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

Chronic critical illness after trauma injury: outcomes and experience in a trauma center

OBJECTIVE

To determine the prevalence, risk factors and functional results of chronic critical illness (CCI) in polytrauma patients.

DESIGN

Single-center observational retrospective study.

SETTING

ICU at a tertiary hospital in Santander, Spain, between 2015 and 2019.

PATIENTS

Adult trauma patients who survived beyond 48 h after injury. CCI was defined as the need for mechanical ventilation for at least 14 days or tracheostomy for difficult weaning.

MEASUREMENTS AND MAIN RESULTS

About 62/575 developed CCI. These patients were characterized by higher ISS score [17 (SD 10) vs. 13.8 (SD 8.2); p < 0.001] and higher NISS (26 (SD 11) vs. 19.2 (SD 10.5); p = 0.001). CCI group had greater proportion of hospital-acquired infections (100% vs. 18.1%; p < 0.001), and acute kidney failure (33.9% vs. 22.8% p < 0.001). During the first 24 h of admission, CCI group required in a greater proportion surgical intervention (50% vs. 29%; p = 0.001), and blood products (31.3% vs. 20.5%; p < 0.047). Hospital ward stay was longer in CCI patients [9.5 days (IQR 5-16.9) vs. 43.9 (IQR 30.3-53) p < 0.001]. The CCI mortality was higher (19.5% vs. 8.1%; p = 0.004). Surgical intervention in the first 24 h (OR 2.5 95% CI 1.1-4.1), age (> 55 years) (OR 2.1 95%CI 1.1-4.2), ISS score (OR 1.1 95%CI 1.02-1.3), GCS score (OR 0.8 95%CI 0.4-23.2) and multiple organ failure (OR 9.5 95%CI 3.9-23.2) were predictors of CCI in the multivariate analysis.

CONCLUSIONS

CCI after severe trauma appears in a considerable proportion of patients. Early identification and implementation of specific interventions could change the evolution of this process.

A Modified Physical Disability Screening Model after Treatment in the Intensive Care Unit: A Nationwide Derivation-Validation Study

BACKGROUND

Many of the survivors of critical illnesses in the intensive care unit (ICU) suffer from physical disability for months after the treatment in the ICU. Identifying patients who are susceptible to disability is essential. The purpose of the study was to modify a model for early in-ICU prediction of the patient's risk for physical disability two months after the treatment in the ICU.

METHODS

A prospective multicenter derivation-validation study was conducted from 1 July 2015, to 31 August 2016. We modified a model consisting of three risk factors in the derivation group and tested the modified model in the validation group. They were asked for their physical abilities before being admitted, two months after discharge from the ICU by a binary ADL staircases questionnaire. The univariate and multivariate logistic regression was used to modify physical disability components in the derivation data set. Receiver operating characteristic curves were used to determine the sensitivity and specificity of the threshold values in the validation group.

RESULTS

Five-hundred nineteen survivors were enrolled in the derivation group, and 271 in the validation. In multivariable analysis, the odds ratio (OR) of physical disability significantly increased with educational level ≤ elementary school (OR: 36.96, 95%CI: 18.14-75.29), inability to sit without support (OR: 15.16, 95%CI: 7.98-28.80), and having a fracture (OR: 12.74, 95%CI: 4.47-36.30). The multivariable validation model indicated that education level, inability to sit without support, and having a fracture simultaneously had sensitivity 71.3%, specificity 88.2%, LR+ 6.0, LR- 0.33, PPV 90.9, and NPV 64.9 to predict physical disability. Applying the coefficients derived from the multivariable logistic regression fitted on the derivation dataset in the validation dataset and computing diagnostic index sensitivity 100%, specificity 60.5%, LR+ 2.5, LR- 0.003, PPV 80.8, and NPV 100. The modified model had an excellent prediction ability for physical disability (AUC ± SE = 0.881 ± 0.016).

CONCLUSIONS

Low education level, inability to sit without support, and having a fracture in a modified model were associated with the development of physical disability after discharge from ICU. Therefore, these clinical variables should be considered when organizing follow-up care for ICU survivors.

