Critical care medicine in the United States 2000-2005: an analysis of bed numbers, occupancy rates, payer mix, and costs

Bedside versus operating room tracheostomy: A cost-effectiveness and economic evaluation

BACKGROUND

Prior studies have compared outcomes and costs between bedside tracheostomy (BT) and operating room tracheostomy (ORT). However, studies have not performed a formal cost-effectiveness analysis of BT versus ORT.

METHODS

We present a cost-effectiveness study using Markov microsimulation for BT versus ORT. We abstracted model parameters from currently available literature and performed deterministic and probabilistic sensitivity analyses.

RESULTS

BT was more cost-effective than ORT at a $100,000/quality-adjusted life year willingness to pay (WTP) threshold. Our model was sensitive to postoperative pneumonia rates and pneumonia treatment costs. BT was more cost-effective in most iterations within a range of WTP thresholds from $0 to $200,000.

CONCLUSIONS

BT is more cost-effective than ORT for critically ill patients at low-average risk for postoperative pneumonia. Our findings support considering bedside tracheostomy before performing the same procedure in the operating room, regardless of whether the approach is percutaneous or open.

The Cost of Antivenom: A Cost Minimization Study using the North American Snakebite Registry

Envenomation is a global health issue, with over 9,000 encounters managed in the United States yearly. The introduction of immunoglobulin fragment antivenom has reduced the risk of hypersensitivity. This study compares treatment costs of crotaline envenomation using the Fab and F(ab')2 antivenoms as reported to the North American Snakebite Registry (NASBR), a nationwide surveillance tool.

METHODS

This was a retrospective analysis of NASBR data between 2018 and 2020. The following data points were assessed: patient demographics (age, gender, race), snake species, type of antivenom used, and treatment costs. Unit costs were estimated based on United States Centers for Medicare and Medicaid Services data. Average (mean) per patient costs from the payer perspective were calculated by multiplying resources by the unit costs. Sensitivity analyses were performed regarding cost variance and snake species. All costs reported in this study are in U.S. dollars.

RESULTS

The average total cost of treatment was $31,343 per person, with medications contributing 72% of the total. Average total cost among patients who received Fab treatments was $33,347 per person compared to $19,747 among patients who received F(ab')2. Antivenom costs accounted for 75% of the total cost in the Fab group and 42% in the F(ab')2 group. F(ab')2 required more vials than Fab (median 18 versus 10). Non-antivenom costs such as hospitalizations were higher in the F(ab')2 group. Using average sale prices increased average total cost to $52,572; Fab remained more expensive.

CONCLUSION

Antivenom is the primary cost driver in snakebite treatment in North America. Treatment with F(ab')2 resulted in lower overall costs, driven by lower cost of antivenom. F(ab')2 did not significantly lower overall resource use except for blood product administration.

Carotid endarterectomy is less expensive than transcarotid artery revascularization

OBJECTIVE

Transcarotid artery revascularization (TCAR) is safe and effective for treatment of carotid stenosis, with comparable short-term outcomes with carotid endarterectomy (CEA). Few peer-reviewed studies evaluated the comparative costs of these two procedures. The objective of this study was to compare the costs of these procedures at a single institution.

METHODS

This was a retrospective analysis of patients receiving TCAR or CEA at a single tertiary care center from August 2018 to July 2023. Patient characteristics, demographics, and procedure cost data were extracted from the electronic medical record. Stay costs were calculated using estimates derived from literature and adjusted for inflation. A subset of patient charts from June 2022 to July 2023 were used to calculate a baseline procedure cost for the TCAR and CEA cohorts, with individual implant cost from each chart added to obtain estimated procedure cost. Patients with insufficient chart data or who were converted from TCAR to CEA were excluded from analysis.

RESULTS

Of 187 patients, 51 received TCAR and 136 received CEA. Patients undergoing TCAR were significantly older (74 vs 70 years; P = .007) and more likely to have a history of prior ipsilateral carotid intervention (9.8% vs 0.7%; P = .003), contralateral carotid intervention (18% vs 13%; P = .003), or neck surgery (35% vs 18%; P = .01). Procedure length was shorter in the TCAR group (104 vs 130 minutes; P = .002). No differences were found between TCAR and CEA in postoperative rates of stroke, myocardial infarction, or in-hospital mortality. Of the 56 patients for whom procedure cost data was collected, TCAR was found to have a higher procedure cost ($9114 for TCAR; $1409 for CEA; P < .001) and higher net hospitalization cost ($14,090 for TCAR; $7512 for CEA; P < .001). In the entire cohort, there were no differences in duration of post-procedure intensive care unit stay (1.5 vs 2.88 days; P = .2), hospital stay (2.18 vs 1.96 days; P = .4), or in stay cost ($5525 vs $5178; P = .06). There were significant differences in estimated procedure cost ($9100 for TCAR; $1412 for CEA; P < .001) and estimated net hospitalization cost ($14,625 for TCAR; $6591 for CEA; P < .001).

CONCLUSIONS

This study found that the cost to undergo TCAR was significantly higher than CEA at this institution. When factored into the net cost of hospitalization, TCAR more than doubled the net cost of perioperative stay. Further analysis is warranted to determine areas of cost optimization for carotid revascularization.

Impact of tracheostomy on clinical outcomes in ventilated patients with severe pneumonia: a propensity-matched cohort study

BACKGROUND/AIMS

Tracheostomy is a crucial intervention for severe pneumonia patients requiring prolonged mechanical ventilation (MV). However, debate persists regarding the influence of tracheostomy timing and performance on long-term survival outcomes. This study utilized propensity score matching to assess the impact of tracheostomy timing and performance on patient survival outcomes.

METHODS

A retrospective observational study employing propensity score matching was conducted of respiratory intensive care unit (ICU) patients who underwent prolonged acute MV due to severe pneumonia from 2008 to 2023. The primary outcome was the 90-day cumulative mortality rate, with secondary outcomes including ICU medical resource utilization rates.

RESULTS

Out of 1,078 patients, 545 underwent tracheostomy with a median timing of 7 days. The tracheostomy group exhibited lower 90-day cumulative mortality and a higher survival probability (hazard ratio [HR] 0.52, 95% confidence interval [CI] 0.43-0.63) than the no-tracheostomy group. The tracheostomy group had higher ICU medical resource utilization rates and medical expenditures. The early tracheostomy group (≤ 7 days) had lower ICU medical resource utilization rates and medical expenditures than the late tracheostomy group (> 7 days). However, there were no significant differences in the 90-day cumulative mortality rate and survival probability based on tracheostomy timing (HR 0.94, 95% CI 0.70-1.28).

CONCLUSION

Tracheostomy in patients with severe pneumonia requiring prolonged MV significantly reduced the 90-day mortality rate, and early tracheostomy may offer additional benefits for resource utilization efficiency. These findings underscore the importance of considering tracheostomy timing in optimizing patient outcomes and healthcare resource allocation.

Exploring timely and safe discharge from ICU: a comparative study of machine learning predictions and clinical practices

BACKGROUND

The discharge practices from the intensive care unit exhibit heterogeneity and the recognition of eligible patients for discharge is often delayed. Recognizing the importance of safe discharge, which aims to minimize readmission and mortality, we developed a dynamic machine-learning model. The model aims to accurately identify patients ready for discharge, offering a comparison of its effectiveness with physician decisions in terms of safety and discrepancies in discharge readiness assessment.

METHODS

This retrospective study uses data from patients in the medical ICU from 2015-to-2019 to develop ML models. The models were based on dynamic ICU-readily available features such as hourly vital signs, laboratory results, and interventions and were developed using various ML algorithms. The primary outcome was the hourly prediction of ICU discharge without readmission or death within 72 h post-discharge. These outcomes underwent subsequent validation within a distinct cohort from the year 2020. Additionally, the models' performance was assessed in comparison to physician judgments, with any discrepancies between the two carefully analyzed.

RESULT

In the 2015-to-2019 cohort, the study included 17,852 unique ICU admissions. The LightGBM model outperformed other algorithms, achieving a AUROC of 0.91 (95%CI 0.9-0.91) and performance was held in the 2020 validation cohort (n = 509) with an AUROC of 0.85 (95%CI 0.84-0.85). The calibration result showed Brier score of 0.254 (95%CI 0.253-0.255). The physician agreed with the models' discharge-readiness prediction in 84.5% of patients. In patients discharged by physicians but not deemed ready by our model, the relative risk of 72-h post-ICU adverse outcomes was 2.32 (95% CI 1.1-4.9). Furthermore, the model predicted patients' readiness for discharge between 5 (IQR: 2-13.5) and 9 (IQR: 3-17) hours earlier in our selected thresholds.

