ABSTRACT
BACKGROUND: Guidance documents are a valuable resource to clinicians to guide evidenced-based decision making. The quality of guidelines in anaesthesia and across other specialties has been demonstrated to be poor. COVID-19 presented an urgent need for immediate guidance for anaesthetists as frontline clinicians. The aim of this study was to evaluate the quality of COVID-19 guidance documents using the internationally validated Appraisal of Guidelines for Research & Evaluation (AGREE) II tool. METHODS: A search was conducted in Ovid EMBASE and Ovid MEDLINE to identify all COVID-19 anaesthesia guidance documents from 2020-2021. Thirty-eight guidance documents were selected for analysis by 4 independent appraisers using the AGREE II instrument, across its 6 domains and 23 items. A scoring threshold for high quality was agreed by the working group via consensus. RESULTS: Overall, the body of COVID-19 guidance documents achieved poor scores using AGREE II. Only 5% of documents met the high-quality criteria. Markers of quality included international and multi-institutional collaboration. Document title ('guideline' vs 'consensus statement'/ 'recommendations') did not yield any differences in domain scores and overall quality ratings. Compared with recent general anaesthesia guidelines, COVID-19 guidelines performed significantly worse. CONCLUSIONS: COVID-19 guidance documents published during the first two years of the pandemic lacked rigour and appropriate quality. This raises concern about their trustworthiness for use in clinical practice. Enhanced systems are required to ensure the integrity of rapidly formulated guidance.
Subject(s)
Anesthesia , COVID-19 , Humans , ConsensusABSTRACT
Guidance documents are a valuable resource to clinicians to guide evidenced-based decision making. The quality of guidelines in anaesthesia and across other specialties has been demonstrated to be poor. COVID-19 presented an urgent need for immediate guidance for anaesthetists as frontline clinicians. The aim of this study was to evaluate the quality of COVID-19 guidance documents using the internationally validated Appraisal of Guidelines for Research & Evaluation (AGREE) II tool. A search was conducted in Ovid EMBASE and Ovid MEDLINE to identify all COVID-19 anaesthesia guidance documents from 2020-2021. Thirty-eight guidance documents were selected for analysis by 4 independent appraisers using the AGREE II instrument, across its 6 domains and 23 items. A scoring threshold for high quality was agreed by the working group via consensus. Overall, the body of COVID-19 guidance documents achieved poor scores using AGREE II. Only 5% of documents met the high-quality criteria. Markers of quality included international and multi-institutional collaboration. Document title (‘guideline’ vs ‘consensus statement’/’recommendations’) did not yield any differences in domain scores and overall quality ratings. Compared with recent general anaesthesia guidelines, COVID-19 guidelines performed significantly worse. COVID-19 guidance documents published during the first two years of the pandemic lacked rigour and appropriate quality. This raises concern about their trustworthiness for use in clinical practice. Enhanced systems are required to ensure the integrity of rapidly formulated guidance.
ABSTRACT
OBJECTIVES: To prevent the emergence of new waves of COVID-19 caseload and associated mortalities, it is imperative to understand better the efficacy of various control measures on the national and local development of this pandemic in space-time, characterise hotspot regions of high risk, quantify the impact of under-reported measures such as international travel and project the likely effect of control measures in the coming weeks. METHODS: We applied a deep recurrent reinforced learning based model to evaluate and predict the spatiotemporal effect of a combination of control measures on COVID-19 cases and mortality at the local authority (LA) and national scale in England, using data from week 5 to 46 of 2020, including an expert curated control measure matrix, official statistics/government data and a secure web dashboard to vary magnitude of control measures. RESULTS: Model predictions of the number of cases and mortality of COVID-19 in the upcoming 5 weeks closely matched the actual values (cases: root mean squared error (RMSE): 700.88, mean absolute error (MAE): 453.05, mean absolute percentage error (MAPE): 0.46, correlation coefficient 0.42; mortality: RMSE 14.91, MAE 10.05, MAPE 0.39, correlation coefficient 0.68). Local lockdown with social distancing (LD_SD) (overall rank 3) was found to be ineffective in preventing outbreak rebound following lockdown easing compared with national lockdown (overall rank 2), based on prediction using simulated control measures. The ranking of the effectiveness of adjunctive measures for LD_SD were found to be consistent across hotspot and non-hotspot regions. Adjunctive measures found to be most effective were international travel and quarantine restrictions. CONCLUSIONS: This study highlights the importance of using adjunctive measures in addition to LD_SD following lockdown easing and suggests the potential importance of controlling international travel and applying travel quarantines. Further work is required to assess the effect of variant strains and vaccination measures.