Characteristics and Outcomes of Patients Discharged Directly Home from a Medical Intensive Care Unit

Introduction: Discharging patients directly home from the ICU is becoming increasingly common, largely driven by decreased ward bed availability. We evaluated readmission patterns of ICU patients discharged directly home. Methods: Retrospective review was conducted of direct discharges from the ICU to home between June 2017 and June 2019. The primary outcome of interest was 30-day hospital readmission. Patients were dichotomized by “wait-time” between transfer order and hospital discharge (\u3c24 hours or ≥24 hours). Outcomes were compared using t-test, Fisher exact, and chi-squared. Risk-adjustment was performed using the Mortality Probability Model (MPM0-III). ICU workload was estimated using the nine equivalents of nursing manpower use score (NEMS). Results: 331 patients were identified, with a mean time of 0.72 [0 - 5.84] days between ICU transfer order and discharge to home. 68.3% (226/331) of patients waited \u3c24 hours for discharge. There was no difference in severity-of-illness or admission NEMS between the groups. 10.3% (45/331) of patients presented for evaluation within 30 days of discharge. 10.3% (34/331) of patients were readmitted. There was no significant difference in 30-day readmission between patients who were discharged after waiting \u3c24 hours vs. waiting ≥24 hours (p=0.70). Discussion: Patients returning directly home from the ICU without discharge delay were not readmitted more frequently within 30 days than those discharged after a delay exceeding 24 hours. Further investigation into identifying patients eligible for safe, early discharge may reduce unnecessary critical care resource utilization

Characteristics and Outcomes of Patients Directly Discharged to Home from the Intensive Care Unit

Introduction: Given the current era of decreasing hospital bed availability, there has been a rise in the practice of direct discharge to home (DDH) from ICUs. We evaluated the demographics, clinical characteristics, outcomes and readmission patterns among DDH patients. Methods: Retrospective review of patients from 2 MICUs from June 2017 to June 2019 at Thomas Jefferson University hospital, an urban tertiary care center. Primary outcome of interest was 30-day hospital readmission. Patients were dichotomized into two groups based on time between ward transfer order and hospital discharge (\u3c24 or ≥24 hours). Risk adjustment performed with Mortality Probability Model (MPM0 -III). ICU workload at admission and discharge was estimated with nine equivalents of nursing manpower use score (NEMS). Patient characteristics compared using t-test and Fisher exact or χ2 test. Results: 331 DDH patients were analyzed, with the majority (68.3%, 226/331) waiting \u3c24 hours for discharge. Mean LOS significantly longer in patients who had waited ≥24 hours prior to discharge compared to that of patients who waited \u3c24 hours (4.63 vs 2.65 days, p\u3c0.001). 10.3% (45/331) presented to TJU for evaluation within 30 days of discharge. Of these patients, 75.6% (34/45) were readmitted. No significant difference in severity-of-illness, admission NEMS, or 30-day readmission between the 2 groups (p=0.70). Discussion: Shorter wait-times for ICU patients after being determined ready for DDH were associated with shorter hospital and ICU LOS but not with an increase in 30-day readmissions. Further examining pre-discharge and post-discharge data could better identify those at risk of readmission

Characteristics and Outcomes of Patients Discharged Directly Home from a Medical Intensive Care Unit

RATIONALE: Discharging patients directly from ICUs is an increasingly common practice, largely due to decreased availability of ward beds. The purpose of this study was to describe the population and evaluate the outcomes of patients discharged directly from the MICU. METHODS: We conducted a retrospective chart review of direct discharges to home from June 2018 to June 2019 from two MICUs. Patients were separated into two groups based on wait time (\u3c24 hours or ≥ 24 hours) between ward transfer order and actual discharge. The primary outcome was 30-day hospital readmission. Risk was adjusted using Mortality Probability Model (MPM-III); ICU workload at admission and discharge was estimated using the nine equivalents of nursing manpower use score (NEMS). Patient characteristics were compared using t-test and Fisher exact or X2. RESULTS: There was no difference in severity-of-illness or admission NEMS between the two groups. Patients who waited \u3c24 hours for discharge were more likely to be admitted from home. Patients who waited ≥24 hours prior to discharge had significantly longer mean hospital LOS compared to those who waited \u3c24 hours (4.63 days vs. 2.65 days, p\u3c0.001). There was no significant difference in 30-day readmission between patients who were discharged after waiting \u3c24 hours vs. waiting ≥24 hours (p=0.70). CONCLUSION: Patients who returned directly home from the MICU without any discharge delay were not readmitted to the hospital more frequently within 30 days than those discharged to home after a delay exceeding 24 hours. Further investigation into identifying those patients for whom early discharge planning directly to home from the ICU is viable and safe may aid in reducing unnecessary critical care resource utilization

Characterization Of Drug Interactions With Serum Proteins by Using High-Performance Affinity Chromatography

