Dataset Information

Does delaying discharge from intensive care until after tracheostomy removal affect 30-day mortality? Propensity score matched cohort study.

ABSTRACT:

Objective

To investigate the short-term mortality effect of discharge from an intensive care unit (ICU) with a tracheostomy in place in comparison to delaying discharge until after tracheostomy removal.

Design

A propensity score matched cohort study using data from the TracMan study.

Setting

Seventy-two UK ICUs taking part in the TracMan study, a randomised controlled trial comparing early tracheostomy (within 4 days of critical care admission) with deferred tracheostomy (after 10 days if still indicated).

Participants

622 patients who underwent a tracheostomy while in the TracMan study between November 2004 and November 2008. 144 patients left ICU with a tracheostomy. 999 days of observation from 294 patients were included in the control pool.

Interventions

We matched patients discharged with a tracheostomy in place 1:1 with patients who remained in an ICU until either their tracheostomy was removed or they died with the tracheostomy in place. Propensity models were developed according to discharge destination, accounting for likely confounding factors.

Primary outcome measure

The primary outcome was 30-day mortality from the matching day. For the 'discharged with a tracheostomy' group, this was death within 30 days after the discharge day. For the 'remained in ICU' group, this was death within 30 days after the matched day.

Results

22 (15.3%) patients who left ICU with a tracheostomy died within 30 days compared with 26 (18.1%) who remained in ICU (relative risk 0.98, 95%?CI 0.43 to 2.23).

Conclusion

Keeping patients on an ICU to provide tracheostomy care was not found to affect mortality. Tracheostomy presence may indicate a higher risk of mortality due to underlying diseases and conditions rather than posing a risk in itself.The TracMan trial was registered on the ISRCTN database (ISRCTN28588190).

SUBMITTER: Vollam S

PROVIDER: S-EPMC7282394 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Publications

Does delaying discharge from intensive care until after tracheostomy removal affect 30-day mortality? Propensity score matched cohort study.

Vollam Sarah S Harrison David A DA Young J Duncan JD Watkinson Peter J PJ

BMJ open 20200607 6

<h4>Objective</h4>To investigate the short-term mortality effect of discharge from an intensive care unit (ICU) with a tracheostomy in place in comparison to delaying discharge until after tracheostomy removal.<h4>Design</h4>A propensity score matched cohort study using data from the TracMan study.<h4>Setting</h4>Seventy-two UK ICUs taking part in the TracMan study, a randomised controlled trial comparing early tracheostomy (within 4 days of critical care admission) with deferred tracheostomy (a ...[more]

PMID: 32513895

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Project description:BACKGROUND:Early tracheostomy has been associated with shorter hospital stay and fewer complications in adult trauma patients. Guidelines for tracheostomy have not been established for children with severe traumatic brain injury (TBI). The purpose of this study was to (1) define nationwide trends in time to extubation and time to tracheostomy and (2) determine if early tracheostomy is associated with decreased length of stay and fewer complications in children with severe TBI. METHODS:Records of children (<15 years) with severe TBI (head Abbreviated Injury Severity [AIS] score ?3) who were mechanically ventilated (>48 hours) were obtained from the National Trauma Data Bank (2007-2015). Outcomes after early (?14 days) and late (?15 days) tracheostomy placement were compared using 1:1 propensity score matching to control for potential confounding by indication. Propensity scores were calculated based on age, race, pulse, blood pressure, Glasgow Coma Scale motor score, injury mechanism, associated injury Abbreviated Injury Severity scores, TBI subtype, craniotomy, and intracranial pressure monitor placement. RESULTS:Among 6,101 children with severe TBI, 5,740 (94%) were extubated or died without tracheostomy, 95% of the time within 18 days. Tracheostomy was performed in 361 children (6%) at a median [interquartile range] of 15 [10, 22] days. Using propensity score matching, we compared 121 matched pairs with early or late tracheostomy. Early tracheostomy was associated with fewer ventilator days (14 [9, 19] vs. 25 [19, 35]), intensive care unit days (19 [14, 25] vs. 31 [24, 43]), and hospital days (26 [19, 41] vs. 39 [31, 54], all p < 0.05). Pneumonia (24% vs. 41%), venous thromboembolism (3% vs. 13%), and decubitus ulcer (4% vs. 13%) occurred less frequently with early tracheostomy (p < 0.05). CONCLUSIONS:Early tracheostomy is associated with shorter hospital stay and fewer complications among children with severe TBI. Extubation without tracheostomy is rare beyond 18 days after injury. LEVEL OF EVIDENCE:Prognostic and epidemiological, retrospective comparative study, level III.

