Cellular host response sepsis test for risk stratification of patients in the emergency department: A pooled analysis

OBJECTIVES

Sepsis is one of the most common, costly, and misdiagnosed conditions in U.S. emergency departments (EDs). ED providers often treat on nonspecific signs, subjective suspicion, or presumption of infection, resulting in over- and undertreatment. An increased understanding of host response has opened a new direction for sepsis diagnostics. The IntelliSep test is a U.S. Food and Drug Administration-cleared cellular host response diagnostic that could help distinguish sepsis in ED settings. Our objective was to evaluate the potential of the cellular host response test to expedite appropriate care for patients who present with signs of infection.

METHODS

We performed a pooled analysis of five adult (≥18 years) cohorts enrolled at seven geographically diverse U.S. sites in separate studies. Structured blinded adjudication was used to classify presence or absence of sepsis, and only patients with high confidence in the adjudicated label were included (n = 1002), defined as patients for whom there was consensus in the determination of sepsis per the Sepsis-3 and severe sepsis per the Sepsis-2 definitions between both the independent adjudication panel and the site-level physician.

RESULTS

Among patients with signs or suspicion of infection, the test achieved similar or better performance compared to other indicators in identifying patients at high risk for sepsis (specificity > 83%) and significantly superior performance in identifying those at low risk (sensitivity > 92%; 0% sepsis-associated mortality). The test also stratified severity of illness, as shown by 30-day in-hospital mortality (p < 0.001), hospital length of stay (p < 0.01), and use of hospital resources (p < 0.001).

CONCLUSIONS

Our data suggest that the cellular host response test provides clinically actionable results for patients at both high and low risk for sepsis and provides a rapid, objective means for risk stratification of patients with signs of infection. If integrated into standard of care, the test may help improve outcomes and reduce unnecessary antibiotic use.

Analysis of Cutaneous Lupus Hospitalizations: A United States National Population-Based Study

Background There are limited studies analyzing cutaneous lupus erythematosus (CLE) hospitalizations. In this study, we aimed to analyze baseline demographics of systemic lupus erythematosus (SLE) and CLE patients, identify the most common reasons for hospitalizations, and find out the hospitalization outcomes.  Materials and methods We performed the analysis using the National (Nationwide) Inpatient Sample (NIS) database between 2016 and 2019. For the CLE cohort, data for adults aged 18 years and older with the primary or secondary diagnosis of CLE using International Classification of Disease - 10th revision (ICD-10) codes were extracted. For comparison, the SLE cohort was identified by patients aged 18 years and older with primary or secondary diagnoses of SLE using ICD-10 codes. Chi-squared test was used to compare baseline demographic characteristics. Multivariable logistic and linear regression was used to calculate outcomes of interest. Results In comparison to the SLE cohort, the CLE cohort was not only older in age and lower percentage female, but also had shorter length of stay, less total hospital charge, and the majority had Medicare as primary insurance. The SLE cohort included predominantly African American patients while the CLE cohort was majority Caucasian patients. The cardiovascular risks were more prevalent in the CLE cohort and most commonly admitted for sepsis, cardiovascular disease, and mental health disorders. Conclusion Our study highlights the importance of outpatient follow-up in CLE patients to closely monitor cardiovascular risk factors, early identification of infections, and routine mental health screenings to reduce hospitalizations and resource utilization.

Patient profiles, initial hospital encounter characteristics, and hospital re-encounters of patients with a hospital emergency department visit or inpatient admission for major depressive disorder

OBJECTIVES

To gain a better understanding of the characteristics of patients with a hospital encounter for major depressive disorder (MDD) and evaluate associated hospital resource utilization, hospital charges and costs, and hospital re-encounters.

METHODS

Adult patients with a hospital encounter (i.e. emergency department [ED] visit only or inpatient admission) with MDD as the primary discharge diagnosis (index event) during July 2018‒March 2019 were selected from the Premier Healthcare Database. Patient characteristics, hospital resource utilization, and hospital charges and costs were evaluated during index events. During a 12-month follow-up, hospital re-encounters (MDD-related and all-cause ED visit only or inpatient readmissions) were examined.

RESULTS

The study population included 77,178 patients with an index hospital encounter (ED visit only: 49.9%; inpatient admission: 50.1%) for MDD. The most common secondary mental health-related diagnosis was suicidal ideation/behavior, which was recorded in 51.8% of patients. The mean age was 38.2 years, 53.0% were female, and 72.1% were Caucasian. Among patients with an ED visit only, the mean index hospital charges and costs were $3,608 and $639, respectively. Among those with inpatient admissions, the mean length of stay was 4.9 days, and the mean index hospital charges and costs were $17,107 and $6,095, respectively. During the 12-month follow-up, 13.3% of patients in the overall study population had an MDD-related hospital re-encounter (primary or secondary discharge diagnosis code indicating MDD); nearly one-third (31.3%) occurred within 30 days post-discharge. During the follow-up, 28.1% had an all-cause hospital re-encounter with 29.7% having occurred within 30 days post-discharge.

