Intensive Care Unit Resources Research Articles

What would have made work in the COVID-19 ICU less demanding? A qualitative study from 13 Swedish COVID-19 ICUs.

The COVID-19 pandemic stretched Swedish intensive care unit (ICU) resources to an extent never experienced before, but even before the pandemic staffing was difficult and the number of staffed ICU beds was low. Studies have revealed high levels of COVID-19 ICU staff burn-out and fatigue, and as similar situations with high demands are likely to occur in the future a better understanding of resources that improve staff resilience is important. Using the job-demand resource theory as a framework, we explored ICU professionals' views on demands and resources when working in COVID-19 ICUs with the aim to highlight factors that increased the job resources. Data were collected via a web survey distributed to COVID-19 ICU professionals, including both regular and temporary roles, working in 13 COVID-19 ICU wards in Stockholm and Sörmland counties during the spring 2021. A total of 251 written responses to the question "What would have made work in the COVID-19 ICU less demanding?" were analyzed using thematic analysis. One year later a member-checking focus group interview was conducted to validate and further explore staff experiences. The main themes were work strategy, fairness and support, continuity, accessible leadership, introduction/information, and crisis preparedness. The analysis of the focus group conducted confirmed the main results and the extreme demands on ICU staff during the initial stages of the pandemic. To increase staff health and performance in a long-term crisis our results suggest; maintaining workplace leadership, scheduling work in advance and, when possible, schedule for recovery.

Evaluation of score-based tertiary triage policies during the COVID-19 pandemic: simulation study with real-world intensive care data.

The explicit prohibition of discontinuing intensive care unit (ICU) treatment that has already begun by the newly established German Triage Act in favor of new patients with better prognoses (tertiary triage) under crisis conditions may prevent saving as many patients as possible and therefore may violate the international well-accepted premise of undertaking the "best for the most" patients. During the COVID-19 pandemic, authorities set up lockdown measures and infection-prevention strategies to avoid an overburdened health-care system. In cases of situational overload of ICU resources, when transporting options are exhausted, the question of atertiary triage of patients arises. We provide data-driven analyses of score- and non-score-based tertiary triage policies using simulation and real-world electronic health record data in aCOVID-19 setting. Ten different triage policies, for example, based on the Simplified Acute Physiology Score (SAPSII), are compared based on the resulting mortality in the ICU and inferential statistics. Our study shows that score-based tertiary triage policies outperform non-score-based tertiary triage policies including compliance with the German Triage Act. Based on our simulation model, aSAPSII score-based tertiary triage policy reduces mortality in the ICU by up to 18percentage points. The longer the queue of critical care patients waiting for ICU treatment and the larger the maximum number of patients subject to tertiary triage, the greater the effect on the reduction of mortality in the ICU. ASAPSII score-based tertiary triage policy was superior in our simulation model. Random allocation or "first come, first served" policies yield the lowest survival rates, as will adherence to the new German Triage Act. An interdisciplinary discussion including an ethical and legal perspective is important for the social interpretation of our data-driven results.

Asian Neonatal Network Collaboration (AsianNeo): a study protocol for international collaborative comparisons of health services and outcomes to improve quality of care for sick newborn infants in Asia – survey, cohort and quality improvement studies

IntroductionReducing neonatal deaths in premature infants in low- and middle-income countries is key to reducing global neonatal mortality. International neonatal networks, along with patient registries of premature infants, have contributed...

HPR98 Consumption of Hospital Resources in Intensive Care Units in Brazil: A Challenge for Health Financing

HPR98 Consumption of Hospital Resources in Intensive Care Units in Brazil: A Challenge for Health Financing

Hospital and regional variations in intensive care unit admission for patients with invasive mechanical ventilation

