A data-driven combined prediction method for the demand for intensive care unit healthcare resources in public health emergencies.

BACKGROUND: Public health emergencies are characterized by uncertainty, rapid transmission, a large number of cases, a high rate of critical illness, and a high case fatality rate. The intensive care unit (ICU) is the "last line of defense" for saving lives. And ICU resources play a critical role in the treatment of critical illness and combating public health emergencies. OBJECTIVE: This study estimates the demand for ICU healthcare resources based on an accurate prediction of the surge in the number of critically ill patients in the short term. The aim is to provide hospitals with a basis for scientific decision-making, to improve rescue efficiency, and to avoid excessive costs due to overly large resource reserves. METHODS: A demand forecasting method for ICU healthcare resources is proposed based on the number of current confirmed cases. The number of current confirmed cases is estimated using a bilateral long-short-term memory and genetic algorithm support vector regression (BILSTM-GASVR) combined prediction model. Based on this, this paper constructs demand forecasting models for ICU healthcare workers and healthcare material resources to more accurately understand the patterns of changes in the demand for ICU healthcare resources and more precisely meet the treatment needs of critically ill patients. RESULTS: Data on the number of COVID-19-infected cases in Shanghai between January 20, 2020, and September 24, 2022, is used to perform a numerical example analysis. Compared to individual prediction models (GASVR, LSTM, BILSTM and Informer), the combined prediction model BILSTM-GASVR produced results that are closer to the real values. The demand forecasting results for ICU healthcare resources showed that the first (ICU human resources) and third (medical equipment resources) categories did not require replenishment during the early stages but experienced a lag in replenishment when shortages occurred during the peak period. The second category (drug resources) is consumed rapidly in the early stages and required earlier replenishment, but replenishment is timelier compared to the first and third categories. However, replenishment is needed throughout the course of the epidemic. CONCLUSION: The first category of resources (human resources) requires long-term planning and the deployment of emergency expansion measures. The second category of resources (drugs) is suitable for the combination of dynamic physical reserves in healthcare institutions with the production capacity reserves of corporations. The third category of resources (medical equipment) is more dependent on the physical reserves in healthcare institutions, but care must be taken to strike a balance between normalcy and emergencies.

Multidrug-resistant pathogens and ventilator-associated pneumonia in critically ill COVID-19 and non-COVID-19 patients: a prospective observational monocentric comparative study.

BACKGROUND: The COVID-19 pandemic has increased the incidence of ventilator-associated pneumonia (VAP) among critically ill patients. However, a comparison of VAP incidence in COVID-19 and non-COVID-19 cohorts, particularly in a context with a high prevalence of multidrug-resistant (MDR) organisms, is lacking. MATERIAL AND METHODS: We conducted a single-center, mixed prospective and retrospective cohort study comparing COVID-19 patients admitted to the intensive care unit (ICU) of the "Città della Salute e della Scienza" University Hospital in Turin, Italy, between March 2020 and December 2021 (COVID-19 group), with a historical cohort of ICU patients admitted between June 2016 and March 2018 (NON-COVID-19 group). The primary objective was to define the incidence of VAP in both cohorts. Secondary objectives were to evaluate the microbial cause, resistance patters, risk factors and impact on 28 days, ICU and in-hospital mortality, duration of ICU stay, and duration of hospitalization). RESULTS: We found a significantly higher incidence of VAP (51.9% - n = 125) among the 241 COVID-19 patients compared to that observed (31.2% - n = 78) among the 252 NON-COVID-19 patients. The median SOFA score was significantly lower in the COVID-19 group (9, Interquartile range, IQR: 7-11 vs. 10, IQR: 8-13, p < 0.001). The COVID-19 group had a higher prevalence of Gram-positive bacteria-related VAP (30% vs. 9%, p < 0.001), but no significant difference was observed in the prevalence of difficult-to-treat (DTR) or MDR bacteria. ICU and in-hospital mortality in the COVID-19 and NON-COVID-19 groups were 71% and 74%, vs. 33% and 43%, respectively. The presence of COVID-19 was significantly associated with an increased risk of 28-day all-cause hospital mortality (Hazard ratio, HR: 7.95, 95% Confidence Intervals, 95% CI: 3.10-20.36, p < 0.001). Tracheostomy and a shorter duration of mechanical ventilation were protective against 28-day mortality, while dialysis and a high SOFA score were associated with a higher risk of 28-day mortality. CONCLUSION: COVID-19 patients with VAP appear to have a significantly higher ICU and in-hospital mortality risk regardless of the presence of MDR and DTR pathogens. Tracheostomy and a shorter duration of mechanical ventilation appear to be associated with better outcomes.

