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      Early versus late tracheostomy after decompressive craniectomy for stroke

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          Abstract

          Background

          Stroke patients requiring decompressive craniectomy are at high risk of prolonged mechanical ventilation and ventilator-associated pneumonia (VAP). Tracheostomy placement may reduce the duration of mechanical ventilation. Predicting which patients will require tracheostomy and the optimal timing of tracheostomy remains a clinical challenge. In this study, the authors compare key outcomes after early versus late tracheostomy and develop a useful pre-operative decision-making tool to predict post-operative tracheostomy dependence.

          Methods

          We performed a retrospective analysis of prospectively collected registry data. We developed a propensity-weighted decision tree analysis to predict tracheostomy requirement using factors present prior to surgical decompression. In addition, outcomes include probability functions for intensive care unit length of stay, hospital length of stay, and mortality, based on data for early (≤ 10 days) versus late (> 10 days) tracheostomy.

          Results

          There were 168 surgical decompressions performed on patients with acute ischemic or spontaneous hemorrhagic stroke between 2010 and 2015. Forty-eight patients (28.5%) required a tracheostomy, 35 (20.8%) developed VAP, and 126 (75%) survived hospitalization. Mean ICU and hospital length of stay were 15.1 and 25.8 days, respectively. Using GCS, SOFA score, and presence of hydrocephalus, our decision tree analysis had 63% sensitivity and 84% specificity for predicting tracheostomy requirement. The early group had fewer ventilator days (7.3 versus 15.2, p < 0.001) and shorter hospital length of stay (28.5 versus 44.4 days, p = 0.014). VAP rates and mortality were similar between the two groups. Withdrawal of treatment interventions shortly post-operatively confounded mortality outcomes.

          Conclusion

          Early tracheostomy shortens duration of mechanical ventilation and length of stay after surgical decompression for stroke, but it did not impact mortality or VAP rates. A decision tree is a practical tool that may be helpful in guiding pre-operative decision-making with patients’ families.

          Electronic supplementary material

          The online version of this article (10.1186/s40560-017-0269-1) contains supplementary material, which is available to authorized users.

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          Most cited references21

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          Effect of early vs late tracheostomy placement on survival in patients receiving mechanical ventilation: the TracMan randomized trial.

          Tracheostomy is a widely used intervention in adult critical care units. There is little evidence to guide clinicians regarding the optimal timing for this procedure. To test whether early vs late tracheostomy would be associated with lower mortality in adult patients requiring mechanical ventilation in critical care units. An open multicentered randomized clinical trial conducted between 2004 and 2011 involving 70 adult general and 2 cardiothoracic critical care units in 13 university and 59 nonuniversity hospitals in the United Kingdom. Of 1032 eligible patients, 909 adult patients breathing with the aid of mechanical ventilation for less than 4 days and identified by the treating physician as likely to require at least 7 more days of mechanical ventilation. Patients were randomized 1:1 to early tracheostomy (within 4 days) or late tracheostomy (after 10 days if still indicated). The primary outcome measure was 30-day mortality and the analysis was by intention to treat. Of the 455 patients assigned to early tracheostomy, 91.9% (95% CI, 89.0%-94.1%) received a tracheostomy and of 454 assigned to late tracheostomy, 44.9% (95% CI, 40.4%-49.5%) received a tracheostomy. All-cause mortality 30 days after randomization was 30.8% (95% CI, 26.7%-35.2%) in the early and 31.5% (95% CI, 27.3%-35.9%) in the late group (absolute risk reduction for early vs late, 0.7%; 95% CI, -5.4% to 6.7%). Two-year mortality was 51.0% (95% CI, 46.4%-55.6%) in the early and 53.7% (95% CI, 49.1%-58.3%) in the late group (P = .74). Median critical care unit length of stay in survivors was 13.0 days in the early and 13.1 days in the late group (P = .74). Tracheostomy-related complications were reported for 6.3% (95% CI, 4.6%-8.5%) of patients (5.5% in the early group, 7.8% in the late group). For patients breathing with the aid of mechanical ventilation treated in adult critical care units in the United Kingdom, tracheostomy within 4 days of critical care admission was not associated with an improvement in 30-day mortality or other important secondary outcomes. The ability of clinicians to predict which patients required extended ventilatory support was limited. isrctn.org Identifier: ISRCTN28588190.
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            Ventilator-associated pneumonia in the ICU

