Type Of Intensive Care Unit Research Articles

Comparing Outcomes and Infection Risk in Medical, Surgical, and Trauma Intensive Care Patients with Alcohol Use Disorder.

Introduction: Alcohol is the most frequently abused drug in the United States, and alcohol use disorder (AUD) is a common comorbidity in intensive care units (ICUs). Patients and Methods: We performed a retrospective chart review of patients admitted to an ICU between January 2017 and March 2019 at a tertiary hospital serving a large rural population. Patients with diagnoses of AUDs were included. Patients were excluded if they did not require ICU care. Patient demographics, hospital course, infection type, culture results, and mortality were evaluated. We compared medical, surgical, and trauma ICU patient outcomes and infections. Results: In total, 527 patients met inclusion and exclusion criteria. Trauma ICU patients had the least pre-existing comorbidities, and surgical ICU patients had the longest lengths of stay. There was no difference in in-hospital mortality between ICU groups; however, surgical and medical ICU patients had significantly greater rates of in-hospital mortality compared with trauma ICU patients. Infections were common across all ICU types, occurring in 40% of patients. There was no difference in infection rate between ICU types. In multi-variable analysis controlling for age, gender, liver failure, chronic kidney disease, thrombocytopenia, complications, and blood transfusions, infection remained an independent predictor of in-hospital mortality (adjusted odds ratio 3.3, 95% confidence interval 1.7-6.4). Septic shock occurred in 57% of infections and was associated with an increased risk of mortality (38% vs. 2%, p < 0.001). Pneumonia was the most common infection occurring in 28% of the cohort, followed by bacteremia (7%), skin/soft tissue infections (6%), urinary tract infection (5%), intra-abdominal infections (4%), and C. difficile (2%). Conclusions: AUDs in all types of ICU patients are associated with high rates of infections and high morbidity and mortality.

Association Between the Ultrasound Evaluation of Muscle Mass and Adverse Outcomes in Critically Ill Patients: A Prospective Cohort Study.

Computed tomography (CT)-derived low muscle mass is associated with adverse outcomes in critically ill patients. Muscle ultrasound is a promising strategy for quantitating muscle mass. We evaluated the association between baseline ultrasound rectus femoris cross-sectional area (RF-CSA) and intensive care unit (ICU) mortality. Secondary outcomes were the determinants of RF-CSA, and the diagnostic performance of RF-CSA after adjustment for body size. A prospective, single-center, observational cohort study was conducted in 3 ICUs (general, neuroscience, coronavirus disease-2019 [COVID-19]) of a university-affiliated hospital. Consecutive, mechanically ventilated patients with predicted length of stay >72 hours were included. RF-CSA was assessed at the dominant leg by ultrasound. Association with ICU mortality was tested using multivariable logistic regression. Diagnostic performance of RF-CSA was compared after adjustment by sex (CSA-sex), body surface area (CSA-BSA), and squared height (CSA-H2). A total of 316 patients were enrolled: age 69 [60-76], 211 men and 183 ICU survivors. Older age (odds ratio, OR [95% confidence interval, CI], 1.03 [1.01-1.05]), the type of ICU (neuroscience: 0.82 [0.38-1.79], COVID-19: 4.1 [2.01-8.38]), a higher modified Nutrition and Rehabilitation Investigators Consortium (NUTRIC) score (1.43 [1.21-1.70]), and a lower RF-CSA (0.41 [0.29-0.58]) were associated with ICU mortality. Baseline RF-CSA was lower in women, with higher nutritional risk, older age, and larger body size. Unadjusted RF-CSA had an area under the receiver operating characteristic (ROC) curve for ICU mortality of 0.720 [0.663-0.776], and this value was not significantly different from that of CSA-sex, CSA-BSA, and CSA-H2 (P = .1487). Low baseline RF-CSA was associated with increased ICU mortality. Admission RF-CSA was lower in women, with high nutritional risk, in older subjects and with lower body size. Absolute muscle mass was significantly associated with mortality, with no significant increase in this relationship when adjusting for sex or body size.