Association between body mass index and delirium incidence in critically ill patients: a retrospective cohort study based on the MIMIC-IV Database.

OBJECTIVES: Delirium is a form of brain dysfunction with high incidence and is associated with many negative outcomes in the intensive care unit. However, few studies have been large enough to reliably examine the associations between body mass index (BMI) and delirium, especially in critically ill patients. The objective of this study was to investigate the association between BMI and delirium incidence in critically ill patients. DESIGN: A retrospective cohort study. SETTING: Data were collected from the Medical Information Mart for Intensive Care-IV V2.0 Database consisting of critically ill participants between 2008 and 2019 at the Beth Israel Deaconess Medical Center in Boston. PARTICIPANTS: A total of 20 193 patients with BMI and delirium records were enrolled in this study and were divided into six groups. PRIMARY OUTCOME MEASURE: Delirium incidence. RESULTS: Generalised linear models and restricted cubic spline analysis were used to estimate the associations between BMI and delirium incidence. A total of 30.81% of the patients (6222 of 20 193) developed delirium in the total cohort. Compared with those in the healthy weight group, the patients in the different groups (underweight, overweight, obesity grade 1, obesity grade 2, obesity grade 3) had different relative risks (RRs): RR=1.10, 95% CI=1.02 to 1.19, p=0.011; RR=0.93, 95% CI=0.88 to 0.97, p=0.003; RR=0.88, 95% CI=0.83 to 0.94, p<0.001; RR=0.94, 95% CI=0.86 to 1.03, p=0.193; RR=1.14, 95% CI=1.03 to 1.25, p=0.010, respectively. For patients with or without adjustment variables, there was an obvious U-shaped relationship between BMI as a continuous variable and delirium incidence. CONCLUSION: BMI was associated with the incidence of delirium. Our results suggested that a BMI higher or lower than obesity grade 1 rather than the healthy weight in critically ill patients increases the risk of delirium incidence.

Prognostic Value of Leukocyte-Based Risk Model for Acute Kidney Injury Prediction in Critically Ill Acute Exacerbation of Chronic Obstructive Pulmonary Disease Patients.

Purpose: Acute kidney injury (AKI) is a common complication of acute exacerbation of chronic obstructive pulmonary disease (AECOPD), and inflammation is the potential link between AKI and AECOPD. However, little is known about the incidence and risk stratification of AKI in critically ill AECOPD patients. In this study, we aimed to establish risk model based on white blood cell (WBC)-related indicators to predict AKI in critically ill AECOPD patients. Material and Methods: For the training cohort, data were taken from the Medical Information Mart for eICU Collaborative Research Database (eICU-CRD) database, and for the validation cohort, data were taken from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. The study employed logistic regression analysis to identify the major predictors of WBC-related biomarkers on AKI prediction. Subsequently, a risk model was developed by multivariate logistic regression, utilizing the identified significant indicators. Results: Finally, 3551 patients were enrolled in training cohort, 926 patients were enrolled in validation cohort. AKI occurred in 1206 (33.4%) patients in training cohort and 521 (56.3%) patients in validation cohort. According to the multivariate logistic regression analysis, four WBC-related indicators were finally included in the novel risk model, and the risk model had a relatively good accuracy for AKI in the training set (C-index, 0.764, 95% CI 0.749-0.780) as well as in the validation set (C-index, 0.738, 95% CI: 0.706-0.770). Even after accounting for other models, the critically ill AECOPD patients in the high-risk group (risk score > 3.44) still showed an increased risk of AKI (odds ratio: 4.74, 95% CI: 4.07-5.54) compared to those in low-risk group (risk score ≤ 3.44). Moreover, the risk model showed outstanding calibration capability as well as therapeutic usefulness in both groups for AKI and ICU mortality and in-hospital mortality of critical ill AECOPD patients. Conclusion: The novel risk model showed good AKI prediction performance. This risk model has certain reference value for the risk stratification of AECOPD complicated with AKI in clinically.

