A prognostic model for one-year mortality in patients requiring prolonged mechanical ventilation

Easing Suffering for ICU Patients and Their Families: Evidence and Opportunities for Primary and Specialty Palliative Care in the ICU

Intensive care unit (ICU) admissions are often accompanied by many physical and existential pressure points that can be extraordinarily wearing on patients and their families and surrogate decision makers (SDMs). Multidisciplinary palliative support, including physicians, advanced practice nurses, nutritionists, chaplains and other team members, may alleviate many of these sources of potential suffering. However, the palliative needs of ICU patients undoubtedly exceed the bandwidth of current consultative specialty palliative medicine teams. Informed by standard-of-care palliative medicine domains, we review common ICU symptoms (pain, dyspnea and thirst) and their prevalence, sources and their treatment. We then identify palliative needs and impacts in the domains of communication, SDM support and transitions of care for patients and their families through their journey in the ICU, from discharge and recovery at home to chronic critical illness, post-ICU disability or death. Finally, we examine the evidence for strategies to incorporate specialty palliative medicine and palliative principles into ICU care for the improvement of patient- and family-centered care. While randomized controlled studies have failed to demonstrate measurable improvement in pre-determined outcomes for patient- and family-relevant outcomes, embracing the principles of palliative medicine and assuring their delivery in the ICU is likely to translate to overall improvement in humanistic, person-centered care that supports patients and their SDMs during and following critical illness.

Consequences of a stay in the intensive care unit and outpatient follow-up care for chronic critically ill patients: A retrospective data analysis

BACKGROUND

Patients with chronic critical illness (CCI) represent a particularly vulnerable patient population with significant quality-of-life consequences and a need for follow-up care. Existing research on their quality-of-life trajectory and outpatient follow-up care is limited.

OBJECTIVES

The aim of this study was to (i) describe a quality improvement project focussing on patients with CCI in the Swiss setting; (ii) explain the consequences of an intensive care unit (ICU) stay for patients with CCI; and (iii) evaluate outpatient follow-up care for patients with CCI.

METHODS

This retrospective descriptive mixed-methods longitudinal study used routine data from outpatient follow-up care between October 2018 and June 2022. The pre-ICU data were collected retrospectively for the week before ICU admission (baseline); prospectively at 3, 6, and 12 months after ICU discharge; and during an outpatient follow-up care at 6 months. Its main outcomes were health-related quality of life (HRQOL). Patients with CCI were defined as those having a ICU stay longer than 7 days.

RESULTS

This study enrolled 227 patients with outpatient follow-up care, but only 77 were analysed at all four timepoints. Their EuroQol five-dimension five-level questionnaire-Visual Analogue Scale scores ranged from 0 to 100, with a median of 85 (interquartile range = 0-100) and a mean of 77.2 (standard deviation ± 23.52) before their ICU stay. Their scores had almost returned to the baseline 12 months after their ICU stay. While some reported existing restrictions in the individual HRQOL dimensions before their ICU stay, patients and their families appreciated the outpatient follow-up care including an ICU visit.

CONCLUSION

Patients with CCI have different HRQOL trajectories over time. Patients with CCI can have a good HRQOL despite their impairments; however, the HRQOL trajectories of many patients remain unclear. The focus must be on identifying the illness trajectories and on measuring and maintaining their long-term HRQOL.

The impact of comorbidities on prolonged mechanical ventilation in patients with chronic obstructive pulmonary disease

BACKGROUND

In patients with chronic obstructive pulmonary disease (COPD) and acute respiratory failure, approximately 10% of them are considered to be at high risk for prolonged mechanical ventilation (PMV, > 21 days). PMV have been identified as independent predictors of unfavorable outcomes. Our previous study revealed that patients aged 70 years older and COPD severity were at a significantly higher risk for PMV. We aimed to analyze the impact of comorbidities and their associated risks in patients with COPD who require PMV.

METHODS

The data used in this study was collected from Kaohsiung Medical University Hospital Research Database. The COPD subjects were the patients first diagnosed COPD (index date) between January 1, 2012 and December 31, 2020. The exclusion criteria were the patients with age less than 40 years, PMV before the index date or incomplete records. COPD and non-COPD patients, matched controls were used by applying the propensity score matching method.

RESULTS

There are 3,744 eligible patients with COPD in the study group. The study group had a rate of 1.6% (60 cases) patients with PMV. The adjusted HR of PMV was 2.21 (95% CI 1.44-3.40; P < 0.001) in the COPD patients than in non-COPD patients. Increased risks of PMV were found significantly for patients with diabetes mellitus (aHR 4.66; P < 0.001), hypertension (aHR 3.20; P = 0.004), dyslipidemia (aHR 3.02; P = 0.015), congestive heart failure (aHR 6.44; P < 0.001), coronary artery disease (aHR 3.11; P = 0.014), stroke (aHR 6.37; P < 0.001), chronic kidney disease (aHR 5.81 P < 0.001) and Dementia (aHR 5.78; P < 0.001).

CONCLUSIONS

Age, gender, and comorbidities were identified as significantly higher risk factors for PMV occurrence in the COPD patients compared to the non-COPD patients. Beyond age, comorbidities also play a crucial role in PMV in COPD.

Development of a Prognostic Scoring System for Tracheostomized Patients Requiring Prolonged Ventilator Care: A Ten-Year Experience in a University-Affiliated Tertiary Hospital

Background and Objectives: This study aimed to assess the value of a novel prognostic model, based on clinical variables, comorbidities, and demographic characteristics, to predict long-term prognosis in patients who received mechanical ventilation (MV) for over 14 days and who underwent a tracheostomy during the first 14 days of MV. Materials and Methods: Data were obtained from 278 patients (66.2% male; median age: 71 years) who underwent a tracheostomy within the first 14 days of MV from February 2011 to February 2021. Factors predicting 1-year mortality after the initiation of MV were identified by binary logistic regression analysis. The resulting prognostic model, known as the tracheostomy-ProVent score, was computed by assigning points to variables based on their respective ß-coefficients. Results: The overall 1-year mortality rate was 64.7%. Six factors were identified as prognostic indicators: platelet count < 150 × 103/μL, PaO2/FiO2 < 200 mmHg, body mass index (BMI) < 23.0 kg/m2, albumin concentration < 2.8 g/dL on day 14 of MV, chronic cardiovascular diseases, and immunocompromised status at admission. The tracheostomy-ProVent score exhibited acceptable discrimination, with an area under the receiver operating characteristic curve (AUC) of 0.786 (95% confidence interval: 0.733-0.833, p < 0.001) and acceptable calibration (Hosmer-Lemeshow chi-square: 2.753, df: 8, p = 0.949). Based on the maximum Youden index, the cut-off value for predicting mortality was set at ≥2, with a sensitivity of 67.4% and a specificity of 76.3%. Conclusions: The tracheostomy-ProVent score is a good predictive tool for estimating 1-year mortality in tracheostomized patients undergoing MV for >14 days. This comprehensive model integrates clinical variables and comorbidities, enhancing the precision of long-term prognosis in these patients.

PROLONGED MECHANICAL VENTILATION IN ACUTE RESPIRATORY DISTRESS SYNDROME

ABSTRACT

Purpose: Trajectory of acute respiratory distress syndrome (ARDS) spans from rapidly improving cases to cases receiving prolonged mechanical ventilation (PMV). We attempted to estimate temporal trends of prevalence and mortality of PMV and to identify risk factors associated with mortality of patients with ARDS receiving PMV. Methods: We performed a secondary analysis of individual patient data from six randomized controlled clinical trials conducted by the ARDS Network. Prolonged mechanical ventilation was defined as the need for mechanical ventilation for >21 consecutive days. Results: Of 4,216 patients with ARDS, 646 (15.3%) received PMV. Prevalence of PMV gradually declined from 18.4% in the ARDS Network: Low-Tidal-Volume Trial (published in 2000) trial to 10.9% in the SAILS (2014) trial ( R2 = 0.728, P = 0.031). Ninety-day mortality of patients receiving PMV did not change over time ( R2 = 0.271, P = 0.290) and remained as high as 36.8%. Ιn the three most recent trials, risk factors associated with mortality among the 250 patients with ARDS receiving PMV included age, malignancy, pneumonia as the cause of ARDS, coagulation dysfunction, and hepatic dysfunction during the first 21 days after trial enrollment. Conclusion: Although prevalence of PMV among patients enrolled in ARDS Network trials gradually declined, mortality did not change. Risk factors associated with mortality were mostly nonmodifiable.

Early versus late tracheostomy in critically ill COVID-19 patients

BACKGROUND

The role of early tracheostomy as an intervention for critically ill COVID-19 patients is unclear. Previous reports have described prolonged intensive care stays and difficulty weaning from mechanical ventilation in critically ill COVID-19 patients, particularly in those developing acute respiratory distress syndrome. Pre-pandemic evidence on the benefits of early tracheostomy is conflicting but suggests shorter hospital stays and lower mortality rates compared to late tracheostomy.

OBJECTIVES

To assess the benefits and harms of early tracheostomy compared to late tracheostomy in critically ill COVID-19 patients.

SEARCH METHODS

We searched the Cochrane COVID-19 Study Register, which comprises CENTRAL, PubMed, Embase, ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, and medRxiv, as well as Web of Science (Science Citation Index Expanded and Emerging Sources Citation Index) and WHO COVID-19 Global literature on coronavirus disease to identify completed and ongoing studies without language restrictions. We conducted the searches on 14 June 2022.