LIMITATIONS

Due to constraints of the Premier Healthcare Database, healthcare resource utilization and costs outside of the hospital could not be evaluated.

CONCLUSIONS

Patients with a hospital encounter for MDD are relatively young, commonly have suicidal ideation/behavior, utilize substantial hospital resources, and have a high risk for a hospital re-encounter in the 30 days post-discharge.

Neutrophil-to-Lymphocyte Ratios and Infections after Traumatic Brain Injury: Associations with Hospital Resource Utilization and Long-Term Outcome

Traumatic brain injury (TBI) induces immune dysfunction that can be captured clinically by an increase in the neutrophil-to-lymphocyte ratio (NLR). However, few studies have characterized the temporal dynamics of NLR post-TBI and its relationship with hospital-acquired infections (HAI), resource utilization, or outcome. We assessed NLR and HAI over the first 21 days post-injury in adults with moderate-to-severe TBI (n = 196) using group-based trajectory (TRAJ), changepoint, and mixed-effects multivariable regression analysis to characterize temporal dynamics. We identified two groups with unique NLR profiles: a high (n = 67) versus a low (n = 129) TRAJ group. High NLR TRAJ had higher rates (76.12% vs. 55.04%, p = 0.004) and earlier time to infection (p = 0.003). In changepoint-derived day 0–5 and 6–20 epochs, low lymphocyte TRAJ, early in recovery, resulted in more frequent HAIs (p = 0.042), subsequently increasing later NLR levels (p ≤ 0.0001). Both high NLR TRAJ and HAIs increased hospital length of stay (LOS) and days on ventilation (p ≤ 0.05 all), while only high NLR TRAJ significantly increased odds of unfavorable six-month outcome as measured by the Glasgow Outcome Scale (GOS) (p = 0.046) in multivariable regression. These findings provide insight into the temporal dynamics and interrelatedness of immune factors which collectively impact susceptibility to infection and greater hospital resource utilization, as well as influence recovery.

Forecasting COVID-19 Hospital Census: A Multivariate Time-Series Model Based on Local Infection Incidence

BACKGROUND

COVID-19 has been one of the most serious global health crises in world history. During the pandemic, health care systems require accurate forecasts for key resources to guide preparation for patient surges. Forecasting the COVID-19 hospital census is among the most important planning decisions to ensure adequate staffing, number of beds, intensive care units, and vital equipment.

OBJECTIVE

The goal of this study was to explore the potential utility of local COVID-19 infection incidence data in developing a forecasting model for the COVID-19 hospital census.

METHODS

The study data comprised aggregated daily COVID-19 hospital census data across 11 Atrium Health hospitals plus a virtual hospital in the greater Charlotte metropolitan area of North Carolina, as well as the total daily infection incidence across the same region during the May 15 to December 5, 2020, period. Cross-correlations between hospital census and local infection incidence lagging up to 21 days were computed. A multivariate time-series framework, called the vector error correction model (VECM), was used to simultaneously incorporate both time series and account for their possible long-run relationship. Hypothesis tests and model diagnostics were performed to test for the long-run relationship and examine model goodness of fit. The 7-days-ahead forecast performance was measured by mean absolute percentage error (MAPE), with time-series cross-validation. The forecast performance was also compared with an autoregressive integrated moving average (ARIMA) model in the same cross-validation time frame. Based on different scenarios of the pandemic, the fitted model was leveraged to produce 60-days-ahead forecasts.

RESULTS

The cross-correlations were uniformly high, falling between 0.7 and 0.8. There was sufficient evidence that the two time series have a stable long-run relationship at the .01 significance level. The model had very good fit to the data. The out-of-sample MAPE had a median of 5.9% and a 95th percentile of 13.4%. In comparison, the MAPE of the ARIMA had a median of 6.6% and a 95th percentile of 14.3%. Scenario-based 60-days-ahead forecasts exhibited concave trajectories with peaks lagging 2 to 3 weeks later than the peak infection incidence. In the worst-case scenario, the COVID-19 hospital census can reach a peak over 3 times greater than the peak observed during the second wave.

CONCLUSIONS

When used in the VECM framework, the local COVID-19 infection incidence can be an effective leading indicator to predict the COVID-19 hospital census. The VECM model had a very good 7-days-ahead forecast performance and outperformed the traditional ARIMA model. Leveraging the relationship between the two time series, the model can produce realistic 60-days-ahead scenario-based projections, which can inform health care systems about the peak timing and volume of the hospital census for long-term planning purposes.