[Predictive value of von Willebrand factor for venous thromboembolism in critically ill patients based on propensity score matching].

OBJECTIVE: To analyze the predictive value of von Willebrand factor (vWF) for venous thromboembolism (VTE) of patients in intensive care unit (ICU) by using propensity score matching (PSM). METHODS: Patients admitted to ICU of the Second Affiliated Hospital of Kunming Medical University from December 2020 to June 2022 who stayed in ICU for ≥72 hours and underwent daily bedside vascular ultrasound screening were included. Baseline data such as age, gender, primary disease, and chronic comorbidities were collected. Coagulation indexes before admission to ICU and 24 hours and 48 hours after ICU admission were collected, including prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), international normalized ratio (INR), fibrinogen (Fib), fibrin monomer (FM), vWF, D-dimer, antithrombin III (ATIII), etc. Patients were divided into VTE group and non-VTE group according to whether they had VTE or not [diagnosis of VTE: patients underwent daily ultrasound screening of bedside blood vessels (both upper and lower limbs, visceral veins), and those suspected of having thrombosis were confirmed by ultrasonographer or pulmonary angiography]. Using PSM analysis method, the VTE group was used as the benchmark to conduct 1 : 1 matching of age, whether there was malignant tumor, whether there was infection, whether there was diabetes, and coagulation indicators before admission to ICU. Finally, the cases with balanced covariates between the two groups were obtained. The risk factors of VTE were analyzed by multivariate Logistic regression analysis. Receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of vWF in the occurrence of VTE in critically ill patients. RESULTS: A total of 120 patients were enrolled, of which 18 (15.0%) were diagnosed with VTE within 72 hours after admission to ICU, and 102 (85.0%) were not found to have thrombus in ICU. Before PSM, there were significant differences in age, gender, proportion of malignant tumor and infection, and coagulation indexes between VTE group and non-VTE group. After PSM, 14 pairs were successfully matched, and the unbalanced covariables between the two groups reached equilibrium. Multivariate Logistic regression analysis showed that vWF was an independent risk factor for VTE at 48 hours after ICU admission in critically ill patients [odds ratio (OR) = 1.165, 95% confidence interval (95%CI) was 1.000-1.025, P = 0.004]. ROC curve analysis showed that the area under the ROC curve (AUC) of vWF at 48 hours after ICU admission for predicting VTE was 0.782, 95%CI was 0.618-0.945, P = 0.007. When the optimal cut-off value was 312.12%, the sensitivity was 67.7% and the specificity was 93.0. CONCLUSIONS: Dynamic monitoring of vWF is helpful to predict the occurrence of VTE in ICU patients, and vWF at 48 hours after ICU admission has certain value in predicting the occurrence of VTE.

Coexistence of a fluid responsive state and venous congestion signals in critically ill patients: a multicenter observational proof-of-concept study.

BACKGROUND: Current recommendations support guiding fluid resuscitation through the assessment of fluid responsiveness. Recently, the concept of fluid tolerance and the prevention of venous congestion (VC) have emerged as relevant aspects to be considered to avoid potentially deleterious side effects of fluid resuscitation. However, there is paucity of data on the relationship of fluid responsiveness and VC. This study aims to compare the prevalence of venous congestion in fluid responsive and fluid unresponsive critically ill patients after intensive care (ICU) admission. METHODS: Multicenter, prospective cross-sectional observational study conducted in three medical-surgical ICUs in Chile. Consecutive mechanically ventilated patients that required vasopressors and admitted < 24 h to ICU were included between November 2022 and June 2023. Patients were assessed simultaneously for fluid responsiveness and VC at a single timepoint. Fluid responsiveness status, VC signals such as central venous pressure, estimation of left ventricular filling pressures, lung, and abdominal ultrasound congestion indexes and relevant clinical data were collected. RESULTS: Ninety patients were included. Median age was 63 [45-71] years old, and median SOFA score was 9 [7-11]. Thirty-eight percent of the patients were fluid responsive (FR+), while 62% were fluid unresponsive (FR-). The most prevalent diagnosis was sepsis (41%) followed by respiratory failure (22%). The prevalence of at least one VC signal was not significantly different between FR+ and FR- groups (53% vs. 57%, p = 0.69), as well as the proportion of patients with 2 or 3 VC signals (15% vs. 21%, p = 0.4). We found no association between fluid balance, CRT status, or diagnostic group and the presence of VC signals. CONCLUSIONS: Venous congestion signals were prevalent in both fluid responsive and unresponsive critically ill patients. The presence of venous congestion was not associated with fluid balance or diagnostic group. Further studies should assess the clinical relevance of these results and their potential impact on resuscitation and monitoring practices.

