and challenges

	VET	Workplace gaps and challenges
	users Flight crew	• Limited knowledge of specific aircraft/systems → refer to more experienced colleagues; train in a simulator	• Human factor issues (e.g. workload, fatigue) → address issues during debriefing
		• Handling of scenarios (e.g. weather patterns)	• Logistical challenges
		not encountered in training → consult with	• Getting used to geo-political
		senior crew members	influences and foreign cultures

Table 4 :

 4 Changes and factors which will impact the workplace in the near future

	VET users	Changes and factors
	Flight crew Technology (automatic take-off, Single	Climate change
		Pilot Operations (SPO), etc.)	The global economy
		Drones and drone transportation	Training tools
		Regulation	Airline policies
		Contagious diseases	Security
	Air Traffic	Technology (remote towers, assistance	Contagious diseases
	Control	systems driven by Artificial Intelligence (AI), etc.)	Climate change

Table 6 :

 6 Top three competency areas for each group of VET users

		VET users
		Flight crew	Air Traffic Control	Airport operations	UAS operations
	area	complexity Dealing with	IT/computer literacy	IT/computer literacy	Technical expertise
	Competency	Adaptability IT/computer literacy	Adaptability Technical expertise	Technical expertise Problem solving	Dealing with complexity Adaptability