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.

Insights into the challenges faced by chronically critically ill patients, their families and healthcare providers: An interpretive description

OBJECTIVE

To describe and understand the challenges of patients with chronic critical illness (CCI), their families and healthcare providers during the disease trajectory.

METHODOLOGY/DESIGN

This qualitative study follows Thorne's methodology of interpretive description and was guided by the ethnographic method of observation and participation. Five cases, each comprising one patient with chronic critical illness their family members and several healthcare providers, were followed from the intensive care unit of a university hospital in Switzerland across different settings. In total, five patients with chronic critical illness, 12 family members and 92 healthcare providers (nurses, nursing students, care assistants, physiotherapists and occupational therapists and physicians) were observed.

FINDINGS

Regardless of the medical diagnoses and disease trajectories of the patients with chronic critical illness, all cases faced three main challenges: 1. Dealing with the unpredictability of the disease trajectory beyond the underlying disease. 2. Coping with the complexity of care. 3. Perceiving communication challenges despite all involved parties' dependency on it.

CONCLUSION

Unpredictability is not only a unique characteristic of the prolonged disease trajectory of patients with chronic critical illness, but also one of the main challenges of the participants. Therefore, the way unpredictability is handled is dependent on changes in the complexity of care and communication, highlighting the need for participation, information, empathy, clarity and honesty among all participants.

Which criteria is a better predictor of ICU admission in trauma patients? An artificial neural network approach

PURPOSE

One of the most critical concerns in the intensive care unit (ICU) section is identifying the best criteria for entering patients to this part. This study aimed to predict the best compatible criteria for entering trauma patients in the ICU section.

METHOD

The present study was a historical cohort study. The data were collected from 2448 trauma patients referring to Shahid Rajaee Hospital between January 2015 and January 2017 in Shiraz, Iran. The artificial neural network (ANN) models with cross-validation and logistic regression (LR) with a backward method was used for data analysis. The final analysis was performed on a total of 958 patients who were transferred to the ICU section.

RESULTS

Based on the present results, the motor component of the GCS score at each cutoff point had the highest importance. The results also showed better performance for the AUC and accuracy rate for ANN compared with LR.

CONCLUSION

The most critical indicators in predicting the optimal use of ICU services in this study were the Motor component of the GCS. Results revealed that the ANN had a better performance than the LR in predicting the main outcomes of the traumatic patients in both the accuracy and AUC index. Trauma section surgeons and ICU specialists will benefit from this study's results and can assist them in making decisions to predict the patient outcomes before entering the ICU.

Long-term outcome of prolonged critical illness: A multicentered study in North Brisbane, Australia

Background

Although critical illness is usually of high acuity and short duration, some patients require prolonged management in intensive care units (ICU) and suffer long-term morbidity and mortality.

Objective

To describe the long-term survival and examine determinants of death among patients with prolonged ICU admission.

Methods

A retrospective cohort of adult Queensland residents admitted to ICUs for 14 days or longer in North Brisbane, Australia was assembled. Comorbid illnesses were classified using the Charlson definitions and all cause case fatality established using statewide vital statistics.

Results

During the study a total of 28,742 adult Queensland residents had first admissions to participating ICUs of which 1,157 (4.0%) had prolonged admissions for two weeks or longer. Patients with prolonged admissions included 645 (55.8%), 243 (21.0%), and 269 (23.3%) with ICU lengths of stay lasting 14–20, 21–27, and ≥28 days, respectively. Although the severity of illness at admission did not vary, pre-existing comorbid illnesses including myocardial infarction, congestive heart failure, kidney disease, and peptic ulcer disease were more frequent whereas cancer, cerebrovascular accidents, and plegia were less frequently observed among patients with increasing ICU lengths of stay lasting 14–20, 21–27, and ≥28 days. The ICU, hospital, 90-day, and one-year all cause case-fatality rates were 12.7%, 18.5%, 20.2%, and 24.9%, respectively, and were not different according to duration of ICU stay. The median duration of observation was 1,037 (interquartile range, 214–1888) days. Although comorbidity, age, and admitting diagnosis were significant, neither ICU duration of stay nor severity of illness at admission were associated with overall survival outcome in a multivariable Cox regression model.