Depressive symptoms over time among survivors after critical illness: A systematic review and meta-analysis.

OBJECTIVE: Critical illness survivors frequently experience various degrees of depressive symptoms, which hinder their recovery and return to daily life. However, substantial variability in the prevalence of depressive symptoms has been reported among critical illness survivors. The exact prevalence remains uncertain. METHODS: A systematic search was performed in PubMed, Embase, CINAHL, and PsycINFO from inception to August 2023 for observational studies that reported depressive symptoms in adult critical illness survivors. The random-effects model was used to estimate the prevalence of depressive symptoms. Subgroup analysis and meta-regression were conducted to explore potential moderators of heterogeneity. Study quality was evaluated using the Joanna Briggs Institute's tool and the GRADE approach. RESULTS: Fifty-two studies with 24,849 participants met the inclusion criteria. Overall prevalence estimate of depressive symptoms was 21.1% (95% CI, 18.3-24.1%). The prevalence of depressive symptoms remains stable over time. Point prevalence estimates were 21.3% (95% CI, 9.9-35.4%), 19.9% (95% CI, 14.6-25.9%), 18.5% (95% CI, 9.6-29.2%), 21.0% (95% CI, 16.8-25.5%), and 22.6% (95% CI, 14.4-31.8%) at <3, 3, 6, 12, and > 12 months after discharge from intensive care unit (ICU), respectively. CONCLUSIONS: Depressive symptoms may impact 1 in 5 adult critically ill patients within 1 year or more following ICU discharge. An influx of rehabilitation service demand is expected, and risk stratification to make optimal clinical decisions is essential. More importantly, to propose measures for the prevention and improvement of depressive symptoms in patients after critical care, given the continuous, dynamic management of ICU patients, including ICU stay, transition to general wards, and post-hospital.

Risk factors for prolonged mechanical ventilation in critically ill patients with influenza-related acute respiratory distress syndrome.

BACKGROUND: Patients with influenza-related acute respiratory distress syndrome (ARDS) are critically ill and require mechanical ventilation (MV) support. Prolonged mechanical ventilation (PMV) is often seen in these cases and the optimal management strategy is not established. This study aimed to investigate risk factors for PMV and factors related to weaning failure in these patients. METHODS: This retrospective cohort study was conducted by eight medical centers in Taiwan. All patients in the intensive care unit with virology-proven influenza-related ARDS requiring invasive MV from January 1 to March 31, 2016, were included. Demographic data, critical illness data and clinical outcomes were collected and analyzed. PMV is defined as mechanical ventilation use for more than 21 days. RESULTS: There were 263 patients with influenza-related ARDS requiring invasive MV enrolled during the study period. Seventy-eight patients had PMV. The final weaning rate was 68.8% during 60 days of observation. The mortality rate in PMV group was 39.7%. Risk factors for PMV were body mass index (BMI) > 25 (kg/m2) [odds ratio (OR) 2.087; 95% confidence interval (CI) 1.006-4.329], extracorporeal membrane oxygenation (ECMO) use (OR 6.181; 95% CI 2.338-16.336), combined bacterial pneumonia (OR 4.115; 95% CI 2.002-8.456) and neuromuscular blockade use over 48 h (OR 2.8; 95% CI 1.334-5.879). In addition, risk factors for weaning failure in PMV patients were ECMO (OR 5.05; 95% CI 1.75-14.58) use and bacteremia (OR 3.91; 95% CI 1.20-12.69). CONCLUSIONS: Patients with influenza-related ARDS and PMV have a high mortality rate. Risk factors for PMV include BMI > 25, ECMO use, combined bacterial pneumonia and neuromuscular blockade use over 48 h. In addition, ECMO use and bacteremia predict unsuccessful weaning in PMV patients.

