Elderly Intensive Care Unit Patients Research Articles

Short-term mortality among very elderly cancer patients in the intensive care unit: A retrospective cohort study based on the Medical Information Mart for Intensive Care IV database.

The objective of this study is to examine the epidemiological characteristics of very elderly patients (aged over 80 years) with cancer admitted to the intensive care unit (ICU), and to elucidate the association between Acute Physiology Score III (APS-III) and 28-day mortality. A retrospective analysis was conducted using data extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Patients aged 80 years and above were assigned to three groups: non-cancer group, non-metastatic cancer group, and metastatic cancer group, based on their cancer diagnosis and its extent, Kaplan-Meier curves were constructed among these patient groups. Furthermore, patients were divided into a survival group and a non-survival group based on their 28-day survival status after ICU admission. Univariate and multivariate logistic regression analyses were performed to detect the risk factors for 28-day mortality among these patients. Additionally, this investigation sought to establish a dose-response relationship by exploring the graded association between APS-III scores and the 28-day mortalities among patients diagnosed with cancer. A total of 42,037 medical records were screened, from which 11,461 elderly patients aged over 80 years were included, comprising 1020 (8.90%) with non-metastatic cancer, 537 (4.68%) with metastatic cancer, and 9904 (86.41%) without cancer. Significant differences in 28-day mortality were observed between both the non-metastatic and metastatic cancer groups compared to the non-cancer group (20.98% and 22.35% vs. 15.75%, p < 0.001). However, no statistically significant difference was detected in the 28-day mortality rate when comparing the non-metastatic cancer group directly with the metastatic cancer group (20.98% vs. 22.35%, p = 0.576). Univariate analysis revealed significant differences (p < 0.001) in age, gender, BMI, aCCI excluding cancer point, ventilation, presence of cancer, and status of metastatic cancer between the survival and non-survival groups. In the multivariate logistic regression, the odds ratio (OR) for ventilation was found to be 2.154 (95% CI: 1.799-2.578), cancer conferred an OR of 1.499 (95% CI: 1.137-1.975), metastatic cancer showed an OR of 1.171 (95% CI: 0.745-1.841), APS-III showed an OR of 1.038 (95% CI: 1.034-1.042). A dose-response relationship was observed, demonstrating that when the APS-III score exceeded 80 points, the 28-day mortality rate surpassed 50% among the very elderly cancer patients in ICU. More than one-tenth of critically ill very elderly patients admitted to the ICU are diagnosed with cancer. Among ICU patients, those with cancer face a short-term mortality risk approximately 1.5 times higher than those without a cancer diagnosis. Interestingly, while our findings do not indicate an escalated mortality risk due to metastasis within the cancer patient cohort, the presence of cancer itself remains a significant factor influencing ICU mortality rates in this very elderly population.

Machine learning for the prediction of delirium in elderly intensive care unit patients

Machine learning for the prediction of delirium in elderly intensive care unit patients

Interpretable machine learning models for predicting the incidence of antibiotic- associated diarrhea in elderly ICU patients

BackgroundAntibiotic-associated diarrhea (AAD) can prolong hospitalization, increase medical costs, and even lead to higher mortality rates. Therefore, it is essential to predict the incidence of AAD in elderly intensive care unit(ICU) patients. The objective of this study was to create a prediction model that is both interpretable and generalizable for predicting the incidence of AAD in elderly ICU patients.MethodsWe retrospectively analyzed data from the First Medical Center of the People’s Liberation Army General Hospital (PLAGH) in China. We utilized the machine learning model Extreme Gradient Boosting (XGBoost) and Shapley’s additive interpretation method to predict the incidence of AAD in elderly ICU patients in an interpretable manner.ResultsA total of 848 adult ICU patients were eligible for this study. The XGBoost model predicted the incidence of AAD with an area under the receiver operating characteristic curve (ROC) of 0.917, sensitivity of 0.889, specificity of 0.806, accuracy of 0.870, and an F1 score of 0.780. The XGBoost model outperformed the other models, including logistic regression, support vector machine (AUC = 0.809), K-nearest neighbor algorithm (AUC = 0.872), and plain Bayes (AUC = 0.774).ConclusionsWhile the XGBoost model may not excel in absolute performance, it demonstrates superior predictive capabilities compared to other models in forecasting the incidence of AAD in elderly ICU patients categorized based on their characteristics.