            Introduction Ventilator-associated pneumonia (VAP) is defined as pneumonia that occurs 48-72 hours or thereafter follow¬ing endotracheal intubation, characterized by the pre¬sence of a new or progressive infiltrate, signs of systemic infection (fever, altered white blood cell count), changes in sputum characteristics, and detection of a causative agent [1]. VAP contributes to approximately half of all cases of hospital-acquired pneumonia [1], [2]. VAP is estimated to occur in 9-27 % of all mechanically ventilated patients, with the highest risk being early in the course of hospitalization [1], [3]. It is the second most common nosocomial infection in the intensive care unit (ICU) and the most common in mechanically ventilated patients [4], [5]. VAP rates range from 1.2 to 8.5 per 1,000 ventilator days and are reliant on the definition used for diagnosis [6]. Risk for VAP is greatest during the first 5 days of mechanical ventilation (3 %) with the mean duration between intubation and development of VAP being 3.3 days [1], [7]. This risk declines to 2 %/day between days 5 to 10 of ventilation, and 1 %/day thereafter [1], [8]. Earlier studies placed the attributable mortality for VAP at between 33-50 %, but this rate is variable and relies heavily on the underlying medical illness [1]. Over the years, the attributable risk of death has decreased and is more recently estimated at 9-13 % [9], [10], largely because of implementation of preventive strategies. Approximately 50 % of all antibiotics adminis¬tered in ICUs are for treatment of VAP [2], [4]. Early onset VAP is defined as pneumonia that occurs within 4 days and this is usually attributed to antibiotic sensitive pathogens whereas late onset VAP is more likely caused by multidrug resistant (MDR) bacteria and emerges after 4 days of intubation [1], [4]. Thus, VAP poses grave implications in endotracheally intubated adult patients in ICUs worldwide and leads to increased adverse outcomes and healthcare costs. Independent risk factors for development of VAP are male sex, admission for trauma and intermediate underlying disease severity, with odds ratios (OR) of 1.58, 1.75 and 1.47-1.70, respectively [7]. Pathogenesis The complex interplay between the endotracheal tube, presence of risk factors, virulence of the invading bacteria and host immunity largely determine the development of VAP. The presence of an endotracheal tube is by far the most important risk factor, resulting in a violation of natural defense mechanisms (the cough reflex of glottis and larynx) against micro aspiration around the cuff of the tube [4], [11]. Infectious bacteria obtain direct access to the lower respiratory tract via: (1) micro aspiration, which can occur during intubation itself; (2) development of a biofilm laden with bacteria (typically Gram-negative bacteria and fungal species) within the endotracheal tube; (3) pooling and trickling of secretions around the cuff; and (4) impairment of mucociliary clearance of secretions with gravity dependence of mucus flow within the airways [11-13]. Pathogenic material can also collect in surrounding anatomic structures, such as the stomach, sinuses, nasopharynx and oropharynx, with replacement of normal flora by more virulent strains [11], [12], [14]. This bacterium-enriched material is also constantly thrust forward by the positive pressure exerted by the ventilator. Whereas reintubation following extubation increases VAP rates, the use of non-invasive positive pressure ventilation has been associated with significantly lower VAP rates [4]. Host factors such as the severity of underlying disease, previous surgery and antibiotic exposure have all been implicated as risk factors for development of VAP [1]. In addition, it has recently been noted that critically ill patients may have impaired phagocytosis and behave as functionally immunosuppressed even prior to emergence of nosocomial infection [4], [15], [16]. This effect is attributed to the detrimental actions of the anaphylatoxin, C5a, which impairs neutrophil phagocytic activity and impairs phagocytosis by neutrophils [15]. More recently, a combined dysfunction of T-cells, monocytes, and neu¬trophils has been noted to predict acquisition of noso¬comial infection [16]. For example, elevation of regula¬tory T-cells (Tregs), monocyte deactivation (measured by monocyte HLA-DR expression) and neutrophil dysfunc¬tion (measured by CD88 expression), have cumulatively shown promise in predicting infection in the critically ill population, as compared to healthy controls [16]. Microbiology The type of organism that causes VAP usually depends on the duration of mechanical ventilation. In general, early VAP is caused by pathogens that are sensitive to anti¬biotics, whereas late onset VAP is caused by multi-drug resistant and more difficult to treat bacteria. However, this is by no means a rule and merely a guide to initiate antibiotic therapy until further clinical information is available. Typically, bacteria causing early-onset VAP include Streptococcus pneumoniae (as well as other streptococcus species), Hemophilus influenzae, methicillin-sensitive Staphylococcus aureus (MSSA), antibiotic-sensitive enteric Gram-negative bacilli, Escherichia coli, Klebsiella pneumonia, Enterobacter species, Proteus species and Serratia marcescens. Culprits of late VAP are typically MDR bacteria, such as methicillin-resistant S. aureus(MRSA), Acinetobacter, Pseudomonas aeruginosa, and extended-spectrum beta-lactamase producing bacteria (ESBL) [4]. The exact prevalence of MDR organisms is variable between institutions and also within institutions [1]. Patients with a history of hospital admission for ≥ 2 days in the past 90 days, nursing home residents, patients receiving chemotherapy or antibiotics in the last 30 days and patients undergoing hemodialysis at out¬patient centers are susceptible to drug resistant bacteria [1], [4]. Commonly found bacteria in the oropharynx can attain clinically significant numbers in the lower airways. These bacteria include Streptococcus viridans, Coryne-bacterium, coagulase-negative staphylococcus (CNS) and Neisseria species. Frequently, VAP is due to polymicrobial infection. VAP from fungal and viral causes has a very low incidence, especially in the immunocompetent host [1]. Pathogens causing VAP, their frequency (in paren¬thesis) and their possible mode of multi-drug resistance, if any, are listed below [1-3]: 1. Pseudomonas (24.4 %): Upregulation of efflux pumps, decreased expression of outer membrane porin channel, acquisition of plasmid-mediated metallo-beta-lactamases. 2. S. aureus (20.4 %, of which > 50 % MRSA): Production of a penicillin-binding protein (PBP) with reduced affinity for beta-lactam antibiotics. Encoded by the mecA gene. 3. Enterobacteriaceae (14.1 % -includes Klebsiella spp., E. coli, Proteus spp., Enterobacter spp., Serratia spp., Citrobacter spp.): Plasmid mediated production of ESBLs, plasmid-mediated AmpC-type enzyme. 4. Streptococcus species (12.1 %). 5. Hemophilus species (9.8 %). 6. Acinetobacter species (7.9 %): Production of metallo-enzymes or carbapenemases. 7. Neisseria species (2.6 %). 8. Stenotrophomonas maltophilia (1.7 %). 9. Coagulase-negative staphylococcus (1.4 %). 