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BackgroundUneven vaccination and less resilient health care systems mean hospitals in LMICs are at risk of being overwhelmed during periods of increased COVID-19 infection. Risk-scores proposed for rapid triage of need for admission from the emergency department (ED) have been developed in higher-income settings during initial waves of the pandemic.MethodsRoutinely collected data for public hospitals in the Western Cape, South Africa from the 27thAugust 2020 to 11thMarch 2022 were used to derive a cohort of 446,084 ED patients with suspected COVID-19. The primary outcome was death or ICU admission at 30 days. The cohort was divided into derivation and Omicron variant validation sets. We developed the LMIC-PRIEST score based on the coefficients from multivariable analysis in the derivation cohort and existing triage practices. We externally validated accuracy in the Omicron period and a UK cohort.ResultsWe analysed 305,564, derivation 140,520 Omicron and 12,610 UK validation cases. Over 100 events per predictor parameter were modelled. Multivariable analyses identified eight predictor variables retained across models. We used these findings and clinical judgement to develop a score based on South African Triage Early Warning Scores and also included age, sex, oxygen saturation, inspired oxygen, diabetes and heart disease. The LMIC-PRIEST score achieved C-statistics: 0.82 (95% CI: 0.82 to 0.83) development cohort; 0.79 (95% CI: 0.78 to 0.80) Omicron cohort; and 0.79 (95% CI: 0.79 to 0.80) UK cohort. Differences in prevalence of outcomes led to imperfect calibration in external validation. However, use of the score at thresholds of three or less would allow identification of very low-risk patients (NPV ≥0.99) who could be rapidly discharged using information collected at initial assessment.ConclusionThe LMIC-PRIEST score shows good discrimination and high sensitivity at lower thresholds and can be used to rapidly identify low-risk patients in LMIC ED settings.What is already known on this subjectUneven vaccination in low- and middle-income countries (LMICs) coupled with less resilient health care provision mean that emergency health care systems in LMICs may still be at risk of being overwhelmed during periods of increased COVID-19 infection.Risk-stratification scores may help rapidly triage need for hospitalisation. However, those proposed for use in the ED for patients with suspected COVID-19 have been developed and validated in high-income settings.What this study addsThe LMIC-PRIEST score has been robustly developed using a large routine dataset from the Western Cape, South Africa and is directly applicable to existing triage practices in LMICs.External validation across both income settings and COVID-19 variants showed good discrimination and high sensitivity (at lower thresholds) to a composite outcome indicating need for inpatient admission from the EDHow this study might affect research, practice or policyUse of the LMIC-PRIEST score at thresholds of three or less would allow identification of very low-risk patients (negative predictive value ≥0.99) across all settings assessedDuring periods of increased demand, this could allow the rapid identification and discharge of patients from the ED using information collected at initial assessment.

BACKGROUND At the time of the UK COVID-19 lockdowns, online health forums (OHFs) were one of the relatively few remaining accessible sources of peer support for people living with breast cancer. Cancer services were heavily affected by the pandemic in many ways including the closure of many of the customary support services. Previous research indicates that loneliness, anxiety, distress and depression caused by COVID-19 were common amongst people living with breast cancer, and this suggests that the role of the OHF in providing users with support, information and empathy could have been of increased importance at that time. OBJECTIVE The aim of this paper is to examine how people living with breast cancer used an online health forum during COVID-19. METHODS This qualitative study thematically analysed posts from the discussion forums of an OHF provided by the UK charity, Breast Cancer Now. We selected 1,053 posts from the time of two UK lockdowns: 16 March - 15 June 2020 (Lockdown 1), and 6 January – 8 March 2021 (Lockdown 3) for analysis from two of the forum’s boards (for recently diagnosed people and for those undergoing chemotherapy). We analysed the data using Braun & Clarke’s original six steps for thematic analysis, but following a ‘codebook’ approach. Some descriptive statistics were also obtained. RESULTS We found that COVID-19 amplified the forum’s value to its users. As cancer patients, participants were in a situation that was ‘bad enough already’ and COVID-19 amplified this. The forum, already highly regarded, became even more valued for the information and peer support it continued to provide. It also increased in value because COVID-19 caused some special information needs that the forum users were uniquely well-placed to fulfil, as people experiencing the ‘double whammy’ of cancer-during-covid. The forum also met emotional needs generated by the pandemic, and was valued as a place where loneliness during COVID-19 might be relieved and users’ spirits lifted in a variety of ways specific to the time. We found some differences in usage between the two periods and the two boards: most noticeable was the greater fear and anxiety expressed at the start of Lockdown 1. Both the start and end of the lockdown periods were particularly difficult for participants. The end of lockdowns were seen as potentially increasing isolation, as patients saw everyone else resuming normal life, whilst they had to remain cautious. CONCLUSIONS The forums were an important source of support and information to their users, with their value increasing during the lockdowns for a variety of reasons. Our findings will be helpful to organizations offering OHFs, and to healthcare workers advising people living with breast cancer on sources of support.