Knowledge, attitudes and practices of intensive care unit physicians towards the management of acute respiratory distress syndrome in China: a cross-sectional survey

ObjectivesThis study aimed to assess the knowledge, attitudes and practices (KAP) of intensive care unit (ICU) physicians in China towards acute respiratory distress syndrome (ARDS).DesignA cross-sectional study was conducted between...

How emotional contagion shapes spiritual care competence: Insights from a cross-sectional study on intensive care nurses.

Intensive care units (ICUs) are environments where nurses are open to emotional interactions because of complex structures and dynamic relationships. Nurses' susceptibility to emotional contagion and their spiritual care competence may affect the quality of care by influencing their ability to manage and respond to the emotional dynamics present in these environments. This study aimed to determine the level of emotional contagion and spiritual care competence in intensive care nurses. This study is a descriptive cross-sectional study conducted with 199 nurses working in the ICUs of a training and research hospital in Turkey. The data were collected between December 2021 and June 2022 using the Emotional Contagion Scale (ECS) and the Spiritual Care Competence Scale (SCCS). The mean score of the nurses was 50.29 ± 15.36 on the ECS and 90.29 ± 29.53 on the SCCS. A statistically significant difference was found between the ECS and SCCS and gender, marital status, weekly working hours and some approaches about spiritual care (p < .05). It was determined that there was a statistically significant positive correlation between the total scales and sub-dimensions of the ECS and SCCS (p < .05). In this study, it was found that intensive care nurses' susceptibility to emotional contagion was high, and that their spiritual care competence was at a moderate level. The results show that gender, marital status, weekly working hours, type of ICU and some approaches about spiritual care are crucial factors in nurses' emotional contagion and spiritual care competence. In addition, as the intensive care nurses' susceptibility to emotional contagion increased, their spiritual care competence also increased. The results of this study will guide the planning of interventions to protect intensive care nurses from the negative effects of emotional contagion and increase their spiritual care competence. It is necessary to protect intensive care nurses from the negative effects of emotional contagion and to increase their competences in spiritual care.

Machine Learning-Based Predictions of Mortality and Readmission in Type 2 Diabetes Patients in the ICU

Prognostic outcomes for patients with type 2 diabetes in the intensive care unit (ICU), including mortality and readmission rates, are critical for informed clinical decision-making. Although existing research has established a link between type 2 diabetes and adverse outcomes in the ICU, the potential of machine learning techniques for enhancing predictive accuracy has not been fully realized. This study seeks to develop and validate predictive models employing machine learning algorithms to forecast mortality and 30-day post-discharge readmission rates among ICU type 2 diabetes patients, thereby enhancing predictive accuracy and supporting clinical decision-making. Data were extracted and preprocessed from the MIMIC-III database, focusing on 14,222 patients with type 2 diabetes and their corresponding ICU admission records. Comprehensive information, including vital signs, laboratory results, and demographic characteristics, was utilized. Six machine learning algorithms—bagging, AdaBoost, GaussianNB, logistic regression, MLP, and SVC—were developed and evaluated using 10-fold cross-validation to predict mortality at 3 days, 30 days, and 365 days, as well as 30-day post-discharge readmission rates. The machine learning models demonstrated strong predictive performance for both mortality and readmission rates. Notably, the bagging and AdaBoost models showed superior performance in predicting mortality across various time intervals, achieving AUC values up to 0.8112 and an accuracy of 0.8832. In predicting 30-day readmission rates, the MLP and AdaBoost models yielded the highest performance, with AUC values reaching 0.8487 and accuracy rates of 0.9249. The integration of electronic health record data with advanced machine learning techniques significantly enhances the accuracy of mortality and readmission predictions in ICU type 2 diabetes patients. These models facilitate the identification of high-risk patients, enabling timely interventions, improving patient outcomes, and demonstrating the significant potential of machine learning in clinical prediction and decision support.

Clinical vs. autopsy diagnostic discrepancies in the intensive care unit: a systematic review and meta-analysis of autopsy series.