BackgroundPatients who receive invasive mechanical ventilation (IMV) in the intensive care unit (ICU) have exhibited lower in-hospital mortality rates than those who are treated outside. However, the patient-, hospital-, and regional factors influencing the ICU admission of patients with IMV have not been quantitatively examined.MethodsThis retrospective cohort study used data from the nationwide Japanese inpatient administrative database and medical facility statistics. We included patients aged ≥ 15 years who underwent IMV between April 2018 and March 2019. The primary outcome was ICU admission on the day of IMV initiation. Multilevel logistic regression analyses incorporating patient-, hospital-, or regional-level variables were used to assess cluster effects by calculating the intraclass correlation coefficient (ICC), median odds ratio (MOR), and proportional change in variance (PCV).ResultsAmong 83,346 eligible patients from 546 hospitals across 140 areas, 40.4% were treated in ICUs on their IMV start day. ICU admission rates varied widely between hospitals (median 0.7%, interquartile range 0–44.5%) and regions (median 28.7%, interquartile range 0.9–46.2%). Multilevel analyses revealed significant effects of hospital cluster (ICC 82.2% and MOR 41.4) and regional cluster (ICC 67.3% and MOR 12.0). Including patient-level variables did not change these ICCs and MORs, with a PCV of 2.3% and − 1.0%, respectively. Further adjustment for hospital- and regional-level variables decreased the ICC and MOR, with a PCV of 95.2% and 85.6%, respectively. Among the hospital- and regional-level variables, hospitals with ICU beds and regions with ICU beds had a statistically significant and strong association with ICU admission.ConclusionsOur results revealed that primarily hospital and regional factors, rather than patient-related ones, opposed ICU admissions for patients with IMV. This has important implications for healthcare policymakers planning interventions for optimal ICU resource allocation.

Critical care services in Bagmati province of Nepal: A cross sectional survey

Background This study aimed to assess the current status of critical care services in 13 districts of Bagmati Province in Nepal, with a focus on access, infrastructure, human resources, and intensive care unit (ICU) services. Methods A cross-sectional survey was conducted among healthcare workers employed in 87 hospitals having medical/surgical ICUs across Bagmati Province. Data were collected through structured questionnaires administered via face-to-face and telephone interviews. Descriptive analysis was used for data analysis, involving frequencies and percentages. Results From 87 hospitals, a total of 123 ICUs were identified in the province, providing 1167 beds and 615 functioning ventilators. The average ICU bed availability per 100,000 population was 19, ranging from 3.6 in Makwanpur to 33.9 in Kathmandu. Out of 13 districts, 95% of beds were concentrated in just four districts, while six had no ICU facilities. Of the available facilities, 69.9% were owned by private entities. One-to-one nurse-to-ventilated bed ratio was maintained by 63.4% of ICUs during daytime, and 62.6% at nighttime. Furthermore, 74.8% of ICUs had consultants trained in critical care medicine. While essential equipment availability was higher in Bagmati province, gaps existed in the availability of oxygen plants and isolation rooms. Similarly, many ICUs offered continuous medical education and cardiopulmonary resuscitation (CPR) training, but improvements were necessary in clinical audits, antibiotic stewardship programs, and research engagement. Conclusions Disparities in critical care resources were evident across districts in Bagmati Province, highlighting the need for a balanced and decentralized approach to ensure equitable access to care. Although there were disparities, numerous ICUs were effectively carrying out multiple critical care procedures. This study suggests conducting a nationwide mapping of ICU resources, prioritizing infrastructure development, optimizing resource allocation, and establishing national protocols.

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

BackgroundPublic 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.ObjectiveThis 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.MethodsA 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.ResultsData 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.ConclusionThe 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.

The epidemiology and treatment outcomes of COVID-19 patients admitted to an intensive care unit in an Iranian hospital in Neyshabur city.

The COVID-19 pandemic and the infection of numerous individuals from diverse societies have emerged as major global challenges. Given the limited resources in intensive care units, effective bed management and resource allocation require a deep understanding of the disease. This study aimed to assess the epidemiology and treatment outcomes of COVID-19 patients admitted to an intensive care unit in an Iranian hospital in Neyshabur city. This cross-sectional study was conducted on COVID-19 patients hospitalized in intensive care units in Razavi Khorasan, Iran in 2021. Census sampling was used to include all intensive care units. Of the initial 480 cases, 54 cases were excluded based on the exclusion criteria, leaving 426 cases for the study. Data were collected with the help of a data collection form that was designed by the researcher and its content validity and reliability were measured with Cronbach's alpha coefficient (α = 89%.). Data were analyzed with SPSS version 20 software. Descriptive and inferential statistics were used to analyze the data. Mean, standard deviation, and interquartile range indicators were used for descriptive statistics, and absolute frequency and relative frequency (percentage) were used to show numbers and ratios. The mean (SD) age of the patients was 66.33 (15.05) years, and 49.3% were female. The results showed that arterial blood oxygen saturation, respiratory rate, and Alzheimer's disease were significant variables for predicting mortality. Furthermore, arterial blood oxygen saturation, respiratory rate, and the need for transfusion of blood products were significant variables in predicting hospitalization and the risk of acute respiratory distress syndrome (ARDS). This study demonstrated that arterial blood oxygen saturation, respiratory rate, and Alzheimer's disease are crucial variables for predicting death. Furthermore, arterial blood oxygen saturation and respiratory rate are significant factors in predicting the risk of ARDS.