CONCLUSION

The study underscores the potential of ML models in predicting patient discharge readiness, mirroring physician behavior closely while identifying eligible patients earlier. It also highlights ML models can serve as a promising screening tool to enhance ICU discharge, presenting a pathway toward more efficient and reliable critical care decision-making.

The Financial Impact of Post Intensive Care Syndrome

This review explores the financial consequences that survivors of critical illness often face following hospitalization in an intensive care unit (ICU). As part of the "post-intensive care syndrome" (PICS), these survivors often experience, in addition to physical and emotional challenges of PICS, major financial burdens resulting from their prolonged ICU treatments. The escalating costs of ICU care, coupled with the potential long-term effects on survivors' ability to work and maintain financial stability, have brought financial toxicity to the forefront of health care discussions. The current review examines the causes and consequences of financial toxicity.

Safety and Outcome of Admission to Step-Down Level of Care in Patients with Low-Risk Spontaneous Intracerebral Hemorrhage: A Systematic Review and Meta-analysis

Spontaneous intracerebral hemorrhage (ICH) is the most devastating type of stroke, and it is associated with high morbidity and mortality. Patients with a spontaneous ICH are routinely admitted to an intensive care unit (ICU). However, an ICU is a valuable and limited resource, and not all patients may require this level of care. The authors conducted a systematic review and meta-analysis evaluating the safety and outcome of admission to a step-down level of care or stroke unit (SU) compared to intensive care in adult patients with low-risk spontaneous ICH. PubMed, Embase, and the Cochrane Library were searched for randomized clinical trials and observational cohort studies. The Mantel-Haenszel method or inverse variance, as applicable, was applied to calculate an overall effect estimate for each outcome by combining the specific risk ratio (RR) or standardized mean difference. Risk of bias was analyzed using the Newcastle-Ottawa Scale. The protocol was registered in PROSPERO (CRD42023481915). The primary outcome examined was in-hospital mortality. Secondary outcomes were unfavorable short-term outcome, length of hospital stay, and (re)admission to the ICU. Five retrospective cohort studies involving 1347 patients were included in the qualitative analysis. Two of the studies had severity-matched groups. The definition of low-risk ICH was heterogeneous among the studies. Admission to an SU was associated with a similar rate of mortality compared to admission to an ICU (1.4% vs. 0.6%; RR 1.66; 95% confidence interval [CI] 0.24-11.41; P = 0.61), a similar rate of unfavorable short-term outcome (14.6% vs. 19.2%; RR 0.77; 95% CI 0.43-1.36; P = 0.36), and a significantly shorter mean length of stay (standardized mean difference - 0.87 days; 95% CI - 1.15 to - 0.60; P < 0.01). Risk of bias was low to moderate for each outcome. The available literature suggests that a select subgroup of patients with ICH may be safely admitted to the SU without affecting short-term outcome, potentially saving in-hospital resources and reducing length of stay. Further studies are needed to identify specific and reliable characteristics of this subgroup of patients.

Comparing Outcomes Between Advanced Practice Providers and Housestaff Teams in the Cardiac Intensive Care Unit

Background

With an increasing demand for critical care expertise and limitations in intensivist availability, innovative staffing models, such as the utilization of advanced practice providers (APPs), have emerged.

Objectives

The purpose of the study was to compare patient outcomes between APP and housestaff teams in the cardiac intensive care unit (CICU).

Methods

This retrospective study, spanning March 2022 to July 2023, compares patient characteristics and outcomes between two CICU teams embedded in the same CICU at a large urban academic hospital: one staffed by housestaff and the other by APPs (80% physician assistants, 20% nurse practitioners) who each had approximately 1 to 2 years of experience in the CICU. The primary outcome was CICU mortality. Multivariable Cox regression analyses and Kaplan-Meier curves were used to assess the primary outcome.

Results

A total of 1,620 admissions were analyzed: 1,013 patients on the housestaff service and 607 patients on the APP service. There were no significant differences in patient demographics, admitting diagnoses, use of vasoactive medications, inotropes, or mechanical circulatory support. There was no difference in CICU mortality (8.4% vs 8.2%, adjusted hazard ratio 0.73; 95% CI: 0.51-1.05; P = 0.10), in-hospital mortality (13.5% vs 13.8%, aHR 0.82; 95% CI: 0.62-1.08; P = 0.17), or in-hospital length of stay between the housestaff and APP teams. Patients managed by the housestaff team had a lower CICU length of stay (2 days IQR: 1-4 days] vs 3 days [IQR: 1-5 days], P = 0.047). Fellowship rotation scores (based on surveys completed by the cardiology fellows) of the CICU also improved after the implementation of the APP-based team (3.87 ± 0.14 before vs 4.61 ± 0.06 after, P < 0.0001).

Conclusions

Our moderately sized study demonstrated no difference in CICU or in-hospital mortality between patients managed by a housestaff team versus those managed by an APP team.

Timely ICU Outcome Prediction Utilizing Stochastic Signal Analysis and Machine Learning Techniques with Readily Available Vital Sign Data

The ICU is a specialized hospital department that offers critical care to patients at high risk. The massive burden of ICU-requiring care requires accurate and timely ICU outcome predictions for alleviating the economic and healthcare burdens imposed by critical care needs. Existing research faces challenges such as feature extraction difficulties, low accuracy, and resource-intensive features. Some studies have explored deep learning models that utilize raw clinical inputs. However, these models are considered non-interpretable black boxes, which prevents their wide application. The objective of the study is to develop a new method using stochastic signal analysis and machine learning techniques to effectively extract features with strong predictive power from ICU patients' real-time time series of vital signs for accurate and timely ICU outcome prediction. The results show the proposed method extracted meaningful features and outperforms baseline methods, including APACHE IV (AUC = 0.750), deep learning-based models (AUC = 0.732, 0.712, 0.698, 0.722), and statistical feature classification methods (AUC = 0.765) by a large margin (AUC = 0.869). The proposed method has clinical, management, and administrative implications since it enables healthcare professionals to identify deviations from prognostications timely and accurately and, therefore, to conduct proper interventions.

Utilization and Outcomes in U.S. ICU Hospitalizations

OBJECTIVES

Despite its importance, detailed national estimates of ICU utilization and outcomes remain lacking. We aimed to characterize trends in ICU utilization and outcomes over a recent 12-year period in the United States.

DESIGN/SETTING

In this longitudinal study, we examined hospitalizations involving ICU care ("ICU hospitalizations") alongside hospitalizations not involving ICU care ("non-ICU hospitalizations") among traditional Medicare beneficiaries using 100% Medicare part A claims data and commercial claims data for the under 65 adult population from 2008 to 2019.

PATIENTS/INTERVENTIONS

There were 18,313,637 ICU hospitalizations and 78,501,532 non-ICU hospitalizations in Medicare, and 1,989,222 ICU hospitalizations and 16,732,960 non-ICU hospitalizations in the commercially insured population.

MEASUREMENTS AND MAIN RESULTS

From 2008 to 2019, about 20% of Medicare hospitalizations and 10% of commercial hospitalizations involved ICU care. Among these ICU hospitalizations, length of stay and ICU length of stay decreased on average. Mortality and hospital readmissions on average also decreased, and they decreased more among ICU hospitalizations than among non-ICU hospitalizations, for both Medicare and commercially insured patients. Both Medicare and commercial populations experienced a growth in shorter ICU hospitalizations (between 2 and 7 d in length), which were characterized by shorter ICU stays and lower mortality. Among these short hospitalizations in the Medicare population, for common clinical diagnoses cared for in both ICU and non-ICU settings, patients were increasingly triaged into an ICU during the study period, despite being younger and having shorter hospital stays.

CONCLUSIONS

ICUs are used in a sizeable share of hospitalizations. From 2008 to 2019, ICU length of stay and mortality have declined, while short ICU hospitalizations have increased. In particular, for clinical conditions often managed both within and outside of an ICU, shorter ICU hospitalizations involving younger patients have increased. Our findings motivate opportunities to better understand ICU utilization and to improve the value of ICU care for patients and payers.

What defines the "value" of robotic surgery for patients with gastrointestinal cancers? Perspectives from a U.S. Cancer Center

The use of robotic surgery has experienced rapid growth across diverse medical conditions, with a notable emphasis on gastrointestinal cancers. The advanced technologies incorporated into robotic surgery platforms have played a pivotal role in enabling the safe performance of complex procedures, including gastrectomy and pancreatectomy, through a minimally invasive approach. However, there exists a noteworthy gap in high-level evidence demonstrating that robotic surgery for gastric and pancreatic cancers has substantial benefits compared to traditional open or laparoscopic methods. The primary impediment hindering the broader implementation of robotic surgery is its cost. The escalating healthcare expenses in the United States have prompted healthcare providers and payors to explore patient-centered, value-based healthcare models and reimbursement systems that embrace cost-effectiveness. Thus, it is important to determine what defines the value of robotic surgery. It must either maintain or enhance oncological quality and improve complication rates compared to open procedures. Moreover, its true value should be apparent in patients' expedited recovery and improved quality of life. Another essential aspect of robotic surgery's value lies in minimizing or even eliminating opioid use, even after major operations, offering considerable benefits to the broader public health landscape. A quicker return to oncological therapy has the potential to improve overall oncological outcomes, while a speedier return to work not only alleviates individual financial distress but also positively impacts societal productivity. In this article, we comprehensively review and summarize the current landscape of health economics and value-based care, with a focus on robotic surgery for gastrointestinal cancers.

