Trach and trace: observational outcomes of patients with COVID-19 who received a tracheostomy during the first pandemic surge in North Central London

Introduction

The COVID-19 pandemic resulted in large numbers of patients requiring prolonged mechanical ventilation and subsequent insertion of a tracheostomy (1). Initial reports exploring the clinical outcomes of patients with tracheostomy following a COVID-19 diagnosis have been limited by; a lack of standardisation of reported variables, incomplete or short follow up periods, and small sample sizes (2). In particular, the process of tracheostomy weaning in this cohort has not previously been reported.

There is ongoing debate regarding the benefits of tracheostomy placement in terms of reducing intensive care length of stay (LoS) and duration of mechanical ventilation (3, 4, 5, 6, 7, 8). Benefits of tracheostomy include; patient comfort, ease of physical rehabilitation and, the ability to speak, eat and drink (9, 10).

It was recognised that tracheostomy insertion may facilitate an increase in intensive care bed capacity during the first U.K. COVID-19 surge (11, 12). COVID-19 is highly contagious and tracheostomy insertion is thought to be an aerosol generating procedure (AGP) therefore, the procedure poses risk to healthcare professionals (13). In order to mitigate risk, international guidance was produced for tracheostomy insertion (14, 15, 16) in patients with COVID-19. Delaying tracheostomy insertion may reduce risks for healthcare workers (13), however a delay in tracheostomy insertion has the potential to expose the patient to the known risks of prolonged intubation (17, 18). The relationship between time to tracheostomy insertion and clinical outcomes in patients with COVID-19 remains unclear.

Aims

The aim of this project was to report observational outcomes in adult patients diagnosed with COVID-19 who required temporary tracheostomies over the time period covering the first pandemic wave (6th March 2020–31st July 2020) The specific objectives were to report:

• Time from intensive care admission to tracheostomy; extubation trial prior to tracheostomy and time from intubation to tracheostomy. Time from intubation to tracheostomy may be explored for temporal categorisation depending on the data distribution.

• Ventilator and tracheostomy weaning interventions including; time to first cuff deflation, time to first one way valve (OWV) application, OWV use ‘inline’ with the ventilator, and time to spontaneous breathing trials (SBT).

• Decannulation outcomes including; time to decannulation, successful decannulation and the clinician responsible for decannulation.

• Intensive care and hospital LoS.

• Associations between patient/tracheostomy characteristics and patient outcomes.

Methods

Patient sample

Adult patients (aged >16 years) diagnosed with COVID-19 who required a tracheostomy inserted between 6th March–31st July 2020 at four acute hospital sites in London (St Bartholomew’s Hospital, The Royal London Hospital, The Royal Free Hospital, and Homerton University Hospital). Patients with long-term tracheostomies originally prior to admission were excluded.

Data collection

Prior to (and during) the COVID-19 pandemic each service routinely collected data on patients with a tracheostomy through a common ‘minimal data set’ (Box 1). Data collection continued up to 1st October 2020. Cohort data from each site was subsequently anonymised and combined to create a single database. Prior to analysis, the database was scrutinised for consistency and coding and corrections made as required.

Box 1: Minimum data set.

Data analysis

Statistical analyses were performed using Microsoft Excel and IBM SPSS Statistics. Data normality was assessed by data distribution in histograms and differences between means and medians. Descriptive statistics of numerical variables are presented as means and standard deviation (SD) if normally distributed and otherwise as medians and interquartile ranges (IQRs). Categorical variables are presented as numbers and percentages. Numeric and binary categorical variables were compared using the independent sample t-test for parametric data and Mann Whitney U tests for nonparametric data. For comparisons between a numeric variable and a categorical variable with more than two groups, Kruskal Wallis ANOVA was utilised. For comparing categorical variables, Chi square and Fishers Exact test were used for parametric and nonparametric data respectively. A time to event analysis was completed for intensive care and hospital LoS. Initial analysis of the ‘time from intubation to tracheostomy’ variable (for example, duration of endotracheal tube) delineated three distinct groups [<15 days (early), 15–27 days (late) and >27 days (delayed)], which were subsequently used to assess between group differences.