Effect of a fall within three months of admission on delirium in critically Ill elderly patients: a population-based cohort study

BackgroundDelirium is common among elderly patients in the intensive care unit (ICU) and is associated with prolonged hospitalization, increased healthcare costs, and increased risk of death. Understanding the potential risk factors and early prevention of delirium is critical to facilitate timely intervention that may reverse or mitigate the harmful consequences of delirium.AimTo clarify the effects of pre-admission falls on ICU outcomes, primarily delirium, and secondarily pressure injuries and urinary tract infections. MethodsThe study relied on data sourced from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Statistical tests (Wilcoxon rank-sum or chi-squared) compared cohort characteristics. Logistic regression was employed to investigate the association between a history of falls and delirium, as well as secondary outcomes, while Kaplan–Meier survival curves were used to assess short-term survival in delirium and non-delirium patients.ResultsStudy encompassed 22,547 participants. Delirium incidence was 40%, significantly higher in patients with a history of falls (54.4% vs. 34.5%, p < 0.001). Logistic regression, controlling for confounders, not only confirmed that a history of falls elevates the odds of delirium (OR: 2.11; 95% CI: 1.97–2.26; p < 0.001) but also showed it increases the incidence of urinary tract infections (OR:1.50; 95% CI:1.40–1.62; p < 0.001) and pressure injuries (OR:1.36; 95% CI:1.26–1.47; p < 0.001). Elderly delirium patients exhibited lower 30-, 180-, and 360-day survival rates than non-delirium counterparts (all p < 0.001).ConclusionsThe study reveals that history of falls significantly heighten the risk of delirium and other adverse outcomes in elderly ICU patients, leading to decreased short-term survival rates. This emphasizes the critical need for early interventions and could inform future strategies to manage and prevent these conditions in ICU settings.

Nomogram predictive model for in-hospital mortality risk in elderly ICU patients with urosepsis

BackgroundUrinary tract infection (UTI) is a common cause of sepsis. Elderly patients with urosepsis in intensive care unit (ICU) have more severe conditions and higher mortality rates owing to factors such as advanced age, immunosenescence, and persistent host inflammatory responses. However, comprehensive studies on nomograms to predict the in-hospital mortality risk in elderly patients with urosepsis are lacking. This study aimed to construct a nomogram predictive model to accurately assess the prognosis of elderly patients with urosepsis and provide therapeutic recommendations.MethodsData of elderly patients with urosepsis were extracted from the Medical Information Mart for Intensive Care (MIMIC) IV 2.2 database. Patients were randomly divided into training and validation cohorts. A predictive nomogram model was constructed from the training set using logistic regression analysis, followed by internal validation and sensitivity analysis.ResultsThis study included 1,251 patients. LASSO regression analysis revealed that the Glasgow Coma Scale (GCS) score, red cell distribution width (RDW), white blood count (WBC), and invasive ventilation were independent risk factors identified from a total of 43 variables studied. We then created and verified a nomogram. The area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA) of the nomogram were superior to those of the traditional SAPS-II, APACHE-II, and SOFA scoring systems. The Hosmer-Lemeshow test results and calibration curves suggested good nomogram calibration. The IDI and NRI values showed that our nomogram scoring tool performed better than the other scoring systems. The DCA curves showed good clinical applicability of the nomogram.ConclusionsThe nomogram constructed in this study is a convenient tool for accurately predicting in-hospital mortality in elderly patients with urosepsis in ICU. Improving the treatment strategies for factors related to the model could improve the in-hospital survival rates of these patients.

Inflammaging in Multidrug-Resistant Sepsis of Geriatric ICU Patients and Healthcare Challenges.

Multidrug-resistant sepsis (MDR) is a pressing concern in intensive care unit (ICU) settings, specifically among geriatric patients who experience age-related immune system changes and comorbidities. The aim of this review is to explore the clinical impact of MDR sepsis in geriatric ICU patients and shed light on healthcare challenges associated with its management. We conducted a comprehensive literature search using the National Center for Biotechnology Information (NCBI) and Google Scholar search engines. Our search incorporated keywords such as "multidrug-resistant sepsis" OR "MDR sepsis", "geriatric ICU patients" OR "elderly ICU patients", and "complications", "healthcare burdens", "diagnostic challenges", and "healthcare challenges" associated with MDR sepsis in "ICU patients" and "geriatric/elderly ICU patients". This review explores the specific risk factors contributing to MDR sepsis, the complexities of diagnostic challenges, and the healthcare burden faced by elderly ICU patients. Notably, the elderly population bears a higher burden of MDR sepsis (57.5%), influenced by various factors, including comorbidities, immunosuppression, age-related immune changes, and resource-limited ICU settings. Furthermore, sepsis imposes a significant economic burden on healthcare systems, with annual costs exceeding $27 billion in the USA. These findings underscore the urgency of addressing MDR sepsis in geriatric ICU patients and the need for tailored interventions to improve outcomes and reduce healthcare costs.