Catheter-associated urinary tract infections (CAUTIs) and non-CAUTI hospital-onset urinary tract infections: Relative burden, cost, outcomes and related hospital-onset bacteremia and fungemia infections

OBJECTIVE

To describe the relative burden of catheter-associated urinary tract infections (CAUTIs) and non-CAUTI hospital-onset urinary tract infections (HOUTIs).

METHODS

A retrospective observational study of patients from 43 acute-care hospitals was conducted. CAUTI cases were defined as those reported to the National Healthcare Safety Network. Non-CAUTI HOUTI was defined as a positive, non-contaminated, non-commensal culture collected on day 3 or later. All HOUTIs were required to have a new antimicrobial prescribed within 2 days of the first positive urine culture. Outcomes included secondary hospital-onset bacteremia and fungemia (HOB), total hospital costs, length of stay (LOS), readmission risk, and mortality.

RESULTS

Of 549,433 admissions, 434 CAUTIs and 3,177 non-CAUTI HOUTIs were observed. The overall rate of HOB likely secondary to HOUTI was 3.7%. Total numbers of secondary HOB were higher in non-CAUTI HOUTIs compared to CAUTI (101 vs 34). HOB secondary to non-CAUTI HOUTI was more likely to originate outside the ICU compared to CAUTI (69.3% vs 44.1%). CAUTI was associated with adjusted incremental total hospital cost and LOS of $9,807 (P < .0001) and 3.01 days (P < .0001) while non-CAUTI HOUTI was associated with adjusted incremental total hospital cost and LOS of $6,874 (P < .0001) and 2.97 days (P < .0001).

CONCLUSION

CAUTI and non-CAUTI HOUTI were associated with deleterious outcomes. Non-CAUTI HOUTI occurred more often and was associated with a higher facility aggregate volume of HOB than CAUTI. Patients at risk for UTIs in the hospital represent a vulnerable population who may benefit from surveillance and prevention efforts, particularly in the non-ICU setting.

Does Alcohol Use Influence Hospitalization Outcomes in Adults Suffering Craniomaxillofacial Fractures From Street Fighting?

Study Design

This retrospective cohort study utilized the National Inpatient Sample (NIS) database for the years 2016-2018. Incidences of street fighting were identified using the corresponding ICD-10 codes.

Objective

To determine whether alcohol use (measured by blood alcohol content (BAC)) in patients sustaining maxillofacial trauma from hand-to-hand fighting influence hospitalization outcomes.

Methods

The primary predictor variable was BAC stratified into six categories of increasing magnitude. The primary outcome variable was mean length of hospital stay (days). The secondary outcome variable was total hospital charges (US dollars).

Results

Our final sample consisted of 3038 craniomaxillofacial fractures. Each additional year in age added +$545 in hospital charges (P < .01). Non-elective admissions added $14 210 in hospital charges (P < .05). Patients admitted in 2018 experienced approximately $7537 more in hospital charges (P < .01). Le Fort fractures (+$61 921; P < .01), mandible fractures (+$13 227, P < .01), and skull base fractures (+$22 170; P < .05) were all independently associated with increased hospital charges. Skull base fractures added +7.6 days to the hospital stay (P < .01) and each additional year in patient age added +.1 days to the length of the hospital stay (P < .01).

Conclusions

BAC levels did not increase length of stay or hospitalization charges. Le Fort fractures, mandible fractures, and skull base fracture each independently increased hospital charges. This reflects the necessary care (ie, ICU) and treatment (ie, ORIF) of such fractures. Older adults and elderly patients are associated with increased length of stay and hospital charges-they are likely to struggle in navigating the healthcare system and face socioeconomic barriers to discharge.

Pro-Con Debate: Universal Versus Selective Continuous Monitoring of Postoperative Patients

In this Pro-Con commentary article, we discuss use of continuous physiologic monitoring for clinical deterioration, specifically respiratory depression in the postoperative population. The Pro position advocates for 24/7 continuous surveillance monitoring of all patients starting in the postanesthesia care unit until discharge from the hospital. The strongest arguments for universal monitoring relate to inadequate assessment and algorithms for patient risk. We argue that the need for hospitalization in and of itself is a sufficient predictor of an individual's risk for unexpected respiratory deterioration. In addition, general care units carry the added risk that even the most severe respiratory events will not be recognized in a timely fashion, largely due to higher patient to nurse staffing ratios and limited intermittent vital signs assessments (e.g., every 4 hours). Continuous monitoring configured properly using a "surveillance model" can adequately detect patients' respiratory deterioration while minimizing alarm fatigue and the costs of the surveillance systems. The Con position advocates for a mixed approach of time-limited continuous pulse oximetry monitoring for all patients receiving opioids, with additional remote pulse oximetry monitoring for patients identified as having a high risk of respiratory depression. Alarm fatigue, clinical resource limitations, and cost are the strongest arguments for selective monitoring, which is a more targeted approach. The proponents of the con position acknowledge that postoperative respiratory monitoring is certainly indicated for all patients, but not all patients need the same level of monitoring. The analysis and discussion of each point of view describes who, when, where, and how continuous monitoring should be implemented. Consideration of various system-level factors are addressed, including clinical resource availability, alarm design, system costs, patient and staff acceptance, risk-assessment algorithms, and respiratory event detection. Literature is reviewed, findings are described, and recommendations for design of monitoring systems and implementation of monitoring are described for the pro and con positions.

Predictors of Functional Decline Among Critically Ill Surgical Patients: A National Analysis

INTRODUCTION

Functional decline is associated with critical illness, though this relationship in surgical patients is unclear. This study aims to characterize functional decline after intensive care unit (ICU) admission among surgical patients.

METHODS

We performed a retrospective analysis of surgical patients admitted to the ICU in the Cerner Acute Physiology and Chronic Health Evaluation database, which includes 236 hospitals, from 2007 to 2017. Patients with and without functional decline were compared. Predictors of decline were modeled.

RESULTS

A total of 52,838 patients were included; 19,310 (36.5%) experienced a functional decline. Median ages of the decline and nondecline groups were 69 (interquartile range 59-78) and 63 (interquartile range 52-72) years, respectively (P < 0.01). The nondecline group had a larger proportion of males (59.1% versus 55.3% in the decline group, P < 0.01). After controlling for sociodemographic covariates, comorbidities, and disease severity upon ICU admission, patients undergoing pulmonary (odds ratio [OR] 6.54, 95% confidence interval [CI] 2.67-16.02), musculoskeletal (OR 4.13, CI 3.51-4.87), neurological (OR 2.67, CI 2.39-2.98), gastrointestinal (OR 1.61, CI 1.38-1.88), and skin and soft tissue (OR 1.35, CI 1.08-1.68) compared to cardiovascular surgeries had increased odds of decline.

CONCLUSIONS

More than one in three critically ill surgical patients experienced a functional decline. Pulmonary, musculoskeletal, and neurological procedures conferred the greatest risk. Additional resources should be targeted toward the rehabilitation of these patients.

Explainable artificial intelligence model for mortality risk prediction in the intensive care unit: a derivation and validation study

BACKGROUND

The lack of transparency is a prevalent issue among the current machine-learning (ML) algorithms utilized for predicting mortality risk. Herein, we aimed to improve transparency by utilizing the latest ML explicable technology, SHapley Additive exPlanation (SHAP), to develop a predictive model for critically ill patients.

METHODS

We extracted data from the Medical Information Mart for Intensive Care IV database, encompassing all intensive care unit admissions. We employed nine different methods to develop the models. The most accurate model, with the highest area under the receiver operating characteristic curve, was selected as the optimal model. Additionally, we used SHAP to explain the workings of the ML model.

RESULTS

The study included 21 395 critically ill patients, with a median age of 68 years (interquartile range, 56-79 years), and most patients were male (56.9%). The cohort was randomly split into a training set (N = 16 046) and a validation set (N = 5349). Among the nine models developed, the Random Forest model had the highest accuracy (87.62%) and the best area under the receiver operating characteristic curve value (0.89). The SHAP summary analysis showed that Glasgow Coma Scale, urine output, and blood urea nitrogen were the top three risk factors for outcome prediction. Furthermore, SHAP dependency analysis and SHAP force analysis were used to interpret the Random Forest model at the factor level and individual level, respectively.