SELECTION CRITERIA

We followed standard Cochrane methodology. We included randomized controlled trials (RCTs) and non-randomized studies of interventions (NRSI) evaluating early tracheostomy compared to late tracheostomy during SARS-CoV-2 infection in critically ill adults irrespective of gender, ethnicity, or setting.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methodology. To assess risk of bias in included studies, we used the Cochrane RoB 2 tool for RCTs and the ROBINS-I tool for NRSIs. We used the GRADE approach to assess the certainty of evidence for outcomes of our prioritized categories: mortality, clinical status, and intensive care unit (ICU) length of stay. As the timing of tracheostomy was very heterogeneous among the included studies, we applied GRADE only to studies that defined early tracheostomy as 10 days or less, which was chosen according to clinical relevance.

MAIN RESULTS

We included one RCT with 150 participants diagnosed with SARS-CoV-2 infection and 24 NRSIs with 6372 participants diagnosed with SARS-CoV-2 infection. All participants were admitted to the ICU, orally intubated and mechanically ventilated. The RCT was a multicenter, parallel, single-blinded study conducted in Sweden. Of the 24 NRSIs, which were mostly conducted in high- and middle-income countries, eight had a prospective design and 16 a retrospective design. We did not find any ongoing studies. RCT-based evidence We judged risk of bias for the RCT to be of low or some concerns regarding randomization and measurement of the outcome. Early tracheostomy may result in little to no difference in overall mortality (RR 0.82, 95% CI 0.52 to 1.29; RD 67 fewer per 1000, 95% CI 178 fewer to 108 more; 1 study, 150 participants; low-certainty evidence). As an indicator of improvement of clinical status, early tracheostomy may result in little to no difference in duration to liberation from invasive mechanical ventilation (MD 1.50 days fewer, 95%, CI 5.74 days fewer to 2.74 days more; 1 study, 150 participants; low-certainty evidence). As an indicator of worsening clinical status, early tracheostomy may result in little to no difference in the incidence of adverse events of any grade (RR 0.94, 95% CI 0.79 to 1.13; RD 47 fewer per 1000, 95% CI 164 fewer to 102 more; 1 study, 150 participants; low-certainty evidence); little to no difference in the incidence of ventilator-associated pneumonia (RR 1.08, 95% CI 0.23 to 5.20; RD 3 more per 1000, 95% CI 30 fewer to 162 more; 1 study, 150 participants; low-certainty evidence). None of the studies reported need for renal replacement therapy. Early tracheostomy may result in little benefit to no difference in ICU length of stay (MD 0.5 days fewer, 95% CI 5.34 days fewer to 4.34 days more; 1 study, 150 participants; low-certainty evidence). NRSI-based evidence We considered risk of bias for NRSIs to be critical because of possible confounding, study participant enrollment into the studies, intervention classification and potentially systematic errors in the measurement of outcomes. We are uncertain whether early tracheostomy (≤ 10 days) increases or decreases overall mortality (RR 1.47, 95% CI 0.43 to 5.00; RD 143 more per 1000, 95% CI 174 less to 1218 more; I2 = 79%; 2 studies, 719 participants) or duration to liberation from mechanical ventilation (MD 1.98 days fewer, 95% CI 0.16 days fewer to 4.12 more; 1 study, 50 participants), because we graded the certainty of evidence as very low. Three NRSIs reported ICU length of stay for 519 patients with early tracheostomy (≤ 10 days) as a median value, which we could not include in the meta-analyses. We are uncertain whether early tracheostomy (≤ 10 days) increases or decreases the ICU length of stay, because we graded the certainty of evidence as very low.

AUTHORS' CONCLUSIONS

We found low-certainty evidence that early tracheostomy may result in little to no difference in overall mortality in critically ill COVID-19 patients requiring prolonged mechanical ventilation compared with late tracheostomy. In terms of clinical improvement, early tracheostomy may result in little to no difference in duration to liberation from mechanical ventilation compared with late tracheostomy. We are not certain about the impact of early tracheostomy on clinical worsening in terms of the incidence of adverse events, need for renal replacement therapy, ventilator-associated pneumonia, or the length of stay in the ICU. Future RCTs should provide additional data on the benefits and harms of early tracheostomy for defined main outcomes of COVID-19 research, as well as of comparable diseases, especially for different population subgroups to reduce clinical heterogeneity, and report a longer observation period. Then it would be possible to draw conclusions regarding which patient groups might benefit from early intervention. Furthermore, validated scoring systems for more accurate predictions of the need for prolonged mechanical ventilation should be developed and used in new RCTs to ensure safer indication and patient safety. High-quality (prospectively registered) NRSIs should be conducted in the future to provide valuable answers to clinical questions. This could enable us to draw more reliable conclusions about the potential benefits and harms of early tracheostomy in critically ill COVID-19 patients.

Analysis of risk factors of prolonged mechanical ventilation in patients with severe burn injury

BACKGROUND

Mechanical ventilation is an essential means of life support for patients with severe burns. However, prolonged mechanical ventilation (PMV) increases the incidence of complications and length of hospital stay. Therefore, studying the risk factors of mechanical ventilation duration is of great significance for reducing the duration of mechanical ventilation, reducing related complications, and improving the success rate of severe burn treatment.

METHOD

This study was a retrospective study of patients with burns ≥30% of the area admitted to the BICU of Guangzhou Red Cross Hospital affiliated with Jinan University from January 2016 to January 2023 who were mechanically ventilated. Patients were classified into the prolonged mechanical ventilation group if they were mechanically ventilated for ≥21 days. Then, independent risk factors for prolonged mechanical ventilation were determined by logistic regression analysis of the collected data.

RESULT

Of all the 112 enrolled patients, 79 had prolonged mechanical ventilation, with an incidence of 70.5%. Logistic regression analysis revealed that including abbreviated burn severity index (ABSI%) (P < 0.001), moderate and severe inhalation injury (P = 0.005, P = 0.044), albumin (P = 0.032), lactic acid (P < 0.001) were independent risk factors for prolonged mechanical ventilation. In addition, ventilator-related complications were 44% in the PMV group and 21% in the non-PMV group.

CONCLUSION

ABSI%, inhalation injury, albumin, and lactic acid on admission are the risk factors for PMV in severe burn patients. In addition, ventilator-related complications were higher in group PMV than in group non-PMV in our study.

External validation of the ProVent score for prognostication of 1-year mortality of critically ill patients with prolonged mechanical ventilation: a single-centre, retrospective observational study in Austria

OBJECTIVES

In critically ill patients requiring mechanical ventilation for at least 21 days, 1-year mortality can be estimated using the ProVent score, calculated from four variables (age, platelet count, vasopressor use and renal replacement therapy). We aimed to externally validate discrimination and calibration of the ProVent score and, if necessary, to update its underlying regression model.

DESIGN

Retrospective, observational, single-centre study.

SETTING

11 intensive care units at one tertiary academic hospital.

PATIENTS

780 critically ill adult patients receiving invasive mechanical ventilation for at least 21 days.

PRIMARY OUTCOME MEASURE

1-year mortality after intensive care unit discharge.

RESULTS

380 patients (49%) had died after 1 year. One-year mortality for ProVent scores from 0 to 5 were: 15%, 27%, 57%, 66%, 72% and 76%. Area under the receiver operating characteristic curve of the ProVent probability model was 0.76 (95% CI 0.72 to 0.79), calibration intercept was -0.43 (95% CI -0.59 to -0.27) and calibration slope was 0.76 (95% CI 0.62 to 0.89). Model recalibration and extension by inclusion of three additional predictors (total bilirubin concentration, enteral nutrition and surgical status) improved model discrimination and calibration. Decision curve analysis demonstrated that the original ProVent model had negative net benefit, which was avoided with the extended ProVent model.

CONCLUSIONS

The ProVent probability model had adequate discrimination but was miscalibrated in our patient cohort and, as such, could potentially be harmful. Use of the extended ProVent score developed by us could possibly alleviate this concern.

Prognostic factors and outcomes in COVID-19 patients requiring prolonged mechanical ventilation: a retrospective cohort study

Background:

Mechanical ventilation (MV) in coronavirus disease 2019 (COVID-19) patients is associated with high mortality and extensive resource utilization. The aim of this study was to investigate prognostic factors and outcomes associated with prolonged mechanical ventilation (PMV) in COVID-19 patients.

Methods:

This was a retrospective cohort study of COVID-19 patients requiring invasive MV who were hospitalized between 1 March 2020 and 30 June 2021 in the intensive care units (ICUs) of three referral hospitals belonging to a single health system. Data were extracted from electronic health records. PMV was defined as  > 17 days of MV.

Results:

Of 355 patients studied, 86 (24%) required PMV. PMV patients had lower PaO2/FiO2 ratio, higher PCO2, and higher plateau and driving pressures during the first 2 weeks of MV than their short MV (SMV; ⩽ 17 days) counterparts. PMV patients received more proning, neuromuscular blockade, and tracheostomy, had longer ICU and hospital length of stay (LOS), and required discharge to an inpatient rehabilitation facility more frequently (all p < 0.001). Overall 30-day mortality was 43.9%, with no statistically significant difference between PMV and SMV groups. In PMV patients, smoking, Charlson comorbidity index > 6, and week 2 PaO2/FiO2 ratio < 150 and plateau pressure ⩾ 30 were positively associated with 30-day mortality. In a multivariate model, results were directionally consistent with the univariate analysis but did not reach statistical significance.

Conclusion:

PMV is commonly required in COVID-19 patients with respiratory failure. Despite the higher need for critical care interventions and LOS, more than half of the PMV cohort survived to hospital discharge. Higher PaO2/FiO2 ratio, lower plateau pressure, and fewer comorbidities appear to be associated with survival in this group.