SNARE-ing the Reason for Post-Cardiac Surgery Critical Illness-Related Corticosteroid Insufficiency.

Critical illness-related corticosteroid insufficiency (CIRCI) can cause hemodynamic instability in neonates after congenital heart surgery with manifestations that increase morbidity and potential mortality. We retrospectively reviewed neonates who underwent cardiac surgery between August 2018 and July 2020 at a freestanding children's hospital, had next-generation sequencing performed, and had their cortisol levels drawn as standard clinical care after cardiac surgery. The groups were defined as CIRCI (with a cortisol level ≤ 4.5 mcg/dL) and non-CIRCI (level > 4.5 mcg/dL). The CIRCI group (n = 8) had a 100% incidence of heterozygous gene mutation on STX1A with splicing or loss of function, and this mutation was not found in the non-CIRCI group (n = 8). Additional gene mutations were found in the CIRCI group on RAB6A, ABCA3, SIDT2, and LILRB3, with no incidence in the non-CIRCI group. Three additional mutations were found across the CIRCI group in INPPL1 and FAM189A2 (both splicing and missense), with 12-25% of patients in the non-CIRCI group also displaying these mutations. Novel genetic abnormalities were seen in neonates with symptoms of CIRCI with potential cardiac implications from a gene mutation for STX1A. Compounding effects of additional gene mutations need to be confirmed and explored for potential predisposition to hemodynamic instability during times of stress.

Epidemiology and outcomes of early versus late septic acute kidney injury in critically ill patients: A retrospective cohort study.

BACKGROUND: It was recently proposed to distinguish early from late sepsis-associated acute kidney injury (SA-AKI). We aimed to determine the relative frequency of these entities in critically ill patients and to describe their characteristics and outcomes. METHODS: We included in this retrospective cohort study all adult patients admitted for sepsis in a tertiary ICU between 2010 and 2020. We excluded those on chronic dialysis or without consent. We extracted serum creatinine, hourly urinary output, and clinical and socio-demographic data from medical records until day 7 or ICU discharge. AKI presence and characteristics were assessed daily using KDIGO criteria. We compared patients with early (occurring within 2 days of admission) or late (occurring between day 2 and day 7) SA-AKI. We conducted sensitivity analyses using different definitions for early/late SA-AKI. RESULTS: Among 1835 patients, 1660 (90%) fulfilled SA-AKI criteria. Of those, 1610 (97%) had early SA-AKI, and 50 (3%) had late SA-AKI. Similar proportions were observed when only considering AKI with elevated sCr (71% vs. 3%), severe AKI (67% vs. 6%), or different time windows for early SA-AKI. Compared with early SA-AKI patients, those with late SA-AKI were younger (median age [IQR] 59 [49-70] vs. 69 [58-76] years, p < 0.001), had lower Charlson comorbidity index (3 [1-5] vs. 5 [3-7], p < 0.001) and lower SAPSII scores (41 [34-50] vs. 53 [43-64], p < 0.001). They had similar (24% vs. 26%, p = 0.75) in-hospital mortality. CONCLUSIONS: AKI is almost ubiquitous in septic critically ill patients and present within two days of admission. The timing from ICU admission might not be relevant to distinguish different phenotypes of SA-AKI. ETHICS APPROVAL: Ethics Committee Vaud, Lausanne, Switzerland (n°2017-00008).

Endotoxemia Correlates with Kidney Function and Length of Stay in Critically Ill Patients.