The aim of this study was to assess whether there is a discrepancy between clinical and autopsy-based diagnoses in adult intensive care unit (ICU) patients. We conducted a systematic review of cohort studies reporting on conventional autopsy-confirmed missed diagnoses. The discrepancy rate was per study calculated by dividing the number of patients with a missed diagnosis by the number of autopsies. Missed diagnoses were classified according to the Goldman classification as 'major' and 'minor' with major missed diagnoses further differentiated into Class I missed diagnoses (i.e., diagnoses that may have altered therapy or survival) and Class II missed diagnoses (i.e., diagnoses that would not have altered therapy or survival). Class I missed diagnoses constitute the primary outcome of interest. Pooled estimates for discrepancy rates (95% confidence intervals) were calculated using a mixed-effects logistic regression model with 'study' as random effect. Meta-regression was used to assess relationships between major discrepancy rates and autopsy rates, start year of study, and ICU type. Forty-two studies were identified totaling 6305 analyzed autopsies and 1759 patients with missed diagnoses. The pooled discrepancy rates for Class I and major missed diagnoses were 6.5% (5-8.5) and 19.3% (15.3-24), respectively. Meta-regression analysis revealed that autopsy rate was inversely associated with discrepancy rate. Class I discrepancy rates did not change over time. Burn and trauma ICUs had lower discrepancy rates as compared to medical ICUs, possibly because of higher autopsy rates. Missed diagnoses remain common in ICUs. A higher autopsy rate does not reveal more major diagnostic errors. These data support a clinically driven autopsy policy rather than a systematic autopsy policy.

Alarm Management in Provisional COVID-19 Intensive Care Units: Retrospective Analysis and Recommendations for Future Pandemics.

In response to the high patient admission rates during the COVID-19 pandemic, provisional intensive care units (ICUs) were set up, equipped with temporary monitoring and alarm systems. We sought to find out whether the provisional ICU setting led to a higher alarm burden and more staff with alarm fatigue. We aimed to compare alarm situations between provisional COVID-19 ICUs and non-COVID-19 ICUs during the second COVID-19 wave in Berlin, Germany. The study focused on measuring alarms per bed per day, identifying medical devices with higher alarm frequencies in COVID-19 settings, evaluating the median duration of alarms in both types of ICUs, and assessing the level of alarm fatigue experienced by health care staff. Our approach involved a comparative analysis of alarm data from 2 provisional COVID-19 ICUs and 2 standard non-COVID-19 ICUs. Through interviews with medical experts, we formulated hypotheses about potential differences in alarm load, alarm duration, alarm types, and staff alarm fatigue between the 2 ICU types. We analyzed alarm log data from the patient monitoring systems of all 4 ICUs to inferentially assess the differences. In addition, we assessed staff alarm fatigue with a questionnaire, aiming to comprehensively understand the impact of the alarm situation on health care personnel. COVID-19 ICUs had significantly more alarms per bed per day than non-COVID-19 ICUs (P<.001), and the majority of the staff lacked experience with the alarm system. The overall median alarm duration was similar in both ICU types. We found no COVID-19-specific alarm patterns. The alarm fatigue questionnaire results suggest that staff in both types of ICUs experienced alarm fatigue. However, physicians and nurses who were working in COVID-19 ICUs reported a significantly higher level of alarm fatigue (P=.04). Staff in COVID-19 ICUs were exposed to a higher alarm load, and the majority lacked experience with alarm management and the alarm system. We recommend training and educating ICU staff in alarm management, emphasizing the importance of alarm management training as part of the preparations for future pandemics. However, the limitations of our study design and the specific pandemic conditions warrant further studies to confirm these findings and to explore effective alarm management strategies in different ICU settings.

Impact of Capacity Strain on the Health Status of Patients Discharged From an Intensive Care Unit

Intensive care units (ICUs) play a vital role in hospitals and often experience capacity strain. Using data from a large teaching hospital, we empirically examine the effect of ICU capacity strain on patient discharge. We find that capacity strain has no effect on the health status of discharged patients and that capacity strain leads to a shorter length-of-stay in the ICU, but the magnitude of the effect is less than half a day in the most extreme scenarios. In post-hoc analyses, we find evidence the discharge process is expedited by starting discharges earlier in the day when capacity is strained, demonstrating that more efficient discharges can free up space without compromising patient health. In addition, we find a decrease in patient admissions during periods of capacity strain. To our knowledge, this is the first study to examine the direct relationship between ICU capacity strain and patient health at discharge, and it builds on the existing literature that has examined the effects of ICU capacity strain on proxies for patient health at discharge. We advocate that hospitals use outcome measures based on patient status at discharge to accurately assess the impact of capacity strain on quality of care. In addition, our work highlights the need for tailored research approaches and management practices for different types of ICUs, as generalizing the impact of ICU capacity strain across different settings may lead to inaccuracies.