Chronic Critical Illness in Patients with COVID-19: Characteristics and Outcome of Prolonged Intensive Care Therapy

The spread of SARS-CoV-2 caused a worldwide healthcare threat. High critical care admission rates related to Coronavirus Disease 2019 (COVID-19) respiratory failure were observed. Medical advances helped increase the number of patients surviving the acute critical illness. However, some patients require prolonged critical care. Data on the outcome of patients with a chronic critical illness (CCI) are scarce. Single-center retrospective study including all adult critically ill patients with confirmed COVID-19 treated at the Department of Intensive Care Medicine at the University Medical Center Hamburg-Eppendorf, Germany, between 1 March 2020 and 8 August 2021. We identified 304 critically ill patients with COVID-19 during the study period. Of those, 55% (n = 167) had an ICU stay ≥21 days and were defined as chronic critical illness, and 45% (n = 137) had an ICU stay <21 days. Age, sex and BMI were distributed equally between both groups. Patients with CCI had a higher median SAPS II (CCI: 39.5 vs. no-CCI: 38 points, p = 0.140) and SOFA score (10 vs. 6, p < 0.001) on admission. Seventy-three per cent (n = 223) of patients required invasive mechanical ventilation (MV) (86% vs. 58%; p < 0.001). The median duration of MV was 30 (17-49) days and 7 (4-12) days in patients with and without CCI, respectively (p < 0.001). The regression analysis identified ARDS (OR 3.238, 95% CI 1.827-5.740, p < 0.001) and referral from another ICU (OR 2.097, 95% CI 1.203-3.654, p = 0.009) as factors significantly associated with new-onset of CCI. Overall, we observed an ICU mortality of 38% (n = 115) in the study cohort. In patients with CCI we observed an ICU mortality of 28% (n = 46) compared to 50% (n = 69) in patients without CCI (p < 0.001). The 90-day mortality was 28% (n = 46) compared to 50% (n = 70), respectively (p < 0.001). More than half of critically ill patients with COVID-19 suffer from CCI. Short and long-term survival rates in patients with CCI were high compared to patients without CCI, and prolonged therapy should not be withheld when resources permit prolonged therapy.

Long-Term Survival and Medical Costs of Patients with Prolonged Mechanical Ventilation and Tracheostomy: A Nationwide Cohort Study

Few large-scale studies have focused on tracheostomy in patients with prolonged mechanical ventilation. This retrospective population-based study extracted data from the longitudinal National Health Insurance Research Database in Taiwan to compare long-term mortality between patients on prolonged mechanical ventilation with and without tracheostomy and their related medical expenditures. Data on newly developed respiratory failure in patients on ventilator support were extracted from 1 January 2002 to 31 December 2008. Of 10,705 patients included, 1372 underwent tracheostomy (n = 563) or translaryngeal intubation (n = 779). Overall survival of the patients with tracheostomy was followed for 5 years. Average survival was 4.98 years for the patients with tracheostomy and 5.48 years for the patients with translaryngeal intubation (not significant). Sex, age, premium-based monthly salary difference, occupation, urbanization level, chronic obstructive pulmonary disease, chronic heart failure, chronic renal disease, and cerebrovascular diseases were significantly associated with mortality for endotracheal intubation. Male sex, chronic heart failure, chronic renal disease, age ≥45 years, and low income were associated with significantly higher mortality. Although total medical expenditures were higher for the patients with tracheostomy, annual medical expenditures were not significantly different. There were no differences in long-term mortality between the two groups.

Deep learning to predict long-term mortality in patients requiring 7 days of mechanical ventilation

Background

Among patients with acute respiratory failure requiring prolonged mechanical ventilation, tracheostomies are typically placed after approximately 7 to 10 days. Yet half of patients admitted to the intensive care unit receiving tracheostomy will die within a year, often within three months. Existing mortality prediction models for prolonged mechanical ventilation, such as the ProVent Score, have poor sensitivity and are not applied until after 14 days of mechanical ventilation. We developed a model to predict 3-month mortality in patients requiring more than 7 days of mechanical ventilation using deep learning techniques and compared this to existing mortality models.

Methods

Retrospective cohort study. Setting: The Medical Information Mart for Intensive Care III Database. Patients: All adults requiring ≥ 7 days of mechanical ventilation. Measurements: A neural network model for 3-month mortality was created using process-of-care variables, including demographic, physiologic and clinical data. The area under the receiver operator curve (AUROC) was compared to the ProVent model at predicting 3 and 12-month mortality. Shapley values were used to identify the variables with the greatest contributions to the model.

Results

There were 4,334 encounters divided into a development cohort (n = 3467) and a testing cohort (n = 867). The final deep learning model included 250 variables and had an AUROC of 0.74 for predicting 3-month mortality at day 7 of mechanical ventilation versus 0.59 for the ProVent model. Older age and elevated Simplified Acute Physiology Score II (SAPS II) Score on intensive care unit admission had the largest contribution to predicting mortality.

Discussion

We developed a deep learning prediction model for 3-month mortality among patients requiring ≥ 7 days of mechanical ventilation using a neural network approach utilizing readily available clinical variables. The model outperforms the ProVent model for predicting mortality among patients requiring ≥ 7 days of mechanical ventilation. This model requires external validation.

Functional Status After Pulmonary Rehabilitation as a Predictor of Weaning Success and Survival in Patients Requiring Prolonged Mechanical Ventilation

Background: Comprehensive rehabilitation programs are recommended for patients with prolonged mechanical ventilation (PMV) to facilitate functional recovery and ventilator weaning, but whether the functional status after rehabilitation influences outcome has not been clearly evaluated. This study aimed to investigate the association between post-rehabilitation functional status and weaning and survival outcome in PMV patients. Methods: We retrospectively enrolled PMV patients admitted to the respiratory care center (RCC), a post-ICU weaning facility with protocolized rehabilitation program, from January 2016 through December 2017. Functional status was measured by the de Morton Mobility Index (DEMMI), with a cut-off value set at 20 points. The primary outcomes were the weaning status at RCC discharge and hospital survival. The secondary outcomes were overall survival and survival at 3 months after RCC discharge. We followed patients until 3 months after RCC discharge or death. Logistic and Cox regressions were performed to identify significant parameters associated with weaning success and survival. Results: In total, 320 patients were enrolled. The weaning success rate was 71.6%. The survival rate at RCC discharge, hospital discharge, and 3 months after RCC discharge was 89.1, 77.5, and 66.6%, respectively. Post-rehabilitation DEMMI ≥ 20 (odds ratio [OR], 3.514; 95% confidence interval [CI], 1.436-8.598; P = 0.006) was the most significantly associated with weaning success. The weaning success and higher post-rehabilitation DEMMI were the two most significant independent factors associated with both hospital survival (weaning success, OR, 12.272; 95% CI, 5.281-28.517; P < 0.001; post-rehabilitation DEMMI ≥ 20, OR, 6.298; 95% CI, 1.302-30.477; P = 0.022) and survival at 3 months after RCC discharge (weaning success, OR, 38.788; 95% CI, 11.505-130.762; P < 0.001; post-rehabilitation DEMMI ≥ 20, OR, 4.830; 95% CI, 1.072-21.756; P = 0.040). Post-rehabilitation DEMMI ≥ 20 remained significantly association with overall survival at 3 months after RCC discharge (hazard ratio, 0.237; 95% CI, 0.072-0.785; P = 0.018). Conclusions: Post-rehabilitation functional status of PMV patients was independently associated with weaning success, as well as hospital and 3-month overall survival after RCC discharge. Post-rehabilitation, but not pre-rehabilitation, functional status was a significant parameter associated with weaning success and survival in patients requiring PMV.

Chronic Critical Illness and PICS Nutritional Strategies

The nutritional hallmark of chronic critical illness (CCI) after sepsis is persistent inflammation, immunosuppression, and catabolism syndrome (PICS), which results in global resistance to the anabolic effect of nutritional supplements. This ultimately leaves these patients in a downward phenotypic spiral characterized by cachexia with profound weakness, decreased capacity for rehabilitation, and immunosuppression with the propensity for sepsis recidivism. The persistent catabolism is driven by a pathologic low-grade inflammation with the inability to return to homeostasis and by ongoing increased energy expenditure. Better critical care support systems and advances in technology have led to increased intensive care unit (ICU) survival, but CCI due to PICS with poor long-term outcomes has emerged as a frequent phenotype among ICU sepsis survivors. Unfortunately, therapies to mitigate or reverse PICS-CCI are limited, and recent evidence supports that these patients fail to respond to early ICU evidence-based nutrition protocols. A lack of randomized controlled trials has limited strong recommendations for nutrition adjuncts in these patients. However, based on experience in other conditions characterized by a similar phenotype, immunonutrients aimed at counteracting inflammation, immunosuppression, and catabolism may be important for improving outcomes in PICS-CCI patients. This manuscript intends to review several immunonutrients as adjunctive therapies in treating PICS-CCI.

Development of a prognostic scoring system in patients with pneumonia requiring ventilator care for more than 4 days: a single-center observational study

BACKGROUND

The aim of the present study was to develop a prognostic model using demographic characteristics, comorbidities, and clinical variables measured on day 4 of mechanical ventilation (MV) for patients with prolonged acute mechanical ventilation (PAMV; MV for >96 hours).

METHODS

Data from 437 patients (70.9% male; median age, 68 years) were obtained over a period of 9 years. All patients were diagnosed with pneumonia. Binary logistic regression identified factors predicting mortality at 90 days after the start of MV. A PAMV prognosis score was calculating ß-coefficient values and assigning points to variables.

