Prolonged hospital length of stay in pediatric trauma: a model for targeted interventions

Physical Health-Related Quality of Life and Postsurgical Outcomes in Brain Tumor Resection Patients

Background  Patient-reported outcome measures (PROMs) have gained traction in assessing patients' health around surgery. Among these, the 29-item Patient-Reported Outcomes Measurement Information System (PROMIS-29) is a widely accepted tool for evaluating overall health, yet its applicability in cranial neurosurgery remains uncertain. Objective  This study aimed to evaluate the predictive value of preoperative PROMIS-29 scores for postoperative outcomes in patients undergoing brain tumor resection. Materials and Methods  We identified adult patients undergoing brain tumor resection at a single neurosurgical center between January 2018 and December 2021. We analyzed physical health (PH) summary scores to determine optimal thresholds for predicting length of stay (LOS), discharge disposition (DD), and 30-day readmission. Bivariate analyses were conducted to examine the distribution of PH scores based on patient characteristics. Multivariate logistic regression models were employed to assess the association between preoperative PH scores and short-term postoperative outcomes. Results  Among 157 patients (mean age 55.4 years, 58.0% female), 14.6% exhibited low PH summary scores. Additionally, 5.7% experienced prolonged LOS, 37.6% had nonroutine DDs, and 19.1% were readmitted within 30 days. Bivariate analyses indicated that patients with low PH summary scores, indicating poorer baseline PH, were more likely to have malignant tumors, nonelective admissions, and adverse outcomes. In multivariate analysis, low PH summary scores independently predicted increased odds of prolonged LOS (odds ratio [OR] = 6.09, p  = 0.003), nonroutine DD (OR = 4.25, p  = 0.020), and 30-day readmission (OR = 3.93, p  = 0.020). Conclusion  The PROMIS-29 PH summary score serves as a valuable predictor of short-term postoperative outcomes in brain tumor patients. Integrating this score into clinical practice can enhance the ability to anticipate meaningful postoperative results.

Preoperative patient-reported physical health-related quality of life predicts short-term postoperative outcomes in brain tumor patients

BACKGROUND

Patient-reported outcome measures (PROMs) are increasingly used to assess patients' perioperative health. The PROM Information System 29 (PROMIS-29) is a well-validated global health assessment instrument for patient physical health, though its utility in cranial neurosurgery is unclear.

OBJECTIVE

To investigate the utility of preoperative PROMIS-29 physical health (PH) summary scores in predicting postoperative outcomes in brain tumor patients.

METHODS

Adult brain tumor patients undergoing resection at a single institution (January 2018-December 2021) were identified and prospectively received PROMIS-29 surveys during pre-operative visits. PH summary scores were constructed and optimum prediction thresholds for length of stay (LOS), discharge disposition (DD), and 30-day readmission were approximated by finding the Youden index of the associated receiver operating characteristic curves. Bivariate analyses were used to study the distribution of low (z-score≤-1) versus high (z-score>-1) PH scores according to baseline characteristics. Logistic regression models quantified the association between preoperative PH summary scores and post-operative outcomes.

RESULTS

A total of 157 brain tumor patients were identified (mean age 55.4±15.4 years; 58.0% female; mean PH score 45.5+10.5). Outcomes included prolonged LOS (24.8%), non-routine discharge disposition (37.6%), and 30-day readmission (19.1%). On bivariate analysis, patients with low PH scores were significantly more likely to be diagnosed with a high-grade tumor (69.6% vs 38.85%, p=0.010) and less likely to have elective surgery (34.8% vs 70.9%, p=0.002). Low PH score was associated with prolonged LOS (26.1% vs 22%, p<0.001), nonroutine discharge (73.9% vs 31.3%, p<0.001) and 30-day readmission (43.5% vs 14.9%, p=0.003). In multivariate analysis, low PH scores predicted greater LOS (odds ratio [OR]=6.09, p=0.003), nonroutine discharge (OR=4.25, p=0.020), and 30-day readmission (OR=3.93, p=0.020).

CONCLUSION

The PROMIS-29 PH summary score predicts short-term postoperative outcomes in brain tumor patients and may be incorporated into prospective clinical workflows.

Quality indicators for hospital burn care: a scoping review

BACKGROUND

Burn treatments are complex, and for this reason, a specialised multidisciplinary approach is recommended. Evaluating the quality of care provided to acute burn patients through quality indicators makes it possible to develop and implement measures aiming at better results. There is a lack of information on which indicators to evaluate care in burn patients. The purpose of this scoping review was to identify a list of quality indicators used to evaluate the quality of hospital care provided to acute burn patients and indicate possible aspects of care that do not have specific indicators in the literature.

METHOD

A comprehensive scoping review (PRISMA-ScR) was conducted in four databases (PubMed, Cochrane Library, Embase, and Lilacs/VHL) between July 25 and 30, 2022 and redone on October 6, 2022. Potentially relevant articles were evaluated for eligibility. General data and the identified quality indicators were collected for each included article. Each indicator was classified as a structure, process, or outcome indicator.