Characteristics, Complications, and Outcomes of Critical Illness in Patients with Parkinson Disease.

Adults with Parkinson disease (PD) are hospitalized at higher rates than age-matched controls, and these hospitalizations are associated with significant morbidity. However, little is known about the consequences of critical illness requiring intensive care unit (ICU)-level care in patients with PD. The aim of this study was to define the characteristics and outcomes of adults with PD admitted to the ICU. We performed a retrospective nested case-control study using the Medical Information Mart for Intensive Care IV data set. Adults with PD were identified, and the index ICU admission for these subjects was matched 1:4 with index ICU admissions without a PD diagnosis based on age, sex, comorbidities, illness severity, ICU type, and need for mechanical ventilation. Primary outcomes were in-hospital mortality and discharge location. Secondary outcomes were length of stay and prespecified complications. A total of 630 adults with PD were identified. Patients with PD were older and were more likely to be male, have more comorbidities, and have higher illness severity at presentation. A matched analysis revealed adults with PD did not have a significant difference in in-hospital mortality but were more likely to be discharged to ahigher level of care. Adults with PD had longer hospital lengths of stay and increased odds of delirium, pressure ulcers, and ileus. During critical illness, patients with PD are at increased risk for longer hospital lengths of stay and complications and require a higher level of care at discharge than matched controls. These findings reveal targets for interventions to improve outcomes for patients with PD and may inform discussions about goals of care in this population.

The search for optimal nocturnal diurnal heart rate Index targets in ICU patients: a retrospective observational study from large ICU database.

Circadian rhythms play a crucial role in cardiovascular health, with the nocturnal diurnal heart rate index (NDHRI) reflecting significant circadian variations. However, the optimal NDHRI target in Intensive Care Unit (ICU) patients remains undefined. This study aims to establish an evidence-based NDHRI target range and assess its association with mortality. Data from the eICU Collaborative Research Database (n = 32,412) were analyzed. NDHRI was calculated by dividing cumulative nighttime heart rate area by daytime area. Generalized additive models (GAMs) explored the non-linear relationship between mean NDHRI and mortality, adjusting for confounders. Subgroup analyses were conducted based on ethnicity, ICU type, and comorbidities. A U-shaped association was observed between hospital mortality and mean NDHRI (P < 0.001). The optimal NDHRI range (40.0%-45.0%) demonstrated the lowest mortality rates. The duration spent within this range correlated inversely with mortality (P < 0.001). Subgroup analyses consistently supported these findings across diverse patient profiles. Our findings suggest an association between maintaining NDHRI within the 40.0%-45.0% range and lower mortality rates in critically ill patients, highlighting the potential utility of monitoring circadian heart rate variations in the ICU. Further research and future randomized controlled trials are essential to confirm causality and should consider this NDHRI range as a pivotal reference target.

Radiologic Evaluation of Oral Health Status in Patients Admitted to the Intensive Care Unit: A Multi-Institutional Retrospective Study.

Introduction: Surveys distributed among intensive care unit (ICU) nurses reveal a significant need for dental care, with many acknowledging poor oral hygiene management. Poor oral health in ICU patients is linked to systemic problems, including aspiration pneumonia, necessitating pre-intervention assessments for bacterial diseases and dental risks. This study aims to evaluate the oral health status of ICU patients across three institutions through retrospective analysis. Methods: This retrospective study assessed the oral health status of ICU patients, using computed tomography (CT) images from three institutions over ten years. Through CT images, the oral status was evaluated in terms of total and lost tooth count and the presence of oral lesions (periapical lesions, cysts and tumors, caries, tartar, moderate to severe periodontal bone loss, tooth fractures). Variables included gender, age, the duration of ICU stay, and types of ICU. Statistical analysis was performed using chi-square tests, independent-sample t-tests, and logistic regression analysis. Results: Of the 450 participants, 430 were analyzed, revealing a prevalence of oral lesions in 67.0% of subjects. The prevalence of oral lesions was higher in males (71.5%) than females (57.7%, p = 0.006), and higher in those aged 40 and above (72.1%) compared to those under the age of 40 (47.8%, p < 0.001). This study found significant differences in oral health status based on gender, age, and ICU type, with surgical ICU patients generally having better oral health. Risk factors for oral lesions included gender, age, and duration of ICU stay. Conclusions: Most ICU patients have at least one oral lesion, regardless of the reason for their ICU admission. In particular, male ICU patients aged 40 and above have a higher prevalence of oral lesions, necessitating careful oral health assessment and treatment.