RESULTS

The overall 90-day mortality rate was 47.1%. Five factors (age ≥65 years, body mass index <18.5 kg/m2, hemato-oncologic diseases as comorbidities, requirement for vasopressors on day 4 of MV and requirement for neuromuscular blocking agents on day 4 of MV) were identified as prognostic indicators. Each factor was valued as +1 point, and used to develop a PAMV prognosis score. This score showed acceptable discrimination (area under the receiver operating characteristic curve of 0.695 for mortality, 95% confidence interval 0.650-0.738, p<0.001), and calibration (Hosmer-Lemeshow chi-square=6.331, with df 7 and p=0.502). The cutoff value for predicting mortality based on the maximum Youden index was ≤2 (sensitivity, 87.5%; specificity, 41.3%). For patients with PAMV scores ≤1, 2, 3 and ≥4, the 90-day mortality rates were 29.2%, 45.7%, 67.9%, and 90.9%, respectively (P<0.001).

CONCLUSIONS

Our study developed a PAMV prognosis score for predicting 90-day mortality. Further research is needed to validate the utility of this score.

Mortality outcomes of patients on chronic mechanical ventilation in different care settings: A systematic review

Objectives

To determine the outcomes of chronically ventilated patients outside the setting of intensive care units.

Design

Systematic review.

Setting and participants

Studies evaluating patients on chronic invasive mechanical ventilation in different care settings.

Methods

A systematic literature search of the PubMed, Embase, Cochrane Library, CINAHL (EBSCOhost), LILACS and Scopus databases from inception to March 27, 2020. Studies reporting mortality outcomes of patients ≥18 years of age on chronic invasive mechanical ventilation in intensive care units and other care settings were eligible for inclusion.

Results

Sixty studies were included in the systematic review. Mortality rates ranged from 13.7% to 77.8% in ICUs (n = 17 studies), 7.8%-51.0% in non-ICUs including step-down units and inpatient wards (n = 26 studies), and 12.0%-91.8% in home or nursing home settings (n = 19 studies). Age was associated with mortality in all care settings. Weaning rates ranged from 10.0% to 78.2% across non-ICU studies. Studies reporting weaning as their primary outcome demonstrated higher success rates in weaning. Home care studies reported low incidences of ventilator failure. None of the studies reported ventilator malfunction as the primary cause of death.

Conclusions and implications

Mortality outcomes across various settings were disparate due to methodological and clinical heterogeneity among studies. However, there is evidence to suggest non-ICU venues of care as a comparable alternative to ICUs for stable, chronically ventilated patients, with the additional benefit of providing specialized weaning programs. By synthesizing the global data on managing chronically ventilated patients in various care settings, this study provides health care systems and providers alternative venue options for the delivery of prolonged ventilatory care in the context of limited ICU resources.

Prolonged Weaning: S2k Guideline Published by the German Respiratory Society

Mechanical ventilation (MV) is an essential part of modern intensive care medicine. MV is performed in patients with severe respiratory failure caused by respiratory muscle insufficiency and/or lung parenchymal disease; that is, when other treatments such as medication, oxygen administration, secretion management, continuous positive airway pressure (CPAP), or nasal high-flow therapy have failed. MV is required for maintaining gas exchange and allows more time to curatively treat the underlying cause of respiratory failure. In the majority of ventilated patients, liberation or "weaning" from MV is routine, without the occurrence of any major problems. However, approximately 20% of patients require ongoing MV, despite amelioration of the conditions that precipitated the need for it in the first place. Approximately 40-50% of the time spent on MV is required to liberate the patient from the ventilator, a process called "weaning". In addition to acute respiratory failure, numerous factors can influence the duration and success rate of the weaning process; these include age, comorbidities, and conditions and complications acquired during the ICU stay. According to international consensus, "prolonged weaning" is defined as the weaning process in patients who have failed at least 3 weaning attempts, or require more than 7 days of weaning after the first spontaneous breathing trial (SBT). Given that prolonged weaning is a complex process, an interdisciplinary approach is essential for it to be successful. In specialised weaning centres, approximately 50% of patients with initial weaning failure can be liberated from MV after prolonged weaning. However, the heterogeneity of patients undergoing prolonged weaning precludes the direct comparison of individual centres. Patients with persistent weaning failure either die during the weaning process, or are discharged back to their home or to a long-term care facility with ongoing MV. Urged by the growing importance of prolonged weaning, this Sk2 Guideline was first published in 2014 as an initiative of the German Respiratory Society (DGP), in conjunction with other scientific societies involved in prolonged weaning. The emergence of new research, clinical study findings and registry data, as well as the accumulation of experience in daily practice, have made the revision of this guideline necessary. The following topics are dealt with in the present guideline: Definitions, epidemiology, weaning categories, underlying pathophysiology, prevention of prolonged weaning, treatment strategies in prolonged weaning, the weaning unit, discharge from hospital on MV, and recommendations for end-of-life decisions. Special emphasis was placed on the following themes: (1) A new classification of patient sub-groups in prolonged weaning. (2) Important aspects of pulmonary rehabilitation and neurorehabilitation in prolonged weaning. (3) Infrastructure and process organisation in the care of patients in prolonged weaning based on a continuous treatment concept. (4) Changes in therapeutic goals and communication with relatives. Aspects of paediatric weaning are addressed separately within individual chapters. The main aim of the revised guideline was to summarize both current evidence and expert-based knowledge on the topic of "prolonged weaning", and to use this information as a foundation for formulating recommendations related to "prolonged weaning", not only in acute medicine but also in the field of chronic intensive care medicine. The following professionals served as important addressees for this guideline: intensivists, pulmonary medicine specialists, anaesthesiologists, internists, cardiologists, surgeons, neurologists, paediatricians, geriatricians, palliative care clinicians, rehabilitation physicians, intensive/chronic care nurses, physiotherapists, respiratory therapists, speech therapists, medical service of health insurance, and associated ventilator manufacturers.

Sudden Cardiac Arrest Survivorship: A Scientific Statement From the American Heart Association

Cardiac arrest systems of care are successfully coordinating community, emergency medical services, and hospital efforts to improve the process of care for patients who have had a cardiac arrest. As a result, the number of people surviving sudden cardiac arrest is increasing. However, physical, cognitive, and emotional effects of surviving cardiac arrest may linger for months or years. Systematic recommendations stop short of addressing partnerships needed to care for patients and caregivers after medical stabilization. This document expands the cardiac arrest resuscitation system of care to include patients, caregivers, and rehabilitative healthcare partnerships, which are central to cardiac arrest survivorship.

Predictors of 1-year mortality in patients on prolonged mechanical ventilation after surgery in intensive care unit: a multicenter, retrospective cohort study

Objectives

The requirement of prolonged mechanical ventilation (PMV) is associated with increased medical care demand and expenses, high early and long-term mortality, and worse life quality. However, no study has assessed the prognostic factors associated with 1-year mortality among PMV patients, not less than 21 days after surgery. This study analyzed the predictors of 1-year mortality in patients requiring PMV in intensive care units (ICUs) after surgery.

Methods

In this multicenter, respective cohort study, 124 patients who required PMV after surgery in the ICUs of five tertiary hospitals in Beijing between January 2007 and June 2016 were enrolled. The primary outcome was the duration of survival within 1 year. Predictors of 1-year mortality were identified with a multivariable Cox proportional hazard model. The predictive effect of the ProVent score was also validated.

Results

Of the 124 patients enrolled, the cumulative 1-year mortality was 74.2% (92/124). From the multivariable Cox proportional hazard analysis, cancer diagnosis (hazard ratio [HR] 2.14, 95% confidence interval [CI] 1.37–3.35; P < 0.01), no tracheostomy (HR 2.01, 95% CI 1.22–3.30; P < 0.01), enteral nutrition intolerance (HR 1.88, 95% CI 1.19–2.97; P = 0.01), blood platelet count ≤150 × 10⁹/L (HR 1.77, 95% CI 1.14–2.75; P = 0.01), requirement of vasopressors (HR 1.78, 95% CI 1.13–2.80; P = 0.02), and renal replacement therapy (HR 1.71, 95% CI 1.01–2.91; P = 0.047) on the 21st day of mechanical ventilation (MV) were associated with shortened 1-year survival.

Conclusions

For patients who required PMV after surgery, cancer diagnosis, no tracheostomy, enteral nutrition intolerance, blood platelet count ≤150 × 10⁹/L, vasopressor requirement, and renal replacement therapy on the 21st day of MV were associated with shortened 1-year survival. The prognosis in PMV patients in ICUs can facilitate the decision-making process of physicians and patients’ family members on treatment schedule.

The chronic ICU patient: Is intensive care worthwhile for patients with very prolonged ICU-stay (≥ 90 days)?

BACKGROUND

Due to medical advances, an increasing number of patients are surviving the acute critical illness. However, some patients require a prolonged critical care treatment. Data on outcome and functional status of patients with an ICU-stay ≥90 days are scarce.

METHODS

Single-center retrospective study including all adult patients with ICU stay ≥90 days treated at the department of intensive care medicine at the university medical center Hamburg-Eppendorf, Germany, between January 1st 2008 and December 31st 2016.

RESULTS

Out of 65,249 patients, we identified 96 (0.1%) patients with a very prolonged ICU stay. Median age was 61 (49.8-67) years, 30 (31%) patients were female. Patients were admitted to ICU due to abdominal (28%) reasons, followed by sepsis (23%) and transplantation (15%). Fourteen patients received organ-transplantation: 9 received liver-, 4 lung- and 1 heart-transplantation. All patients needed mechanical ventilation (MV), median duration was 74.1 (55-95.1) days. Sixty-Three (66%) patients survived the ICU-stay and 1-Year survival rate was 28%. Overall eight (8%) patients had a favourable outcome after 1-Year. Severity of illness (SOFA, SAPS II) on admission were comparable. Length of MV, use of renal replacement therapy (both p < .01) and maximum lactate (5.3 vs 11.5 mmol/l; p < .001) were significantly higher in ICU non-survivors. ICU-stay was significantly longer in ICU non-survivors (137 vs 107 days; p < .05). Cox-regression-model revealed age (HR 1.02, 95% CI 1.00-1.04, p < .05) and surgical admission (HR 0.50, 95% CI 0.28-0.90, p < .05) as independent predictors of 1-year mortality.

