External validation of triage tools for adults with suspected COVID-19 in a middle-income setting: an observational cohort study.

BACKGROUND: Tools proposed to triage ED acuity in suspected COVID-19 were derived and validated in higher income settings during early waves of the pandemic. We estimated the accuracy of seven risk-stratification tools recommended to predict severe illness in the Western Cape, South Africa. METHODS: An observational cohort study using routinely collected data from EDs across the Western Cape, from 27 August 2020 to 11 March 2022, was conducted to assess the performance of the PRIEST (Pandemic Respiratory Infection Emergency System Triage) tool, NEWS2 (National Early Warning Score, version 2), TEWS (Triage Early Warning Score), the WHO algorithm, CRB-65, Quick COVID-19 Severity Index and PMEWS (Pandemic Medical Early Warning Score) in suspected COVID-19. The primary outcome was intubation or non-invasive ventilation, death or intensive care unit admission at 30 days. RESULTS: Of the 446 084 patients, 15 397 (3.45%, 95% CI 34% to 35.1%) experienced the primary outcome. Clinical decision-making for inpatient admission achieved a sensitivity of 0.77 (95% CI 0.76 to 0.78), specificity of 0.88 (95% CI 0.87 to 0.88) and the negative predictive value (NPV) of 0.99 (95% CI 0.99 to 0.99). NEWS2, PMEWS and PRIEST scores achieved good estimated discrimination (C-statistic 0.79 to 0.82) and identified patients at risk of adverse outcomes at recommended cut-offs with moderate sensitivity (>0.8) and specificity ranging from 0.41 to 0.64. Use of the tools at recommended thresholds would have more than doubled admissions, with only a 0.01% reduction in false negative triage. CONCLUSION: No risk score outperformed existing clinical decision-making in determining the need for inpatient admission based on prediction of the primary outcome in this setting. Use of the PRIEST score at a threshold of one point higher than the previously recommended best approximated existing clinical accuracy.

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

1482 Figure 2Performance of tools predicting composite primary outcome for the Omicron period[Figure omitted. See PDF] 1482 Table 1Triage tool diagnostic accuracy statistics (95% CI) for predicting any adverse outcome (entire study period)Tool N* C-statistic Threshold N (%) above threshold Sensitivity Specificity PPV NPV CRB-65 432,584 0.70 (0.70, 0.71) >0 102,964 (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) NEWS2 433,101 0.80 (0.79, 0.80) >1 178835 (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) PMEWS 438,810 0.79 (0.79, 0.79) >2 199,386 (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) PRIEST 438,880 0.82 (0.82, 0.82) >4 158,893 (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) WHO 437,850 0.71 (0.71, 0.72) >0 235,775 (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) TEWS 432,612 0.72 (0.71, 0.72) >2 134,097 (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 COVID 446,088 0.70 (0.69, 0.70) >3 35,145 (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 <3 parameters were excluded from analysis when estimating performance 1482 Table 2Triage tool diagnostic accuracy statistics (95% CI) for predicting any adverse outcome (Omicron period)Tool N* C-statistic Threshold N (%) above threshold Sensitivity Specificity PPV NPV CRB-65 136,961 0.69 (0.68, 0.70) >0 31,373 (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) NEWS2 137,125 0.77 (0.76, 0.78) >1 76,183 (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) PMEWS 138,954 0.76 (0.75, 0.76) >2 59,876 (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) PRIEST 158,893 0.78 (0.77, 0.79) >4 46,529 (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) WHO 138,666 0.62 (0.61, 0.63) >0 72,599 (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) TEWS 136,967 0.73 (0.72, 0.74) >2 39,509 (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 COVID 140520 0.61 (0.60, 0.63) >3 8,210 (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 <3 parameters were excluded from analysis when estimating performanceResults 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) o 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.

A COVID-19 field hospital in a conference centre - The Cape Town, South Africa experience.

BACKGROUND: The coronavirus pandemic has put extreme pressure on health care services in South Africa. AIM: To describe the design, patients and outcomes of a field hospital during the first wave of the coronavirus disease 2019 (COVID-19) pandemic. SETTING: The Cape Town International Convention Centre was the first location in Cape Town to be commissioned as a field hospital that would serve as an intermediate care bed facility. METHODS: This was a retrospective descriptive study of patients admitted to this facility between 8th June 2020 and 14th August 2020 using deidentified data extracted from patient records. RESULTS: There were 1502 patients admitted, 56.4% female, with a mean age of 58.6 years (standard deviation [s.d.]: 14.2). The majority of patients (82.9%) had at least one comorbidity, whilst 15.4% had three or more. Nearly 80.0% (79.8%) of patients required oxygen and 63.5% received steroids, and only 5.7% of patients were required to be transferred for escalation of care. The mean length of stay was 6 days (s.d.: 4.8) with an overall mortality of 5.7%. CONCLUSION: This study highlights the role of a field hospital in providing surge capacity. Its use halved the predicted duration of stay at acute care hospitals, allowing them the capacity to manage more unstable and critical patients. Adaptability and responsivity as well as adequate referral platforms proved to be crucial. Daily communication with the whole health care service platform was a critical success factor. This study provides information to assist future health planning and strategy development in the current pandemic and future disease outbreaks.

SEeking AnsweRs for Care Homes during the COVID-19 pandemic (COVID SEARCH).

The care and support of older people residing in long-term care facilities during the COVID-19 pandemic has created new and unanticipated uncertainties for staff. In this short report, we present our analyses of the uncertainties of care home managers and staff expressed in a self-formed closed WhatsApp™ discussion group during the first stages of the pandemic in the UK. We categorised their wide-ranging questions to understand what information would address these uncertainties and provide support. We have been able to demonstrate that almost one-third of these uncertainties could have been tackled immediately through timely, responsive and unambiguous fact-based guidance. The other uncertainties require appraisal, synthesis and summary of existing evidence, commissioning or provision of a sector- informed research agenda for medium to long term. The questions represent wider internationally relevant care home pandemic-related uncertainties.