The effectiveness of nurses’ psychosocial interventions for sensory deprivation in intensive care patients: a systematic review and meta-analysis

ObjectiveThis systematic review and meta-analysis aimed to assess the effectiveness of nurses’ psychosocial interventions for addressing sensory deprivation in intensive care units (ICUs).Materials and methodsA comprehensive search of PubMed, Web of Science, EBSCOhost, Google Scholar, CİNAHL, Embase, Cochrane Library, and YÖK Thesis Center databases was conducted from August 2023 to May 2024, without any temporal restrictions. In addition, a physical search was made in the university library for grey literature.ResultsThe study revealed that nurses’ psychosocial interventions significantly improved patients’ level of consciousness (SMD = 1.042, %95 CI = 0.716 to 1.369; Z = 6.25; p < .05) and sleep quality in ICUs (SMD=1.21, 95% CI= 0.232 to 1.810; Z = 2.49; p < .05). The effectiveness of psychosocial interventions varied based on the type of intervention, patient age, ICU type, patient group, and intervention duration. Notably, auditory stimuli and aromatherapy demonstrated particularly high effect sizes, significantly enhancing patients’ levels of consciousness and sleep quality.ConclusionIn conclusion, psychosocial interventions aimed at reducing sensory deprivation in intensive care units exert beneficial effects on individuals, notably enhancing their level of consciousness and improving sleep quality.

Workplace violence against physicians in intensive care units in Turkey: A cross-sectional study.

Background Although there are many studies on violence against physicians in the literature, there are few studies on violence against physicians working in intensive care units (ICUs). We aimed to investigate the frequency, type and underlying factors of violence against physicians working in ICUs in Turkey in the past 1 year. Methods We collected data by sending a questionnaire about violence against physicians working in ICUs via e-mail and WhatsApp between 1 and 15 May 2022. IBM SPSS Statistics V.24.0 was used for data analysis. The chi-square test and Fisher precision test were used to compare categorical data. Results Over one-third (38.6%) of the 354 physicians participating in our study reported that they had been exposed to violence in the past year, while 20.7% reported that they had been exposed to violence more than once in the past year. There was a significant relationship between the frequency of exposure to violence, female gender, age group, title, subspecialization status, working style and duration of working in the ICU (p<0.05). There was no relationship between the working area, type of hospital and ICU and exposure to violence (p>0.05). The presence of restriction and control points at the entrance to ICUs prevented violence (p<0.05). Conclusion Physicians working in ICUs encounter violence against them. The frequency of violence increased after the Covid-19 pandemic. A significant relationship was found between the frequency of violence and female gender, age group, title, subspecialization status, working style and duration of working in ICUs.

The Relationship Between Intensive Care Unit (ICU) Delirium Severity and 2-Year Mortality