CONCLUSIONS

Only a small number of patients requires a very prolonged ICU stay. Two-third of patients survive the ICU stay and about one-third 1-Year. However, about 10% of patients have a remarkable recovery with a favourable overall outcome after 1-Year.

Duration of Respiratory Failure After Trauma Is Not Associated With Increased Long-Term Mortality

OBJECTIVES

Although 1-year survival in medically critically ill patients with prolonged mechanical ventilation is less than 50%, the relationship between respiratory failure after trauma and 1-year mortality is unknown. We hypothesize that respiratory failure duration in trauma patients is associated with decreased 1-year survival.

DESIGN

Retrospective cohort of trauma patients.

SETTING

Single center, level 1 trauma center.

PATIENTS

Trauma patients admitted from 2011 to 2014; respiratory failure is defined as mechanical ventilation greater than or equal to 48 hours, excluded head Abbreviated Injury Score greater than or equal to 4.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Mortality was calculated from the Washington state death registry. Cohort was divided into short (≤ 14 d) and long (> 14 d) ventilation groups. We compared survival with a Cox proportional hazard model and generated a receiver operator characteristic to describe the respiratory failure and mortality relationship. Data are presented as medians with interquartile ranges and hazard ratios with 95% CIs. We identified 1,503 patients with respiratory failure; median age was 51 years (33-65 yr) and Injury Severity Score was 19 (11-29). Median respiratory failure duration was 3 days (2-6 d) with 10% of patients in the long respiratory failure group. Cohort mortality at 1 year was 16%, and there was no difference in mortality between short and long duration of respiratory failure. Predictions for 1-year mortality based on respiratory failure duration demonstrated an area under the receiver operator characteristic curve of 0.57. We determined that respiratory failure patients greater than or equal to 75 years had an increased hazard of death at 1 year, hazard ratio, 6.7 (4.9-9.1), but that within age cohorts, respiratory failure duration did not influence 1-year mortality.

CONCLUSIONS

Duration of mechanical ventilation in the critically injured is not associated with 1-year mortality. Duration of ventilation following injury should not be used to predict long-term survival.

Association between Medical Costs and the ProVent Model in Patients Requiring Prolonged Mechanical Ventilation

BACKGROUND

The purpose of this study was to determine whether components of the ProVent model can predict the high medical costs in Korean patients requiring at least 21 days of mechanical ventilation (prolonged mechanical ventilation [PMV]).

METHODS

Retrospective data from 302 patients (61.6% male; median age, 63.0 years) who had received PMV in the past 5 years were analyzed. To determine the relationship between medical cost per patient and components of the ProVent model, we collected the following data on day 21 of mechanical ventilation (MV): age, blood platelet count, requirement for hemodialysis, and requirement for vasopressors.

RESULTS

The mortality rate in the intensive care unit (ICU) was 31.5%. The average medical costs per patient during ICU and total hospital (ICU and general ward) stay were 35,105 and 41,110 US dollars (USD), respectively. The following components of the ProVent model were associated with higher medical costs during ICU stay: age <50 years (average 42,731 USD vs. 33,710 USD, p=0.001), thrombocytopenia on day 21 of MV (36,237 USD vs. 34,783 USD, p=0.009), and requirement for hemodialysis on day 21 of MV (57,864 USD vs. 33,509 USD, p<0.001). As the number of these three components increased, a positive correlation was found betweeen medical costs and ICU stay based on the Pearson's correlation coefficient (γ) (γ=0.367, p<0.001).

CONCLUSION

The ProVent model can be used to predict high medical costs in PMV patients during ICU stay. The highest medical costs were for patients who required hemodialysis on day 21 of MV.

Clinical evidence for respiratory insufficiency type II predicts weaning failure in long-term ventilated, tracheotomised patients: a retrospective analysis

Background

Patients who require a prolonged weaning process comprise a highly heterogeneous group of patients amongst whom the outcome differs significantly. The present study aimed to identify the factors that predict whether the outcome for prolonged weaning will be successful or unsuccessful.

Methods

Data from tracheotomised patients who underwent prolonged weaning on a specialised weaning unit were assessed retrospectively via an electronic and paper-bound patient chart. Factors for weaning success were analysed by univariate and multivariate analyses.

Results

Out of the 124 patients examined, 48.4% were successfully weaned (n = 60). Univariate analysis revealed that long-term home mechanical ventilation prior to current weaning episode; time between intubation and the first spontaneous breathing trial (SBT); time between intubation and the first SBT of less than 30 days; lower PaCO₂ prior to, and at the end of, the first SBT; and lower pH values at the end of the first SBT were predictors for successful weaning. Following multivariate analysis, the absence of home mechanical ventilation prior to admission, a maximum time period of 30 days between intubation and the first SBT, and a non-hypercapnic PaCO₂ value at the end of the first SBT were predictive of successful weaning.

Conclusions

The current analysis demonstrates that the evidence for respiratory insufficiency type II provided by clinical findings serves as a predictor of weaning failure.

Modification of the prolonged mechanical ventilation prognostic model score to predict short-term and 1-year mortalities

BACKGROUND AND OBJECTIVE

We aimed to validate the use of the Prolonged Mechanical Ventilation Prognostic Model (ProVent) score in medically ill patients with co-morbidities and to modify the score to improve the prediction power of 1-year mortality.

METHODS

We conducted a retrospective study of all patients who required at least 14 days of mechanical ventilation (MV) and established two groups (14-20 and ≥21 days of MV) based on the MV duration. We performed external validation of the present ProVent Model in our patients on Day 14 (or Day 21 for the ≥21-day MV group) of MV, and established the extended ProVent model, while considering the albumin and bilirubin levels and co-morbidities (chronic obstructive pulmonary disease and cancer).

RESULTS

A total of 1288 patients (666 and 622 with 14-20 and ≥21 days of MV, respectively) with at least 14 days of MV were enrolled. The 1-year mortality was 79.9% and 78.7% in the ≥21- and 14-20-day groups, respectively. Most of the observed mortality rates in all groups were within the 95% CI of predicted mortality as per the ProVent Model, except for the ProVent scores of 0 and 5. In the ProVent model, the area under the curve for the prediction of 1-year mortality was 0.69 in all patients with ≥14 days of MV, whereas in the extended ProVent model, the area under the curve was 0.89.

CONCLUSION

The extended ProVent model, which considers co-morbidities and laboratory data, increases the prediction power of 1-year mortality in patients who require prolonged MV.

Chronic critical illness: are we saving patients or creating victims?

The technological advancements that allow support for organ dysfunction have led to an increase in survival rates for the most critically ill patients. Some of these patients survive the initial acute critical condition but continue to suffer from organ dysfunction and remain in an inflammatory state for long periods of time. This group of critically ill patients has been described since the 1980s and has had different diagnostic criteria over the years. These patients are known to have lengthy hospital stays, undergo significant alterations in muscle and bone metabolism, show immunodeficiency, consume substantial health resources, have reduced functional and cognitive capacity after discharge, create a sizable workload for caregivers, and present high long-term mortality rates. The aim of this review is to report on the most current evidence in terms of the definition, pathophysiology, clinical manifestations, treatment, and prognosis of persistent critical illness.

The outcomes and prognostic factors of acute respiratory failure in the patients 90 years old and over

This retrospective cohort study investigated the outcomes and prognostic factors in nonagenarians (patients 90 years old or older) with acute respiratory failure. Between 2006 and 2016, all nonagenarians with acute respiratory failure requiring invasive mechanical ventilation (MV) were enrolled. Outcomes including in-hospital mortality and ventilator dependency were measured. A total of 173 nonagenarians with acute respiratory failure were admitted to the intensive care unit (ICU). A total of 56 patients died during the hospital stay and the rate of in-hospital mortality was 32.4%. Patients with higher APACHE (Acute Physiology and Chronic Health Evaluation) II scores (adjusted odds ratio [OR], 5.91; 95 % CI, 1.55-22.45; p = 0.009, APACHE II scores ≥ 25 vs APACHE II scores < 15), use of vasoactive agent (adjust OR, 2.67; 95% CI, 1.12-6.37; p = 0.03) and more organ dysfunction (adjusted OR, 11.13; 95% CI, 3.38-36.36, p < 0.001; ≥ 3 organ dysfunction vs ≤ 1 organ dysfunction) were more likely to die. Among the 117 survivors, 25 (21.4%) patients became dependent on MV. Female gender (adjusted OR, 3.53; 95% CI, 1.16-10.76, p = 0.027) and poor consciousness level (adjusted OR, 4.98; 95% CI, 1.41-17.58, p = 0.013) were associated with MV dependency. In conclusion, the mortality rate of nonagenarians with acute respiratory failure was high, especially for those with higher APACHE II scores or more organ dysfunction.

Chronic Critical Illness: Application of What We Know

Over the last decade, chronic critical illness (CCI) has emerged as an epidemic in intensive care unit (ICU) survivors worldwide. Advances in ICU technology and implementation of evidence-based care bundles have significantly decreased early deaths and have allowed patients to survive previously lethal multiple organ failure (MOF). Many MOF survivors, however, experience a persistent dysregulated immune response that is causing an increasingly predominant clinical phenotype called the persistent inflammation, immunosuppression, and catabolism syndrome (PICS). The elderly are especially vulnerable; thus, as the population ages the prevalence of this CCI/PICS clinical trajectory will undoubtedly grow. Unfortunately, there are no proven therapies to prevent PICS, and multimodality interventions will be required. The purpose of this review is to: (1) discuss CCI as it relates to PICS, (2) identify the burden on healthcare and poor outcomes of these patients, and (3) describe possible nutrition interventions for the CCI/PICS phenotype.