Safety and Feasibility of a “Fast‐Track” Monitoring Protocol for Patients Treated With Intravenous Thrombolytic Therapy

Background Our health care systems continue to face significant strain due to chronically taxed intensive care resources. A subgroup of patients following thrombolytic stroke may not require prolonged intensive monitoring, alleviating some burden. Here, we describe the safety, feasibility, and utility of a Fast‐Track Protocol (FTP) for early deescalation of high‐acuity monitoring. Methods We compared a prospective cohort of patients on the FTP at our stroke centers from April 2020 to February 2022 to a similar retrospective cohort. Those who presented with a National Institutes of Health Stroke Scale <10 and without large‐vessel occlusion or flow‐limiting stenosis, intravenous antihypertensive use, and any hemodynamic or respiratory concerns were eligible. Primary outcomes included early neurologic deterioration, defined as worsening of National Institutes of Health Stroke Scale score of ≥4 points at 24 hours, parenchymal hemorrhage, and symptomatic intracranial hemorrhage. Results Of 574 patients undergoing thrombolysis, 119 (21%) were eligible for the FTP. A total of 100 (88%) were included for analysis. The median±interquartile range hospitalization was 2.0±1.6 days. None of the 4 cases of early neurologic deterioration were due to hemorrhage. No symptomatic intracranial hemorrhages occurred, and no patients on the FTP were transferred back to the intensive care unit. Median±interquartile range 90‐day modified Rankin scale score was 1±1. Conclusion FTP is a safe and feasible strategy to triage intensive care unit patients and decrease unnecessary intensive care unit monitoring. This is important in a postpandemic era as intensive care unit resources continue to fluctuate. Future studies are needed to establish the optimal level of monitoring in patients following thrombolysis.

Opportunity for Reduction of Intensive Care Unit Resource Utilization in Pediatric Blunt Liver and Spleen Injuries: A National Trauma Data Bank Analysis

IntroductionGuidelines for blunt liver and spleen injury (BLSI) by the Arizona-Texas-Oklahoma-Memphis-Arkansas Consortium (ATOMAC) emphasize hemodynamic stability over injury grade when considering non-operative management (NOM). In this study, we examined rates of intensive care unit (ICU) admission for children with isolated low-risk BLSI among US hospitals. MethodsThe National Trauma Data Bank (NTDB) was queried for patients ages 1-15 admitted between 2017 and 2019 with BLSI. Patients with penetrating injuries and/or concomitant non-abdominal injuries with AIS score ≥3 were excluded. Isolated BLSI was considered low-risk if the patient had normal admission vitals and did not require operative intervention. Primary outcomes measured were ICU admission, ICU length of stay (LOS), and overall LOS. Results5777 patients ages 15 and under presented with isolated BLSI during the study period. 2031/5777 (35.2%) were considered low-risk. Low-risk patients had lower rates of ICU admission compared to high-risk patients (30.9% vs. 41.6%, p < 0.001) and had shorter ICU LOS (median 2 days vs. 2, p < 0.001) and shorter overall LOS (median 41 h vs. 54, p < 0.001). Pediatric verified and non-pediatric verified trauma centers had similar rates of ICU admission (36.8% vs. 38.9%, p = 0.11). ConclusionFurther work is needed to capture opportunities for reduction in ICU utilization in isolated BLSI. Level of EvidenceIII

Association Between High Sensitivity Troponin Levels Following Pediatric Orthotopic Heart Transplantation and Intensive Care Unit Resource Utilization.