10. Others (4.7 % -includes Corynebacterium, Moraxella, Enterococcus, fungi). Diagnosis At the present time, there is no universally accepted, gold standard diagnostic criterion for VAP. Several clinical methods have been recommended but none have the needed sensitivity or specificity to accurately identify this disease [17]. Daily bedside evaluation in conjunction with chest radiography can only be suggestive of the presence or absence of VAP, but not define it [18]. Clinical diagnosis of VAP can still miss about a third of VAPs in the ICU compared to autopsy findings and can incorrectly diagnose more than half of patients, likely due to poor interobserver agreement between clinical criteria [8], [18], [19]. Postmortem studies comparing VAP diag¬nosis with clinical criteria showed 69 % sensitivity and 75 % specificity, in comparison to autopsy findings [20]. The American Thoracic Society (ATS) and the Infectious Diseases Society of America (IDSA) guidelines recommend obtaining lower respiratory tract samples for culture and microbiology [1]. Analysis of these samples can be quantitative or qualitative. This guideline also allows use of tracheal aspirates for their negative predictive value (94 % for VAP). Johanson et al. described clinical criteria for diagnosis of VAP as follows [21]: The clinical pulmonary infection score (CPIS) takes into account clinical, physiological, microbiological and radiographic evidence to allow a numerical value to predict the presence or absence of VAP (Table 1) [18], [22]. Scores can range between zero and 12 with a score of ≥ 6 showing good correlation with the presence of VAP [22]. Despite the clinical popularity of the CPIS, debate continues regarding its diagnostic validity. One meta¬analysis of 13 studies evaluating the accuracy of CPIS in diagnosing VAP reported pooled estimates for sensitivity and specificity for CPIS as 65 % (95 % CI 61-69 %) and 64 % (95 % CI 60-67 %), respectively [23]. Despite its apparent straightforward calculation, the inter-observer variability in CPIS calculation remains substantial, jeopardizing its routine use in clinical trials [24]. Of all the criteria used to calculate the CPIS, only time-dependent changes in the PaO2/FiO2 ratio early in VAP may provide some predictive power for VAP outcomes in clinical trials, namely clinical failure and mortality [25]. However, a trial by Singh and colleagues [26] demonstrated that the CPIS is an effective clinical tool for determining whether to stop or continue antibiotics for longer than 3 days. In that study, antibiotics were discontinued at day 3 for patients who had been random¬ized to receive ciprofloxacin instead of standard of care, if their CPIS remained ≤ 6. Mortality and length of ICU stay did not differ despite a shorter duration (p = 0.0001) and lower cost (p = 0.003) of antimicrobial therapy in the experimental as compared with the standard therapy arm, and the development of antimicrobial resistance was lower among patients whose antibiotics were discontinued compared to those who received standard of care. 1. New or progressive radiographic consolidation or infiltrate. In addition, at least 2 of the following: 2. Temperature > 38 °C 3. Leukocytosis (white blood cell count ≥ 12,000 cells/ mm3) or leukopenia (white blood cell count 11,000/mm3 1 ≥ 500 Band cells 2 Tracheal secretions (subjective visual scale) None 0 Mild/non-purulent 1 Purulent 2 Radiographic findings (on chest radiography, excluding CHF and ARDS) No infiltrate 0 Diff use/patchy infiltrate 1 Localized infiltrate 2 Culture results (endotracheal aspirate) No or mild growth 0 Moderate or florid growth 1 Moderate or florid growth AND pathogen consistent with Gram stain 2 Oxygenation status (defined by PaO2:FiO2) > 240 or ARDS 0 ≤ 240 and absence of ARDS 2 ARDS: acute respiratory distress syndrome; CHF: congestive heart failure Respiratory samples can be obtained using several techniques: The ATS/IDSA guidelines note that use of a bronchoscopic bacteriologic strategy has been shown to reduce 14-day mortality when compared with a clinical strategy (16.2 % vs. 25.8 %, p = 0.02) [1]. When samples are obtained by BAL techniques (BAL, mini-BAL or PSB), the diagnostic threshold is 103 colony forming units (cfu)/ml for protected specimen brushing and 104 cfu/ml for BAL. In one multicenter study, BAL-and PSB-based diagnosis was associated with significantly more antibiotic-free days (11.5 ± 9.0 vs. 7.5 ± 7.6, p 4 days) requires broad spectrum antibiotics whereas early onset (≤ 4 days) can be treated with limited spectrum antibiotics [1]. An updated local antibiogram for each hospital and each ICU based on local bacteriological patterns and susceptibilities is essential to guide optimally dosed initial empiric therapy [1]. With any empiric antibiotic regimen, de-escalation is the key to reduce emergence of resistance [33]. Delays in initiation of antibiotic treatment may add to the excess mortality risk with VAP [1]. Tables 2 and 3 highlight the recom¬mended treatment regimens for VAP. Owing to the high rate of resistance to monotherapy observed with P .aeruginosa, combination therapy is always recommended. Acinetobacter species respond best to carbapenems (also active against ESBL positive Enterobacteriaceae), colistin, polymyxin B and ampicillin/sulbactam [36], [37]. Although MDR organisms are usually associated with late-onset VAP, recent evidence suggests that they are increasingly associated with early-onset VAP as well [37], [38]. The role of inhaled antibiotics in the setting of failure of systemic antibiotics is unclear [1]. The usual duration of treatment for early-onset VAP is 8 days and longer in the case of late-onset VAP or if MDR organisms are suspected or identified [39-41]. Table 2 Comparison of recommended initial empiric therapy for ventilator-associated pneumonia (VAP) according to time of onset [1], [34], [41] Early-onset VAP Late-onset VAP Second or third generation cephalosporin: e. g., ceftriaxone: 2 g daily; Cephalosporin cefuroxime: 1.5 g every 8 hours; e. g., cefepime: 1-2 g every 8 hours; cefotaxime: 2 g every 8 hours ceftazidime 2 g every 8 hours OR OR Fluoroquinolones Carbepenem e. g., levofloxacin: 750 mg daily; e. g., imipenem + cilastin: 500 mg every 6 hours or 1 g every 8 hours; moxifloxacin: 400 mg daily meropenem: 1 g every 8 hours OR OR Aminopenicillin + beta-lactamase inhibitor e. g., ampicillin + sulbactam: 3 g Beta-lactam/beta-lactamase inhibitor every 8 hours e. g., piperacillin + tazobactam: 4.5 g every 6 hours OR PLUS Ertapenem Aminoglycoside 1 g daily e. g., amikacin: 20 mg/kg/day; gentamicin: 7 mg/kg/day; tobramycin: 7 mg/kg/day OR Antipseudomonal fluoroquinolone e. g., ciprofloxacin 400 mg every 8 hours; levofloxacin 750 mg daily PLUS Coverage for MRSA e. g., vancomycin: 15 mg/kg every 12 hours OR linezolid: 600 mg every 12 hours Optimal dosage includes adjusting for hepatic and renal failure. Trough levels for vancomycin (15-20 mcg/ml), amikacin ( 6 may correlate with VAP, the sensitivity, specificity and inter-rater agreement of this criterion alone are not encouraging. Microbiological data should be used for tailoring antibiotic therapy and not be restricted only to diagnosis. The pitfall in using empiric antibiotics for suspicion of VAP is the potential for antibiotic overuse, emergence of resistance, unnecessary adverse effects and potential toxicity. The major goals of VAP management are early, appropriate antibiotics in adequate doses followed by de-escalation based on microbiological culture results and the clinical response of the patient. Antimicrobial stewardship programs involving pharmacists, physicians and other healthcare providers optimize antibiotic selection, dose, and duration to increase efficacy in targeting causative pathogens and allow the best clinical outcome. List of abbreviations used ARDS: acute respiratory distress syndrome; ATS: American Thoracic Society; BAL: Bronchoalveolar lavage; CDC: Centers for Disease Control and Prevention; CHF: congestive heart failure; CI: confidence interval; CNSL coagulase-negative staphylococcus; CPIS: clinical pulmonary infection score; ESBL: extended-spectrum beta-lactamase producing bacteria (ESBL); FiO2: fraction of inspired oxygen; ICU: intensive care unit; IVAC: infection-related ventilator-associated complication; IDSA: Infectious Diseases Society of America; MDR: multi drug resistant; Mini-BAL-mini-bronchoalvelolar lavage; MRSA: methicillin-resistant Staphylococcus aureus; MSSA: methicillin-senstive Staphylococcus aureus; OR: odds ratios; PBP: penicillin-binding protein; PEEP: positive end-expiratory pressure; PSB: protected specimen brush; Tregs: regulatory T-cells; VAP: ventilator-associated pneumonia. Competing interests The authors declare that they have no competing interests.
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              Withdrawal of support in intracerebral hemorrhage may lead to self-fulfilling prophecies.