Validation of the Prognosis for Prolonged Ventilation (ProVent) score in patients receiving 14days of mechanical ventilation

PURPOSE

To evaluate the performance of the Prognosis for Prolonged Ventilation (ProVent) 14 score in patients requiring prolonged mechanical ventilation (PMV).

MATERIALS AND METHODS

Data were obtained from 366 patients receiving at least 14days of MV between January 2011 and December 2015 at a university-affiliated tertiary care hospital in Korea. ProVent 14 scores were assessed using the six standard variables. Model discrimination was assessed with the area under the receiver operating characteristic curve. Kaplan-Meier estimates were stratified according to the ProVent 14 score to predict 1-year survival.

RESULTS

The median age of the study group was 62years (range, 50-72years); 65% were male, and medical patients comprised 66% of the group. Overall mortality at 1year was 43%. For ProVent 14 scores ranging from 0 to ≥4, 1-year mortality rates were 7%, 22%, 41%, 52%, and 75%, respectively (log-rank test, P<0.001). The area under the receiver operating characteristic curve of the ProVent 14 score predicting 1-year mortality was 0.74 (95% confidence interval, 0.69-0.78).

CONCLUSIONS

The ProVent 14 score accurately identified patients receiving PMV with a high 1-year mortality risk. Further validation in a larger sample is required.

Chronic Critical Illness: The Limbo Between Life and Death

The entity of chronic critical illness (CCI) has shown a rise in the past decades for popularity and prevalence. CCI is loosely defined as the group of patients who require the intensive care setting for weeks to months; its hallmark is prolonged mechanical ventilation. The outcomes of chronically critically ill patients have been dismal and have not improved over time; 1-year survival hovers at approximately 50%. Given the high mortality, prognostic variables are important when making medical decisions. CCI encompasses a syndrome that includes altered pathophysiology across a variety of organ systems. Another crucial element of CCI is the symptom burden that patients experience which include feelings of dyspnea, difficulty communicating and pain. This patient population necessitates the combined efforts of multiple care teams and the early integration of palliative and critical care. Future directions need to include improving the symptom management and communication for patients with CCI.

How Long Does (S)He Have? Retrospective Analysis of Outcomes After Palliative Extubation in Elderly, Chronically Critically Ill Patients

OBJECTIVE

For chronically critically ill elderly patients on mechanical ventilation, prognosis for significant recovery may be minimal. These individuals, or their surrogates, may decide for "palliative extubation." A common prognostic question arises: "How long does she/he have?" This study describes demographics, mortality, time to death, and factors associated with death after palliative extubation.

DESIGN, SETTING, AND PATIENTS

Retrospective 3-year study in community hospital with ethnically diverse elderly population. Chronically critically ill patients followed from palliative extubation to death or survival to discharge.

MEASURES

Mortality/survival following palliative extubation, time to death or discharge, factors associated with death.

RESULTS

Hundred and forty-eight subjects underwent palliative extubation. Mean age: 78 years, 60% female, ethnically diverse with 46% white, and 54% others. Top diagnostic categories: sepsis (47%) and respiratory failure (22%). After extubation, 114 patients (77%) died in hospital and 34 (23%) were discharged. Of those who died, median time to death 8.9 hours (range, 4 min to 7 d). Mortality proportion was 56% at 24 hours and increased with time. Factors associated with early death: Systolic blood pressure less than 90 (p = 0.002) and Charlson Comorbidity Index that is above 6 or 0 (p = 0.002).

CONCLUSIONS

Palliative extubation at end of life was an option selected by an ethnically diverse elderly population. Approximately three-fourths of subjects died in hospital, and one-fourth was discharged alive. Over 50% who died did so within 24 hours, making this useful information for counseling and anticipatory planning. Subjects with systolic blood pressure less than 90 and Charlson Comorbidity Index that is very low or very high had higher mortality.

Predicting Performance Status 1 Year After Critical Illness in Patients 80 Years or Older: Development of a Multivariable Clinical Prediction Model

OBJECTIVE

We sought to develop and internally validate a clinical prediction model to estimate the outcome of very elderly patients 12 months after being admitted to the ICU.

DESIGN

Prospective, longitudinal cohort study.

SETTING

Twenty-two Canadian ICUs.

PATIENTS

We recruited 527 patients 80 years or older who had a medical or urgent surgical diagnosis and were admitted to an ICU for at least 24 hours.

MEASUREMENTS AND MAIN RESULTS

At baseline, we completed a comprehensive geriatric assessment of enrolled patients; survival and functional status was determined 12 months later. We defined recovery from critical illness as Palliative Performance Scale score of greater than or equal to 60. We used logistic regression analysis to examine factors associated with this outcome. Of the 434 patients (82%) whose Palliative Performance Scale was known at 12 months, 50% had died and 29% (126/434) had a score of greater than or equal to 60. In the multivariable model, we found that being married, having a primary diagnosis of emergency coronary artery bypass grafting or valve replacement, and higher baseline Palliative Performance Scale were independently predictive of a 12-month Palliative Performance Scale score of greater than or equal to 60. Male sex, primary diagnosis of stroke, and higher Acute Physiology and Chronic Health Evaluation II score, Charlson comorbidity index, or clinical frailty scale were independently predictive of Palliative Performance Scale score of less than 60.

CONCLUSION

Approximately one-quarter of very old ICU patients achieve a reasonable level of function 1 year after admission. This prediction model applied to individual patients may be helpful in decision making about the utility of life support for very elderly patients who are admitted to the ICU.

Prognostic Factors for Long-Term Mortality in Critically Ill Patients Treated With Prolonged Mechanical Ventilation: A Systematic Review

OBJECTIVES

Long-term survival for patients treated with prolonged mechanical ventilation is generally poor; however, patient-level factors associated with long-term mortality are unclear. Our objective was to systematically review the biomedical literature and synthesize data for prognostic factors that predict long-term mortality in prolonged mechanical ventilation patients.

DATA SOURCES

We searched PubMed, CINAHL, and Cochrane Library from 1988 to 2015 for studies on prolonged mechanical ventilation utilizing a comprehensive strategy without language restriction.

STUDY SELECTION

We included studies of adults 1) receiving mechanical ventilation for more than or equal to 14 days, 2) admitted to a ventilator weaning unit, or 3) received a tracheostomy for acute respiratory failure. We analyzed articles that used a multivariate analysis to identify patient-level factors associated with long-term mortality (≥ 6 mo from when the patient met criteria for receiving prolonged mechanical ventilation).

DATA EXTRACTION

We used a standardized data collection tool and assessed study quality with a customized Newcastle-Ottawa Scale. We abstracted the strength of association between each prognostic factor and long-term mortality. Individual prognostic factors were then designated as strong, moderate, weak, or inconclusive based on an a priori previously published schema.

DATA SYNTHESIS

A total of 7,411 articles underwent relevance screening; 419 underwent full article review. We identified 14 articles that contained a multivariate analysis. We abstracted 19 patient-level factors that showed association with long-term mortality. Six factors demonstrated strong strength of evidence for association with the primary outcome: age, vasopressor requirement, thrombocytopenia, preexisting kidney disease, failed ventilator liberation, and acute kidney injury ± hemodialysis requirement. All factors, except preexisting kidney disease and failed ventilator liberation, were measured at the time the patients met criteria for prolonged mechanical ventilation.

CONCLUSIONS

Despite the magnitude of the public health challenge posed by the prolonged mechanical ventilation population, only 14 articles in the biomedical literature have tested patient-level factors associated with long-term mortality. Further research is needed to inform optimal patient selection for prolonged mechanical ventilation.

Can body mass index predict clinical outcomes for patients with acute lung injury/acute respiratory distress syndrome? A meta-analysis

BACKGROUND

The effects of body mass index (BMI) on the prognosis of acute respiratory distress syndrome (ARDS) are controversial. We aimed to further determine the relationship between BMI and the acute outcomes of patients with ARDS.

METHODS

We searched the Pubmed, Embase, Medline, Cochrane Central Register of Controlled Trials (CENTRAL), and ISI Web of Science for trials published between 1946 and July 2016, using "BMI" or "body mass index" or "overweight" or "obese" and "ARDS" or "ALI" or "acute respiratory distress syndrome" or "acute lung injury", without limitations on publication type or language. Heterogeneity and sensitivity analyses were conducted, and a random-effects model was applied to calculate the odds ratio (OR) or mean difference (MD). Review Manager (RevMan) was used to test the hypothesis using the Mann-Whitney U test. The primary outcome was unadjusted mortality, and secondary outcomes included mechanical ventilation (MV)-free days and length of stay (LOS) in the intensive care unit (ICU) and in hospital.

RESULTS

Five trials with a total of 6268 patients were pooled in our final analysis. There was statistical heterogeneity between normal-weight and overweight patients in LOS in the ICU (I ² = 71%, χ ² = 10.27, P = 0.02) and in MV-free days (I ² = 89%, χ ² = 18.45, P < 0.0001). Compared with normal weight, being underweight was associated with higher mortality (OR 1.59, 95% confidence interval (CI) 1.22, 2.08, P = 0.0006), while obesity and morbid obesity were more likely to result in lower mortality (OR 0.68, 95% CI 0.57, 0.80, P < 0.00001; OR 0.72, 95% CI 0.56, 0.93, P = 0.01). MV-free days were much longer in patients with morbid obesity (MD 2.64, 95% CI 0.60, 4.67, P = 0.01), but ICU and hospital LOS were not influenced by BMI. An important limitation of our analysis is the lack of adjustment for age, sex, illness severity, comorbid illness, and interaction of outcome parameters.