The utility of troponin levels, including high sensitivity troponin T (hs-TnT), after orthotopic heart transplant (OHT) is controversial. Conflicting data exist regarding its use as a marker of acute rejection. Few studies have examined possible associations of hs-TnT levels immediately after OHT with metrics of intensive care unit (ICU) resource utilization or risk of acute rejection. We performed a retrospective cohort chart review including all OHT recipients < 20years of age at our center between June 2019 and December 2022. Patients were divided into two groups based on supra- or sub-median initial hs-TnT levels (median 3462.5ng/L). Primary outcome was days requiring ICU-level care, secondary outcomes included days intubated, days requiring positive pressure ventilation (PPV), days on inotropic medications, actual ICU length of stay, Vasoactive Inotrope Scores (VIS) on postoperative days (POD) 0 through 7, and acute rejection at 30days and one year after OHT. Patients with higher hs-TnT required ICU level care for longer [13.5 (10-17.5) vs. 9.5 (8-12) days, p = 0.01] and spent more days intubated [6 (4-7) vs. 3 (3-5) days, p < 0.001], on PPV [9 (6-15) vs. 6 (5-8.5) days, p = 0.02], and on inotropes [11 (9-14) vs. 8 (7-11) days, p = 0.025]. VIS was only different between groups on POD7 [5 (3-7) vs. 3 (0-5), p = 0.04]. There was no difference in rejection between the groups. Higher hs-TnT immediately following pediatric OHT may predict higher ICU resource utilization, despite no difference in VIS, although it does not predict acute rejection in the first year after OHT.

Age Distribution and Clinical Results of Critically Ill Patients above 65-Year-Old in an Aging Society: A Retrospective Cohort Study.

Increasing age has been observed among patients admitted to the intensive care unit (ICU). Age traditionally considered a risk factor for ICU mortality. We investigated how the epidemiology and clinical outcomes of older ICU patients have changed over a decade. We analyzed patients admitted to the ICU at a university hospital in Seoul, South Korea. We defined patients aged 65 and older as older patients. Changes in age groups and mortality risk factors over the study period were analyzed. A total of 32,322 patients were enrolled who aged ≥65 years admitted to the ICUs between January 1, 2007, and December 31, 2017. Patients aged ≥65 years accounted for 35% and of these, the older (O, 65 to 74 years) comprised 19,630 (66.5%), very older (VO, 75 to 84 years) group 8,573 (29.1%), and very very older (VVO, ≥85 years) group 1,300 (4.4%). The mean age of ICU patients over the study period increased (71.9±5.6 years in 2007 vs. 73.2±6.1 years in 2017) and the proportions of the VO and VVO group both increased. Over the period, the proportion of female increased (37.9% in 2007 vs. 43.3% in 2017), and increased ICU admissions for medical reasons (39.7% in 2007 vs. 40.2% in 2017). In-hospital mortality declined across all older age groups, from 10.3% in 2007 to 7.6% in 2017. Hospital length of stay (LOS) decreased in all groups, but ICU LOS decreased only in the O and VO groups. The study indicates a changing demographic in ICUs with an increase in older patients, and suggests a need for customized ICU treatment strategies and resources.

Neonatal Intensive Care Unit Resource Use for Infants at 22 Weeks’ Gestation in the US, 2008-2021

During the past decade, clinical guidance about the provision of intensive care for infants born at 22 weeks' gestation has changed. The impact of these changes on neonatal intensive care unit (NICU) resource utilization is unknown. To characterize recent trends in NICU resource utilization for infants born at 22 weeks' gestation compared with other extremely preterm infants (≤28 weeks' gestation) and other NICU-admitted infants. This is a serial cross-sectional study of 137 continuously participating NICUs in 29 US states from January 1, 2008, through December 31, 2021. Participants included infants admitted to the NICU. Data analysis was performed from October 2022 to August 2023. Year and gestational age at birth. Measures of resource utilization included NICU admissions, NICU bed-days, and ventilator-days. Of 825 112 infants admitted from 2008 to 2021, 60 944 were extremely preterm and 872 (466 [53.4%] male; 18 [2.1%] Asian; 318 [36.5%] Black non-Hispanic; 218 [25.0%] Hispanic; 232 [26.6%] White non-Hispanic; 86 [9.8%] other or unknown) were born at 22 weeks' gestation. NICU admissions at 22 weeks' gestation increased by 388%, from 5.7 per 1000 extremely preterm admissions in 2008 to 2009 to 27.8 per 1000 extremely preterm admissions in 2020 to 2021. The number of NICU admissions remained stable before the publication of updated clinical guidance in 2014 to 2016 and substantially increased thereafter. During the study period, bed-days for infants born at 22 weeks increased by 732%, from 2.5 per 1000 to 20.8 per 1000 extremely preterm NICU bed-days; ventilator-days increased by 946%, from 5.0 per 1000 to 52.3 per 1000 extremely preterm ventilator-days. The proportion of NICUs admitting infants born at 22 weeks increased from 22.6% to 45.3%. Increases in NICU resource utilization during the period were also observed for infants born at less than 22 and at 23 weeks but not for other gestational ages. In 2020 to 2021, infants born at less than or equal to 23 weeks' gestation comprised 1 in 117 NICU admissions, 1 in 34 of all NICU bed-days, and 1 in 6 of all ventilator-days. In this serial cross-sectional study of 137 US NICUs from 2008 to 2021, an increasing share of resources in US NICUs was allocated to infants born at 22 weeks' gestation, corresponding with changes in national clinical guidance.