Constructing a Nomogram Model to Estimate the Risk of Ventilator-Associated Pneumonia for Elderly Patients in the Intensive Care Unit.

Ventilator-associated pneumonia (VAP) causes heavy losses in terms of finances, hospitalization, and death for elderly patients in the intensive care unit (ICU); however, the risk is difficult to evaluate due to a lack of reliable assessment tools. We aimed to create and validate a nomogram to estimate VAP risk to provide early intervention for high-risk patients. Between January 2016 and March 2021, 293 patients from a tertiary hospital in China were retrospectively reviewed as a training set. Another 84 patients were enrolled for model validation from April 2021 to February 2022. Least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression analysis were employed to select predictors, and a nomogram model was constructed. The calibration, discrimination, and clinical utility of the nomogram were verified. Finally, a web-based online scoring system was created to make the model more practical. The predictors were hypoproteinemia, long-term combined antibiotic use, intubation time, length of mechanical ventilation, and tracheotomy/intubation. The area under the curve (AUC) was 0.937 and 0.925 in the training and validation dataset, respectively, suggesting the model exhibited effective discrimination. The calibration curve demonstrated high consistency with the observed result and the estimated values. Decision curve analysis (DCA) demonstrated that the nomogram was clinically applicable. We have created a novel nomogram model that can be utilized to anticipate VAP risk in elderly ICU patients, which is helpful for healthcare professionals to detect patients at high risk early and adopt protective interventions.

Risk factor analysis and nomogram development for predicting 28-day mortality in elderly ICU patients with sepsis and type 2 diabetes mellitus

Background: Type 2 diabetes mellitus (T2DM) significantly contributes to sepsis, with patients suffering from both conditions exhibiting greater severity and higher mortality rates compared to those with sepsis alone. Elderly individuals in the intensive care unit (ICU) are particularly prone to these comorbidities. A nomogram prediction model was developed to accurately assess prognosis and guide treatment for elderly patients with sepsis and T2DM. Methods: Data from 1489 patients with sepsis and T2DM in the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were analyzed and categorized into 28-days survival ( n = 1156) and 28-days death groups ( n = 333). The dataset’s clinical characteristics were employed to create a nomogram predicting 28-days mortality in elderly ICU patients with sepsis and T2DM. The least absolute shrinkage and selection operator (LASSO) regression identified candidate predictors, followed by a multivariate logistic regression analysis incorporating variables with p &lt; .05 into the final model. A nomogram was then constructed using these significant risk predictors. The model’s discriminatory power was evaluated through a receiver operating curve (ROC) and the area under the curve (AUC). Additionally, model performance was assessed using a calibration plot and the Hosmer-Lemeshow goodness-of-fit test (HL test), and clinical utility was examined via decision curve analysis (DCA). Results: Risk factors incorporated into the nomogram included age, ICU length of stay, mean blood pressure (MBP), metastatic solid tumor, Sequential Organ Failure Assessment (SOFA) score, Logistic Organ Dysfunction System (LODS) score, blood urea nitrogen (BUN), and vasopressor use. The predictive model demonstrated robust discrimination, with an AUC of 0.802 (95% CI 0.768–0.835) in the training dataset and 0.753 (95% CI 0.697–0.809) in the validation set. Calibration was confirmed with the HL test ( p &gt; .05), and DCA indicated clinical usefulness. Conclusion: This new nomogram serves as a practical tool for predicting 28-days mortality among elderly ICU patients with sepsis and T2DM. Optimizing treatment strategies based on this model could enhance 28-days survival rates for these patients.