CONCLUSION

A transparent ML model for predicting outcomes in critically ill patients using SHAP methodology is feasible and effective. SHAP values significantly improve the explainability of ML models.

A Nursing Care Model for Surge Capacity Management in Intensive Care Units During the COVID-19 Pandemic: Experience From Qatif Central Hospital, Saudi Arabia

Introduction The COVID-19 pandemic resulted in a surge of critically ill patients requiring intensive care. This posed challenges for healthcare systems in managing increased ICU bed demands with limited resources. Methods A retrospective qualitative review of institutional documents and plans was conducted. Key strategies related to ICU bed expansion, nursing staff classification and training, clinical supervision, and performance evaluation were analyzed. Results Qatif Central Hospital increased ICU beds from 20 to 50 by converting other clinical areas. Nursing staff were categorized based on critical care experience, and additional training was provided to non-ICU nurses. A preceptor-led nursing care model with staff responsibilities was implemented. Periodic evaluations ensured continued competence.  Conclusion The nursing care model at Qatif Central Hospital effectively facilitated ICU surge capacity while maintaining care quality. The model offers a viable framework for other healthcare institutions facing similar challenges. However, the study is limited by its retrospective design and focus on a single institution.

Epidemiology and disease burden of patients requiring neurocritical care: a Brazilian multicentre cohort study

Acute neurological emergencies are highly prevalent in intensive care units (ICUs) and impose a substantial burden on patients. This study aims to describe the epidemiology of patients requiring neurocritical care in Brazil, and their differences based on primary acute neurological diagnoses and to identify predictors of mortality and unfavourable outcomes, along with the disease burden of each condition at intensive care unit admission. This prospective cohort study included patients requiring neurocritical care admitted to 36 ICUs in four Brazilian regions who were followed for 30 days or until ICU discharge (Aug-Sep in 2018, 1 month). Of 4245 patients admitted to the participating ICUs, 1194 (28.1%) were patients with acute neurological disorders requiring neurocritical care and were included. Patients requiring neurocritical care had a mean mortality rate 1.7 times higher than ICU patients not requiring neurocritical care (17.21% versus 10.1%, respectively). Older age, emergency admission, higher number of potential secondary injuries, and worse APACHE II, SAPS III, SOFA, and Glasgow coma scale scores on ICU admission are independent predictors of mortality and poor outcome among patients with acute neurological diagnoses. The estimated total DALYs were 4482.94 in the overall cohort, and the diagnosis with the highest DALYs was traumatic brain injury (1634.42). Clinical, epidemiological, treatment, and ICU outcome characteristics vary according to the primary neurologic diagnosis. Advanced age, a lower GCS score and a higher number of potential secondary injuries are independent predictors of mortality and unfavourable outcomes in patients requiring neurocritical care. The findings of this study are essential to guide education policies, prevention, and treatment of severe acute neurocritical diseases.

Differences in Prevalence of Transfusion Protocols between Critically Ill Neurologic and Non-Neurologic Patient Populations

This study describes the prevalence of blood transfusion protocols in ICUs caring for neurologically vs. non-neurologically injured patients across a sample of US ICUs. This prospective, observational multi-center cohort study is a subgroup analysis of the USCIITG-CIOS, comprising 69 ICUs across the US (25 medical, 24 surgical, 20 mixed ICUs). Sixty-four ICUs were in teaching hospitals. A total of 6179 patients were enrolled, with 1266 (20.4%) having central nervous system (CNS) primary diagnoses. We evaluated whether CNS versus non-CNS diagnosis was associated with care in ICUs with restrictive transfusion protocols (RTPs) or massive transfusion protocols (MTPs) and whether CNS versus non-CNS diagnosis was associated with receiving blood products or colloids during the initial 24 h of care. Protocol utilization in CNS vs. non-CNS patients was as follows: RTPs-36.9% vs. 42.9% (p < 0.001); MTPs-48.3% vs. 47.4% (p = 0.57). Blood product transfusions in the first 24 h of ICU care (comparing CNS vs. non-CNS patients) were as follows: packed red blood cells-4.3% vs. 14.6% (p < 0.001); fresh frozen plasma-2.9% vs. 5.1% (p < 0.001); colloid blood products-3.2% vs. 9.2% (p < 0.001). In this cohort, we found differences in ICU utilization of RTPs, but not MTPs, when comparing where critically ill patients with neurologic versus non-neurologic primary diagnoses received ICU care.

Intensive Care Unit activity in France from the national database between 2013 and 2019: More critically ill patients, shorter stay and lower mortality rate

BACKGROUND

Knowledge of the occurrence and outcome of admissions to Intensive Care Units (ICU) over time is important to inform healthcare services planning. This observational study aims at describing the activity of French ICUs between 2013 and 2019.

METHODS

Patient admission characteristics, organ dysfunction scores, therapies, ICU and hospital lengths of stay and case fatality were collected from the French National Hospital Database (population-based cohort). Logistic regression models were developed to investigate the association between age, sex, SAPS II, organ failure, and year of care on in-ICU case fatality.

FINDINGS

Among 1,594,801 ICU admissions, the yearly ICU admission increased from 3.3 to 3.5 per year per 1000 inhabitants (bed occupancy rate between 83.4 and 84.3%). The mean admission SAPS II was 42 ± 22, with a gradual annual increase. The median lengths of stay in ICU and in hospital were 3 (interquartile range (IQR) = [1-7]) and 11 days (IQR = [6-21]), respectively, with a progressive decrease over time. The in-ICU and hospital mortality case fatalities decreased from 18.0% to 17.1% and from 21.1% to 19.9% between 2013 and 2019, respectively. Male sex, age, SAPS II score, and the occurrence of any organ failure were associated with a higher case fatality rate. After adjustment on age, sex, SAPS II and organ failure, in-ICU case fatality decreased in 2019 as compared to 2013 (adjusted Odds Ratio = 0.87 [95% confidence interval, 0.85-0.89]).

INTERPRETATION

During the study, an increasing incidence of ICU admission was associated with higher severity of illness but lower in-ICU case fatality.

Cost comparisons and factors related to cost per stay in intensive care units in Belgium

BACKGROUND

Given the variability of intensive care unit (ICU) costs in different countries and the importance of this information for guiding clinicians to effective treatment and to the organisation of ICUs at the national level, it is of value to gather data on this topic for analysis at the national level in Belgium. The objectives of the study were to assess the total cost of ICUs and the factors that influence the cost of ICUs in hospitals in Belgium.

METHODS

This was a retrospective cohort study using data collected from the ICUs of 17 Belgian hospitals from January 01 to December 31, 2018. A total of 18,235 adult ICU stays were included in the study. The data set was a compilation of inpatient information from analytical cost accounting of hospitals, medical discharge summaries, and length of stay data. The costs were evaluated as the expenses related to the management of hospital stays from the hospital's point of view. The cost from the hospital perspective was calculated using a cost accounting analytical methodology in full costing. We used multivariate linear regression to evaluate factors associated with total ICU cost per stay. The ICU cost was log-transformed before regression and geometric mean ratios (GMRs) were estimated for each factor.

RESULTS

The proportion of ICU beds to ward beds was a median [p25-p75] of 4.7% [4.4-5.9]. The proportion of indirect costs to total costs in the ICU was 12.1% [11.4-13.3]. The cost of nurses represented 57.2% [55.4-62.2] of direct costs and this was 15.9% [12.0-18.2] of the cost of nurses in the whole hospital. The median cost per stay was €4,267 [2,050-9,658] and was €2,160 [1,545-3,221] per ICU day. The main factors associated with higher cost per stay in ICU were Charlson score, mechanical ventilation, ECMO, continuous hemofiltration, length of stay, readmission, ICU mortality, hospitalisation in an academic hospital, and diagnosis of coma/convulsions or intoxication.

CONCLUSIONS

This study demonstrated that, despite the small proportion of ICU beds in relation to all services, the ICU represented a significant cost to the hospital. In addition, this study confirms that nursing staff represent a significant proportion of the direct costs of the ICU. Finally, the total cost per stay was also important but highly variable depending on the medical factors identified in our results.

