Prevalence and development of chronic critical illness in acute patients admitted to a respiratory intensive care setting

The obesity paradox and 90 day mortality in chronic critically ill patients: a cohort study using a large clinical database

BACKGROUND

This study investigates the obesity paradox, where obesity is linked to lower mortality in certain patient groups, focusing on its impact on long-term mortality in chronic critically ill (CCI) patients.

METHODS

We retrospectively analyzed CCI patients from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database's Intensive Care Unit, categorizing them into six groups based on Body Mass Index (BMI). Using stepwise multivariable Cox regression and restricted cubic spline models, we examined the association between BMI and 90 day mortality, accounting for confounding variables through subgroup analyses.

RESULTS

The study included 1996 CCI patients, revealing a 90 day mortality of 34.12%. Overweight and obese patients exhibited significantly lower mortality compared to normal-weight individuals. Adjusted analysis showed lower mortality risks in overweight and obese groups (HRs 0.60 to 0.72, p < 0.001). The cubic spline model indicated a negative correlation between BMI and 90 day mortality, with subgroup analyses highlighting interactions with age.

CONCLUSION

Our findings confirm the obesity paradox in CCI patients, especially among the elderly (65-85 years) and very elderly (≥ 85 years). The results suggest a beneficial association of higher BMI in older CCI patients, though caution is advised for those under 45.

Chronic critical illness in critically ill COVID-19 patients

OBJECTIVES

To evaluate the presence of chronic critical illness (CCI) in COVID-19 patients and compare clinical characteristics and prognosis of patients with and without CCI admitted to intensive care unit (ICU).

METHODS

It was a retrospective, observational study at a university hospital ICU. Patients were accepted as CCI if they had prolonged ICU stay (≥14 days) and got ≥1 score for cardiovascular sequential organ failure assessment (SOFA) score and ≥2 score in other parameters on day 14 of ICU admission which was described as persistent organ dysfunction.

RESULTS

131 of 397 (33%) patients met CCI criteria. CCI patients were older (p = 0.003) and frailer (p < 0.001). Their Acute Physiology and Chronic Health Evaluation (APACHE) II and SOFA scores were higher, PaO2/FiO2 ratio was lower (p < 0.001). Requirement of invasive mechanical ventilation (IMV), steroid use, and septic shock on admission were higher in the CCI group (p < 0.001). CCI patients had higher ICU and hospital mortality than other patients (54.2% vs. 19.9% and 55.7% vs. 22.6%, p < 0.001, respectively). Regression analysis revealed that IMV (OR: 8.40, [5.10-13.83], p < 0.001) and PaO2/FiO2 < 150 on admission (OR: 2.25, [1.36-3.71], p = 0.002) were independent predictors for CCI.

DISCUSSION

One-third of the COVID-19 patients admitted to the ICU were considered as CCI with significantly higher ICU and hospital mortality.

Immunometabolic features of natural killer cells are associated with infection outcomes in critical illness

Immunosuppression increases the risk of nosocomial infection in patients with chronic critical illness. This exploratory study aimed to determine the immunometabolic signature associated with nosocomial infection during chronic critical illness. We prospectively recruited patients who were admitted to the respiratory care center and who had received mechanical ventilator support for more than 10 days in the intensive care unit. The study subjects were followed for the occurrence of nosocomial infection until 6 weeks after admission, hospital discharge, or death. The cytokine levels in the plasma samples were measured. Single-cell immunometabolic regulome profiling by mass cytometry, which analyzed 16 metabolic regulators in 21 immune subsets, was performed to identify immunometabolic features associated with the risk of nosocomial infection. During the study period, 37 patients were enrolled, and 16 patients (43.2%) developed nosocomial infection. Unsupervised immunologic clustering using multidimensional scaling and logistic regression analyses revealed that expression of nuclear respiratory factor 1 (NRF1) and carnitine palmitoyltransferase 1a (CPT1a), key regulators of mitochondrial biogenesis and fatty acid transport, respectively, in natural killer (NK) cells was significantly associated with nosocomial infection. Downregulated NRF1 and upregulated CPT1a were found in all subsets of NK cells from patients who developed a nosocomial infection. The risk of nosocomial infection is significantly correlated with the predictive score developed by selecting NK cell-specific features using an elastic net algorithm. Findings were further examined in an independent cohort of COVID-19-infected patients, and the results confirm that COVID-19-related mortality is significantly associated with mitochondria biogenesis and fatty acid oxidation pathways in NK cells. In conclusion, this study uncovers that NK cell-specific immunometabolic features are significantly associated with the occurrence and fatal outcomes of infection in critically ill population, and provides mechanistic insights into NK cell-specific immunity against microbial invasion in critical illness.

