key: cord-1004414-cpc6nh2p authors: Ferro, Ashley; Kotecha, Sanjeev; Auzinger, Georg; Yeung, Elizabeth; Fan, Kathleen title: Systematic review and meta-analysis of tracheostomy outcomes in covid-19 patients date: 2021-05-18 journal: Br J Oral Maxillofac Surg DOI: 10.1016/j.bjoms.2021.05.011 sha: cdda41004755177ab7f4da3e89d0ace899cad21c doc_id: 1004414 cord_uid: cpc6nh2p A systematic review and meta-analysis of the entire COVID-19 Tracheostomy cohort was conducted to determine the cumulative incidence of complications, mortality, time to decannulation and ventilatory weaning. Outcomes of surgical versus percutaneous and outcomes relative to tracheostomy timing were also analysed. Studies reporting outcome data on patients with COVID-19 undergoing tracheostomy were identified and screened by 2 independent reviewers. Preferred Reporting Items or Systematic Reviews and Meta-Analysis (PRISMA) guidelines were followed. Outcome data were analysed using a random-effects model. From 1016 unique studies, 39 articles reporting outcomes for a total of 3929 patients were included for meta-analysis. Weighted mean follow-up time was 42.03 ± 26 days post-tracheostomy. Meta-analysis showed that 61.2% of patients were weaned from mechanical ventilation [95%CI 52.6%-69.5%], 44.2% of patients were decannulated [95%CI 33.96%-54.67%], and cumulative mortality was found to be 19.23% [95%CI 15.2%-23.6%] across the entire tracheostomy cohort. The cumulative incidence of complications was 14.24% [95%CI 9.6%-19.6%], with bleeding accounting for 52% of all complications. No difference was found in incidence of mortality (RR1.96; p = 0.34), decannulation (RR1.35, p = 0.27), complications (RR0.75, p = 0.09) and time to decannulation (SMD 0.46, p = 0.68) between percutaneous and surgical tracheostomy. Moreover, no difference was found in mortality (RR1.57, p = 0.43) between early and late tracheostomy, and timing of tracheostomy did not predict time to decannulation. 10 confirmed nosocomial staff infections were reported from 1398 tracheostomies. This study provides an overview of outcomes of tracheostomy in COVID-19 patients, and contributes to our understanding of tracheostomy decisions in this patient cohort. The outbreak and global propagation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 , led the World Health Organization to declare a pandemic in March 2020. Extraordinary burden has been placed on healthcare systems as a consequence of the respiratory and other end-organ sequelae of COVID-19, with many patients requiring intensive care unit (ICU) admission for invasive mechanical ventilation and other organ support [1] [2] [3] . Tracheostomies may be undertaken where prolonged mechanical ventilation is anticipated in order to facilitate weaning from both mechanical ventilation and sedation, as well as to try and reduce length of stay and ventilator-associated morbidity 4, 5 . Furthermore, tracheostomies may help to ameliorate resource constraints by increasing tube tolerance, which can reduce the incidence of accidental extubations and thus mitigate the strain on critical care services inherent to the COVID-19 pandemic 2,6,7 . To date, several studies have been published pertaining to tracheostomies in patients with COVID-19. Nevertheless, there is lacking consensus with regards to tracheostomy strategy and this is exacerbated by limited data, patient heterogeneity and the dynamic nature of the pandemic [8] [9] [10] [11] . This study therefore had several aims. First, to synthesise the current outcome data on all COVID-19 patients who have undergone tracheostomy; second, to compare outcomes and patient demographics between those patients that have had surgical or percutaneous tracheostomy; third, to determine whether timing of tracheostomy post-intubation influences outcomes and, finally, to provide recommendations to improve the quality of reporting on COVID-19 outcome data as the pandemic progresses. Study characteristics were independently extracted from selected articles by 2 independent investigators. The following baseline characteristics were extracted: total number of tracheostomies; patient age; body mass index (BMI); comorbidities; smoking status; proportion of female vs male; tracheostomy type; patient ethnicity; pre-operative C-reactive protein (CRP); pre-operative respiratory indices (including fraction of inspired oxygen (FiO2); mean partial pressure of oxygen (PaO2) and positive end-expiratory pressure (PEEP)); Acute Physiology and Chronic Health Evaluation II (APACHE II) score; and time from intubation to tracheostomy. Collected outcome criteria include number of patients decannulated; number of patients successfully weaned off mechanical ventilation; the time from tracheostomy to decannulation