1482 Prognostic accuracy of triage tools for adults with suspected COVID-19 in a middle-income setting

Aims, Objectives and BackgroundUneven vaccination in low- and middle-income settings and less resilient health care provision mean that emergency health care systems may still be at risk of being overwhelmed during periods of increased COVID-19 infection. Risk stratification tools proposed to allow rapid triage of need for admission in ED settings have almost exclusively been developed and validated in high-income settings during early waves of the pandemic.Our study aimed to estimate the accuracy of risk-stratification tools recommended to predict severe illness in adults with suspected COVID-19 infection in the Western Cape of South Africa.Method and DesignAn observational cohort study using routinely electronically collected clinical information in all state-run hospitals in the Western Cape between 27th August 2020 and 11th March 2022 was conducted to assess performance of the PRIEST tool, NEWS2, the WHO algorithm, CRB-65, TEWS, Quick Covid Severity Index and PMEWS in patients with suspected COVID-19. The primary outcome was death, respiratory support or ICU admission.Abstract 1482 Figure 1Performance of tools predicting composite primary outcome for total study periodAbstract 1482 Figure 2Performance of tools predicting composite primary outcome for the Omicron periodAbstract 1482 Table 1Triage tool diagnostic accuracy statistics (95% CI) for predicting any adverse outcome (entire study period)ToolN*C-statisticThresholdN (%) above thresholdSensitivitySpecificityPPVNPVCRB-65432,5840.70(0.70, 0.71)>0102,964 (23.8%)0.61(0.61, 0.61)0.78(0.77, 0.78)0.09(0.09, 0.09)0.98(0.98, 0.98)NEWS2433,1010.80(0.79, 0.80)>1178835 (41.3%)0.83(0.83, 0.83)0.6(0.6,0.6)0.07(0.07–0.07)0.99(0.99, 0.99)PMEWS438,8100.79(0.79, 0.79)>2199,386 (45.4%)0.85(0.85, 0.85)0.56(0.56, 0.56)0.06(0.06, 0.07)0.99 (0.99,0.99)PRIEST438,8800.82(0.82, 0.82)>4158,893 (36.2%)0.83(0.83, 0.83)0.65 (0.65,0.66)0.08(0.08, 0.08)0.99(0.99, 0.99)WHO437,8500.71(0.71, 0.72)>0235,775 (53.8%)0.82(0.81, 0.82)0.47(0.47, 0.47)0.05(0.05, 0.05)0.99(0.99, 0.99)TEWS432,6120.72(0.71, 0.72)>2134,097 (31%)0.62(0.62, 0.62)0.70(0.70, 0.70)0.07(0.07, 0.07)0.98(0.98, 0.98)Quick COVID446,0880.70(0.69, 0.70)>335,145 (7.9%)0.33(0.33, 0.33)0.93(0.93, 0.93)0.14(0.14, 0.14)0.98(0.98, 0.98)*Patients with Abstract 1482 Table 2Triage tool diagnostic accuracy statistics (95% CI) for predicting any adverse outcome (Omicron period)ToolN*C-statisticThresholdN (%) above thresholdSensitivitySpecificityPPVNPVCRB-65136,9610.69(0.68, 0.70)>031,373 (22.9%)0.59(0.59, 0.59)0.78(0.78, 0.78)0.05(0.05, 0.05)0.99(0.99, 0.99)NEWS2137,1250.77(0.76, 0.78)>176,183 (55.6%)0.87(0.87, 0.87)0.45(0.45, 0.45)0.03(0.03, 0.03)0.99(0.99, 0.99)PMEWS138,9540.76(0.75, 0.76)>259,876 (43.1%)0.80(0.80, 0.80)0.58(0.58, 0.58)0.04(0.04, 0.04)0.99(0.99, 0.99)PRIEST158,8930.78(0.77, 0.79)>446,529 (33.5%)0.75(0.75, 0.75)0.67(0.67, 0.67)0.04(0.04, 0.04)0.99(0.99, 0.99)WHO138,6660.62(0.61, 0.63)>072,599 (52.4%)0.70(0.70, 0.70)0.48(0.48, 0.48)0.03(0.03, 0.03)0.99(0.99, 0.99)TEWS136,9670.73(0.72, 0.74)>239,509 (28.8%)0.64(0.64, 0.64)0.72(0.72, 0.72)0.04(0.04, 0.04)0.99(0.99, 0.99)Quick COVID1405200.61(0.60, 0.63)>38,210(6.4%)0.17(0.17, 0.17)0.94(0.94, 0.94)0.06(0.06, 0.06)0.98(0.98, 0.98)*Patients with Results and ConclusionOf the 446,084 patients, 15,397 patients (3.45%, 95% CI:34% to 35.1%) experienced the primary outcome. Figure 1 presents the ROC curves for the triage tools for the total study period and figure 2 for the period of the Omicron wave. NEWS2, PMEWS, PRIEST tool and WHO algorithm identified patients at risk of adverse outcomes at recommended cut-offs with moderate sensitivity (>0.8) and specificity ranging from 0.47 (NEWS2) to 0.65 (PRIEST tool). The low prevalence of the primary outcome, especially in the Omicron period, meant use of these tools would have more than doubled admissions with only a small reduction in risk of false negative triage.Triage tools developed specifically in low- and middle-income settings may be needed to provide accurate risk prediction. Existing triage tools may need to be used at varying thresholds to reflect different baseline-line risks of adverse outcomes in different settings.