Comparison of Ketamine to Haloperidol for Preventing Delirium in ICU Elderly Patients

Background: Delirium is a common concern among elderly intensive care unit (ICU) patients. Ketamine’s effectiveness in preventing delirium remains controversial despite its demonstrated neuroprotective properties and cognitive benefits in previous studies. Objectives: This study aimed to compare the safety and efficacy of ketamine and haloperidol in preventing delirium in elderly ICU patients. Methods: This randomized clinical trial involved 44 non-intubated patients aged over 65 years in a general ICU. The patients received low-dose intravenous ketamine (20 mg) or intramuscular haloperidol (2.5 mg). Delirium was assessed using the Richmond Agitation Sedation Scale (RASS) at 5, 10, and 15 minutes. The primary outcome was the percentage of patients achieving adequate sedation (RASS ≤ +1). The secondary outcome was time to reach adequate sedation. Adverse effects and physician satisfaction were evaluated after 60 minutes. Results: No significant difference in delirium was observed between the groups after interventions or within each group over time. However, the ketamine group had significantly lower delirium incidence at 5 minutes. The percentage of patients achieving adequate sedation was higher in the ketamine group (86.4%) than in the haloperidol group (36.4%) (P = 0.002). There was a delirium difference between groups at 10 minutes (P = 0.31) or 15 minutes (P = 0.082). Physician satisfaction did not differ significantly (P = 0.144). Conclusions: The present study suggests that the administration of low-dose ketamine to elderly ICU patients might reduce delirium incidence, supporting its beneficial effect for delirium control.

The association between Geriatric Nutritional Risk Index and the risk of Invasive Candidiasis in critically ill older adults

BackgroundInvasive candidiasis is the most common hospital-acquired fungal infection in intensive care units (ICU). The Geriatric Nutritional Risk Index (GNRI) score was developed to evaluate the nutritional status of elderly adults. We aimed to assess the association between the GNRI score and the risk of invasive candidiasis in elderly patients admitted to ICU.MethodsHospitalization information of elderly patients with invasive candidiasis was collected retrospectively from Medical Information Mart for Intensive Care (MIMIC) IV and MIMIC-III Clinical Database CareVue subset from 2001 to 2019. The main outcome of this study was the diagnosis of invasive candidiasis in patients. We employed a multivariable Cox regression and propensity score matching to balance the influence of confounding factors on the outcome. Furthermore, we conducted sensitivity analyses by categorizing the GNRI into classes based on thresholds of 98, 92, and 81.ResultsA total of 6739 patients were included in the study, among whom 134 individuals (2%) were diagnosed with invasive candidiasis. The GNRI scores of patients with invasive candidiasis upon admission to the ICU were significantly lower, measuring 88.67 [79.26–98.27], compared to the control group with a score of 99.36 [87.98-110.45] (P < 0.001). The results of the multivariable Cox regression analysis demonstrated a strong association between higher GNRI scores and a decreased risk of invasive candidiasis infection (HR: 0.98, 95% CI: 0.97–0.99, P = 0.002). Consistently, similar results were obtained when analyzing the propensity score-matched cohort (HR: 0.99, 95% CI: 0.98-1, P = 0.028). Sensitivity analyses further confirmed a significantly increased risk of invasive candidiasis infection with lower GNRI scores. Specifically, the following associations were observed: GNRI ≤ 98 (HR: 1.83, 95% CI: 1.23–2.72, P = 0.003), GNRI ≤ 92 (HR: 1.68, 95% CI: 1.17–2.4, P = 0.005), 82 ≤ GNRI ≤ 92 (HR: 1.63, 95% CI: 1.01–2.64, P = 0.046), GNRI ≤ 81 (HR: 2.31, 95% CI: 1.44–3.69, P < 0.001).ConclusionsLower GNRI score was significantly associated with an increased risk of invasive candidiasis in elderly patients in ICU. Further research is needed to validate whether improving nutrition can prevent invasive candidiasis.