              Withdrawal of support in patients with severe brain injury invariably leads to death. Preconceived notions about futility of care in patients with intracerebral hemorrhage (ICH) may prompt withdrawal of support, and modeling outcome in patient populations in whom withdrawal of support occurs may lead to self-fulfilling prophecies. Subjects included consecutive patients with supratentorial ICH. Radiographic characteristics of the hemorrhage, clinical variables, and neurologic outcome were assessed. Attitudes about futility of care were examined among members of the departments of neurology and neurologic surgery through a written survey and case presentations. There were 87 patients with supratentorial ICH; overall mortality was 34.5% (30/87). Mortality was 66.7% (18/27) in patients with Glasgow Coma Score 60 cm(3). Medical support was withdrawn in 76.7% (23/30) of patients who died. Inclusion of a variable to account for the withdrawal of support in a model predicting outcome negated the predictive value of all other variables. Patients undergoing surgical decompression were unlikely to have support withdrawn, and surgery was less likely to be performed in older patients (p < 0.01) and patients with left hemispheric hemorrhage (p = 0.04). Survey results suggested that practitioners tend to be overly pessimistic in prognosticating outcome based upon data available at the time of presentation. The most important prognostic variable in determining outcome after ICH is the level of medical support provided. Withdrawal of support in patients felt likely to have a "poor outcome" biases predictive models and leads to self-fulfilling prophecies. Our data show that individual patients in traditionally "poor outcome" categories can have a reasonable neurologic outcome when treated aggressively.
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                Author and article information