Deconstructing the effects of stochasticity on transmission of hospital-acquired infections in ICUs

The inherent stochasticity in transmission of hospital-acquired infections (HAIs) has complicated our understanding of transmission pathways. It is particularly difficult to detect the impact of changes in the environment on acquisition rate due to stochasticity. In this study, we investigated the impact of uncertainty (epistemic and aleatory) on nosocomial transmission of HAIs by evaluating the effects of stochasticity on the detectability of seasonality of admission prevalence. For doing so, we developed an agent-based model of an ICU and simulated the acquisition of HAIs considering the uncertainties in the behaviour of the healthcare workers (HCWs) and transmission of pathogens between patients, HCWs, and the environment. Our results show that stochasticity in HAI transmission weakens our ability to detect the effects of a change, such as seasonality patterns, on acquisition rate, particularly when transmission is a low-probability event. In addition, our findings demonstrate that data compilation can address this issue, while the amount of required data depends on the size of the said change and the degree of uncertainty. Our methodology can be used as a framework to assess the impact of interventions and provide decision-makers with insight about the minimum required size and target of interventions in a healthcare facility.

The effects of breast milk odor on the physiological and behavioral responses caused by venipuncture pain in term infants: A clinical trial study

BACKGROUND

Pain management is very important for infants who are unable to express it verbally. Pain control is one of the nursing actions and part of their duties. This study attempted to determine the effects of breast milk odor on the physiological and behavioral responses caused by venipuncture pain in full-term infants at an educational hospital.

MATERIALS AND METHODS

This randomized clinical trial study was carried out on 3-5 days' term and healthy babies with a gestational age of 34 weeks and later in the 9-Day Hospital of Torbet Heydariyeh, Iran, 2021. The sample size, taking into account the possibility of a 10% dropout of samples included 20 babies for each group and a total of 40 babies were selected by convenience sampling. To collect data, a checklist of demographic characteristics, a registration form for physiological responses, and the modified behavioral pain scale were used.

RESULTS

The results of this study showed that breast milk odor has a positive effect on behavioral responses (P < 0.001) and also a significant relationship was observed between the effects of breast milk odor and physiological responses percentage of oxygen uptake and pulse (P < 0.001). However, no significant relationship was observed between breast milk odor and breathing variables (P > 0.05).

CONCLUSIONS

According to the results, olfactory stimulation with breast milk during venous blood sampling showed positive effects on physiological responses and pain reduction in infants. Therefore, it is recommended to use soothing stimuli such as the smell of breast milk during painful procedures in babies.

Liver-Support Therapies in Critical Illness-A Comparative Analysis of Procedural Characteristics and Safety

Extracorporeal liver-support therapies remain controversial in critically ill patients, as most studies have failed to show an improvement in outcomes. However, heterogeneous timing and inclusion criteria, an insufficient number of treatments, and the lack of a situation-dependent selection of available liver-support modalities may have contributed to negative study results. We retrospectively investigated the procedural characteristics and safety of the three liver-support therapies CytoSorb, Molecular Adsorbent Recirculating System (MARS) and therapeutic plasma exchange (TPE). Whereas TPE had its strengths in a shorter treatment duration, in clearing larger molecules, affecting platelet numbers less, and improving systemic coagulation and hemodynamics, CytoSorb and MARS were associated with a superior reduction in particularly small protein-bound and water-soluble substances. The clearance magnitude was concentration-dependent for all three therapies, but additionally related to the molecular weight for CytoSorb and MARS therapy. Severe complications did not appear. In conclusion, a better characterization of disease-driving as well as beneficial molecules in critically ill patients with acute liver dysfunction is crucial to improve the use of liver-support therapy in critically ill patients. TPE may be beneficial in patients at high risk for bleeding complications and impaired liver synthesis and hemodynamics, while CytoSorb and MARS may be considered for patients in whom the elimination of smaller toxic compounds is a primary objective.

A risk nomogram for predicting prolonged intensive care unit stays in patients with chronic obstructive pulmonary disease

BACKGROUND

Providing intensive care is increasingly expensive, and the aim of this study was to construct a risk column line graph (nomograms)for prolonged length of stay (LOS) in the intensive care unit (ICU) for patients with chronic obstructive pulmonary disease (COPD).

METHODS

This study included 4,940 patients, and the data set was randomly divided into training (n = 3,458) and validation (n = 1,482) sets at a 7:3 ratio. First, least absolute shrinkage and selection operator (LASSO) regression analysis was used to optimize variable selection by running a tenfold k-cyclic coordinate descent. Second, a prediction model was constructed using multifactorial logistic regression analysis. Third, the model was validated using receiver operating characteristic (ROC) curves, Hosmer-Lemeshow tests, calibration plots, and decision-curve analysis (DCA), and was further internally validated.

RESULTS

This study selected 11 predictors: sepsis, renal replacement therapy, cerebrovascular disease, respiratory failure, ventilator associated pneumonia, norepinephrine, bronchodilators, invasive mechanical ventilation, electrolytes disorders, Glasgow Coma Scale score and body temperature. The models constructed using these 11 predictors indicated good predictive power, with the areas under the ROC curves being 0.826 (95%CI, 0.809-0.842) and 0.827 (95%CI, 0.802-0.853) in the training and validation sets, respectively. The Hosmer-Lemeshow test indicated a strong agreement between the predicted and observed probabilities in the training (χ2 = 8.21, p = 0.413) and validation (χ2 = 0.64, p = 0.999) sets. In addition, decision-curve analysis suggested that the model had good clinical validity.

CONCLUSION

This study has constructed and validated original and dynamic nomograms for prolonged ICU stay in patients with COPD using 11 easily collected parameters. These nomograms can provide useful guidance to medical and nursing practitioners in ICUs and help reduce the disease and economic burdens on patients.

Medical transformer for multimodal survival prediction in intensive care: integration of imaging and non-imaging data

When clinicians assess the prognosis of patients in intensive care, they take imaging and non-imaging data into account. In contrast, many traditional machine learning models rely on only one of these modalities, limiting their potential in medical applications. This work proposes and evaluates a transformer-based neural network as a novel AI architecture that integrates multimodal patient data, i.e., imaging data (chest radiographs) and non-imaging data (clinical data). We evaluate the performance of our model in a retrospective study with 6,125 patients in intensive care. We show that the combined model (area under the receiver operating characteristic curve [AUROC] of 0.863) is superior to the radiographs-only model (AUROC = 0.811, p < 0.001) and the clinical data-only model (AUROC = 0.785, p < 0.001) when tasked with predicting in-hospital survival per patient. Furthermore, we demonstrate that our proposed model is robust in cases where not all (clinical) data points are available.

Routine Versus On-Demand Blood Sampling in Critically Ill Patients: A Systematic Review

OBJECTIVES

We aimed to provide an overview of the current evidence on routine versus on-demand blood sampling in critical care. We assessed the reported proportion of patients exposed to daily routine blood sampling, the tests performed, characteristics associated with more frequent blood sampling, and the reported benefits and harms of routine blood sampling compared with on-demand sampling.

DATA SOURCES

We systematically searched the Cochrane Library, the Excerpta Medica Database, and the Medical Literature Analysis and Retrieval System Online for studies assessing routine versus on-demand blood testing in critically ill patients from inception to September 2022.

STUDY SELECTION

Abstracts and full texts were assessed independently and in duplicate by two reviewers.

STUDY EXTRACTION

Data were extracted independently and in duplicate by two reviewers using predefined extraction forms.

DATA SYNTHESIS

Of 12,212 records screened, 298 full-text articles were assessed for eligibility. We included 70 studies; 50 nonrandomized interventional studies and 20 observational studies. Exposure to routine blood testing was 52-100% (very low certainty of evidence). Blood testing seemed to occur more frequently in medical intensive care settings with a median of 18 blood tests per patient day (interquartile range, 10-33) (very low certainty of evidence). Mixed biochemistry seemed to be the most frequently performed blood tests across all settings (five tests per patient day; interquartile range, 2-10) (very low certainty of evidence). Reductions in routine blood testing seemed to be associated with reduced transfusion rates and costs without apparent adverse patient outcomes (low certainty of evidence).

CONCLUSIONS

In this systematic review, routine blood testing in critically ill patients was common and varied considerably. A reduction in routine blood testing appeared to be associated with reduced transfusion rates and costs without adverse effects, but the evidence was very uncertain.

Hospital Prices for Pediatric Tympanostomy Tube Placement and Adenotonsillectomy in 2021

OBJECTIVES

Hospital prices vary substantially for myringotomy with tympanostomy tube placement (M&T) and adenotonsillectomy (T&A). The Centers for Medicare and Medicaid Services recently implemented hospital price transparency requirements to help families make financially informed decisions about where to seek care. We sought to determine price availability and the extent of price variation for these procedures.

METHODS

We performed a cross-sectional analysis of the Turquoise Health Hospital Rates Data Platform, which extracts prices for facility fees from publicly available hospital chargemasters. We determined the proportion of hospitals serving pediatric patients that published payer-specific prices for M&T and T&A. We additionally characterized the extent of variation in payer-specific prices both across and within hospitals.