CONCLUSIONS

Obesity and morbid obesity are associated with lower mortality in patients with ARDS.

Differences between prolonged weaning patients from medical and surgical intensive care units

BACKGROUND

It is not clear whether patients entering a specialized, interdisciplinary weaning unit from surgical or medical intensive care units (ICU) distinguish substantially. The purpose of the present study was to assess differences in patients with prolonged weaning being referred from surgical and medical ICU.

METHODS

Data collected from April 2013 to April 2014 was conducted for retrospective analysis. Mortality rates, demographic data, clinical, and microbial differences in 150 patients with prolonged weaning were assessed (80 surgical and 70 medical).

RESULTS

Surgical ICU referrals tended to be older (70.7 ± 11.3 vs. 67.3 ± 12.3, P = 0.051) and had fewer underlying pulmonary diseases (45% vs. 60%, P = 0.067). Sodium values at the time of referral to the weaning unit were significantly higher in surgical (147.1 ± 9.6) vs. medical (141.3 ± 6.7 mmol/l) patients (P < 0.001). Each 10-unit increase in sodium at the time of referral to the weaning unit was associated with a 2.5-day (95% CI -0.4, 5.4; P = 0.09) prolongation of stay in the weaning unit. Although significant differences in microbiological agents from tracheal aspiration were seen, the infection rate on the weaning unit was similar in both groups. There was no difference in weaning unit mortality between surgical and medical ICU patients (18% vs. 23%; P = 0.41).

CONCLUSION

Few differences were found between patients being referred to a specialized weaning unit from surgical vs. medical ICUs. Besides differences in microbiological characteristics of tracheal secretions, there were also differences in sodium levels, which appear to influence on treatment duration.

Validation and Extension of the Prolonged Mechanical Ventilation Prognostic Model (ProVent) Score for Predicting 1-Year Mortality after Prolonged Mechanical Ventilation

RATIONALE

Prognostic models can inform management decisions for patients requiring prolonged mechanical ventilation. The Prolonged Mechanical Ventilation Prognostic model (ProVent) score was developed to predict 1-year mortality in these patients. External evaluation of such models is needed before they are adopted for routine use.

OBJECTIVES

The goal was to perform an independent external validation of the modified ProVent score and assess for spectrum extension at 14 days of mechanical ventilation.

METHODS

This was a retrospective cohort analysis of patients who received prolonged mechanical ventilation at the University of Iowa Hospitals. Patients who received 14 or more days of mechanical ventilation were identified from a database. Manual review of their medical records was performed to abstract relevant data including the four model variables at Days 14 and 21 of mechanical ventilation. Vital status at 1 year was checked in the medical records or the social security death index. Logistic regressions examined the associations between the different variables and mortality. Model performance at 14 to 20 days and 21+ days was assessed for discrimination by calculating the area under the receiver operating characteristic curve, and calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test.

MEASUREMENTS AND MAIN RESULTS

A total of 180 patients (21+ d) and 218 patients (14-20 d) were included. Overall, 75% were surgical patients. One-year mortality was 51% for 21+ days and 32% for 14 to 20 days of mechanical ventilation. Age greater than 65 years was the strongest predictor of mortality at 1 year in all cohorts. There was no significant difference between predicted and observed mortality rates for patients stratified by ProVent score. There was near-perfect specificity for mortality in the groups with higher ProVent scores. Areas under the curve were 0.69 and 0.75 for the 21+ days and the 14 to 20 days cohorts respectively. P values for the Hosmer-Lemeshow statistics were 0.24 for 21+ days and 0.22 for 14 to 20 days.

CONCLUSIONS

The modified ProVent model was accurate in our cohort. This supports its geographic and temporal generalizability. It can also accurately identify patients at risk of 1-year mortality at Day 14 of mechanical ventilation, but additional confirmation is required. Further studies should explore the implications of adopting the model into routine use.

Relationship Between ICU Length of Stay and Long-Term Mortality for Elderly ICU Survivors

OBJECTIVES

To evaluate the association between length of ICU stay and 1-year mortality for elderly patients who survived to hospital discharge in the United States.

DESIGN

Retrospective cohort study of a random sample of Medicare beneficiaries who survived to hospital discharge, with 1- and 3-year follow-up, stratified by the number of days of intensive care and with additional stratification based on receipt of mechanical ventilation.

INTERVENTIONS

None.

PATIENTS

The cohort included 34,696 Medicare beneficiaries older than 65 years who received intensive care and survived to hospital discharge in 2005.

MEASUREMENTS AND MAIN RESULTS

Among 34,696 patients who survived to hospital discharge, the mean ICU length of stay was 3.4 days (± 4.5 d). Patients (88.9%) were in the ICU for 1-6 days, representing 58.6% of ICU bed-days. Patients (1.3%) were in the ICU for 21 or more days, but these patients used 11.6% of bed-days. The percentage of mechanically ventilated patients increased with increasing length of stay (6.3% for 1-6 d in the ICU and 71.3% for ≥ 21 d). One-year mortality was 26.6%, ranging from 19.4% for patients in the ICU for 1 day, up to 57.8% for patients in the ICU for 21 or more days. For each day beyond 7 days in the ICU, there was an increased odds of death by 1 year of 1.04 (95% CI, 1.03-1.05) irrespective of the need for mechanical ventilation.

CONCLUSIONS

Increasing ICU length of stay is associated with higher 1-year mortality for both mechanically ventilated and non-mechanically ventilated patients. No specific cutoff was associated with a clear plateau or sharp increase in long-term risk.

The outcomes and prognostic factors of patients requiring prolonged mechanical ventilation

The aims of this study were to investigate the outcomes of patients requiring prolonged mechanical ventilation (PMV) and to identify risk factors associated with its mortality rate. All patients admitted to the respiratory care centre (RCC) who required PMV (the use of MV ≥21 days) between January 2006 and December 2014 were enrolled. A total of 1,821 patients were identified; their mean age was 69.8 ± 14.2 years, and 521 patients (28.6%) were aged >80 years. Upon RCC admission, the APACHE II scores were 16.5 ± 6.3, and 1,311 (72.0%) patients had at least one comorbidity. Pulmonary infection was the most common diagnosis (n = 770, 42.3%). A total of 320 patients died during hospitalization, and the in-hospital mortality rate was 17.6%. A multivariate stepwise logistic regression analysis indicated that patients were more likely to die if they who were >80 years of age, had lower albumin levels (<2 g/dl) and higher APACHE II scores (≥15), required haemodialysis, or had a comorbidity. In conclusion, the in-hospital mortality for patients requiring PMV in our study was 17%, and mortality was associated with disease severity, hypoalbuminaemia, haemodialysis, and an older age.

A clinical prediction tool for hospital mortality in critically ill elderly patients

BACKGROUND

Very elderly (80 years of age and above) critically ill patients admitted to medical intensive care units (ICUs) have a high incidence of mortality, prolonged hospital length of stay, and living in a dependent state should they survive.

OBJECTIVE

The objective was to develop a clinical prediction tool for hospital mortality to improve future end-of-life decision making for very elderly patients who are admitted to Canadian ICUs.

DESIGN

This was a prospective, multicenter cohort study.

SETTING

Data from 1033 very elderly medical patients admitted to 22 Canadian academic and nonacademic ICUs were analyzed.

INTERVENTIONS

A univariate analysis of selected predictors to ascertain prognostic power was performed, followed by multivariable logistic regression to derive the final prediction tool.

MAIN RESULTS

We included 1033 elderly patients in the analyses. Mean age was 84.6±3.5 years, 55% were male, mean Acute Physiology and Chronic Health Evaluation II score was 23.1±7.9, Sequential Organ Failure Assessment score was 5.3±3.4, median ICU length of stay was 4.1 (interquartile range, 6.2) days, median hospital length of stay was 16.2 (interquartile range, 25.0) days, and ICU mortality and all-cause hospital mortality were 27% and 41%, respectively. Important predictors of hospital mortality at the time of ICU admission include age (85-90 years of age had an odds ratio of hospital mortality of 1.63 [1.04-2.56]; >90 years of age had an odds ratio of hospital mortality of 2.64 [1.27-5.48]), serum creatinine (120-300 had an odds ratio of hospital mortality of 1.57 [1.01-2.44]; >300 had an odds ratio of hospital mortality of 5.29 [2.43-11.51]), Glasgow Coma Scale (13-14 had an odds ratio of hospital mortality of 2.09 [1.09-3.98]; 8-12 had an odds ratio of hospital mortality of 2.31 [1.34-3.97]; 4-7 had an odds ratio of hospital mortality of 5.75 [3.02-10.95]; 3 had an odds ratio of hospital mortality of 8.97 [3.70-21.74]), and serum pH (<7.15 had an odds ratio of hospital mortality of 2.44 [1.07-5.60]).

CONCLUSION

We identified high-risk characteristics for hospital mortality in the elderly population and developed a Risk Scale that may be used to inform discussions regarding goals of care in the future. Further study is warranted to validate the Risk Scale in other settings and evaluate its impact on clinical decision making.

Timing of onset and burden of persistent critical illness in Australia and New Zealand: a retrospective, population-based, observational study

BACKGROUND

Critical care physicians recognise persistent critical illness as a specific syndrome, yet few data exist for the timing of the transition from acute to persistent critical illness. Defining the onset of persistent critical illness as the time at which diagnosis and illness severity at intensive care unit (ICU) arrival no longer predict outcome better than do simple pre-ICU patient characteristics, we measured the timing of this onset at a population level in Australia and New Zealand, and the variation therein, and assessed the characteristics, burden of care, and hospital outcomes of patients with persistent critical illness.