Project description:BackgroundThe role of tracheostomy in coronavirus disease 2019 (COVID-19) is unclear, with several consensus guidelines advising against this practice. We developed both a dedicated airway team and coordinated education programme to facilitate ward management of tracheostomised COVID-19 patients. Here, we report outcomes in the first 100 COVID-19 patients who underwent tracheostomy at our institution.MethodsThis was a prospective observational cohort study of patients confirmed to have COVID-19 who required mechanical ventilation at Queen Elizabeth Hospital, Birmingham, UK. The primary outcome measure was 30-day survival, accounting for severe organ dysfunction (Acute Physiology and Chronic Health [APACHE]-II score>17). Secondary outcomes included duration of ventilation, ICU stay, and healthcare workers directly involved in tracheostomy care acquiring COVID-19.ResultsA total of 164 patients with COVID-19 were admitted to the ICU between March 9, 2020 and April 21, 2020. A total of 100 patients (mean [standard deviation] age: 55 [12] yr; 29% female) underwent tracheostomy; 64 (age: 57 [14] yr; 25% female) did not undergo tracheostomy. Despite similar APACHE-II scores, 30-day survival was higher in 85/100 (85%) patients after tracheostomy, compared with 27/64 (42%) non-tracheostomised patients {relative risk: 3.9 (95% confidence intervals [CI]: 2.3-6.4); P<0.0001}. In patients with APACHE-II scores ≥17, 68/100 (68%) tracheotomised patients survived, compared with 12/64 (19%) non-tracheotomised patients (P<0.001). Tracheostomy within 14 days of intubation was associated with shorter duration of ventilation (mean difference: 6.0 days [95% CI: 3.1-9.0]; P<0.0001) and ICU stay (mean difference: 6.7 days [95% CI: 3.7-9.6]; P<0.0001). No healthcare workers developed COVID-19.ConclusionIndependent of the severity of critical illness from COVID-19, 30-day survival was higher and ICU stay shorter in patients receiving tracheostomy. Early tracheostomy appears to be safe in COVID-19.

Project description:BackgroundDuring the first wave of the COVID-19 pandemic, shortages of ventilators and ICU beds overwhelmed health care systems. Whether early tracheostomy reduces the duration of mechanical ventilation and ICU stay is controversial.Research questionCan failure-free day outcomes focused on ICU resources help to decide the optimal timing of tracheostomy in overburdened health care systems during viral epidemics?Study design and methodsThis retrospective cohort study included consecutive patients with COVID-19 pneumonia who had undergone tracheostomy in 15 Spanish ICUs during the surge, when ICU occupancy modified clinician criteria to perform tracheostomy in Patients with COVID-19. We compared ventilator-free days at 28 and 60 days and ICU- and hospital bed-free days at 28 and 60 days in propensity score-matched cohorts who underwent tracheostomy at different timings (≤ 7 days, 8-10 days, and 11-14 days after intubation).ResultsOf 1,939 patients admitted with COVID-19 pneumonia, 682 (35.2%) underwent tracheostomy, 382 (56%) within 14 days. Earlier tracheostomy was associated with more ventilator-free days at 28 days (≤ 7 days vs > 7 days [116 patients included in the analysis]: median, 9 days [interquartile range (IQR), 0-15 days] vs 3 days [IQR, 0-7 days]; difference between groups, 4.5 days; 95% CI, 2.3-6.7 days; 8-10 days vs > 10 days [222 patients analyzed]: 6 days [IQR, 0-10 days] vs 0 days [IQR, 0-6 days]; difference, 3.1 days; 95% CI, 1.7-4.5 days; 11-14 days vs > 14 days [318 patients analyzed]: 4 days [IQR, 0-9 days] vs 0 days [IQR, 0-2 days]; difference, 3 days; 95% CI, 2.1-3.9 days). Except hospital bed-free days at 28 days, all other end points were better with early tracheostomy.InterpretationOptimal timing of tracheostomy may improve patient outcomes and may alleviate ICU capacity strain during the COVID-19 pandemic without increasing mortality. Tracheostomy within the first work on a ventilator in particular may improve ICU availability.