No Association of Blood Alcohol Concentration on Burn Patient Outcomes

IntroductionAlcohol abuse is common among burn patients. Burn patients under the influence of alcohol are at risk for developing organ failure, prolonged hospital duration, and increased intensive care unit (ICU) resources. Our study aims to analyze the association between presenting alcohol levels and the outcomes of burn patients. MethodsA retrospective analysis of admitted burn patients was performed from 2016 to 2021. Patients were divided into two groups based on blood alcohol content (BAC), low (<80), and high (≥80) mg/dL. Data included demographics, comorbidities, and outcomes. Univariate analyses were performed, and a P value <0.05 was significant. ResultsA total of 197 patients were included (32.5% females, mean age 47.2 ± 15.2, 26.9% smokers, 28.4% illegal drug abuse, and 56.3% no comorbidities). Mortality was 7.6%, morbidity 20.8%, 39.1% required burn ICU admission, and 25.9% were intubated. When comparing BAC groups, we found no differences in demographics, comorbidities, inhalational injury incidence, carbon monoxide level, intubation, or burn ICU admission rates. The high-BAC group had longer ventilator days (high BAC 16.7 ± 19.3 versus low BAC 7.5 ± 9.1, P = 0.026) and longer stays in the ICU (18.6 ± 21.8 versus 10.7 ± 15.4, P = 0.075). The low-BAC group had more 3rd-degree burn percentage (5.0 ± 15.3 versus 15.4 ± 27.5, P = 0.024). Both morbidity and in-house mortality rates were similar for both groups (23.8% versus 16.0%, P = 0.192, and 6.6% versus 9.3%, P = 0.476, respectively). ConclusionsBurn patients with higher BAC had significantly longer mechanical ventilator days. However, higher alcohol concentrations had no association with regard to mortality, overall length of stay, or complication rates.

Critical care services in Bagmati province of Nepal: A cross sectional survey

Background This study aimed to assess the current status of critical care services in 13 districts of Bagmati Province in Nepal, with a focus on access, infrastructure, human resources, and intensive care unit (ICU) services. Methods A cross-sectional survey was conducted among healthcare workers employed in 87 mixed medical/surgical ICUs across Bagmati Province. Data were collected through structured questionnaires administered via face-to-face and telephone interviews. Descriptive analysis was used for data analysis, involving frequencies and percentages. Results A total of 123 ICUs were identified in the province, providing 1167 beds and 615 functioning ventilators. The average ICU bed availability per 100,000 population was 19, ranging from 3.6 in Makwanpur to 33.9 in Kathmandu. Out of 13 districts, 95% of beds were concentrated in just four districts, while six had no ICU facilities. Of the available facilities, 69.9% were owned by private entities. One-to-one nurse-to-ventilated bed ratio was maintained by 63.4% of ICUs during daytime, and 62.6% at nighttime. Furthermore, 74.8% of ICUs had consultants trained in critical care medicine. While essential equipment availability was higher in Bagmati province, gaps existed in the availability of oxygen plants and isolation rooms. Similarly, many ICUs offered continuous medical education and cardiopulmonary resuscitation (CPR) training, but improvements were necessary in clinical audits, antibiotic stewardship programs, and research engagement. Conclusions Disparities in critical care resources were evident across districts in Bagmati Province, highlighting the need for a balanced and decentralized approach to ensure equitable access to care. Although there were disparities, numerous ICUs were effectively carrying out multiple critical care procedures. This study suggests conducting a nationwide mapping of ICU resources, prioritizing infrastructure development, optimizing resource allocation, and establishing national protocols.