Predictive value of arterial blood lactate to serum albumin ratio for in-hospital mortality of patients with community-acquired pneumonia admitted to the Intensive Care Unit

OBJECTIVE

To investigate the predictive value of the arterial blood lactate to serum albumin ratio (LAR) on in-hospital mortality of patients with community-acquired pneumonia (CAP) admitted to the Intensive Care Unit (ICU).

METHODS

Clinical datasets of 1720 CAP patients admitted to ICU from MIMIC-IV database were retrospectively analyzed. Patients were randomly assigned to the training cohort (n=1204) and the validation cohort (n=516) in a ratio of 7:3. X-tile software was used to find the optimal cut-off value for LAR. The receiver operating curve (ROC) analysis was conducted to compare the performance between LAR and other indicators. Univariate and multivariate Cox regression analyses were applied to select prognostic factors associated with in-hospital mortality. Based on the observed prognostic factors, a nomogram model was created in training cohort, and the validation cohort was utilized to further validate the nomogram.

RESULTS

The optimal cut-off value for LAR in CAP patients admitted to ICU was 1.6 (the units of lactate and albumin were, respectively, 'mmol/L' and 'g/dL'). The ROC analysis showed that the discrimination abilities of LAR were superior to other indicators except Sequential Organ Failure Assessment score and Simplified acute physiology score (SAPSII), which had the same abilities. Age, mean arterial pressure, SpO2, heart rate, SAPSII score, neutrophil-to-lymphocyte ratio, and LAR were found to be independent predictors of poor overall survival in the training cohort by multivariate Cox regression analysis and were incorporated into the nomogram for in-hospital mortality as independent factors. The nomogram model, exhibiting medium discrimination, had a C-index of 0.746 (95% CI = 0.715-0.777) in the training cohort and 0.716 (95% CI = 0.667-0.765) in the validation cohort.

CONCLUSION

LAR could predict in-hospital mortality of patients with CAP admitted to ICU independently as a readily accessible biomarker. The nomogram that included LAR with other independent factors performed well in predicting in-hospital mortality.

Analysis of the Effect of Emergency Ventilators on the Treatment of Critical Illness Based on Smart Medical Big Data

Respiratory failure refers to pulmonary ventilation and ventilatory dysfunction caused by various reasons, which makes the patient unable to maintain the gas exchange required for stillness and causes a series of pathophysiological changes and corresponding clinical manifestations. In order to solve the problem of respiratory failure in critically ill patients, it is of great significance to analyze the role of microprocessor-based emergency ventilator in the treatment of critically ill patients. This article aims to study the role of microprocessor-based emergency ventilator in the treatment of critically ill patients. This paper presents the key technology based on the ARM11 processor. A breathing motion model is detected and established through a ventilator. The research objects are mainly divided into group A and group B. By comparing the two groups of emergency ventilator ventilation, it can effectively prevent the increase in respiratory muscle fatigue, reduce oxygen consumption, improve the patient's ventilation function and oxygen balance, quickly correct hypoxia and carbon dioxide storage, cooperate with drug treatment, and quickly take out the ventilator after relief. Good treatment results were achieved. The results show that the emergency ventilator controlled by a microcomputer is effective. The total effective rate of the control group was 71.11%, which was significantly lower than that of the observation group (86.67%).

Ventilator-associated pneumonia in patients on prolonged mechanical ventilation: description, risk factors for mortality, and performance of the SOFA score

Objective:

Ventilator-associated pneumonia (VAP) is a serious complication of mechanical ventilation (MV). However, data on VAP in patients on prolonged MV (PMV) are scarce. We aimed to describe the characteristics of VAP patients on PMV and to identify factors associated with mortality.

Methods:

This was a retrospective cohort study including VAP patients on PMV. We recorded baseline characteristics, as well as 30-day and 90-day mortality rates. Variables associated with mortality were determined by Kaplan-Meier survival analysis and Cox regression model.