                Contributors
                919-966-5536 , dedrick@unc.edu
                Journal
                J Intensive Care
                J Intensive Care
                Journal of Intensive Care
                BioMed Central (London )
                2052-0492
                4 January 2018
                4 January 2018
                2018
                : 6
                : 1
                Affiliations
                [1 ]ISNI 0000000122483208, GRID grid.10698.36, Department of Neurosurgery, , University of North Carolina School of Medicine, ; 170 Manning Drive, Campus Box 7025, Chapel Hill, NC 27599-7025 USA
                [2 ]ISNI 0000000122483208, GRID grid.10698.36, Department of Biostatistics, , Gillings School of Global Public Health, ; Chapel Hill, NC USA
                [3 ]ISNI 0000000122483208, GRID grid.10698.36, School of Medicine, , University of North Carolina School of Medicine, ; Chapel Hill, NC USA
                [4 ]ISNI 0000 0001 1034 1720, GRID grid.410711.2, Department of Neurology, , University of North Carolina, ; 170 Manning Drive, Campus Box 7025, Chapel Hill, NC USA
                Article
                269
                10.1186/s40560-017-0269-1
                5753520
                29308208
                e03a2468-4d09-49ba-98ca-999ff032ad82
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 30 August 2017
                : 7 December 2017
                Categories
                Research
                Custom metadata
                © The Author(s) 2018

                decompression,ischemic stroke,hemorrhagic stroke,tracheostomy timing,ventilator-associated pneumonia

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