The binding of drugs with serum proteins can affect the activity, distribution, rate of excretion, and toxicity of pharmaceutical agents in the body. One tool that can be used to quickly analyze and characterize these interactions is high-performance affinity chromatography (HPAC). This review shows how HPAC can be used to study drug-protein binding and describes the various applications of this approach when examining drug interactions with serum proteins. Methods for determining binding constants, characterizing binding sites, examining drug-drug interactions, and studying drug-protein dissociation rates will be discussed. Applications that illustrate the use of HPAC with serum binding agents such as human serum albumin, α1-acid glycoprotein, and lipoproteins will be presented. Recent developments will also be examined, such as new methods for immobilizing serum proteins in HPAC columns, the utilization of HPAC as a tool in personalized medicine, and HPAC methods for the high-throughput screening and characterization of drug-protein binding

Characterization Of Drug Interactions With Serum Proteins by Using High-Performance Affinity Chromatography

The binding of drugs with serum proteins can affect the activity, distribution, rate of excretion, and toxicity of pharmaceutical agents in the body. One tool that can be used to quickly analyze and characterize these interactions is high-performance affinity chromatography (HPAC). This review shows how HPAC can be used to study drug-protein binding and describes the various applications of this approach when examining drug interactions with serum proteins. Methods for determining binding constants, characterizing binding sites, examining drug-drug interactions, and studying drug-protein dissociation rates will be discussed. Applications that illustrate the use of HPAC with serum binding agents such as human serum albumin, α1-acid glycoprotein, and lipoproteins will be presented. Recent developments will also be examined, such as new methods for immobilizing serum proteins in HPAC columns, the utilization of HPAC as a tool in personalized medicine, and HPAC methods for the high-throughput screening and characterization of drug-protein binding

Mechanically Ventilated COVID-19 Patients Admitted to the Intensive Care Unit in the United States With or Without Respiratory Failure Secondary to COVID-19 Pneumonia: A Retrospective Comparison of Characteristics and Outcomes

BACKGROUND: There is increasing heterogeneity in the clinical phenotype of patients admitted to the intensive care unit (ICU) with coronavirus disease 2019 (COVID-19,) and reasons for mechanical ventilation are not limited to COVID pneumonia. We aimed to compare the characteristics and outcomes of intubated patients admitted to the ICU with the primary diagnosis of acute hypoxemic respiratory failure (AHRF) from COVID-19 pneumonia to those patients admitted for an alternative diagnosis. METHODS: Retrospective cohort study of adults with confirmed SARS-CoV-2 infection admitted to nine ICUs between March 18, 2020, and April 30, 2021, at an urban university institution. We compared characteristics between the two groups using appropriate statistics. We performed logistic regression to identify risk factors for death in the mechanically ventilated COVID-19 population. RESULTS: After exclusions, the final sample consisted of 319 patients with respiratory failure secondary to COVID pneumonia and 150 patients intubated for alternative diagnoses. The former group had higher ICU and hospital mortality rates (57.7% vs. 36.7%, P CONCLUSIONS: Mechanically ventilated COVID-19 patients admitted to the ICU with COVID-19-associated respiratory failure are at higher risk of hospital death and have worse ICU utilization outcomes than those whose reason for admission is unrelated to COVID pneumonia

Mechanically ventilated COVID-19 patients admitted to the intensive care unit in the United States with or without respiratory failure secondary to COVID-19 pneumonia: a retrospective comparison of characteristics and outcomes

Background There is increasing heterogeneity in the clinical phenotype of patients admitted to the intensive care unit (ICU) with coronavirus disease 2019 (COVID-19,) and reasons for mechanical ventilation are not limited to COVID pneumonia. We aimed to compare the characteristics and outcomes of intubated patients admitted to the ICU with the primary diagnosis of acute hypoxemic respiratory failure (AHRF) from COVID-19 pneumonia to those patients admitted for an alternative diagnosis. Methods Retrospective cohort study of adults with confirmed SARS-CoV-2 infection admitted to nine ICUs between March 18, 2020, and April 30, 2021, at an urban university institution. We compared characteristics between the two groups using appropriate statistics. We performed logistic regression to identify risk factors for death in the mechanically ventilated COVID-19 population. Results After exclusions, the final sample consisted of 319 patients with respiratory failure secondary to COVID pneumonia and 150 patients intubated for alternative diagnoses. The former group had higher ICU and hospital mortality rates (57.7% vs. 36.7%, P<0.001 and 58.9% vs. 39.3%, P<0.001, respectively). Patients with AHRF secondary to COVID-19 pneumonia also had longer ICU and hospital lengths-of-stay (12 vs. 6 days, P<0.001 and 20 vs. 13.5 days, P=0.001). After risk-adjustment, these patients had 2.25 times higher odds of death (95% confidence interval, 1.42–3.56; P=0.001). Conclusions Mechanically ventilated COVID-19 patients admitted to the ICU with COVID-19-associated respiratory failure are at higher risk of hospital death and have worse ICU utilization outcomes than those whose reason for admission is unrelated to COVID pneumonia