Project description:BackgroundPost-hospital discharge follow-up appointments are intended to evaluate patients' recovery following a hospitalization, but it is unclear how appointment statuses are associated with readmissions.ObjectiveTo examine the association between post-discharge ambulatory follow-up status, (1) having a scheduled appointment and (2) arriving to said appointment, and 30-day readmission.Design and settingA retrospective cohort study of patients hospitalized at 12 hospitals in an Integrated Delivery Network and their ambulatory appointments in that same network.Patients and main measuresWe included 50,772 patients who had an ambulatory appointment within 18 months of an inpatient admission in 2018. Primary outcome was readmission within 30 days post-discharge.Key resultsThere were 32,108 (63.2%) patients with scheduled follow-up appointments and 18,664 (36.8%) patients with no follow-up; 28,313 (88.2%) patients arrived, 3149 (9.8%) missed, and 646 (2.0%) were readmitted prior to their scheduled appointments. Overall 30-day readmission rate was 7.3%; 6.0% [5.75-6.31] for those who arrived, 8.8% [8.44-9.25] for those without follow-up, and 10.3% [9.28-11.40] for those who missed a scheduled appointment (p < 0.001). After adjusting for covariates, patients who arrived at their appointment in the first week following discharge were significantly less likely to be readmitted than those not having any follow-up scheduled (medical adjusted hazard ratio (aHR) 0.57 [0.47-0.69], p < 0.001; surgical aHR 0.58 [0.44-0.75], p < 0.001) There was an increased risk at weeks 3 and 4 for medical patients who arrived at a follow-up compared to those with no follow-up scheduled (week 3 aHR 1.29 [1.10-1.51], p = 0.001; week 4 aHR 1.46 [1.26-1.70], p < 0.001).ConclusionsThe benefit of patients arriving to their post-discharge appointments compared with patients who missed their follow-up visits or had no follow-up scheduled, is only significant during first week post-discharge, suggesting that coordination within 1 week of discharge is critical in reducing 30-day readmissions.