Utilization of interpretable machine learning model to forecast the risk of major adverse kidney events in elderly patients in critical care

Major adverse kidney events within 30 d (MAKE30) implicates poor outcomes for elderly patients in the intensive care unit (ICU). This study aimed to predict the occurrence of MAKE30 in elderly ICU patients using machine learning. The study cohort comprised 2366 elderly ICU patients admitted to the Second Xiangya Hospital of Central South University between January 2020 and December 2021. Variables including demographic information, laboratory values, physiological parameters, and medical interventions were used to construct an extreme gradient boosting (XGBoost) -based prediction model. Out of the 2366 patients, 1656 were used for model derivation and 710 for testing. The incidence of MAKE30 was 13.8% in the derivation cohort and 13.2% in the test cohort. The average area under the receiver operating characteristic curve of the XGBoost model was 0.930 (95% CI: 0.912–0.946) in the training set and 0.851 (95% CI: 0.810–0.890) in the test set. The top 8 predictors of MAKE30 tentatively identified by the Shapley additive explanations method were Acute Physiology and Chronic Health Evaluation II score, serum creatinine, blood urea nitrogen, Simplified Acute Physiology Score II score, Sequential Organ Failure Assessment score, aspartate aminotransferase, arterial blood bicarbonate, and albumin. The XGBoost model accurately predicted the occurrence of MAKE30 in elderly ICU patients, and the findings of this study provide valuable information to clinicians for making informed clinical decisions.

Risk factors of aspiration occurrence with different feeding patterns in elderly intensive care unit patients: a cross-sectional study.

Elderly intensive care unit (ICU) patients represent a high-risk group of aspiration. Different feeding patterns will lead to different incidences of aspiration. However, there are few studies on the risk factors of aspiration in elderly ICU patients under different feeding patterns. The aim of this study was to analyze the effects of different eating styles on the occurrence of overt and silent aspiration in elderly ICU patients and to compare the independent risk factors, in order to provide a basis for targeted aspiration prevention. We retrospectively analyzed the incidence of aspiration in elderly patients admitted to the ICU from April 2019 to April 2022, a total of 348 cases. The patients were divided into the oral feeding group, gastric tube feeding group, and post-pyloric feeding group according to their feeding method. Multi-factor logistic regression was used to analyze the independent risk factors for overt and silent aspiration caused by the different eating patterns of patients. Among the 348 elderly ICU patients included, the overall incidence of aspiration was 72%, with a 22% rate of overt aspiration and a 49% rate of silent aspiration. The overt aspiration rates were 16%, 30%, and 21% in the oral, the gastric tube and the post-pyloric feeding group, respectively; while the silent aspiration rates were 52%, 55%, and 40% in the three groups, respectively. Multiple logistic regression analysis showed that the independent risk factors for both overt and silent aspiration were history of aspiration [odds ratio (OR) =0.075, P=0.004; OR =0.205, P=0.042] and gastrointestinal tumor (OR =0.100, P=0.028; OR =0.063, P=0.003) in the oral feeding group. In the gastric tube feeding group, the independent risk factor for both overt and silent aspiration was the history of aspiration (OR =4.038, P=0.040; OR =4.658, P=0.012). In the post-pyloric feeding group, the independent risk factors for both overt and silent aspiration were mechanical ventilation (OR =0.211, P=0.019; OR =0.336, P=0.037) and intra-abdominal hypertension (OR =0.225, P=0.020; OR =0.329, P=0.032). There were significant differences in the influencing factors and characteristics of aspiration among the elderly patients in the ICU with different feeding patterns. Personalized precautions should be implemented early, so as to reduce the possibility of aspiration.

Whole transcriptome analysis to explore the impaired immunological features in critically ill elderly patients with sepsis

BackgroundSepsis is a frequent complication in critically ill patients, is highly heterogeneous and is associated with high morbidity and mortality rates, especially in the elderly population. Utilizing RNA sequencing (RNA-Seq) to analyze biological pathways is widely used in clinical and molecular genetic studies, but studies in elderly patients with sepsis are still lacking. Hence, we investigated the mortality-relevant biological features and transcriptomic features in elderly patients who were admitted to the intensive care unit (ICU) for sepsis.MethodsWe enrolled 37 elderly patients with sepsis from the ICU at Taichung Veterans General Hospital. On day-1 and day-8, clinical and laboratory data, as well as blood samples, were collected for RNA-Seq analysis. We identified the dynamic transcriptome and enriched pathways of differentially expressed genes between day-8 and day-1 through DVID enrichment analysis and Gene Set Enrichment Analysis. Then, the diversity of the T cell repertoire was analyzed with MiXCR.ResultsOverall, 37 patients had sepsis, and responders and non-responders were grouped through principal component analysis. Significantly higher SOFA scores at day-7, longer ventilator days, ICU lengths of stay and hospital mortality were found in the non-responder group, than in the responder group. On day-8 in elderly ICU patients with sepsis, genes related to innate immunity and inflammation, such as ZDHCC19, ALOX15, FCER1A, HDC, PRSS33, and PCSK9, were upregulated. The differentially expressed genes (DEGs) were enriched in the regulation of transcription, adaptive immune response, immunoglobulin production, negative regulation of transcription, and immune response. Moreover, there was a higher diversity of T-cell receptors on day-8 in the responder group, than on day-1, indicating that they had better regulated recovery from sepsis compared with the non-response patients.ConclusionSepsis mortality and incidence were both high in elderly individuals. We identified mortality-relevant biological features and transcriptomic features with functional pathway and MiXCR analyses based on RNA-Seq data; and found that the responder group had upregulated innate immunity and increased T cell diversity; compared with the non-responder group. RNA-Seq may be able to offer additional complementary information for the accurate and early prediction of treatment outcome.