RESULTS

Approximately 40% (n = 909 of 2,266 hospitals) serving pediatric patients disclosed prices for M&T or T&A. Among disclosing hospitals, across-center ratios (adjusted for Medicare hospital wage indices) ranged from 11.0 (M&T; 10th percentile adjusted median price: $536.80 versus 90th percentile adjusted median price: $5,929.93) to 23.4 (revision adenoidectomy age >12 years; 10th percentile: $393.82 versus 90th percentile: $9,209.88). Median within-center price ratios for procedures ranged from 2.2 to 2.7, indicating that some private payers reimbursed the same hospital more than twice as much as other payers for the same procedure.

CONCLUSION

The majority of hospitals serving pediatric patients were non-compliant with federal requirements to disclose prices for M&T and T&A. Among disclosing hospitals, there was wide variation in payer-specific prices between and within institutions. Further research is necessary to understand whether disclosure of prices will enable families to make more financially informed decisions.

LEVEL OF EVIDENCE

3 Laryngoscope, 133:948-955, 2023.

Subjective Ratings of Mental and Physical Health Correlate With EQ-5D-5L Index Values in Survivors of Critical Illness: A Construct Validity Study

OBJECTIVES

Survivors of critical illness commonly show impaired health-related quality of life (HrQoL). We investigated if HrQoL can be approximated by brief, easily applicable items to be used in primary care.

DESIGN

Secondary analysis of data from the multicenter, cluster-randomized controlled Enhanced Recovery after Intensive Care trial ( ClinicalTrials.gov : NCT03671447) and construct validity study.

SETTING

Ten participating clusters of ICUs in the metropolitan area of Berlin, Germany.

PATIENTS

Eight hundred fifty ICU survivors enrolled in a mixed, medical or surgical ICU when they had an expected ICU length of stay of at least 24 hours, were at least 18 years old, and had statutory health insurance coverage.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Patients received follow-ups scheduled 3 and 6 months after ICU discharge. HrQoL was assessed with the EuroQol 5-Dimension 5-Level (EQ-5D-5L), and patients were asked to rate their current mental and physical health state from 0 (worst) to 10 (best). We fitted prediction models for the EQ-5D-5L index value using these two items and additional covariates, applying stepwise regression and adaptive lasso. Subjective mental health (Spearman: 0.59) and subjective physical health (Spearman: 0.68) correlated with EQ-5D-5L index values and were better predictors of EQ-5D-5L index values in the two-item regression (normalized root mean squared error [nRMSE] 0.164; normalized mean absolute error [nMAE] 0.118; R2adj 0.43) than the EQ-5D Visual Analog Scale (nRMSE 0.175; nMAE 0.124; R2adj 0.35). Stepwise regression with additional covariates further increased prediction performance (nRMSE 0.133; nMAE 0.1; R2adj 0.51).

CONCLUSIONS

Asking patients to rate their subjective mental and physical health can be an easily applicable tool for a first impression of the HrQoL in primary care settings.

Socioeconomic Burden of Critically Ill Patients: A Descriptive Study

Background The cost of critical illness treatment is generally recognized as expensive and increasing in India. Critical illness of the individual will affect the socioeconomic status of the individual and the family. The direct and indirect costs of intensive care and its impact on the socioeconomic status of critically ill patients and their families need to be estimated. The present study was carried out to evaluate the socioeconomic burden of critically ill patients admitted to ICUs in Eastern India. Methods A descriptive survey was conducted to measure the socioeconomic burden. One hundred fifteen critically ill patients and their family members were conveniently selected for the study. Critically ill patients admitted to ICUs and those who were bedridden for more than seven days along with anyone the family member, i.e., spouse, father, or mother, were included in the study to estimate the impact of long-term illness on the care providers in the family. Socio-demographic and socioeconomic burdens were analyzed through the interview method. Results Half (49.6%) of the critically ill patients were heads of the family, and their employment is the primary source of income for the family members. Most (60.9%) of the patients belonged to lower socioeconomic status. Critically ill patients spend a maximum (38169.6±3996.2) amount for pharmaceutical expenses. Eventually, the family members accompanying patients lost maximum working days because of the long length of hospital stay. Below upper-lower (p=0.046) class socioeconomic family, age less than 40 (p=0.018) years, and those families depending (p=0.003) on patients' income significantly reported higher socioeconomic burden. Conclusions Critical care hospitalization of patients increases the socioeconomic burden on the whole family, especially in lower-middle-income countries like India. It soberly affects younger age group patients with low socioeconomic status and families depending on the patient's income during their man days.

Trends in Incidences and Survival Rates in Pediatric In-Hospital Cardiopulmonary Resuscitation: A Korean Population-Based Study

Background Although the outcome of cardiopulmonary resuscitation (CPR) is still unsatisfactory, there are few studies about temporal trends of in-hospital CPR incidence and mortality. We aimed to evaluate nationwide trends of in-hospital CPR incidence and its associated risk factors and mortality in pediatric patients using a database of the Korean National Health Insurance between 2012 and 2018. Methods and Results We excluded neonates and neonatal intensive care unit admissions. Incidence of in-hospital pediatric CPR was 0.58 per 1000 admissions (3165 CPR/5 429 471 admissions), and the associated mortality was 50.4%. Change in CPR incidence according to year was not significant in an adjusted analysis (P=0.234). However, CPR mortality increased significantly by 6.6% every year in an adjusted analysis (P<0.001). Hospitals supporting pediatric critical care showed 37.7% lower odds of CPR incidence (P<0.001) and 27.5% lower odds of mortality compared with other hospitals in the adjusted analysis (P<0.001), and they did not show an increase in mortality (P for trend=0.882). Conclusions Temporal trends of in-hospital CPR mortality worsened in Korea, and the trends differed according to subgroups. Study results highlight the need for ongoing evaluation of CPR trends and for further CPR outcome improvement among hospitalized children.

Value-Based Care for Chest Physicians

Value-based care aims to improve the health outcomes of patients, eliminate waste and unwarranted clinical variation, and reduce the total cost of care. Professional medical societies have put forward guidelines to raise awareness on unproven practice patterns (Choosing Wisely Campaign), and payers have sought to replace the traditional fee-for-service payment models with value-based contracts that share financial gains or losses based on achieving high-quality outcomes and lowering the cost of care. Regardless of whether their practices are engaged in value-based arrangements, chest physicians should seek understanding of these principles, participate in designing and implementing practical and impactful high-value initiatives in their practices, and have a national voice on the path forward.

Comparative costs for critically ill patients with limited English proficiency versus English proficiency

OBJECTIVES

To conduct comparative cost analysis of hospital care for critically ill patients with Limited English Proficiency (LEP) versus patients with English proficiency (controls).

PATIENTS AND METHODS

We conducted a historical cohort study using propensity matching at Mayo Clinic Rochester, a quaternary care academic center. We included hospitalized patients who had at least one admission to ICU during a 10-year period between 1/1/2008-12/31/2017.

RESULTS

Due to substantial differences in baseline characteristics of the groups, propensity matching for the covariates age, sex, race, ethnicity, APACHE 3 score, and Charlson Comorbidity score was used, and we achieved the intended balance. The final cohort included 80,404 patients, 4,246 with LEP and 76,158 controls. Patients with LEP had higher costs during hospital admission to discharge, with a mean cost difference of $3861 (95% CI $822 to $6900, p = 0.013) and also higher costs during index ICU admission to hospital discharge, with a mean cost difference of $3166 (95% CI $231 to $6101, p = 0.035). A propensity matched cohort including only those that survived showed those with LEP had significantly greater mean costs for all outcomes. Sensitivity analysis revealed that international patients with LEP had significantly greater overall hospital costs of $9,240 than patients with LEP who resided in the US (95% CI $3341 to $15,140, p = 0.002).

CONCLUSION

This is the first study to demonstrate significantly higher costs for patients with LEP experiencing a critical illness. The causes for this may be increased healthcare utilization secondary to communication deficiencies that impede timely decision making about care.

High-fat low-carbohydrate enteral feeding enriched with olive oil and acute respiratory failure: A double-blind, randomized, controlled trial

BACKGROUND AND AIM

The study evaluated the impact of two types of high fat diet on the outcomes of acute pulmonary failure.

METHODS

A total of 93 Ventilated acute pulmonary failure patients with enteral feeding were assigned randomly to the control group with carbohydrate-based formula (protein: 20%, fat: 30%, carbohydrate: 50%) and two study groups with fat-based formula, including group A (protein: 20%, In equal proportions of olive and sunflower oil 45%, charbohydrate:35%) and group B (protein: 20%, sunflower oil:45%, charbohydrate:35%). The diets were prescribed for 14 days.