Results:

We identified 80 episodes of VAP in 62 subjects on PMV. The medians for age, Charlson Comorbidity Index, SOFA score, and days on MV were, respectively, 69.5 years, 5, 4, and 56 days. Episodes of VAP occurred between days 21 and 50 of MV in 28 patients (45.2%) and, by day 90 of MV, in 48 patients (77.4%). The 30-day and 90-day mortality rates were 30.0% and 63.7%, respectively. There were associations of 30-day mortality with the SOFA score (hazard ratio [HR] = 1.30; 95% CI: 1.12-1.52; p < 0.001) and use of vasoactive agents (HR = 4.0; 95% CI: 1.2-12.9; p = 0.02), whereas 90-day mortality was associated with age (HR = 1.03; 95% CI: 1.00-1.05; p = 0.003), SOFA score (HR = 1.20; 95% CI: 1.07-1.34; p = 0.001), use of vasoactive agents (HR = 4.07; 95% CI: 1.93-8.55; p < 0.001), and COPD (HR = 3.35; 95% CI: 1.71-6.60; p < 0.001).

Conclusions:

Mortality rates in VAP patients on PMV are considerably high. The onset of VAP can occur various days after MV initiation. The SOFA score is useful for predicting fatal outcomes. The factors associated with mortality could help guide therapeutic decisions and determine prognosis.

Adult Pulmonary Intensive and Intermediate Care Units: The Italian Thoracic Society (ITS-AIPO) Position Paper

The imbalance between the prevalence of patients with acute respiratory failure (ARF) and acute-on-chronic respiratory failure and the number of intensive care unit (ICU) beds requires new solutions. The increasing use of non-invasive respiratory tools to support patients at earlier stages of ARF and the increased expertise of non-ICU clinicians in other types of supportive care have led to the development of adult pulmonary intensive care units (PICUs) and pulmonary intermediate care units (PIMCUs). As in other European countries, Italian PICUs and PIMCUs provide an intermediate level of care as the setting designed for managing ARF patients without severe non-pulmonary dysfunction. The PICUs and PIMCUs may also act as step-down units for weaning patients from prolonged mechanical ventilation and for discharging patients still requiring ventilatory support at home. These units may play an important role in the on-going coronavirus disease 2019 pandemic. This position paper promoted by the Italian Thoracic Society (ITS-AIPO) describes the models, facilities, staff, equipment, and operating methods of PICUs and PIMCUs.

Cost of Chronic Critically Ill Patients to the Healthcare System: A Single-center Experience from a Developing Country

Background

An increasing number of patients become chronic critically ill (CCI) and dependent on long-term therapies in the intensive care unit (ICU). Mortality and healthcare costs increase in these patients. In order to deal with this problem, the magnitude and risk factors for CCI must first be determined. Therefore, we aimed at evaluating the incidence cost and risk factors for CCI in our ICU.

Materials and methods

This retrospective cohort study was compiled by recruiting patients admitted to our ICU between January 1, 2017, and December 31, 2018. Patients with an ICU stay of more than 21 days were defined as CCI. Patients who did not survive in the first 21 days were excluded from the study because it could be not known whether these patients would progress to CCI. During the study period, 1,166 patients were followed up, and 475 (40%) of them were excluded and 691 patients were included in the final analyses.

Results

During the study period, 691 patients were included in the study and 152 of them (22%) were CCI. Age, acute physiology and chronic health evaluation (APACHE)-2 score, length of stay, and daily costs were higher in patients with CCI. The cost for a patient with CCI is sixfold that of a patient without CCI. ICU mortality was 47% in patients without CCI and 54% in the CCI patients (p < 0.001).

Conclusion

CCI affects an increasing number of patients and leads to increased mortality rates and cost. Prolonged duration in ICU may cause complications such as secondary infections, sepsis episodes, and acute renal injury. The treatment of these complications may lead to increased mortality and cost.

How to cite this article

Yildirim S, Durmaz Y, Şan Y, Taşkiran İ, Cinleti BA, Kirakli C. Cost of Chronic Critically Ill Patients to the Healthcare System: A Single-center Experience from a Developing Country. Indian J Crit Care Med 2021;25(5):519–523.