Study ObjectiveTools proposed to triage acuity in suspected COVID-19 in the ED have been 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.MethodsAn observational cohort study using routinely collected data from EDs across the Western Cape, from the 27th of August 2020 to 11th March 2022 was conducted to assess performance of the PRIEST tool, NEWS2, TEWS, the WHO algorithm, CRB-65, Quick COVID-19 Severity Index and PMEWS in suspected COVID-19. The primary outcome was death or ICU admission.ResultsOf 446,084 patients, 15,397 patients (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 0.88 (95% CI 0.87 to 0.88) and the negative predictive value (NPV) 0.99 (95% CI 0.99 to 0.99). NEWS2, PMEWS and PRIEST tool 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). Use of the tools at recommended thresholds would have more than doubled admissions with only a 0.01% reduction in false negative triage.ConclusionUse of the PRIEST score, NEWS2 and PMEWS at a threshold of a point higher would achieve similar accuracy to current clinical admission decision, with possible gains in transparency and speed of decision-making.

Background Patients with diabetes may experience different needs according to their diabetes stage. These needs may be met via online health communities in which individuals seek health-related information and exchange different types of social support. Understanding the social support categories that may be more important for different diabetes stages may help diabetes online communities (DOCs) provide more tailored support to web-based users. Objective This study aimed to explore and quantify the categorical patterns of social support observed in a DOC, taking into consideration users’ different diabetes stages, including prediabetes, type 2 diabetes (T2D), T2D with insulin treatment, and T2D remission. Methods Data were collected from one of the largest DOCs in Europe: Diabetes.co.uk. Drawing on a mixed methods content analysis, a qualitative content analysis was conducted to explore what social support categories could be identified in users’ posts. A total of 1841 posts were coded by 5 human annotators according to a modified version of the Social Support Behavior Code, including 7 different social support categories: achievement, congratulations, network support, seeking emotional support, seeking informational support, providing emotional support, and providing informational support. Subsequently, quantitative content analysis was conducted using chi-square post hoc analysis to compare the most prominent social support categories across different stages of diabetes. Results Seeking informational support (605/1841, 32.86%) and providing informational support (597/1841, 32.42%) were the most frequent categories exchanged among users. The overall distribution of social support categories was significantly different across the diabetes stages (χ218=287.2; P.001). Users with T2D under insulin treatment provided more informational and emotional support (P Conclusions This is the first study to highlight what, how, and when different types of social support may be beneficial at different stages of diabetes. Multiple stakeholders may benefit from these findings that may provide novel insights into how these categories can be strategically used and leveraged to support diabetes management.

BackgroundEmergency Medical Services (EMS) have experienced surges in demand as the COVID-19 pandemic has progressed with ambulances services in the UK declaring major incidents due to the risk of care being compromised. COVID-19 specific EMS telephone triage tools have been introduced to help manage demand. There has been no previous evaluation of the accuracy of EMS telephone triage in identifying patients with suspected COVID-19 at risk of serious adverse outcome.We aimed to assess accuracy of EMS telephone triage in identifying patients who need an EMS response and identify factors which affect triage accuracy.MethodPatients who made an emergency call to Yorkshire Ambulance Service between 2nd April and 29th June 2020 and were assessed using an AMPDS pandemic pathway for suspected COVID-19 were linked to Office for National Statistics death registration data, hospital and general practice electronic health care data collected by NHS Digital.Accuracy of decision to dispatch an ambulance was assessed in terms of death or need for organ support at 30 days from the first 999 call. Multivariable logistic regression was used to identify factors associated with false negative and false positive triage.ResultsOf 12, 653 callers included in the study population, 11.1% experienced the primary composite adverse outcome. Using the triage pathway, 16% of callers did not receive an emergency response and they had a lower risk (3.5%) of the primary outcome. Ambulances were dispatched to 4, 230 callers (33.4%) who were not subsequently conveyed to hospital and did not experience the primary outcome (false positive triage). Multivariable modelling found older age and presence of pre-existing respiratory disease were significant predictors of false positive triage.ConclusionEMS telephone triage avoided 16% of calls receiving an emergency ambulance, of whom 3.5% died or needed organ support by 30 days. Telephone triage can therefore reduce the burden of EMS responses but with the cost of a small proportion of patients who do not receive an initial emergency response deteriorating. Research is needed to identify the appropriate balance between over- and under-triage

BackgroundTools 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.MethodsAn 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.ResultsOf 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.ConclusionNo 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.