Project description:BACKGROUND:Restrictive transfusion strategies supported by large randomized trials are resulting in decreased blood utilization in cardiac surgery. What remains to be determined, however, is the impact of lower discharge hemoglobin (Hb) levels on readmission rates. We assessed patients with higher versus lower Hb levels on discharge to compare 30-day readmission rates after coronary artery bypass grafting (CABG). METHODS:We retrospectively evaluated 1552 patients undergoing isolated CABG at our institution from January 2013 to May 2016. We evaluated 2 Hb cohorts: "high" (above) and "low" (below) the mean discharge Hb level of 9.4 g/dL, comparing patient characteristics, blood utilization, and clinical outcomes including 30-day readmission rates. We further evaluated the effects of the lowest (<8 g/dL) discharge Hb levels on 30-day readmission rates by dividing the patients into 4 anemia cohorts based on discharge Hb levels: "no anemia" (>12 g/dL), "mild anemia" (10-11.9 g/dL), "moderate anemia" (8-9.9 g/dL), and "severe anemia" (<8 g/dL). Risk adjustment accounted for age, sex, Charlson comorbidity index, preoperative comorbidities, revision sternotomy, and patient blood management program implementation. RESULTS:The "high" and "low" groups had similar patient characteristics except for Hb levels (mean discharge Hb was 10.4 ± 0.9 vs 8.5 ± 0.6 g/dL, respectively). Notably, no evidence for a difference in 30-day readmission rates was noted between the "high" (76/746; 10.2%) and "low" (97/806; 12.0%) (P = .25) Hb cohorts. The 4 anemia cohorts had differences in age, revision sternotomy incidence, Hb levels, certain patient comorbidities, and time to readmission. On multivariable analysis, the risk-adjusted odds of readmission in the "low" Hb cohort (odds ratio, 1.16; 95% confidence interval, 0.84-1.61; P = .36) was not significant compared to the "high" Hb cohort. Compared to patients with discharge Hb ?8 g/dL, patients with Hb <8 g/dL had a higher incidence of readmission (22/129; 17.1% vs 151/1423; 10.6%; P = .036). On multivariable analysis, Hb <8 g/dL on discharge was predictive of readmission (odds ratio, 1.77; 95% confidence interval, 1.05-2.88; P = .03). The most common reason for readmission was volume overload, followed by infection and arrhythmias. CONCLUSIONS:A discharge Hb level below the institution mean for CABG patients does not provide evidence for an association with an increased 30-day readmission rate. In the small number of patients discharged with Hb <8 g/dL, there is a suggestion of increased risk for readmission and larger more controlled studies are needed to verify or refute this finding.

Project description:We sought to determine if discharge home with home health care (HHC) is an independent predictor of increased readmission after pancreatectomy.We examined 30-day readmissions in patients undergoing pancreatectomy using the Healthcare Cost and Utilization Project State Inpatient Database for California from 2009 to 2011. Readmissions were categorized as severe or nonsevere using the Modified Accordion Severity Grading System. Multivariable logistic regression models were used to examine the association of discharge home with HHC and 30-day readmission using discharge home without HHC as the reference group. Propensity score matching was used as an additional analysis to compare the rate of 30-day readmission between patients discharged home with HHC with patients discharged home without HHC.Of 3,573 patients who underwent pancreatectomy, 752 (21.0%) were readmitted within 30 days of discharge. In a multivariable logistic regression model, discharge home with HHC was an independent predictor of increased 30-day readmission (odds ratio = 1.37; 95% CI, 1.11-1.69; p = 0.004). Using propensity score matching, patients who received HHC had a significantly increased rate of 30-day readmission compared with patients discharged home without HHC (24.3% vs 19.8%; p < 0.001). Patients discharged home with HHC had a significantly increased rate of nonsevere readmission compared with those discharged home without HHC, by univariate comparison (19.2% vs 13.9%; p < 0.001), but not severe readmission (6.4% vs 4.7%; p = 0.08). In multivariable logistic regression models, excluding patients discharged to facilities, discharge home with HHC was an independent predictor of increased nonsevere readmissions (odds ratio = 1.41; 95% CI, 1.11-1.79; p = 0.005), but not severe readmissions (odds ratio = 1.31; 95% CI, 0.88-1.93; p = 0.18).Discharge home with HHC after pancreatectomy is an independent predictor of increased 30-day readmission; specifically, these services are associated with increased nonsevere readmissions, but not severe readmissions.

Dataset Information

Does delaying discharge from intensive care until after tracheostomy removal affect 30-day mortality? Propensity score matched cohort study.

Objective

Design

Setting

Participants

Interventions

Primary outcome measure

Results

Conclusion

Publications

Does delaying discharge from intensive care until after tracheostomy removal affect 30-day mortality? Propensity score matched cohort study.

Similar Datasets

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