Utilization of Hospice Resources in Adult Intensive Care Units: A Comparison Between Users and Non-Users

The application of palliative care is limited and challenging in intensive care units (ICUs) because of complex factors such as time constraints and unpredictable disease progression. Although research results and international consensus stress the early use of palliative care, utilization remains low, resulting in increased risks of ineffective medical care and poor quality of death. Improving this situation requires a comprehensive understanding of the palliative condition in ICUs. This study was designed to investigate the utilization of hospice resources in adult ICUs and to compare this utilization between users and non-users. This retrospective correlation study recruited cases from the adult ICU database of a medical center in northern Taiwan between June and July 2022. Descriptive statistics, independent t-test and chi-square were used to analyze the data. A total of 1,181 records were analyzed, including 458 (38.8%) females and 723 (61.2%) males. Two hundred and seventeen cases (18.4%) used hospice resources. Although 124 (10.4%) of the 1181 cases were identified as "in urgent need of hospice resources" (i.e., died within 30 days of ICU admission), 25 (20.2%) did not use these resources. Significant differences between the urgent-need cases who did and did not use hospice resources were found in terms of age, disease type, degree of frailty, cardiac arrest, infection, state of consciousness, intubation and tracheostomy status, inotropic and vasopressor medication, renal replacement, ECMO placement, delirium, and Acute Physiology and Chronic Health Evaluation III and Sequential Organ Failure Assessment Scores. The roughly 20% of ICU patients in urgent needs of palliative care who did not utilize palliative care resources highlight the needs for continued discussion to better assist patients on palliative care decision-making. The findings show multifaceted differences between those who did and did not access palliative care. Future studies should design and test strategies to facilitate the identification of palliative care needs and ensure the effective allocation of palliative care resources in ICUs.

A New Risk Model based on the Machine Learning Approach for Prediction of Mortality in the Respiratory Intensive Care Unit.

Intensive care unit (ICU) resources are inadequate for the large population in China, so it is essential for physicians to evaluate the condition of patients at admission. In this study, our objective was to construct a machine-learning risk prediction model for mortality in respiratory intensive care units (RICUs). This study involved 817 patients who made 1,063 visits and who were admitted to the RICU from 2012 to 2017. Potential predictors such as demographic information, laboratory results, vital signs and clinical characteristics were considered. We constructed eXtreme Gradient Boosting (XGBoost) models and compared performances with random forest models, logistic regression models and clinical scores such as Acute Physiology and Chronic Health Evaluation II (APACHE II) and the sequential organ failure assessment (SOFA) system. The model was externally validated using data from Medical Information Mart for Intensive Care (MIMIC-III) database. A web-based calculator was developed for practical use. Among the 1,063 visits, the RICU mortality rate was 13.5%. The XGBoost model achieved the best performance with the area under the receiver operating characteristics curve (AUROC) of 0.860 (95% confidence interval (CI): 0.808 - 0.909) in the test set, which was significantly greater than APACHE II (0.749, 95% CI: 0.674 - 0.820; P = 0.015) and SOFA (0.751, 95% CI: 0.669 - 0.818; P = 0.018). The Hosmer-Lemeshow test indicated a good calibration of our predictive model in the test set with a P-value of 0.176. In the external validation dataset, the AUROC of XGBoost model was 0.779 (95% CI: 0.714 - 0.813). The final model contained variables that were previously known to be associated with mortality, but it also included some features absent from the clinical scores. The mean N-terminal pro-B-type natriuretic peptide (NTproBNP) of survivors was significantly lower than that of the non-survival group (2066.43 pg/mL vs. 8232.81 pg/mL; P < 0.001). Our results showed that the XGBoost model could be a suitable model for predicting RICU mortality with easy-to-collect variables at admission and help intensivists improve clinical decision-making for RICU patients. We found that higher NT-proBNP can be a good indicator of poor prognosis.

Exploring factors affecting the timely transition of ventilator assisted individuals in Ontario from acute to long-term care: Perspectives of healthcare professionals.

Ventilator Assisted Individuals (VAIs) frequently remain in intensive care units (ICUs) for a prolonged period once clinically stable due to a lack of transition options. These VAIs occupy ICU beds and resources that patients with more acute needs could better utilize. Moreover, VAIs experience improved outcomes and quality of life in long-term and community-based environments. To better understand the perspectives of healthcare providers (HCPs) working in an Ontario ICU regarding barriers and facilitators to referral and transition of VAIs from the ICU to a long-term setting. We conducted semi-structured interviews with ten healthcare providers involved in VAI transitions. Perceived barriers included long wait times for long-term care settings, insufficient bed availability at discharge locations, medical complexity of patients, long waitlists, and a lack of transparency of waitlists. Facilitators included strong partnerships and trusting relationships between referring and discharge locations, a centralized referral system, and utilization of community partnerships across care sectors. Insufficient resourcing of long-term care is a key barrier to transitioning VAIs from ICU to long-term settings; strong partnerships across care sectors are a facilitator. System-level approaches, such as a single-streamlined referral system, are needed to address key barriers to timely transition.