Conclusions

Most patients with prolonged stays in our ICUs are alive at one year post-admission. Older age and previous comorbidities, but not severity of illness or duration of ICU stay, are associated with adverse long-term mortality outcome.

MR-proAdrenomedullin as a predictor of renal replacement therapy in a cohort of critically ill patients with COVID-19

BACKGROUND

About 20% of ICU patients with COVID-19 require renal replacement therapy (RRT). Mid-regional pro-adrenomedullin (MR-proADM) might be used for risk assessment. This study investigates MR-proADM for RRT prediction in ICU patients with COVID-19.

METHODS

We analysed data of consecutive patients with COVID-19, requiring ICU admission at a university hospital in Germany between March and September 2020. Clinical characteristics, details on AKI, and RRT were assessed. MR-proADM was measured on admission.

RESULTS

64 patients were included (49 (77%) males). Median age was 62.5y (54-73). 47 (73%) patients were ventilated and 50 (78%) needed vasopressors. 25 (39%) patients had severe ARDS, and 10 patients needed veno-venous extracorporeal membrane oxygenation. 29 (45%) patients required RRT; median time from admission to RRT start was 2 (1-9) days. MR-proADM on admission was higher in the RRT group (2.491 vs. 1.23 nmol/l; p = 0.002) and showed the highest correlation with renalSOFA. ROC curve analysis showed that MR-proADM predicts RRT with an AUC of 0.69 (95% CI: 0.543-0.828; p = 0.019). In multivariable logistic regression MR-proADM was an independent predictor (OR: 3.813, 95% CI 1.110-13.102, p<0.05) for RRT requirement.

CONCLUSION

AKI requiring RRT is frequent in ICU patients with COVID-19. MR-proADM on admission was able to predict RRT requirement, which may be of interest for risk stratification and management.

Comparing the performance of SOFA, TPA combined with SOFA and APACHE-II for predicting ICU mortality in critically ill surgical patients: A secondary analysis

INTRODUCTION

Total psoas muscle area (TPA) can indicate the status of the entire human body's skeletal muscle mass. It has been reported that lower TPA can increase the risk of mortality in critically ill patients. The aim of our study was to evaluate the relationship between TPA and ICU mortality and to compare the performance of Sequential Organ Failure Assessment (SOFA), TPA combined with SOFA and Acute Physiology, Chronic Health Evaluation (APACHE-II) for predicting ICU mortality in critically ill surgical patients.

METHODS

This study was a retrospective observational cohort study with a total of 96 critically ill surgical patients, ages 21-96 years old. Main outcome measures included difficult-to-wean (DTW), operation methods, ICU mortality, ICU stay, APACHE II, sepsis and SOFA. CT-scan assessed the TPA. It is acknowledged that the entire study was completed by Hao-Wei Kou et al. and the data were uploaded from plosone.com. The authors used this data only for secondary analysis.

RESULTS

The results showed that TPA is a protective factor for ICU mortality (OR: 0.99 95% [0.99, 1.00], P = 0.0269). In addition, when we defined sarcopenia-based TPA, our study showed that sarcopenia increased the risk of ICU mortality (OR:3.73 (1.27, 10.98) P = 0.0167. Furthermore, discrimination of ICU mortality was significantly higher using SOFA (AUROC, 0.7810 [99% CI, 0.6658-0.8962]) than either TPA (AUROC, 0.7023 [99% CI, 0.5552-0.8494]) or APACHE II score (AUROC, 0.7447 [99% CI, 0.6289-0.8604]). Additionally, when we combined TPA with SOFA score, the ROC of TPA + SOFA (AUROC, 0.8647 [99% CI, 0.7881-0.9412]) was the highest when compared to the other three models.

CONCLUSION

The relationship between TPA and ICU mortality is negative in critically ill surgical patients. In addition, the combination of TPA and SOFA was the best tool among the three scoring systems in providing significant discriminative ability when predicting ICU mortality in critically ill surgical patients.