and successful weaning; the number of patients who died during follow-up and the mean follow-up period. The number of staff members directly involved in tracheostomies who received a positive COVID-19 result or who became symptomatic during the follow up period was also recorded. Outcome data were also collected for surgical versus percutaneous tracheostomy subgroups independently, and for those studies that reported outcomes for early versus late tracheostomy. J o u r n a l P r e -p r o o f The Newcastle-Ottawa Scale (NOS) was used to assess the risk of bias of included studies; this scoring system has been validated for assessing risk of bias for non-randomised cohort studies and is recommended by the Cochrane Collaboration 12 . Disagreement in the NOS score was resolved through consensus. No studies were excluded from meta-analysis on the grounds of bias. Studies were classified as high risk of bias (0-3), moderate risk of bias (4-6 points) and low risk of bias (≥7 points) 13 . Continuous outcomes and baseline characteristics were calculated and reported as weighted combined means using formulae provided by the Cochrane Collaboration 12 . Where means and standard deviations were not provided, they were approximated according to Wan et al, 2014 14 . A meta-analysis of proportions was used to calculate the cumulative incidence of dichotomous outcome variables across all studies: mortality, weaning off mechanical ventilation, decannulation, and complications. The Freeman-Tukey double arcsine transformation was used to obtain weighted summary proportions as part of a random-effects model to account for sample heterogeneity. Results were presented as forest plots, including 95% confidence intervals of proportions. For a meta-analysis of binary outcomes between groups (surgical versus percutaneous or early versus late) the Mantel-Haenszel approach was used as part of a random-effects model. Results are reported as risk ratios (RR) with 95% confidence intervals. Hedges g was used as the measure of standardised mean difference (SMD) between groups where continuous outcome data (such as time to decannulation) were analysed, and a randomeffects model for continuous outcome data was performed with the Hartung-Knapp adjustment. J o u r n a l P r e -p r o o f Study heterogeneity was assessed using tau 2 , and the proportion of true variance of a weighted outcome was estimated using Higgins I 2 . I 2 was interpreted according to Borenstein et al 15 , though 0-40% was considered as low heterogeneity, 30-60% was considered as moderate heterogeneity, 50-90% as substantial heterogeneity and >75% as considerable heterogeneity 12 . A Cochrane Q statistic p-value <0.10 was considered as significant. Univariate linear regression was used to determine the influence of timing of tracheostomy post-intubation on timing of decannulation. Influential outliers were identified according to leverage, standardised residuals and Cooke's distance. Statistical analysis was performed using R Statistical Software version 4.0.0. All scripts for meta-analysis are available upon reasonable request to the corresponding author. The initial literature search identified 2429 records from the 6 databases and through reference screening; 1016 unique records remained following duplicate removal (figure 1). Of these, 46 studies met inclusion criteria. 7 further studies were removed with shared data, leaving 39 studies for meta-analysis [16] [17] [18] [19] [20] [21] [22] . J o u r n a l P r e -p r o o f The Newcastle-Ottawa Scale (NOS) was used to assess bias across the 39 included studies. The median total score was 7 (out of a possible maximum of 9), with a range of 4-8 (Supplementary figure 1). 23 studies scored as low risk of bias; 16 studies scored as high risk of bias. Baseline characteristics of included patients were variably reported throughout the 39 studies. Available pre-operative characteristics are summarised in table 1. The rapidly evolving nature of the COVID-19 pandemic means that providing tracheostomyspecific guidelines in this cohort of patients is inherently challenging due to a high degree of uncertainty with regards to indication, technique and timing 63 . It should be emphasised that due to exceptional pressures placed on healthcare systems globally, treatment pathways have been influenced by factors other than purely patient-related outcomes. In some instances, the choice of tracheostomy technique may instead be dictated by resource allocation 22, 64 . As with pre-COVID-19, the predominant indication for tracheostomy remains the facilitation of weaning with prolonged mechanical ventilation 65 Unfortunately, incomplete data on staff infection preclude any formal comparison of infection rates between early and late