INTRODUCTION: Endotoxin is a key driver of sepsis, which frequently causes acute kidney injury (AKI). However, endotoxins may also be found in non-bacteremic critically ill patients, likely from intestinal translocation. Preclinical models show that endotoxins can directly injure the kidneys, and in COVID-19 patients, endotoxemia correlated with AKI. We sought to determine correlations between endotoxemia and kidney and hospital outcomes in a broad group of critically ill patients. METHODS: In this single-center, serial prospective study, 124 predominantly Caucasian adult patients were recruited within 48 h of admission to Stony Brook University Hospital Intensive Care Unit (ICU). Demographics, vital signs, laboratory data, and outcomes were collected. Circulating endotoxin was measured on days 1, 4, and 8 using the endotoxin activity assay (EAA). The association of EAA with outcomes was examined with EAA: (1) categorized as <0.6, ≥0.6, and nonresponders (NRs); and (2) used as a continuous variable. RESULTS: Patients with EAA ≥0.6 had a higher prevalence of proteinuria, and lower arterial oxygen saturation (SaO2) to fraction of inspired oxygen (FiO2) (SaO2/FiO2) ratio versus patients with EAA <0.6. EAA levels positively correlated with serum creatinine (sCr) levels on day 1. Patients whose EAA level stayed ≥0.6 had a slower decline in sCr compared to those whose EAA started at ≥0.6 and subsequently declined. Patients with AKI stage 1 and EAA ≥0.6 on day 1 showed slower decline in sCr compared to patients with stage 1 AKI and EAA <0.6. EAA ≥0.6 and NR patients had longer hospital stay and delayed ICU discharge versus EAA <0.6. CONCLUSIONS: High EAA levels correlated with worse kidney function and outcomes. Patients whose EAA levels fell, and those with AKI stage I and day 1 EAA <0.6 recovered more quickly compared to those with EAA ≥0.6, suggesting that removal of circulating endotoxins may be beneficial in critically ill patients.

In-hospital catatonia, delirium, and coma and mortality: Results from the delirium and catatonia prospective cohort investigation.

BACKGROUND: Catatonia, a form of acute brain dysfunction typically linked with severe affective and psychotic disorders, occurs in critical illness with delirium and coma. Delirium and coma are associated with mortality, though catatonia's relationship with mortality is unclear. We aim to describe whether catatonia, delirium, and coma are associated with mortality. METHODS: We enrolled a convenience cohort of critically ill adults (N = 378) at an academic medical center. We assessed catatonia, delirium, and coma using the Bush-Francis Catatonia Rating Scale, the Confusion Assessment Method for the Intensive Care Unit and the Richmond Agitation-Sedation Scale, respectively. We tested the associations between previous day brain dysfunction state occurrence with in-hospital and one-year mortality using multivariable time-dependent risk models. Additionally, we tested the association between brain dysfunction duration and one-year mortality. RESULTS: Catatonia was not associated with death on the day after diagnosis during hospitalization, and neither previous catatonia occurrence nor duration was associated with one-year mortality. Delirium was not associated with death on any day following diagnosis during hospitalization, and neither previous delirium occurrence nor duration was associated with one-year mortality. The occurrence of coma was associated with death on any day after diagnosis during hospitalization (HR 2.30,CI 1.19-4.44,p = 0.014), as well as through one year following hospital discharge (HR 1.68,CI 1.09-2.59,p = 0.02). CONCLUSIONS: Coma, but neither catatonia nor delirium, was associated with future day in-hospital and one-year mortality. More research is needed to understand catatonia's clinical impact. Delirium results differ from existing literature likely due to cohort demographics and size. Coma results highlight the prognostic significance of suppressed arousal while critically ill.

Family burden after critical illness: the forgotten caregivers.

OBJECTIVE: To determine the incidence of primary caregiver burden in a cohort of family members of critically ill patients admitted to ICU and to identify risk factors related to its development in both the patient and the family member. DESIGN: Prospective observational cohort study was conducted for 24 months. SETTING: Hospital Universitario Clínico San Cecilio, Granada. PATIENTS: The sample was the primary caregivers of all patients with risk factors for development of PICS (Post-Intensive Care Syndrome). INTERVENTIONS: The follow-up protocol consisted of evaluation 3 months after discharge from the ICU in a specific consultation. MAIN VARIABLES OF INTEREST: The scales used in patients were Barthel, SF-12, HADS, Pfeiffer, IES-6 and in relatives the Apgar and Zarit. RESULTS: A total of 93 patients and caregivers were included in the follow-up. 15 relatives did not complete the follow-up questionnaires and were excluded from the study. The incidence of PICS-F (Family Post Intensive Care Syndrome) defined by the presence of primary caregiver burden in our cohort of patients is 34.6% (n=27), 95% CI 25.0-45.7. The risk factors for the development of caregiver burden are the presence of physical impairment, anxiety or post-traumatic stress in the patient, with no relationship found with the characteristics studied in the family member. CONCLUSIONS: One out of 3 relatives of patients with risk factors for the development of PICS presents at 3 months caregiver burden. This is related to factors dependent on the patient's state of health.