Approval

Ethical approval was not sought as the project was deemed a service evaluation by the Clinical Effectiveness Unit (CEU) at all sites.

Results

Tracheostomy data from 124 patients were included in the analysis (Figure 1).

Figure 1: Tracheostomy data included in analysis.

Demographics

Demographics and baseline characteristics of the sample are displayed in Table 1.

Table 1: Demographics and baseline characteristics.

Results are presented as median (IQR) and n (%).

* = ward: transferred from within the same hospital from ward based care to intensive care. Emergency department: transferred from emergency department to intensive care. Other hospital: transferred to intensive care from another hospital both within and outside of the University college London Partners (UCLP) network.

Ventilator and tracheostomy weaning interventions

Interventions that facilitate mechanical ventilation and tracheostomy weaning, including cuff deflation, OWV application, and spontaneous breathing trials (SBT) are displayed in Table 2.

Table 2: Outcomes related to interventions to facilitate ventilator and tracheostomy weaning.

Values are reported as median (IQR) and n (%).

Tracheostomy management and outcome

The incidence of complications associated with tracheostomy, tracheostomy duration and patient outcomes including intensive care and hospital LoS are displayed in Table 3, Figure 2 and Figure 3.

Table 3: Tracheostomy management and outcome.

Values are reported as median (IQR) and n (%).

Figure 2: hospital length of stay time to event curve.

Figure 3: Proportion of patients remaining in hospital.

Associations between patient/tracheostomy characteristics and patient outcomes

Relationships between the time from intubation to tracheostomy (for example, duration of ETT or time to tracheostomy) and variables which might impact this were explored. There was no correlation between time to tracheostomy and age (r = -0.095, p = 0.292), length of intensive care stay prior to intubation (r = -0.173, p = 0.064), or reasons for tracheostomy insertion (p = 0.229). There was no difference in time to tracheostomy between those who trialled ‘inline’ OWV and those who did not (p = 0.501). No correlations were found between time to tracheostomy and time to SBT (r = 0.060, p = 0.538), time to first cuff deflation trial (r = 0.008, p = 0.0934) or time to first OWV trial (r = 0.035, p = .719). There was a difference in time to tracheostomy between those patients who were transferred between hospitals (26 days (19, 31) and those who were not (17 days (11, 24) (p <0.0001). Moderate correlations were observed between time to tracheostomy and both intensive care LoS (r = 0.519, p <0.0001) and hospital LoS (r = 0.378, p <0.0001).

The extent of any relationship between the time to decannulation from tracheostomy insertion (tracheostomy duration) and variables which might impact this were explored. There was no correlation between duration of tracheostomy and age (r = 0.079, p = 0.422), time to intubation from intensive care admission (r = 0.33, p = 0.746), or reasons for tracheostomy insertion (p = 0.531). There was no difference in tracheostomy duration between those who trialled an ‘inline’ OWV and those who did not (p = 0.876). There was a moderate correlation between time to SBT and the duration of tracheostomy (r = 0.641, p <0.0001). Strong correlations were found between tracheostomy duration and duration of ETT (r = 0.863, p <0.0001), time to first cuff deflation trial (r = 0.707, p <0.0001) and time to first OWV trial (r = 0.775, p <0.0001).

Discussion

Baseline characteristics and time from intubation to tracheostomy

The characteristics of our cohort are consistent with previous COVID-19 tracheostomy reports (16, 20, 21, 22, 23). The predominant indication for tracheostomy insertion was to facilitate ventilator weaning (81.5%). Extubation trials prior to tracheostomy insertion occurred in only 15% of our sample which is in keeping with other practice guidelines (11).