Background:Delirium is an acute brain dysfunction characterized by altered cognition, attention, and level of consciousness. The presence of delirium is associated with increased risk of mortality, neurocognitive decline, and physical impairment; however, the role of ICU delirium severity in long-term health outcomes is less understood. Objective:Characterize the relationship between delirium severity and mortality risk in ICU survivors 2-years after discharge. Methods:A secondary analysis was performed on patient data collected in two randomized controlled trials (Pharmacological Management of Delirium and Deprescribing in the Pharmacologic Management of Delirium, 2009-2015). Participants received delirium assessments twice daily during hospitalization via the Confusion Assessment Method for the ICU (CAM-ICU-7). Patients enrolled at Eskenazi Hospital with complete mortality data were included in this study. Mean delirium severity was categorized as rapidly resolving (0-2), mild to moderate (2.1-5), or severe (&gt;5). Cox proportional hazard model was used to quantify mortality risk associated with delirium severity. Analyses were adjusted for patient demographics, comorbidities, and severity-of-disease. Results:The cohort (n=434) was 54.6% female and 48.6% African American with an average age of 59.8 (SD 16.4). The admission diagnosis was acute respiratory failure/sepsis in 47.9% of patients across medical (n=272), progressive (n=52), and surgical (n=110) ICU types. Approximately one third of the original cohort (n=143) died within 2 years of index discharge. In the multivariate analysis, patients with severe delirium (&gt;5) had nearly twice the adjusted hazard ratio for 2-year mortality compared to patients with mild-moderate delirium (aHR 2.1 [95% CI, 1.3-3.4] and aHR 1.1 [95% CI, 0.7-1.6], p=0.008). Conclusion:Severe delirium during ICU stay was significantly associated with increased 2-year mortality risk in comparison to mild-moderate (subsyndromal) delirium. Impact:The relationship between delirium severity and 2-year mortality underscores the need for further research on the mechanisms underlying ICU delirium and specific interventions to improve long-term outcomes.

Measuring the intensive care experience of intensive care unit patients: A cross-sectional study in western China

BackgroundThe negative experiences of intensive care unit (ICU) patients seriously affect their quality of life and survival outcomes. Thus, it is of great significance to evaluate the monitoring experience of ICU patients for the clinical improvement of their experiences and promote interventions. ObjectivesThe objective of this study was to investigate patients' experiences of ICU and to understand the sources of patient experience and influencing factors. MethodsFrom November 2021 to September 2022, a cross-sectional survey was conducted with 600 inpatients from four grade A–III hospitals in western China. Data were collected using the Chinese version of the Intensive Care Experience Questionnaire. Results585 valid questionnaires were collected, the response rate was 97.5%. ICU patients in western China scored below-the-average for their intensive care experience. Family monthly income, occupation types, medical payment method, type of ICU, ICU admission plan, ICU admission times, mechanical ventilation use, fertility status, analgesia, sedation, and Acute Physiology and Chronic Health Evaluation II scores are important factors influencing ICU patients' intensive care experience. ConclusionsMedical staff need to pay attention to patient experience, improve the awareness of patient stressors and influencing factors, design nursing programs conducive to patient-positive experience, and promote interventions to further improve the long-term prognosis of patients. The results of this study can also be used as a set of nursing-sensitive indicators for evaluating nursing structure, process, and outcomes.

2078. Comparison of Complication Types in Patients Receiving Vesicant Intravenous Antimicrobials or Vasopressors via Midlines and PICCs: A Retrospective Review