METHODS

In this retrospective, population-based, observational study, we used data for ICU admission in Australia and New Zealand from the Australian and New Zealand Intensive Care Society Adult Patient Database. We included all patients older than 16 years of age admitted to a participating ICU. We excluded patients transferred from another hospital and those admitted to an ICU for palliative care or awaiting organ donation. The primary outcome was in-hospital mortality. Using statistical methods in evenly split development and validation samples for risk score development, we examined the ability of characteristics to predict in-hospital mortality.

FINDINGS

Between Jan, 2000, and Dec, 2014, we studied 1 028 235 critically ill patients from 182 ICUs across Australia and New Zealand. Among patients still in an ICU, admission diagnosis and physiological derangements, which accurately predicted outcome on admission (area under the receiver operating characteristics curve 0·898 [95% CI 0·897-0·899] in the validation cohort), progressively lost their predictive ability and no longer predicted outcome more accurately than did simple antecedent patient characteristics (eg, age, sex, or chronic health status) after 10 days in the ICU, thus empirically defining the onset of persistent critical illness. This transition occurred between day 7 and day 22 across diagnosis-based subgroups and between day 6 and day 15 across risk-of-death-based subgroups. Cases of persistent critical illness accounted for only 51 509 (5·0%) of the 1 028 235 patients admitted to an ICU, but for 1 029 345 (32·8%) of 3 138 432 ICU bed-days and 2 197 108 (14·7%) of 14 961 693 hospital bed-days. Overall, 12 625 (24·5%) of 51 509 patients with persistent critical illness died and only 23 968 (46·5%) of 51 509 were discharged home.

INTERPRETATION

Onset of persistent critical illness can be empirically measured at a population level. Patients with this condition consume vast resources, have high mortality, have much less chance of returning home than do typical ICU patients, and require dedicated future research. ICU clinicians should be aware that the risk of in-hospital mortality can change quickly over the first 2 weeks of an ICU course and be sure to incorporate such changes in their decision making and prognostication.

FUNDING

None.

Clinical application of the ProVent score in Korean patients requiring prolonged mechanical ventilation: A 10-year experience in a university-affiliated tertiary hospital

PURPOSE

We evaluated the clinical usefulness of a prognostic scoring system ("the ProVent score") in Korean patients requiring prolonged mechanical ventilation.

MATERIAL AND METHODS

We retrospectively analyzed the data of 184 patients in a medical intensive care unit of a tertiary care hospital between January 2004 and December 2013.

RESULTS

The patients' median age was 65 years, and 66.8% were male. One-year mortality was 67.4%. On day 21 of mechanical ventilation, the ProVent score was 0 in 13 patients (7.1%), 1 in 39 patients (21.2%), 2 in 73 patients (39.7%), 3 in 42 patients (22.8%), and greater than or equal to 4 in 17 patients (9.2%). For patients with a ProVent score ranging from 0 to greater than or equal to 4, 1-year mortality was 46.2%, 53.8%, 68.5%, 76.2%, and 88.2%, respectively. The Kaplan-Meier curves of 1-year survival for each ProVent score showed statistically significant differences (log-rank test: P = .001). Logistic regression analysis showed that only thrombocytopenia was independently associated with 1-year mortality in our cohort (odds ratio = 4.786, P < .001).

CONCLUSIONS

In our study, the ProVent score could be applied to predict 1-year mortality for patients requiring prolonged mechanical ventilation in Korea. Among variables contributing to this score, only thrombocytopenia was an independent prognostic factor for 1-year mortality.

Development and Validation of a Mortality Prediction Model for Patients Receiving 14 Days of Mechanical Ventilation

OBJECTIVES

The existing risk prediction model for patients requiring prolonged mechanical ventilation is not applicable until after 21 days of mechanical ventilation. We sought to develop and validate a mortality prediction model for patients earlier in the ICU course using data from day 14 of mechanical ventilation.

DESIGN

Multicenter retrospective cohort study.

SETTING

Forty medical centers across the United States.

PATIENTS

Adult patients receiving at least 14 days of mechanical ventilation.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Predictor variables were measured on day 14 of mechanical ventilation in the development cohort and included in a logistic regression model with 1-year mortality as the outcome. Variables were sequentially eliminated to develop the ProVent 14 model. This model was then generated in the validation cohort. A simplified prognostic scoring rule (ProVent 14 Score) using categorical variables was created in the development cohort and then tested in the validation cohort. Model discrimination was assessed by the area under the receiver operator characteristic curve. Four hundred ninety-one patients and 245 patients were included in the development and validation cohorts, respectively. The most parsimonious model included age, platelet count, requirement for vasopressors, requirement for hemodialysis, and nontrauma admission. The area under the receiver operator characteristic curve for the ProVent 14 model using continuous variables was 0.80 (95% CI, 0.76-0.83) in the development cohort and 0.78 (95% CI, 0.72-0.83) in the validation cohort. The ProVent 14 Score categorized age at 50 and 65 years old and platelet count at 100×10(9)/L and had similar discrimination as the ProVent 14 model in both cohorts.

CONCLUSION

Using clinical variables available on day 14 of mechanical ventilation, the ProVent 14 model can identify patients receiving prolonged mechanical ventilation with a high risk of mortality within 1 year.

The Outcomes and Prognostic Factors of the Very Elderly Requiring Prolonged Mechanical Ventilation in a Single Respiratory Care Center

This study investigated the outcomes and the prognostic factors among the very elderly (patients ≥80 years old) requiring prolonged mechanical ventilation (PMV).Between 2006 and 2014, all of the very elderly patients of age 80 or more transferred to respiratory care center (RCC) of a tertiary medical center were retrospectively identified, and only patients who used mechanical ventilation (MV) for >3 weeks were included in this study.A total of 510 very elderly patients undergoing PMV were identified. The mean age of the patients was 84.3 ± 3.3 years, and it ranged from 80 to 96 years. Male comprised most of the patients (n = 269, 52.7%), and most of the patients were transferred to RCC from medical ICU (n = 357, 70.0%). The APACHE II scores on RCC admission was 17.6 ± 6.0. At least 1 comorbidity was found in 419 (82.2%) patients. No significant differences of gender, disease severity, diagnosis, dialysis, laboratory examinations, comorbidities, and outcome were found between octogenarians (aged 80-89) and nonagenarians (aged ≥ 90). The overall in-hospital mortality rate was 21.8%. In the multivariate analysis, patients who had APACHE II score ≥ 15(odds ratio [OR], 2.30, 95% confidence interval [CI], 1.36-3.90), or albumin ≤ 2 g/dL (OR, 3.92, 95% CI, 2.17-7.01) were more likely to have significant in-hospital mortality (P < 0.05).The in-hospital mortality rate of the very elderly PMV patients in our RCC is 21.8%, and poor outcomes in this specific population were found to be associated with a higher APACHE II score and lower albumin level.

Decision conflict and regret among surrogate decision makers in the medical intensive care unit

INTRODUCTION

Family members of critically ill patients in the intensive care unit face significant morbidity. It may be the decision-making process that plays a significant role in the psychological morbidity associated with being a surrogate in the ICU. We hypothesize that family members facing end-of-life decisions will have more decisional conflict and decisional regret than those facing non-end-of-life decisions.

METHODS

We enrolled a sample of adult patients and their surrogates in a tertiary care, academic medical intensive care unit. We queried the surrogates regarding decisions they had made on behalf of the patient and assessed decision conflict. We then contacted the family member again to assess decision regret.

RESULTS

Forty (95%) of 42 surrogates were able to identify at least 1 decision they had made on behalf of the patient. End-of-life decisions (defined as do not resuscitate [DNR]/do not intubate [DNI] or continuation of life support) accounted for 19 of 40 decisions (47.5%). Overall, the average Decision Conflict Scale (DCS) score was 21.9 of 100 (range 0-100, with 0 being little decisional conflict and 100 being great decisional conflict). The average DCS score for families facing end-of-life decisions was 25.5 compared with 18.7 for all other decisions. Those facing end-of-life decisions scored higher on the uncertainty subscale (subset of DCS questions that indicates level of certainty regarding decision) with a mean score of 43.4 compared with all other decisions with a mean score of 27.0. Overall, very few surrogates experienced decisional regret with an average DRS score of 13.4 of 100.

CONCLUSIONS

Nearly all surrogates enrolled were faced with decision-making responsibilities on behalf of his or her critically ill family member. In our small pilot study, we found more decisional conflict in those surrogates facing end-of-life decisions, specifically on the subset of questions dealing with uncertainty. Surrogates report low levels of decisional regret.

Chronic critical illness: the price of survival

BACKGROUND

The evolution of the techniques used in the intensive care setting over the past decades has led on one side to better survival rates in patients with acute conditions and severely impaired vital functions. On the other side, it has resulted in a growing number of patients who survive an acute event, but who then become dependent on one or more life support techniques. Such patients are called chronically critically ill patients.

MATERIALS & METHODS

No absolute definition of the disease is currently available, although most patients are characterized by the need for prolonged mechanical ventilation. Mortality rates are still high even after dismissal from intensive care unit (ICU) and transfer to specialized rehabilitation care settings.

RESULTS

In recent years, some studies have tried to clarify the pathophysiological characteristics underlying chronic critical illness (CCI), a disease that is also characterized by severe endocrine and inflammatory impairments, partly accounting for the almost constant set of symptoms.

DISCUSSION

Currently, no specific treatment is available. However, a strategic early therapeutic approach on ICU admission might try to prevent the progress of the acute disease towards chronic critical illness.