A COVID-19 report from the U.K. (20) demonstrated no difference in survival between patients receiving tracheostomy before 10 days or after 10 days (p = 0.73) although only nine patients underwent tracheostomy before day 10 making statistical interpretation difficult. Similarly, no difference in survival was reported in those who underwent a tracheostomy before or after day 14 (p = 0.18). These authors also report shorter duration of mechanical ventilation and reduced intensive care LoS in patients where tracheostomy was performed before day 14 compared to after day 14 (20). Data from COVIDTrach (24) reported median time to tracheostomy in the U.K. was 15 days and mortality 18%. A further U.K. study reported a tracheostomy before day 14 was associated with a reduced LoS (25). The PRoVENT study (26) reported a median time to tracheostomy of 21 days, with a tracheostomy being performed before 21 days being associated with shorter duration of mechanical ventilation but higher mortality. Additionally a meta-analysis indicated early tracheostomy was associated with reduced duration of mechanical ventilation and intensive care stay (1). The longer time to decannulation, intensive care and hospital LoS observed in our delayed tracheostomy group appears to be in keeping with other literature (22, 23). Our report was not designed to evaluate the impact of timing of tracheostomy insertion and the observational nature of our report means we cannot suggest causation. It appears that the decision to insert a tracheostomy should be a multi-professional decision where patient acuity and on-going intervention plans are considered.

Interventions to facilitate ventilator and tracheostomy weaning

We report weaning interventions in COVID-19 patients with tracheostomy. It is accepted that mechanical ventilation is a barrier to communication, resulting in patients’ feelings of anxiety and helplessness (27, 28). Provided a patient can tolerate cuff deflation, a OWV can be inserted ‘inline’ with ventilator tubing to restore voice and enable oral intake. OWV utilisation was not recommended for patients with COVID-19 (29). In our cohort, 9.7% of patients underwent ‘inline’ OWV. We advocated ‘inline’ OWV to facilitate communication (especially in the presence of delirium), on a case-by-case basis. ‘Inline’ OWV did not impact tracheostomy duration (p = 0.876) nor benefit ventilator or tracheostomy weaning and risk versus benefit should be continuously evaluated. It is difficult to establish the prevalence of this technique in clinical practice but this may be an meaningful outcome for patients.

Decannulation outcomes

We report a mean time to tracheostomy decannulation of 21 days. An Italian sample of patients with COVID-19 (30) reported mean time to decannulation of 36 days, while a U.K. cohort reported 12.7 days (20) and an American study reported 16.6 days (16). It should be noted patients in these previous reports had not completed their intensive care or hospital admission, making comparison difficult. Our report has a longer duration of follow up compared to previous COVID-19 literature and may more accurately reflect the duration of tracheostomy in a COVID-19 cohort. International and institutional differences in practice may account for the variation in tracheostomy duration observed.

The clinician responsible for tracheostomy decannulation in our cohort was the physiotherapist in 63% of cases and decannulation was successful in 98% of cases. Our data suggest physiotherapists at our centres have the ability to successfully manage tracheostomy decannulation, which may release medical staff to complete tasks specific to their own practice. The clinician performing decannulation procedures in other COVID-19 literature remains unreported.

Hospital outcomes including mortality, intensive care and hospital length of stay

The mortality rates for tracheostomy patients with a COVID-19 diagnosis vary in the literature. Mortality at a London tertiary centre were reported as 9.7% (31), although follow-up data were only available for 14 days post tracheostomy. Botti et al (30) reported a mortality rate of 34.1%, although it is unclear how long the follow up period was. Data from another U.K. cohort reported 30 day mortality rate for patients with tracheostomy of 31.7% (20) and Chao et al (16) reported a rate of 11.3%, although their dataset was incomplete. Martin-Villares et al (23) reported a 23.7% mortality at one month follow up in a COVID-19 tracheostomy cohort. The mortality rate observed in our study was low (12.9%), and whilst we are unable to identify causes for this, it may reflect the longer follow up period we report. We acknowledge that mortality may have been impacted by institutional and international differences in the management of COVID-19 as understanding about management of the virus improved over time.