Abstract Background Peripherally inserted central catheters (PICC) are frequently used for long-term intravenous access in hospitalized patients; however, their use is associated with an increased risk of catheter-related bloodstream infection (CRBSI). Midline catheters (MC) have emerged as a potentially safer alternative and are associated with reduced rates of CRBSI but increased risk of thrombosis. Until recently, the use of several vasopressors and antibiotics via MC has been limited due to unknown adverse events. We aimed to compare the hazard ratios for CRBSI, thrombosis, catheter occlusion, and overall adverse events (AE) in adult intensive care unit (ICU) patients receiving vesicant antibiotics or vasopressors through PICC or MC. Methods We reviewed patients in 13 ICUs at one quaternary care center from April 2021 to September 2022 who received selected vesicant antibiotics (vancomycin, meropenem, and fluoroquinolones) or vasopressors through either PICC or MC. Patients who received both PICC and MC or other central access during the admission were excluded. Hazard ratios (HR) were compared using Kaplan-Meier survival curves and the log-long rank test. Cox regression was applied to adjust for potential confounding factors, including age, gender, ICU type (medical vs. surgical), duration of therapy, and length of stay. Results 445 patients (359 MCs, 86 PICCs) were included with 4,897 device days (3,910 MCs, 987 PICCs). Patient characteristics were similar across the two arms (Table 1). Figure 1 shows Kaplan-Meier survival estimate curves comparing PICC and MC. After adjusting for confounders (Table 2), the HR for CRBSI (0.86 [95% CI, 0.08 – 9.41)] and thrombosis (0.41 [95% CI, 0.09- 1.91]) were similar between the two devices. Compared to MC, PICCs were associated with higher occlusion rates (HR, 11.93 [95% CI, 2.97 – 47.89]). There were no significant differences in overall AE between the two groups (HR 1.72 [95% CI, 0.81 – 3.64]).Table 1:Characteristics of patients who received PICC or MC.MC: Midline Catheter; PICC: Peripherally Inserted Central Catheter; MICU: Medical Intensive Care Unit; SICU: Surgical Intensive Care Unit; DOT: Days of TherapyFigure 1:Kaplan-Meier Survival Estimate Curves Comparing PICC and MC. PICC: Peripherally Inserted Central Catheter; MC: Midline Catheter; The log-rank test was used for statistical significance.Table 2:Cox proportional-hazards multivariable model. DVT: Deep Vein Thrombosis; SVT: Superficial Vein Thrombosis; PICC: Peripherally Inserted Central Catheter; MC: Midline Catheter; SICU: Surgical Intensive Care Unit; MICU: Medical Intensive Care Unit; DOT: Days of Therapy; CI: 95% Confidence Interval Conclusion This study suggests similar infection and thrombosis hazards in ICU patients receiving vesicant antibiotics and vasopressors via PICC or MC. Notably, the study was not sufficiently powered to detect differences in outcomes. Larger studies are needed to assess the safety of administering these medications in MCs. Disclosures Sabra L. Shay, BSN, MPH, Premier Inc.: Employee

Abstract 13943: Comparison of the Frequency and Time to True Ventricular Tachycardia Among Patients in the Cardiac, Medical/Surgical and Neurologic Intensive Care Units

Introduction: Continuous ECG monitoring is the non-invasive gold standard used to identify ventricular tachycardia (VT), yet 87% of current bedside monitor VTs could be false. Therefore, knowing the burden of true VT is essential to guide treatment to those at greatest risk of poor outcomes. Hypothesis: When stratifying by intensive care unit (ICU) (cardiac, medical/surgical, neurological), there will be differences in: 1) demographic and clinical characteristics of patients with true VT; and 2) frequency and time to first true VT. Methods: Retrospective cohort study of adults admitted to an academic medical center ICU, 9/13-4/15. Potential VTs among 5,679 consecutive ICU patients were manually annotated by clinicians as true/false. Patient-level data were extracted from the health record. We used Kaplan-Meier and Cox proportional hazards methods to calculate time to first true VT and 60-day VT rate by ICU type. Results: There were differences in all characteristics examined (p&lt;0.0001)(Table) and frequency of true VT, stratified by ICU type (log-rank p&lt;0.0001)(Figure). After adjustment for age, gender, and risk factors (Table), CICU patients had a 42% increased rate (HR 1.42, 95% CI 1.16-1.74) and NICU patients had a 28% decreased rate of VT (HR 0.72, 95% CI 0.59-0.89) compared to M/SICU patients. Conclusion: Patients in the CICU experienced true VT much earlier (1.5 days) after admission than patients in the M/SICU and NICU. In addition, CICU patients had a higher rate of true VT and associated VT risk factors as compared to M/SICU and NICU patients. As expected, known cardiac risk factors are associated with true VT, but may be hidden among false alarms during bedside monitoring.

Prognostic Performance of Sequential Organ Failure Assessment, Acute Physiology and Chronic Health Evaluation III, and Simplified Acute Physiology Score II Scores in Patients with Suspected Infection According to Intensive Care Unit Type.

We investigated the prognostic performance of scoring systems by the intensive care unit (ICU) type. This was a retrospective observational study using data from the Marketplace for Medical Information in the Intensive Care IV database. The primary outcome was in-hospital mortality. We obtained Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation (APACHE) III, and Simplified Acute Physiology Score (SAPS) II scores in each ICU type. Prognostic performance was evaluated with the area under the receiver operating characteristic curve (AUROC) and was compared among ICU types. A total of 29,618 patients were analyzed, and the in-hospital mortality was 12.4%. The overall prognostic performance of APACHE III was significantly higher than those of SOFA and SAPS II (0.807, [95% confidence interval, 0.799-0.814], 0.785 [0.773-0.797], and 0.795 [0.787-0.811], respectively). The prognostic performance of SOFA, APACHE III, and SAPS II scores was significantly different between ICU types. The AUROC ranges of SOFA, APACHE III, and SAPS II were 0.723-0.826, 0.728-0.860, and 0.759-0.819, respectively. The neurosurgical and surgical ICUs had lower prognostic performance than other ICU types. The prognostic performance of scoring systems in patients with suspected infection is significantly different according to ICU type. APACHE III systems have the highest prediction performance. ICU type may be a significant factor in the prognostication.