RESULTS

A total of 1548 studies were identified, 82 were included, and their reference lists were searched, adding 19 more publications. Thus, data were collected from 101 studies. This review identified eight structure quality indicators, 72 process indicators, and 19 outcome indicators listed and subdivided according to their objectives.

CONCLUSION

This study obtained a list of quality indicators already used to monitor and evaluate the hospital care of acute burn patients. These indicators may be useful for further research or implementation in quality improvement programs.

TRIAL REGISTRATION

Protocol was registered on the Open Science Framework platform on June 27, 2022 ( https://doi.org/10.17605/OSF.IO/NAW85 ).

Attempted Suicide Is Independently Associated with Increased In-Hospital Mortality and Hospital Length of Stay among Injured Patients at Community Tertiary Hospital in Japan: A Retrospective Study with Propensity Score Matching Analysis

Suicide is an increasingly important public healthcare concern worldwide. Studies examining the effect of attempted suicide on clinical outcomes among patients with trauma are scarce. We conducted a retrospective cohort study at a community emergency department in Japan. We included all severely injured patients with an Injury Severity Score > 15 from January 2002 to December 2021. The primary outcome measure was in-hospital mortality. The other outcome of interest was hospital length of stay. One-to-one propensity score matching was performed to compare these outcomes between suicide attempt and no suicide attempt groups. Of the 2714 eligible patients, 183 (6.7%) had trauma caused by a suicide attempt. In the propensity score-matched analysis with 139 pairs, the suicide attempt group showed a significant increase in-hospital mortality (20.9% vs. 37.4%; odds ratio 2.27; 95% confidence intervals 1.33-3.87) compared with the no suicide attempt group. Among survivors, the median hospital length of stay was significantly longer in the suicide attempt group than that in the no suicide attempt group (9 days vs. 12 days, p = 0.0076). Because of the unfavorable consequences and potential need for additional healthcare, increased attention should be paid to patients with trauma caused by a suicide attempt.

Investigating Length of Stay Patterns and Its Predictors in the South Wales Trauma Network

Background

Length of stay (LOS) is frequently employed as a performance metric for trauma care. Following the establishment of the trauma network worldwide, the assessment and prediction of LOS in different levels of trauma centres have been extensively studied. However, assessing the total patient length of stay from a whole trauma network perspective is unclear. The objective of this study was to systematically analyse the overall Length of Stay (LOS) pattern within the SWTN before its establishment and in the immediate time after its foundation and, secondly, to assess the association between relevant impact factors and LOS.

Methodology

A retrospective secondary analysis based on the trauma admission dataset from Trauma Audit and Research Network(TARN) dataset was conducted. The studied sample covered around 18000 patients admitted to trauma centres from South Wales Major trauma network between January 2012 and October 2021. The primary outcome is the total length of stay in the trauma network. Statistical tests were applied to examine the difference between normal and outlier LOS. Data visualisation was utilised to demonstrate the LOS patterns and potential association between LOS and relevant demographic and clinical predictors.

Results

The distribution of length of stay in SWTN follows a right-skewed distribution with a median of 10 (IQR, 5-18) and a mean of 15.92 days. There were 1520 patients with outliers for LOS. A significant difference (p¡ 0.05) was found between the normal and outlier groups of LOS based on demographic (age, gender and residential information) and clinical characteristics(ward type, maximum of anatomically-based injury severity score(AIS) and probability of survival). Age group, maximum AIS score on specific injured region, ward type and its interaction effect with the number of admissions may associated with the LOS. Specifically, patients admitted to the geriatric ward exhibited notably prolonged LOS, and individuals with more than 2 admissions to long-term care and recovery-related wards such as neurosurgical rehabilitation, spinal injuries and burns wards also displayed elevated LOS.

Conclusion

Our finding supports prior evidence indicating elderly people are vulnerable to longer stays. Moreover, concerning the types of admission wards, patients admitted to rehabilitation wards who underwent more than 2 hospitalisations also faced an increased risk of prolonged stay. Based on these results, policymakers and healthcare providers should contemplate expanding the allocation of medical resources to this demographic to mitigate the length of stay and optimise associated healthcare costs.

Scoring Tool to Predict Need for Early Video-Assisted Thoracoscopic Surgery (VATS) After Pediatric Trauma

BACKGROUND

No widely used stratification tool exists to predict which pediatric trauma patients may require a video-assisted thoracoscopic surgery (VATS). We sought to develop a novel VATS-In-Pediatrics (VIP) score to predict the need for early VATS (within 72 h of admission) for pediatric trauma patients.

METHODS

The pediatric 2017-2020 Trauma Quality Improvement Program database was used and divided into two sets (derivation set using 2017-2019 data and validation set using 2020 data). First, multiple logistic regression models were created to determine the risk of early VATS for patients ≤ 17 years old. Second, the weighted average and relative impact of each independent predictor were used to derive a VIP score. We then validated the score using the area under the receiver operating characteristic (AROC) curve.