Epidemiology and outcomes of previously healthy critically ill patients with COVID-19: A population-based cohort.

Comorbid conditions represent a major risk for severe illness among persons with COVID-19. Previously healthy people with COVID-19 can also develop severe illness, but are expected to have better outcomes than those with comorbid conditions. Nevertheless, recent data suggest that the former may have, counterintuitively, higher risk of death among those with non-COVID sepsis. However, the epidemiology and outcomes of previously healthy people among critically ill patients with COVID-19 are unknown. We used statewide data to identify intensive care unit (ICU) admissions aged ≥18 years in Texas with COVID-19 in 2020. Multilevel logistic regression was used to estimate the association of comorbid state with short-term mortality (defined as in-hospital mortality or discharge to hospice) overall and with higher illness severity among ICU admissions. Among 52,776 ICU admissions with COVID-19, 6373 (12.1%) were previously healthy. Short-term mortality among previously healthy ICU admissions and those with comorbidities was 16.9% versus 34.6%. On adjusted analyses, the odds of short-term mortality were lower among the previously healthy compared to those with comorbidities overall (adjusted odds ratio (aOR) 0.84 (95% CI: 0.73-0.98)), but did not differ among those with ≥3 organ dysfunctions (aOR 1.11 (95% CI: 0.84-1.46)) and the mechanically ventilated (aOR 0.87 (95% CI: 0.68-1.12)), while being higher among those with do-not-resuscitate status (aOR 1.40 (95% CI: 1.04-1.89)). Over one in eight ICU admissions with COVID-19 were previously healthy. Although being previously healthy was associated with lower risk of death compared to those with comorbidities overall, it had no prognostic advantage among the more severely ill.

National ICU Registries as Enablers of Clinical Research and Quality Improvement.

OBJECTIVES: Clinical quality registries (CQRs) have been implemented worldwide by several medical specialties aiming to generate a better characterization of epidemiology, treatments, and outcomes of patients. National ICU registries were created almost 3 decades ago to improve the understanding of case-mix, resource use, and outcomes of critically ill patients. This narrative review describes the challenges, proposed solutions, and evidence generated by National ICU registries as facilitators for research and quality improvement. DATA SOURCES: English language articles were identified in PubMed using phrases related to ICU registries, CQRs, outcomes, and case-mix. STUDY SELECTION: Original research, review articles, letters, and commentaries, were considered. DATA EXTRACTION: Data from relevant literature were identified, reviewed, and integrated into a concise narrative review. DATA SYNTHESIS: CQRs have been implemented worldwide by several medical specialties aiming to generate a better characterization of epidemiology, treatments, and outcomes of patients. National ICU registries were created almost 3 decades ago to improve the understanding of case-mix, resource use, and outcomes of critically ill patients. The initial experience in European countries and in Oceania ensured that through locally generated data, ICUs could assess their performances by using risk-adjusted measures and compare their results through fair and validated benchmarking metrics with other ICUs contributing to the CQR. The accomplishment of these initiatives, coupled with the increasing adoption of information technology, resulted in a broad geographic expansion of CQRs as well as their use in quality improvement studies, clinical trials as well as international comparisons, and benchmarking for ICUs. CONCLUSIONS: ICU registries have provided increased knowledge of case-mix and outcomes of ICU patients based on real-world data and contributed to improve care delivery through quality improvement initiatives and trials. Recent increases in adoption of new technologies (i.e., cloud-based structures, artificial intelligence, machine learning) will ensure a broader and better use of data for epidemiology, healthcare policies, quality improvement, and clinical trials.

Critical illness among patients experiencing homelessness: a retrospective cohort study.