Declining Intensive Care Unit Mortality of COVID-19: A Multi-Center Study

Background: Coronavirus disease 2019 (COVID-19) mortality has waned significantly over time; however, factors contributing towards this reduction largely remain unidentified. The purpose of this study was to evaluate the trend in mortality at our large tertiary academic health system and factors contributing to this trend. Methods: This is a retrospective cohort study of intensive care unit (ICU) patients diagnosed with COVID-19 between March and August 2020 admitted across 14 hospitals in the Philadelphia area. Collected data included demographics, comorbidities, admission risk of mortality score, laboratory values, medical interventions, survival outcomes, hospital and ICU length of stay (LOS) and discharge disposition. Chi-square (χ2) test, Fisher exact test, Cochran-Mantel-Haenszel method, multinomial logistic regression models, independent sample t-test, Mann-Whitney U test and one-way analysis of variance (ANOVA) were used. Results: A total of 1,204 patients were included. Overall mortality was 39%. Mortality declined significantly from 46% in March to 14% in August 2020 (P \u3c 0.05). The most common underlying comorbidities were hypertension (60.2%), diabetes mellitus (44.7%), dyslipidemia (31.6%) and congestive heart failure (14.7%). Hydroxychloroquine (HCQ) use was more commonly associated with the patients who died, while the use of remdesivir, tocilizumab, steroids and duration of these medications were not significantly different. Peak values of ferritin, lactate dehydrogenase (LDH), C-reactive protein (CRP) and D-dimer levels were significantly higher in patients who died (P \u3c 0.05). The mean hospital LOS was significantly longer in the patients who survived compared to the patients who died (18 vs. 12, P \u3c 0.05). Conclusions: The mortality of patients admitted to our ICU system significantly decreased over time. Factors that may have contributed to this may be the result of a better understanding of COVID-19 pathophysiology and treatments. Further research is needed to elucidate the factors contributing to a reduction in the mortality rate for this patient population

DNA Barcode Detects High Genetic Structure within Neotropical Bird Species

BACKGROUND: Towards lower latitudes the number of recognized species is not only higher, but also phylogeographic subdivision within species is more pronounced. Moreover, new genetically isolated populations are often described in recent phylogenies of Neotropical birds suggesting that the number of species in the region is underestimated. Previous COI barcoding of Argentinean bird species showed more complex patterns of regional divergence in the Neotropical than in the North American avifauna. METHODS AND FINDINGS: Here we analyzed 1,431 samples from 561 different species to extend the Neotropical bird barcode survey to lower latitudes, and detected even higher geographic structure within species than reported previously. About 93% (520) of the species were identified correctly from their DNA barcodes. The remaining 41 species were not monophyletic in their COI sequences because they shared barcode sequences with closely related species (N = 21) or contained very divergent clusters suggestive of putative new species embedded within the gene tree (N = 20). Deep intraspecific divergences overlapping with among-species differences were detected in 48 species, often with samples from large geographic areas and several including multiple subspecies. This strong population genetic structure often coincided with breaks between different ecoregions or areas of endemism. CONCLUSIONS: The taxonomic uncertainty associated with the high incidence of non-monophyletic species and discovery of putative species obscures studies of historical patterns of species diversification in the Neotropical region. We showed that COI barcodes are a valuable tool to indicate which taxa would benefit from more extensive taxonomic revisions with multilocus approaches. Moreover, our results support hypotheses that the megadiversity of birds in the region is associated with multiple geographic processes starting well before the Quaternary and extending to more recent geological periods

Adults with childhood-onset chronic conditions admitted to US pediatric and adult intensive care units

PURPOSE: To compare demographics, intensive care units (ICU) admission characteristics, and ICU outcomes among adults with childhood-onset chronic conditions (COCC) admitted to U.S. pediatric and adult ICUs. MATERIALS AND METHODS: Retrospective cross-sectional analyses of 6,088 adults aged 19–40 years admitted in 2008 to 70 pediatric ICUs that participated in the Virtual Pediatric Intensive Care Unit Performance Systems and 50 adult ICUs that participated in Project IMPACT. RESULTS: COCC were present in 53% of young adults admitted to pediatric units, compared to 9% of those in adult units. The most common COCC in both groups were congenital cardiac abnormalities, cerebral palsy, and chromosomal abnormalities. Adults with COCC admitted to pediatric units were significantly more likely to be younger, have lower functional status, and be non-trauma patients than those in adult units. The median ICU length-of-stay was 2 days and the intensive care unit mortality rate was 5% for all COCC patients with no statistical difference between pediatric or adult units. CONCLUSIONS: There are marked differences in characteristics between young adults with COCC admitted to PICUs and adult ICUs. Barriers to accommodating these young adults may be reasons why many such adults have not transitioned from pediatric to adult critical care