Postoperative delirium and its influencing factors in elderly patients with lung cancer in the intensive care unit.

In 2020, there were 2,206,771 new cases of lung cancer worldwide, ranking first in mortality rate postoperative delirium (POD) is a common surgical complication and typically occurs 1-3 days after surgery which leads to prolonged hospital stay. The currently available research on POD in elderly patients was mainly carried out in cardiac surgery, orthopedic, and gastroenterology departments. It is necessary to study the incidence and risk factors of delirium in intensive care unit (ICU) elderly patients after lung cancer surgery. This study is a single-center and singe-arm observational study which examined the incidence of and factors affecting POD in elderly patients with lung cancer in ICU at our center from September 2019 to May 2020. 22 relevant variables including arterial oxygen partial pressure, postoperative sedative drug use, and other data were collected. The Confusion Assessment Method of Intensive Care Unit was used to assess the occurrence of POD, the Chinese version of the Richards-Campbell Sleep Questionnaire was used to assess patients' postoperative sleep quality, and the Mini-Mental State Examination was used to assess patients' preoperative cognitive level. Univariate and multivariate logistic regression analyses were conducted to identify the factors affecting POD in elderly ICU patients with lung cancer. Among the 208 elderly ICU patients who underwent surgery for lung cancer, 32 (15.38%) had POD. The results showed that postoperative blood oxygen level, preoperative cognitive level score and postoperative sleep quality score in delirium group were significantly lower than those in non-delirium group (P values were 0.002, 0.000, 0.000, respectively). The proportion of previous coronary heart disease and postoperative sedation use in delirium group was significantly higher than that in non-delirium group (P=0.008 and 0.008, respectively). It was observed that the preoperative Mini-Mental State Examination (MMSE) score and postoperative Richards-Campbell Sleep Questionnaire (RCSQ) score of the delirium group were significantly lower than those of the non-delirium group, and this trend was still observed after adjusting for influencing factors. It is suggested that the difference of cognitive level in elderly lung cancer population has a significant effect on the occurrence of POD. In clinical work, we should pay more attention to patients with preoperative cognitive impairment, hypoxic state, and postoperative sleep disturbance.

Construction and Validation of a Predictive Model for the Risk of Ventilator-Associated Pneumonia in Elderly ICU Patients.

Ventilator-associated pneumonia (VAP) is among the most important hospital-acquired infections in an intensive-care unit setting. However, clinical practice lacks effective theoretical tools for preventing VAP in the elderly. To describe the independent factors associated with VAP in elderly intensive-care unit (ICU) patients on mechanical ventilation (MV) and to construct a risk prediction model. A total of 1851 elderly patients with MV in ICUs from January 2015 to September 2019 were selected from 12 tertiary hospitals. Study subjects were divided into a model group (n = 1219) and a validation group (n = 632). Two groups of patients were divided into a VAP group and a non-VAP group and compared. Univariate and logistic regression analyses were used to explore influencing factors for VAP in elderly ICU patients with MV, establish a risk prediction model, and draw a nomogram. We used the area under the receiver operating characteristic curve (AUROC) and the Hosmer-Lemeshow goodness-of-fit test to evaluate the predictive effect of the model. Findings regarding the length of ICU stay, surgery, C-reactive protein (CRP), and the number of reintubations were independent risk factors for VAP in elderly ICU patients with MV. Predictive-model verification results showed that the area under the curve (AUC) of VAP risk after MV in the modeling and verification groups was 0.859 and 0.813 (P < 0.001), respectively, while P values for the Hosmer-Lemeshow test in these two groups were 0.365 and 0.485, respectively. The model could effectively predict the occurrence of VAP in elderly patients with MV in ICUs. This study is a retrospective study, so it has not been registered as a clinical study.