PURPOSE: To understand the epidemiology and healthcare use of critically ill patients experiencing homelessness compared to critically ill patients with stable housing. METHODS: This retrospective population-based cohort study included adults admitted to any ICU in Alberta, Canada, for a 3-year period. Administrative and clinical data from the hospital, ICU and emergency department were used to examine healthcare resource use (processes of care, ICU and hospital length of stay, hospital readmission and emergency room visits). Regression was used to quantify differences in healthcare use by housing status. RESULTS: 2.3% (n = 1086) of patients admitted to the ICU were experiencing homelessness; these patients were younger, more commonly admitted for medical reasons and had fewer comorbidities compared to those with stable housing. Processes of care in the ICU were mostly similar, but healthcare use after ICU was different; patients experiencing homelessness who survived their index hospitalization were more than twice as likely to have a visit to the emergency department (OR = 2.3 times, 95% CI 2.0-2.6, < 0.001) or be readmitted to hospital (OR = 2.1, 95% CI 1.8-2.4, p < 0.001) within 30 days, and stayed 10.1 days longer in hospital (95% CI 8.6-11.6, p < 0.001), compared with those who have stable housing. CONCLUSIONS: Patients experiencing homelessness have different characteristics at ICU admission and have similar processes of care in ICU, but their subsequent use of healthcare resources was higher than patients with stable housing. These findings can inform strategies to prepare patients experiencing homelessness for discharge from the ICU to reduce healthcare resource use after critical illness.

Incidence and risk factors of pressure injuries in critically ill patients with COVID-19.

OBJECTIVE: to analyze pressure injury (PI) incidence and risk factors in patients with COVID-19 admitted to an Intensive Care Unit and characterize the identified PIs. METHOD: a retrospective cohort study, consisting of 668 patients, carried out between March 2020 and February 2021. Clinical/demographic and PI variables were collected from medical records and electronic database. Data were analyzed using descriptive and inferential statistics. Logistic regression was performed to analyze risk factors for PI. RESULTS: PI incidence was 30.2% (n=202), with the majority located in the sacral region (52.9%) and in stage 1 (39%). Risk factors were age (p<0.001), Diabetes Mellitus (p=0.005), length of stay (p<0.001), immunosuppression (p=0.034), nutritional risk (p=0.015) and mechanical ventilation (p<0.001). CONCLUSION: PI incidence in critically ill patients with COVID-19 was high.

Research Priorities in Critical Care Cardiology: JACC Expert Panel.

Over the last several decades, the cardiac intensive care unit (CICU) has seen a substantial evolution in the patient population, comorbidities, and diagnoses. However, the generation of high-quality evidence to manage these complex and critically ill patients has been slow. Given the scarcity of clinical trials focused on critical care cardiology (CCC), CICU clinicians are often left to extrapolate from studies that either exclude or poorly represent the patient population admitted to CICUs. The lack of high-quality evidence and limited guidance from society guidelines has led to significant variation in practice patterns for many of the most common CICU diagnoses. Several barriers, both common to critical care research and unique to CCC, have impeded progress. In this multinational perspective, we describe key areas of priority for CCC research, current challenges for investigation in the CICU, and essential elements of a path forward for the field.

Do critical illness survivors with multimorbidity need a different model of care?

There is currently a lack of evidence on the optimal strategy to support patient recovery after critical illness. Previous research has largely focussed on rehabilitation interventions which aimed to address physical, psychological, and cognitive functional sequelae, the majority of which have failed to demonstrate benefit for the selected outcomes in clinical trials. It is increasingly recognised that a person's existing health status, and in particular multimorbidity (usually defined as two or more medical conditions) and frailty, are strongly associated with their long-term outcomes after critical illness. Recent evidence indicates the existence of a distinct subgroup of critical illness survivors with multimorbidity and high healthcare utilisation, whose prior health trajectory is a better predictor of long-term outcomes than the severity of their acute illness. This review examines the complex relationships between multimorbidity and patient outcomes after critical illness, which are likely mediated by a range of factors including the number, severity, and modifiability of a person's medical conditions, as well as related factors including treatment burden, functional status, healthcare delivery, and social support. We explore potential strategies to optimise patient recovery after critical illness in the presence of multimorbidity. A comprehensive and individualized approach is likely necessary including close coordination among healthcare providers, medication reconciliation and management, and addressing the physical, psychological, and social aspects of recovery. Providing patient-centred care that proactively identifies critical illness survivors with multimorbidity and accounts for their unique challenges and needs is likely crucial to facilitate recovery and improve outcomes.