RESULTS

In each group, 16 patients completed the study. The PaCO2 decreased significantly in the study group A compared with the control group at weaning. The risk of separation from mechanical ventilation during study period was eight times higher in the study group A than the control group. On day 10 of intervention, serum hs-CRP decreased significantly in the control group and the study group A compared to the baseline. Serum concentration of total antioxidant capacity was increased significantly in the study group A on day 10 of the intervention, but in the other two groups it was reduced. Gastrointestinal complications, including diarrhea and high gastric residual volume, were not different between the groups.

CONCLUSION

With a fat-based diet high in olive oil, more patients were weaned during the study period. This diet reduced the PaCo₂ at weaning, reduced the serum level of hs-CRP, and increased the serum level of total antioxidant capacity concentration. Fat-based diet high in sunflower oil did not have any beneficial effects on outcomes.

Predicting length of stay in ICU and mortality with temporal dilated separable convolution and context-aware feature fusion

In healthcare, Intensive Care Unit (ICU) bed management is a necessary task because of the limited budget and resources. Predicting the remaining Length of Stay (LoS) in ICU and mortality can assist clinicians in managing ICU beds efficiently. This study proposes a deep learning method based on several successive Temporal Dilated Separable Convolution with Context-Aware Feature Fusion (TDSC-CAFF) modules, and a multi-view and multi-scale feature fusion for predicting the remaining LoS and mortality risk for ICU patients. In each TDSC-CAFF module, temporal dilated separable convolution is used to encode each feature separately, and context-aware feature fusion is proposed to capture comprehensive and context-aware feature representations from the input time-series features, static demographics, and the output of the last TDSC-CAFF module. The CAFF outputs of each module are accumulated to achieve multi-scale representations with different receptive fields. The outputs of TDSC and CAFF are concatenated with skip connection from the output of the last module and the original time-series input. The concatenated features are processed by the proposed Point-Wise convolution-based Attention (PWAtt) that captures the inter-feature context to generate the final temporal features. Finally, the final temporal features, the accumulated multi-scale features, the encoded diagnosis, and static demographic features are fused and then processed by fully connected layers to obtain prediction results. We evaluate our proposed method on two publicly available datasets: eICU and MIMIC-IV v1.0 for LoS and mortality prediction tasks. Experimental results demonstrate that our proposed method achieves a mean squared log error of 0.07 and 0.08 for LoS prediction, and an Area Under the Receiver Operating Characteristic Curve of 0.909 and 0.926 for mortality prediction, on eICU and MIMIC-IV v1.0 datasets, respectively, which outperforms several state-of-the-art methods.

Residency Program Responses to Early COVID-19 Surges Highlight Tension as to Whether Residents Are Learners or Essential Workers

PURPOSE

To quantify the extent to which internal medicine (IM) residents provided care for patients with COVID-19 and examine characteristics of residency programs with or without plans (at some point) to exclude residents from COVID-19 care during the first 6 months of the pandemic.

METHOD

The authors used data from a nationally representative, annually recurring survey of U.S. IM program directors (PDs) to quantify early (March-August 2020) resident participation in COVID-19 care. The survey was fielded from August to December 2020. PDs reported whether they had planned to exclude residents from COVID-19 care (i.e., PTE status). PTE status was tested for association with program and COVID-19 temporal characteristics, resident schedule accommodations, and resident COVID-19 cases.

RESULTS

The response rate was 61.5% (264/429). Nearly half of PDs (45.4%, 118/260) reported their program had planned at some point to exclude residents from COVID-19 care. Northeastern U.S. programs represented a smaller percentage of PTE than non-PTE programs (26.3% vs 36.6%; P = .050). PTE programs represented a higher percentage of programs with later surges than non-PTE programs (33.0% vs 13.6%, P = .048). Median percentage of residents involved in COVID-19 care was 75.0 (interquartile range [IQR]: 22.5-100.0) for PTE programs, compared with 95.0 (IQR: 60.0-100.0) for non-PTE programs ( P < .001). Residents participated most in intensive care units (87.6%, 227/259) and inpatient wards (80.8%, 210/260). Accommodations did not differ by PTE status. PTE programs reported fewer resident COVID-19 cases than non-PTE programs (median percentage = 2.7 [IQR: 0.0-8.6] vs 5.1 [IQR: 1.6-10.7]; P = .011).

CONCLUSIONS

IM programs varied widely in their reported plans to exclude residents from COVID-19 care during the early pandemic. A high percentage of residents provided COVID-19 care, even in PTE programs. Thus, the pandemic highlighted the tension as to whether residents are learners or employees.

Predicting medical events and ICU requirements using a multimodal multiobjective transformer network

Effective utilization of premium hospital resources such as intensive care unit (ICU), operating theater (OT), mechanical ventilator, endotracheal tube, and so on plays a significant role in providing high-quality care to critically ill patients within reasonable costs. Non-availability of specialized resources can lead to dire consequences for such patients, and in the worst case, may even turn out to be fatal. However, these resources cannot be kept idle, as they are expensive to maintain. Therefore, one of the core functions of hospital management is targeted at planning and managing these critical resources in order to provide efficient and effective health-care services to the end-users. Predictive technologies play a big role in this. In this article, we present methods for predicting the length of stay in ICU as well as the need for critical interventions for a patient based on the vital signs, laboratory measurements, and the nursing notes of the patient prepared within the first 24 h of ICU stay. The model has been built and cross-validated on the publicly available Medical Information Mart for Intensive Care (MIMIC-III v1.4) data set. We show that the proposed model performs way better than most of the earlier models in the prediction of ICU stay, which had used patient vitals primarily. Experimental results also demonstrate the advantage of using a multiobjective model over independent models for the prediction of ICU stay and critical interventions. The proposed model uses Local Interpretable Model-agnostic Explanations (LIME) that help in identifying the features responsible for predictive decisions. This is very useful in building trust and confidence in the prediction model among clinical practitioners.

Post-Intensive Care Syndrome after Critical Illness: An Imperative for Effective Prevention

Over the last decades, the importance of intensive care has considerably increased [...].

Telemedicine to Expand Access to Critical Care Around the World

This multiauthored communication gives a state-of-the-art global perspective on the increasing adoption of tele-critical care. Exponentially increasing sophistication in the deployment of Computers, Information, and Communication Technology has ensured extending the reach of limited intensivists virtually and reaching the unreached. Natural disasters, COVID-19 pandemic, and wars have made tele-intensive care a reality. Concerns and regulatory issues are being sorted out, cross-border cost-effective tele-critical care is steadily increasing Components to set up a tele-intensive care unit, and overcoming barriers is discussed. Importance of developing best practice guidelines and retraining is emphasized.

Prognostic Model of ICU Admission Risk in Patients with COVID-19 Infection Using Machine Learning

With the onset of the COVID-19 pandemic, the number of critically sick patients in intensive care units (ICUs) has increased worldwide, putting a burden on ICUs. Early prediction of ICU requirement is crucial for efficient resource management and distribution. Early-prediction scoring systems for critically ill patients using mathematical models are available, but are not generalized for COVID-19 and Non-COVID patients. This study aims to develop a generalized and reliable prognostic model for ICU admission for both COVID-19 and non-COVID-19 patients using best feature combination from the patient data at admission. A retrospective cohort study was conducted on a dataset collected from the pulmonology department of Moscow City State Hospital between 20 April 2020 and 5 June 2020. The dataset contains ten clinical features for 231 patients, of whom 100 patients were transferred to ICU and 131 were stable (non-ICU) patients. There were 156 COVID positive patients and 75 non-COVID patients. Different feature selection techniques were investigated, and a stacking machine learning model was proposed and compared with eight different classification algorithms to detect risk of need for ICU admission for both COVID-19 and non-COVID patients combined and COVID patients alone. C-reactive protein (CRP), chest computed tomography (CT), lung tissue affected (%), age, admission to hospital, and fibrinogen parameters at hospital admission were found to be important features for ICU-requirement risk prediction. The best performance was produced by the stacking approach, with weighted precision, sensitivity, F1-score, specificity, and overall accuracy of 84.45%, 84.48%, 83.64%, 84.47%, and 84.48%, respectively, for both types of patients, and 85.34%, 85.35%, 85.11%, 85.34%, and 85.35%, respectively, for COVID-19 patients only. The proposed work can help doctors to improve management through early prediction of the risk of need for ICU admission of patients during the COVID-19 pandemic, as the model can be used for both types of patients.

Elective Endovascular Treatment of Unruptured Intracranial Aneurysms

Background

Elective endovascular treatment (EVT) of unruptured intracranial aneurysms (UIA) is a commonly used treatment modality. However, the appropriate post-procedure management is not well-defined.

Methods

This was a single-center, retrospective review of all adults undergoing EVT of UIA performed between January 1, 2010, and March 31, 2020. Patients with any current intracranial hemorrhage or clinical symptoms severe enough to warrant emergent intervention were excluded.