Impact of Injuries on Hospital Resource Utilization Among Trauma Patients Admitted due to Accidents Caused by Farm Animals

This study examined the impact of injuries on the hospital resource utilization rate among trauma patients admitted to the Johnson City Medical Center (TN, USA), a rural Level I trauma center, due to accidents caused by farm animals. A total of 52 patients aged >3 years were studied, with the average age being 44 years. Patients above 65 years of age made up almost a quarter of the study population (23%); 63% of the patient population were male. All patients survived their injuries. Twenty-six percent of the patients required orthopedic intervention, with the majority of those patients being male (nine males, five females).

Risk factors for delay in surgery for patients undergoing elective anterior cervical discectomy and fusion

BACKGROUND

Anterior cervical discectomy and fusion (ACDF) is well-tolerated by most patients and commonly necessitates only a short hospital admission. Surgical delay after hospital admission, however, may result in longer hospital stays, consequently increasing hospital resource utilization. The current study evaluates risk factors for surgical delay in patients undergoing elective ACDF.

METHODS

A retrospective analysis of ACS-NSQIP data from 2006-2015 was performed. Patients undergoing elective ACDF were selected using current procedural terminology (CPT) codes (22251, 22252, 22554). A surgical delay was defined as surgery that occurred one day or later after initial hospital admission. Differences in outcomes between the non-delayed and delayed cohorts were evaluated with univariate analysis. Multivariate logistic regression was performed to identify risk factors for surgical delay.

RESULTS

There were a total of 771 (2.0%) surgical delays out of 39,371 patients undergoing elective ACDF from 2006-2015. Multivariate analysis found partially dependent functional status (OR 5.88; 95% CI: 4.48-7.71; P<0.001), totally dependent functional status (OR 18.22; 95% CI: 9.60-34.59; P<0.001), ASA class 4 (OR 2.73; 95% CI: 1.70-4.38; P<0.001), bleeding disorders (OR 1.75; 95% CI: 1.08-2.85; P=0.024), male sex (OR 1.19; 95% CI: 1.03-1.38; P=0.019), and chronic steroid use (OR 1.76; 95% CI: 1.30-2.37; P<0.001) as independent predictors of delay. Univariate analysis found surgical delay was associated with a higher rate of post-operative major adverse events (4.8% vs. 1.1%; P<0.001), mortality (1.0% vs. 0.2%; P<0.001) and greater than five-fold increase in total length of stay (9.52 vs. 1.65 days; P<0.001).

CONCLUSIONS

Impaired pre-operative functional status, a higher comorbidity burden, and chronic steroid use are risk factors for surgical delay, increased complications, and length of stay in patients undergoing elective ACDF. This is helpful information to consider given a rising incidence of cervical fusions in the Medicare population, a wide variation in costs, and increasing popularity of bundled-payment models.

LEVEL OF EVIDENCE

3.

Cost and Hospital Resource Utilization of Staphylococcus aureus Infection Post Elective Posterior Instrumented Spinal Fusion Surgeries in U.S. Hospitals: A Retrospective Cohort Study

STUDY DESIGN

A retrospective cohort study.

OBJECTIVE

The aim of this study was to assess hospital resource utilization and costs associated with Staphylococcus aureus infection within 180 days post elective posterior instrumented spinal fusion surgeries (index surgery) between 2010 and 2015.

SUMMARY OF BACKGROUND DATA

Surgical site infections (SSIs) and blood stream infections (BSIs) post spinal fusion surgeries are associated with worse clinical outcomes and increased costs. Economic data specific to the most common pathogen of infections post spinal fusion surgeries, S. aureus, are limited.

METHODS

We analyzed hospital discharge and microbiology data from 129 U.S. hospitals in Premier Healthcare Database. Selection criteria included age ≥ 18 years; had a primary/secondary ICD-9-CM procedure code for index surgery; and had microbiology data during study period. Outcomes included total hospitalization cost, length of stay, and risk of all-cause readmission. Infection status was classified as culture-confirmed invasive (i.e., BSIs, deep or organ/space SSIs), any, and no S. aureus infection. Multivariable regression analyses were used to compare outcome variables between infection groups controlling for known confounders.

RESULTS

Two hundred ninety-four patients had any S. aureus infection (151 had invasive infection) and 12,918 had no infection. Compared with no infection group, invasive and any infection groups had higher total hospitalization cost (adjusted mean in 2015 U.S. dollars: $88,353 and $64,356 vs. $47,366, P < 0.001), longer length of stay (adjusted mean: 20.98 and 13.15 vs. 6.77 days, P < 0.001), and higher risk of all-cause readmission [adjusted risk ratio: 2.15 (95% confidence interval: 2.06-2.25) for invasive and 1.70 (95% confidence interval: 1.61-1.80) for any infection groups].