Mortality Predictors in Elderly Intensive Care Unit Patients with Acute Kidney Injury Requiring Hemodialysis

Introduction: The incidence of acute kidney injury is increasing in the elderly. This condition is especially serious during the course of critical illness, and the rate of mortality rises with the condition’s increasing severity. We aimed to identify the risk factors for in-hospital, 28-day, and 90-day mortality among elderly patients admitted to the intensive care unit with acute kidney injury requiring dialysis. Materials and Method: We conducted a retrospective study between January 2011 and December 2019 of patients 65 years of age and older who were hospitalized with acute kidney injury requiring dialysis in the intensive care unit of an internal medicine department. Results: A total of 144 patients were evaluated, 63 male (43.75%) and 81 female (56.25%). The in-hospital, 28-day, and 90-day mortality rates were 40.9%, 47.2%, and 56.2%, respectively. Sepsis etiology was associated with poor prognosis. In univariate Cox regression analysis, we identified use of inotropes, final C-reactive protein, neutrophil to lymphocyte ratio as mortality predictors at all three time points. Use of inotropes, final C-reactive protein continued to be predictors of mortality in multivariate analysis. Age was not found to be a factor affecting mortality. Conclusions: Data are limited on the outcomes of elderly patients with acute kidney injury requiring dialysis, but routinely evaluated laboratory parameters in intensive care practice may be predictive of mortality. Our results provide deeper understanding of how these variables interact and contribute to the risk of mortality. Chronological age alone should not be a consideration for hemodialysis. Keywords: Aged; Critical Care; Hemodialysis; Acute Kidney Injury; Mortality.

558: RISK OF H2RA VERSUS PPI FOR DEVELOPING ICU DELIRIUM IN MECHANICALLY VENTILATED OLDER ADULTS

Introduction: Histamine 2-receptor antagonists (H2RA) and proton pump inhibitors (PPI), two acid suppressing drugs, are commonly prescribed for stress ulcer prophylaxis (SUP) in the intensive care unit (ICU). Although both exhibit equivalent effectiveness, recent data suggests a higher risk for ICU delirium with H2RA when compared to PPI. Methods: This was a single-center, retrospective, observational cohort. Mechanically ventilated ≥65 years old patients admitted to a Medical ICU between January 2020 and December 2021 were included if they received at least one dose of H2RA or PPI. Patients were excluded if they received both H2RA and PPI or had a positive Confusion Assessment Method (CAM-ICU) within 24 hours prior to the administration of the drug. Descriptive statistics were used for frequency, median, and mean. Associations between characteristics and the SUP were measured using chi-square, Fisher’s exact, and Wilcoxon rank-sum or t-test. The primary objective was to compare the rate of ICU delirium (≥1 day positive CAM-ICU) in mechanically ventilated older patients receiving H2RA vs. PPI for SUP. Secondary objectives were to compare the percentage of ICU days in delirium and compare the rate of ICU delirium stratified by age (65-75 years old and >75 years old). Results: We screened 236 patients and identified 60 patients for inclusion; 35.0% were female and 70.0% were 65 to 75 years old. Fifty-five percent of patients received H2RA and 45% received PPI. The incidence of delirium in groups was similar; 69.7% (23) for H2RA vs. 63.0% (17) for PPI (p=NS). The percentage of ICU days in delirium was also similar; 37.5% for H2RA vs. 28.2% for PPI (p=NS). Analysis stratified by age also did not show statistical differences between SUP therapies and incidence of delirium or percentage of ICU days in delirium. The relative risk in advanced elderly ICU patients was numerically higher with H2RA (28% greater risk in patients >75 years old vs. 2% greater risk in patients 65-75 years old). Conclusions: We found no association between choice of SUP and risk for ICU delirium development in mechanically ventilated older Medical ICU patients. Larger epidemiologic studies are needed to elucidate whether there is potentially a differential risk between H2RA and PPI in the advanced elderly population.

Characteristics and prognostic factors of very elderly patients admitted to the intensive care unit.