tracheostomy groups, and so a recommendation cannot be made on the appropriate timing of tracheostomy with regard to staff risk. It is telling, however, that of the 1398 tracheostomies from studies which reported viral transmission data, only 10 confirmed healthcare worker infections were reported. This equates to an incidence rate of 7‰, assuming all these transmissions were procedure related. An appreciation of true outcomes across studies is complicated by both incomplete baseline characteristic and outcome data. To facilitate reliable reporting with a view to optimising the reliability of meta-analyses, we have suggested recommendations for minimal reporting. Each baseline characteristic and outcome should be reported for both the total studied population and any subgroups (table 4) . Collaborative projects are currently underway that will contribute to our understanding of tracheostomy outcomes. The COVIDTrach national tracheostomy evaluation database was Its exclusion from the current study was justified given its comparative sparsity of outcome data compared to those studies that contributed data. The full report is now available, J o u r n a l P r e -p r o o f encompassing 1605 tracheostomies from 126 UK hospitals 76 . The results of this study corroborate those of the current meta-analysis. Overall mortality was determined at 18% (285), and median time from intubation to tracheostomy was 15 days (IQR11-21). Moreover, this multicentre study also found no difference in outcomes between percutaneous versus surgical tracheostomy. Interestingly, in contrast to our meta-analysis where no difference in mortality was identified between early and late tracheostomy (defined here as <14 days post-intubation), the COVIDTrach collaborative found that tracheostomy under 7 days post-intubation did portend a poorer prognosis. The reasons for this are unclear. The authors quite sensibly conclude that this may not be a causal relationship and that the question of timing is best addressed through prospective randomised controlled trials. There are several limitations of the current study that are related to the nature of the COVID-19 pandemic. Although the weighted mean follow-up period in this study was 42 days, included studies, by necessity, contain incomplete data. The priority early in the course of the pandemic was rapid collection and dissemination of data, to potentially inform treatment decisions on COVID-19 patients. Thus, the pooled outcomes reported here will likely be underestimated. Moreover, overall weighted means reported in this study are estimates, borne from differences in reporting between individual studies. As highlighted by Benito et al, this likely gives rise to selection bias 69 . Notwithstanding, the current study provides the largest meta-analysis on tracheostomy outcomes in COVID-19 patients to date, and includes an overview of key tracheostomy outcomes, as well as comparisons between clinically relevant patient cohorts. Our findings suggest that there is no difference in mortality, complications, and time to decannulation between surgical and percutaneous tracheostomy in COVID-19 patients. Moreover, no difference in mortality was identified between early and late tracheostomy (where early was defined as <14 days post-intubation), and time to tracheostomy did not influence time to decannulation. We share the recommendation that tracheostomy timing should be decided on a case-by-case basis under the guidance of a multidisciplinary team. Currently, there is insufficient evidence to suggest that early tracheostomy increases risk of viral transmission to staff, particularly with existing robust guidelines on personal protective equipment, and insufficient evidence to suggest that delayed tracheostomy influences outcomes in COVID-19 patients. Furthermore, the type of tracheostomy should be performed according to preferences, equipment familiarity, availability, and expertise. The authors report no commercial or financial associations that might pose or create conflict with information presented in the manuscript. The authors confirm that there are no conflicts of interest. Ethical approval was not required. Written consent was not required. J o u r n a l P r e -p r o o f Tables Table 1: baseline characteristics of included patients. "References" refers to those studies that reported the characteristic. "Count" refers to the number of patients across reporting studies to which the characteristic pertains. Mean and standard deviation, where provided, are combined weighted estimates. SD, standard deviation; BMI, body-mass index; PEEP, positive end-expiratory pressure; APACHE II, Acute Physiology and Chronic Health Evaluation II. 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