Results

Sixty-seven UIA were treated on 58 patients. The mean dome diameter was 6.6 mm (2-20, ±3.9), the most common parent vessel was the internal carotid artery (43.2%, 29/67), and sole flow diverter stents were the most common device used (46.2%, 31/67). Post-treatment, 43.2% (29/67) patients went to the neurocritical care unit (NCCU). The mean NCCU length of stay (LOS) was 1.07 days (range 1-4, ±0.5), and 96.6% (28/29) only spent one day in the NCCU.  There were no (0%, 0/67) anesthesia-related procedural complications. One (1.5%, 1/67) intra-procedural complication was an aneurysm rupture during attempted coiling. There were five (7.4%, 5/67) post-procedural complications: two (3.0%, 2/67) groin hematomas, two (3.0%, 2/67) permanent neurologic events (left lower extremity hypoesthesia and left upper extremity hemiparesis), and one (1.5%, 1/67) temporary neurologic event (aphasia). Post-procedural complications were associated with longer hospital LOS (p=0.02), but not with longer NCCU LOS. No acute management changes occurred for the five patients that developed post-procedural complications. There were no (0%, 0/67) 30-day readmissions.

Conclusion

The overall incidence of post-procedure complications was low. In the future, a possible viable way to reduce hospital costs may involve utilizing a hospital unit that could closely monitor patients but only for a short period of time post-procedure.

Administrative Data Is Insufficient to Identify Near-Future Critical Illness: A Population-Based Retrospective Cohort Study

Background

Prediction of future critical illness could render it practical to test interventions seeking to avoid or delay the coming event.

Objective

Identify adults having >33% probability of near-future critical illness.

Research Design

Retrospective cohort study, 2013-2015.

Subjects

Community-dwelling residents of Manitoba, Canada, aged 40-89 years.

Measures

The outcome was a near-future critical illness, defined as intensive care unit admission with invasive mechanical ventilation, or non-palliative death occurring 30-180 days after 1 April each year. By dividing the data into training and test cohorts, a Classification and Regression Tree analysis was used to identify subgroups with ≥33% probability of the outcome. We considered 72 predictors including sociodemographics, chronic conditions, frailty, and health care utilization. Sensitivity analysis used logistic regression methods.

Results

Approximately 0.38% of each yearly cohort experienced near-future critical illness. The optimal Tree identified 2,644 mutually exclusive subgroups. Socioeconomic status was the most influential variable, followed by nursing home residency and frailty; age was sixth. In the training data, the model performed well; 41 subgroups containing 493 subjects had ≥33% members who developed the outcome. However, in the test data, those subgroups contained 429 individuals, with 20 (4.7%) experiencing the outcome, which comprised 0.98% of all subjects with the outcome. While logistic regression showed less model overfitting, it likewise failed to achieve the stated objective.

Conclusions

High-fidelity prediction of near-future critical illness among community-dwelling adults was not successful using population-based administrative data. Additional research is needed to ascertain whether the inclusion of additional types of data can achieve this goal.

Association between nursing cost and patient outcomes in intensive care units: A retrospective cohort study of Belgian hospitals

INTRODUCTION

Hospitals with better nursing resources report more favourable patient outcomes with almost no difference in cost as compared to those with worse nursing resources. The aim of this study was to assess the association between nursing cost per intensive care unit bed and patient outcomes (mortality, readmission, and length of stay).

METHODOLOGY

This was a retrospective cohort study using data collected from the intensive care units of 17 Belgian hospitals from January 01 to December 31, 2018. Hospitals were dichotomized using median annual nursing cost per bed. A total of 18,235 intensive care unit stays were included in the study with 5,664 stays in the low-cost nursing group and 12,571 in the high-cost nursing group.

RESULTS

The rate of high length of stay outliers in the intensive care unit was significantly lower in the high-cost nursing group (9.2% vs 14.4%) compared to the low-cost nursing group. Intensive care unit readmission was not significantly different in the two groups. Mortality was lower in the high-cost nursing group for intensive care unit (9.9% vs 11.3%) and hospital (13.1% vs 14.6%) mortality. The nursing cost per intensive care bed was different in the two groups, with a median [IQR] cost of 159,387€ [140,307-166,690] for the low-cost nursing group and 214,032€ [198,094-230,058] for the high-cost group. In multivariate analysis, intensive care unit mortality (OR = 0.80, 95% CI: 0.69-0.92, p < 0.0001), in-hospital mortality (OR = 0.82, 95% CI: 0.72-0.93, p < 0.0001), and high length of stay outliers (OR = 0.48, 95% CI: 0.42-0.55, p < 0.0001) were lower in the high-cost nursing group. However, there was no significant effect on intensive care readmission between the two groups (OR = 1.24, 95% CI: 0.97-1.51, p > 0.05).

CONCLUSIONS

This study found that higher-cost nursing per bed was associated with significantly lower intensive care unit and in-hospital mortality rates, as well as fewer high length of stay outliers, but had no significant effect on readmission to the intensive care unit. .

Is the Critical Care Resuscitation Unit Sustainable: A 5-Year Experience of a Beneficial and Novel Model

Background. The 6-bed critical care resuscitation unit (CCRU) is a unique and specialized intensive care unit (ICU) that streamlines the interhospital transfer (IHT—transfer between different hospitals) process for a wide range of patients with critical illness or time-sensitive disease. Previous studies showed the unit successfully increased the number of ICU admissions while reducing the time of transfer in the first year of its establishment. However, its sustainability is unknown. Methods. This was a descriptive retrospective analysis of adult, non-trauma patients who were transferred to an 800-bed quaternary medical center. Patients transferred to our medical center between January 1, 2014 and December 31, 2018 were eligible. We used interrupted time series (ITS) and descriptive analyses to describe the trend and compare the transfer process between patients who were transferred to the CCRU versus those transferred to other adult inpatient units. Results. From 2014 to 2018, 50,599 patients were transferred to our medical center; 31,582 (62%) were non-trauma adults. Compared with the year prior to the opening of the CCRU, ITS showed a significant increase in IHT after the establishment of the CCRU. The CCRU received a total of 7,788 (25%) IHTs during this period or approximately 20% of total transfers per year. Most transfers (41%) occurred via ground. Median and interquartile range [IQR] of transfer times to other ICUs (156 [65–1027] minutes) were longer than the CCRU (46 [22–139] minutes, $P<0.001$ ). For the CCRU, the most common accepting services were cardiac surgery (16%), neurosurgery (11%), and emergency general surgery (10%). Conclusions. The CCRU increases the overall number of transfers to our institution, improves patient access to specialty care while decreasing transfer time, and continues to be a sustainable model over time. Additional research is needed to determine if transferring patients to the CCRU would continue to improve patients’ outcomes and hospital revenue.

Patients With Acute Coronary Syndromes Admitted to Contemporary Cardiac Intensive Care Units: Insights From the CCCTN Registry

BACKGROUND:

With the improvement in outcomes for acute coronary syndrome (ACS), the practice of routine admission to cardiac intensive care units (CICUs) is evolving. We aimed to describe the epidemiology of patients with ACS admitted to contemporary CICUs.

METHODS:

Using the CCCTN (Critical Care Cardiology Trials Network) Registry for consecutive medical CICU admissions across 26 advanced CICUs in North America between 2017 and 2020, we identified patients with a primary diagnosis of ACS at CICU admission and compared patient characteristics, resource utilization, and outcomes to patients admitted with a non-ACS diagnosis and across sub-populations of patients with ACS, including by indication for CICU admission.

RESULTS:

Of 10 118 CICU admissions, 29.4% (n=2978) were for a primary diagnosis of ACS, with significant interhospital variability (range, 13.4%–56.6%). Compared with patients admitted with a diagnosis other than ACS, patients with ACS had fewer comorbidities, lower acute severity of illness with less utilization of advanced CICU therapies (41.3% versus 66.1%, P <0.0001), and lower CICU mortality (5.4% versus 9.9%, P <0.0001). Monitoring alone, without another CICU indication at the time of admission, was the most frequent admission indication in patients with ACS (53.8%); less common indications in patients with ACS included respiratory insufficiency, shock, or the need for vasoactive therapy. Of patients with ACS admitted for monitoring alone, 94.8% did not subsequently require advanced intensive care unit therapies and had a low CICU length of stay (1.5 days [0.9–2.4] versus 2.6 [1.4–5.1], P <0.0001) and CICU mortality (0.6% versus 11.0%, P <0.0001), compared with patients with ACS with an admission indication beyond monitoring.

CONCLUSIONS:

In a registry of tertiary care CICUs, ACS represent ≈1/3 of all admissions with significant variability across hospitals. More than half of the ACS admissions to the CICU were for routine monitoring alone, with a low rate of complications and mortality. This observation highlights an opportunity for prospective studies to refine triage strategies for lower risk patients with ACS.