BackgroundKorea is rapidly becoming a super aging society and is facing the increased burden of critical care for the elderly people. Traditionally, far-advanced age has been regarded as a triage criterion for intensive care unit (ICU) admission. We evaluated how the characteristics and prognostic factors of very elderly patients (≥85 years) admitted to the ICU changed over the last decade.MethodsWe retrospectively evaluated the data of patients admitted to the ICU over 11 years (2007–2017). The clinical characteristics and outcomes of the very elderly-patients group were evaluated. Factors associated with mortality were assessed by a cox regression analysis. ResultsComparing the first half (2007–2012) and the second half (2013–2017) of the study period, the proportion of very elderly group increased from 603/47,657 (1.3%), to 697/37,756 (1.8%) (P<0.001). Among 1,294 very elderly patients, 1,274 patients were analyzed excluding hopeless discharge (n=20). The non-surgical reasons for ICU admission (67.0% vs. 76.1%, P<0.001) and the percentage of patients with co-morbidities (78.3% vs. 82.7%, P=0.048) were increased. Nevertheless, the hospital mortality decreased (21.3% vs. 14.9%, P=0.001). High creatinine levels, use of vasopressors and ventilator weaning failure were associated with in-hospital mortality.ConclusionsThe proportion of very elderly people in the ICU increased over the last decade. The non-surgical causes of ICU admission increased compared with the surgical causes. Despite an increasement in ICU admissions of very elderly patients, in-hospital mortality of very elderly ICU patients decreased.

Outcomes of prolonged mechanical ventilation and tracheostomy in critically ill elderly patients: a historical cohort study.

With an aging global population, the increased proportion of elderly patients in the intensive care unit (ICU) raises important questions regarding optimal management. Currently, data on tracheostomy and its outcomes in the elderly are limited. We aimed to determine the in-hospital survival of elderly ICU patients following tracheostomy, and describe impacts on discharge disposition and functional outcomes. We conducted a historical cohort study at two academic hospitals in Toronto. All patients aged ≥ 70 yr who received a tracheostomy during their ICU stay between January 2010 and June 2016 were included in a retrospective chart review. Data on patient demographics, frailty, tracheostomy indication, and outcomes were collected. The study included 270 patients with a mean (standard deviation) age of 81 (6) yr. The majority were admitted to ICU for respiratory failure (147/270, 54%) and received a tracheostomy for prolonged mechanical ventilation (202/270, 75%). Intensive care unit and hospital mortality were 26% (68/270) and 46% (125/270), respectively. Twenty-five percent (67/270) of patients were decannulated during hospital admission, a median [interquartile range (IQR)] of 41 [25-68] days after tracheostomy. Intensive care unit and hospital length of stay were 31 [17-53] and 81 [46-121] days, respectively. At hospital discharge, 6% (17/270) of patients were discharged home, all were frail (median Clinical Frailty Score of 7) and most were tube-fed (101/270, 70%), unable to speak (81/270, 56%), and nonambulatory (98/270, 68%). In patients aged ≥ 70 yr, tracheostomy during ICU stay marked a transition toward prolonged chronic critical illness. Nearly half of the patients died during the admission, and although a quarter were successfully decannulated, the majority of survivors were left with severe frailty and functional impairment.

Association between out-of-bed mobilization during the ICU stay of elderly patients and long-term autonomy: A cohort study.

Our objective was to estimate the impact of the absence of Out-of-Bed (OoB) mobilization during intensive care unit (ICU) stay among patients ≥70years on their long-term autonomy. We conducted an ancillary study of the multicenter FRAGIREA study, including patients aged over 70years, admitted to ICU for more than 48h. We excluded the patients who died before day 180, who were lost to follow-up, and for whom the baseline autonomy (ADL) score was not available. Patients were classified into the OoB or non-OoB-mobilization group, and the impact of OoB mobilization on the decreased 6-month autonomy was estimated. Among the 548 patients of the FRAGIREA cohort, 276 were included in the present study. Among them, 226 had OoB mobilization and 50 did not. 220/276 (80%) patients experienced the transfer to chair as rehabilitation therapy, passive mobilization and transfer to upright sitting were also frequently performed. A decrease in the 6-month autonomy was observed for 63 (23%) patients. After the elimination of potential confounders, non-OoB-mobilization patients had a greater risk of 6-month decreased autonomy (aOR 2.43 [1.18; 4.98]). Mobilization during the ICU stay of elderly ICU patient survivors was associated with a lower decreased autonomy at 6months.