CONCLUSION

S. aureus infections post elective posterior instrumented spinal fusion surgeries are associated with significantly higher hospitalization cost, length of stay, and 180-day risk of readmission than those with no such infection, which presents substantial burden to hospitals and patients. Reducing such infections may cut costs and hospital resource utilization.

LEVEL OF EVIDENCE

3.

The Effect of Level of Care on Gastroschisis Outcomes

OBJECTIVE

To examine the relationship between level of care in neonatal intensive care units (NICUs) and outcomes for newborns with gastroschisis.

STUDY DESIGN

A retrospective cohort study was conducted at 130 California Perinatal Quality Care Collaborative NICUs from 2008 to 2014. All gastroschisis births were examined according to American Academy of Pediatrics NICU level of care at the birth hospital. Multivariate analyses examined odds of mortality, duration of mechanical ventilation, and duration of stay.

RESULTS

For 1588 newborns with gastroschisis, the adjusted odds of death were higher for those born into a center with a level IIA/B NICU (OR, 6.66; P = .004), a level IIIA NICU (OR, 5.95; P = .008), or a level IIIB NICU (OR, 5.85; P = .002), when compared with level IIIC centers. The odds of having more days on ventilation were significantly higher for births at IIA/B and IIIB centers (OR, 2.05 [P < .001] and OR, 1.91 [P < .001], respectively). The odds of having longer duration of stay were significantly higher at IIA/B and IIIB centers (OR, 1.71 [P < .004]; OR, 1.77 [P < .001]).

CONCLUSIONS

NICU level of care was associated with significant disparities in odds of mortality for newborns with gastroschisis.

Trends and outcome predictors after traumatic brain injury surgery: a nationwide population-based study in Taiwan

OBJECT

The authors sought to analyze trends in hospital resource utilization and mortality rates in a population of patients who had received traumatic brain injury (TBI) surgery.

METHODS

This nationwide population-based cohort study retrospectively analyzed 18,286 patients who had received surgical treatment for TBI between 1998 and 2010. The multiple linear regression model and Cox proportional hazards model were used for multivariate assessment of outcome predictors.

RESULTS

The prevalence rate of surgical treatment for patients with TBI gradually but significantly (p < 0.001) increased by 47.6% from 5.0 per 100,000 persons in 1998 to 7.4 per 100,000 persons in 2010. Age, sex, Deyo-Charlson comorbidity index score, hospital volume, and surgeon volume were significantly associated with TBI surgery outcomes (p < 0.05). Over the 12-year period analyzed, the estimated mean hospital treatment cost increased 19.06%, whereas the in-hospital mortality rate decreased 10.9%. The estimated mean time of overall survival after TBI surgery (± SD) was 83.0 ± 4.2 months, and the overall in-hospital and 1-, 3-, and 5-year survival rates were 74.5%, 67.3%, 61.1%, and 57.8%, respectively.

CONCLUSIONS

These data reveal an increased prevalence of TBI, especially in older patients, and an increased hospital treatment cost but a decreased in-hospital mortality rate. Health care providers and patients should recognize that attributes of the patient and of the hospital may affect hospital resource utilization and the mortality rate. These results are relevant not only to other countries with similar population sizes but also to countries with larger populations.

Trend analysis of hospital resource utilization for prolonged mechanical ventilation patients in Taiwan: a population-based study

BACKGROUND

The aging Taiwan population is expected to require vast medical resources, including prolonged mechanical ventilation (PMV). This study determined the trends in hospital resource utilization and associated factors in PMV patients in Taiwan.

METHODS

All patients who had received mechanical ventilation for > 21 days (International Classification of Diseases, 9th Revision, Clinical Modification codes 518.81-518.89) during 2004-2007 were recruited to the study. Administrative claims data obtained from the Bureau of National Health Insurance of Taiwan were analyzed.

RESULTS

The study analyzed 65,181 patients who had received PMV during 2004-2007. The number of PMVs per 100,000 persons was 94.30 in 2004, and it gradually decreased to 89.38 in 2007, which was a change rate of -5.22%. During the study period, stay significantly decreased, from 35.12 days to 31.61 days, whereas hospital treatment costs significantly increased, from $7,933.17 to $8,257.52 (P < .001). Considerably decreased stay and increased hospital treatment costs were significantly associated with age, number of comorbidities, hospital level, hospital volume, and patient referral source (P < .001).

CONCLUSIONS

These population-based data demonstrated a decrease in the prevalence of PMV, especially for older patients, and that stay decreased; however, hospital treatment costs increased. Moreover, healthcare providers and patients should recognize that attributes of both the patient and the hospital may affect hospital resource utilization. Additionally, these analytical results should be applicable to similar populations in other countries.