Short-term predictor for COVID-19 severity from a longitudinal multi-omics study for practical application in intensive care units

BackgroundThe COVID-19 pandemic challenged the management of technical and human resources in intensive care units (ICU) across the world. Several long-term predictors for COVID-19 disease progression have been discovered. However, predictors to support short-term planning of resources and medication that can be translated to future pandemics are still missing. A workflow was established to identify a predictor for short-term COVID-19 disease progression in the acute phase of intensive care patients to support clinical decision-making. MethodsThirty-two patients with SARS-CoV-2 infection were recruited on admission to the ICU and clinical data collected. During their hospitalization, plasma samples were acquired from each patient on multiple occasions, excepting one patient for which only one time point was possible, and the proteome (Inflammation, Immune Response and Organ Damage panels from Olink® Target 96), metabolome and lipidome (flow injection analysis and liquid chromatography-mass spectrometry) analyzed for each sample. Patient visits were grouped according to changes in disease severity based on their respiratory and organ function, and evaluated using a combination of statistical analysis and machine learning. The resulting short-term predictor from this multi-omics approach was compared to the human assessment of disease progression. Furthermore, the potential markers were compared to the baseline levels of 50 healthy subjects with no known SARS-CoV-2 or other viral infections. ResultsA total of 124 clinical parameters, 271 proteins and 782 unique metabolites and lipids were assessed. The dimensionality of the dataset was reduced, selecting 47 from the 1177 parameters available following down-selection, to build the machine learning model. Subsequently, two proteins (C–C motif chemokine 7 (CCL7) and carbonic anhydrase 14 (CA14)) and one lipid (hexosylceramide 18:2; O2/20:0) were linked to disease progression in the studied SARS-CoV-2 infections. Thus, a predictor delivering the prognosis of an upcoming worsening of the patient's condition up to five days in advance with a reasonable accuracy (79 % three days prior to event, 84 % four to five days prior to event) was found. Interestingly, the predictor's performance was complementary to the clinicians' capabilities to foresee a worsening of a patient. ConclusionThis study presents a workflow to identify omics-based biomarkers to support clinical decision-making and resource management in the ICU. This was successfully applied to develop a short-term predictor for aggravation of COVID-19 symptoms. The applied methods can be adapted for future small cohort studies.

Limitation of Non-Beneficial Interventions and their Impact on the Intensive Care Unit Costs.

Using a plan to limit non-beneficial life support interventions has significantly reduced harm and loss of dignity for patients at the end of life. The association of these limitations with patients' clinical characteristics and health care costs in the intensive care unit (ICU) needs further scientific evidence. To explore decisions to limit non-beneficial life support interventions, their correlation with patients' clinical data, and their effect on the cost of care in the ICU. We included all patients admitted to the general ICU of a hospital in Greece in a two-year (2019-2021) prospective study. Data collection included patient demographic and clinical variables, data related to decisions to limit (withholding, withdrawing) non-beneficial interventions (NBIs), and economic data. Comparisons were made between patients with and without limitation decisions. NBIs were limited in 164 of 454 patients (36.12%). Patients with limitation decisions were associated with older age (70y vs. 62y; p<0,001), greater disease severity score (APACHE IV, 71 vs. 50; p<0,001), longer length of stay (7d vs. 4.5d; p<0,001), and worse prognosis of death (APACHE IV PDR, 48.9 vs. 17.35; p<0,001). All cost categories and total cost per patient were also higher than the patient without limitation of NBIs (9247,79€ vs. 8029,46€, p<0,004). The mean daily cost has not differed between the groups (831,24€ vs. 832,59€; p<0,716). However, in the group of patients with limitations, all cost categories, including the average daily cost (767.31€ vs. 649.12€) after the limitation of NBIs, were reduced to a statistically significant degree (p<0.001). Limiting NBIs in the ICU reduces healthcare costs and may lead to better management of ICU resource use.