Evaluation of medication regimen complexity as a predictor for mortality

While medication regimen complexity, as measured by a novel medication regimen complexity-intensive care unit (MRC-ICU) score, correlates with baseline severity of illness and mortality, whether the MRC-ICU improves hospital mortality prediction is not known. After characterizing the association between MRC-ICU, severity of illness and hospital mortality we sought to evaluate the incremental benefit of adding MRC-ICU to illness severity-based hospital mortality prediction models. This was a single-center, observational cohort study of adult intensive care units (ICUs). A random sample of 991 adults admitted ≥ 24 h to the ICU from 10/2015 to 10/2020 were included. The logistic regression models for the primary outcome of mortality were assessed via area under the receiver operating characteristic (AUROC). Medication regimen complexity was evaluated daily using the MRC-ICU. This previously validated index is a weighted summation of medications prescribed in the first 24 h of ICU stay [e.g., a patient prescribed insulin (1 point) and vancomycin (3 points) has a MRC-ICU = 4 points]. Baseline demographic features (e.g., age, sex, ICU type) were collected and severity of illness (based on worst values within the first 24 h of ICU admission) was characterized using both the Acute Physiology and Chronic Health Evaluation (APACHE II) and the Sequential Organ Failure Assessment (SOFA) score. Univariate analysis of 991 patients revealed every one-point increase in the average 24-h MRC-ICU score was associated with a 5% increase in hospital mortality [Odds Ratio (OR) 1.05, 95% confidence interval 1.02–1.08, p = 0.002]. The model including MRC-ICU, APACHE II and SOFA had a AUROC for mortality of 0.81 whereas the model including only APACHE-II and SOFA had a AUROC for mortality of 0.76. Medication regimen complexity is associated with increased hospital mortality. A prediction model including medication regimen complexity only modestly improves hospital mortality prediction.

Assessment of endotracheal aspirate culture appropriateness among adult ICU patients at an academic medical center

Background: Ventilator-associated pneumonia (VAP) is a significant cause of mortality in intensive care units (ICUs), but minimal research exists regarding the appropriateness of ordering endotracheal aspirate cultures (EACs). We evaluated the diagnostic utility of rationales given for EAC collection in ICUs at an academic medical center to assess potentially inappropriate EAC ordering. Methods: The study population comprised all adult patients admitted to an ICU in 2019 who underwent EAC collection. A random 10% sample from this population, stratified by ICU type, was selected. Clinical and diagnostic characteristics within 24 hours of EAC collection were identified by chart review. Clinical documentation was reviewed to identify ICU provider rationales for ordering EAC. Results: In total, 749 patients underwent EAC collection. Among them, 75 patients comprised the random sample, of whom 7 (9.3%) were excluded due to extubation before culture collection. Figure 1 shows patient distribution by ICU type. From these 68 patients, 105 EACs were collected. Of these, 41 (39%) were positive for potential pathogens, and 59 (56.2%) had explicit rationales for EAC collection, including fever (44.1%), hypoxia (18.6%), leukocytosis (16.9%), secretions (11.9%), shock (10.2%), and radiologic findings (8.5%). Also, 43.8% of EACs had no explicit rationale for collection. Table 1 shows sensitivities, specificities, positive likelihood ratios (LRs), and negative LRs for these rationales and related characteristics. Conclusions: EACs were commonly ordered without clear clinical indications. Of the noted rationales for EAC collections, most performed poorly at predicting positive cultures, which challenged common rationales for ordering EAC. This study could serve as a foundation for diagnostic stewardship interventions for EAC, potentially decreasing unnecessary cultures.Disclosures: None