We have reported a difference in duration of ETT for patients who were transferred between hospitals and those who were not. Inter-hospital transfers occurred to alleviate intensive care capacity and facilitate specialist management such as renal filtration, extracorporeal membrane oxygenation (ECMO) and insertion of tracheostomy. Our data suggest that in our geographical location, transferring patients between hospitals may be related to increased time to tracheostomy insertion and ventilator weaning. We suggest intensive care networks consider this finding in their planning for surge capacity and minimise transfer of patients between intensive care units.

There is a paucity of literature regarding intensive care LoS for patients with COVID-19 who received a temporary tracheostomy. International studies have reported average intensive care LoS of 11 (31), 22 (30) and 25.3 days (20) for patients with COVID-19 and tracheostomy. Hospital LoS for patients with COVID-19 who required a tracheostomy is even rarer with only one reported hospital LoS of 37.2 days (20). The short follow up period for these studies means many participants still had their tracheostomies in situ when the data was reported. We report a median intensive care LoS of 41 days and median hospital LoS of 53 days. Since our data is derived from a larger cohort following patients until they are discharged from the acute hospital, the longer intensive care and hospital stay we report may be a more accurate reflection of these metrics for our geographical location.

Relationships between patient/tracheostomy-characteristics and the duration of ETT

It might be expected that primary airway difficulty as the indication for tracheostomy was associated with longer duration of tracheostomy. This concept was not supported by our data, as there was no difference in duration of tracheostomy between the reasons for tracheostomy insertion (p = 0.247), however it may be difficult to draw conclusions on whether reason for tracheostomy impacted duration of tracheostomy as numbers for other indications were small (Table 1). We could find no other examples in the tracheostomy literature with which to compare or contrast these relationships.

Relationships between patient/tracheostomy characteristics and time to decannulation

We report moderate and strong correlations between tracheostomy duration and time to first cuff deflation trial, time to first OWV trial and time to SBT. Additionally, there were strong correlations between time to tracheostomy and both intensive care LoS and hospital LoS. The MDT approach to tracheostomy weaning within our centres promotes the adoption of early weaning interventions (32). Whilst correlation does not indicate causation, these data support the role of weaning interventions in facilitating tracheostomy weaning and reducing associated LoS. In a non-COVID-19 cohort, time to tracheostomy decannulation was reported as 18 to 13 days, with time to cuff deflation 9 to 7 days (33). A further non COVID-19 study demonstrated time to first cuff deflation as 17 to 10 days and time to OWV use as 14 to 7 days (34). There is a paucity of reporting of weaning interventions making comparisons between our results and both COVID-19 and non-COVID-19 cohorts difficult.

Limitations

Our report is observational in nature for which we must recognise inherent bias. The observational design means inferences and generalisability of results are not possible, and we have not accounted for confounding factors. We did not record duration of mechanical ventilation (which other reports were able to state). We did not record co-morbidity, ethnicity, body mass index or severity of illness to determine whether these inherent risks influenced the results. Neither did we record other inventions patients may have received as part of management of their condition, such as prone positioning which could further confound our results. Regression analysis may have mitigated some of the confounding factors and this approach could be utilised in future work.

Conclusion

This report followed patients admitted to four London hospitals with COVID-19, who required a temporary tracheostomy, until decannulation and hospital discharge. The majority of COVID-19 survivors from these London hospitals who received a tracheostomy were successfully weaned and decannulated with multi-disciplinary team interventions. Comparison between this report and other COVID-19 and non-COVID-19 tracheostomy outcomes is limited due to differences in sample sizes, follow up periods and reporting standards. Inter-institutional and international comparisons of clinical outcomes following tracheostomy insertion may be improved by the development of core variables for tracheostomy reporting. Implementing core variables for tracheostomy reporting may allow the effect of changes to care and management (as occurred during the COVID-19 pandemic) to be robustly evaluated.

Acknowledgements

The authors would like to thank the therapy teams at Barts Health NHS Trust, the Homerton University Hospital Foundation Trust and the Royal Free London NHS Foundation Trust for their assistance with data collection.

Declaration of interests

No competing interests to declare.

Funding

This study was unfunded.

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