RESULTS

From 218,628 patients in the derivation set, 2183 (1.0%) underwent early VATS. A total of 8 independent predictors of VATS were identified, and the VIP score was derived with scores ranging from 0 to 9. The AROC for this was 0.91. The VATS rate increased steadily from 12.5 to 32% then 60.5% at scores of 3, 4, and 6, respectively. In the validation set, from 70,316 patients, 887 (1.3%) underwent VATS, and the AROC was 0.91.

CONCLUSIONS

VIP is a novel and validated scoring tool to predict the need for early VATS in pediatric trauma. This tool can potentially help hospital systems prepare for pediatric patients at high risk for requiring VATS during their first 72 h of admission. Future prospective research is needed to evaluate VIP as a tool that can improve clinical outcomes.

Socioeconomic Factors Are Associated With Severity of Hospitalization in Pediatric Lupus: An Analysis of the 2016 Kids' Inpatient Database

OBJECTIVE

Health disparities in adult lupus, including higher disease severity and activity among those in poverty, have been identified. Similar associations in pediatric lupus have not been clearly established. This study was undertaken to investigate the relationship of income level and other socioeconomic factors with length of stay (LOS) in the hospital and severe lupus features using the 2016 Kids' Inpatient Database (KID).

METHODS

Lupus hospitalizations were identified in children ages 2-20 years in the 2016 KID using International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes (M32). Univariate and multivariate negative binomial regression analyses were used to analyze the association of income level, race and ethnicity, and insurance status with LOS in the hospital. Univariate and multivariate logistic regression analyses were used to analyze the association of the same predictors with the presence of severe lupus features, defined using ICD-10 codes associated with lupus sequelae (e.g., lupus nephritis).

RESULTS

A total of 3,367 unweighted (4,650 weighted) lupus hospitalizations were identified. Income level was found to be a statistically significant predictor of increased LOS in the hospital for those in the lowest income quartile (adjusted incidence rate ratio 1.12 [95% confidence interval (95% CI) 1.02-1.23]). Black race, "other" race, and public insurance were also associated with severe lupus features (adjusted odds ratio [ORadj ] 1.51 [95% CI 1.11-2.06]; ORadj 1.61 [95% CI 1.01-2.55]; and ORadj 1.51 [95% CI 1.17-2.55], respectively).

CONCLUSION

Using a nationally representative data set, income level was found to be a statistically significant predictor of LOS in the hospital among those with the lowest reported income, highlighting a potential target population for intervention. Additionally, Black race and public insurance were associated with severe lupus features.

Predicting Patients at Risk for Prolonged Hospital Stays Following Pediatrics Traumatic Head Injuries in High-Income Developing Country: A Retrospective Cohort Study

BACKGROUND

Traumatic brain injuries (TBIs) in pediatrics are the most common cause of long-term morbidity and mortality, generating a considerable burden on the health care system. In the current retrospective study, we aimed to identify the predictors that contribute to prolonged hospital stays in pediatric TBI.

METHODS

A retrospective cohort study including all pediatric cases (age younger than 14) who presented to Khoula Hospital with TBI and were seen from January 2015 to December 2019. The multivariate binary logistic regression analysis has been used to determine the independent predictors of prolonged hospital stay. Prolonged hospitalization was defined as mean ± 2 standard deviation days.

RESULTS

A total of 866 cases of pediatric TBI were documented. The mean age was 4.33 years. The length of hospital stay ranged from <1 day to 90 days (mean = 3.65, standard deviation = 6.84). Prolonged hospitalization was calculated to be >17 days. Thirty-one patients had prolonged hospital stay out of the studied cohort, with an incidence proportion of prolonged stay = 3.6% (95% CI = 2.4%-5.0%). Prolonged hospitalizations were associated with motor vehicle collision injuries (odds ratio [OR]: 27.028, 95% confidence interval [CI] = 2.744-266.194, P = 0.005); pedestrian injuries (OR = 11.667, 95% CI = 1.017-133.805, P = 0.048), and Glasgow Coma Scale score on arrival of <9 (OR = 8.149, 95% CI = 1.167-56.921, P = 0.034).

CONCLUSIONS

The current study identified motor vehicle collision and pedestrian injuries, as well as initial Glasgow Coma Scale score of <9 as independent predictors of prolonged hospitalization in pediatrics TBI.

Novel Predictive Models for High-Value Care Outcomes Following Glioblastoma Resection

BACKGROUND

Treating patients with glioblastoma (GBM) requires extensive medical infrastructure. Individualized risk assessment for extended length of stay (LOS), nonroutine discharge disposition, and increased total hospital charges is critical to optimize delivery of care. Our study sought to develop predictive models identifying independent risk factors for these outcomes.

METHODS

We retrospectively reviewed patients undergoing GBM resection at our institution between January 2017 and September 2020. Extended LOS and elevated hospital charges were defined as values in the upper quartile of the cohort. Nonroutine discharge was defined as any disposition other than to home. Multivariate models for each outcome included covariates demonstrating P ≤ 0.10 on bivariate analysis.

RESULTS

We identified 265 patients undergoing GBM resection, with an average age of 58.2 years. 24.5% of patients experienced extended LOS, 22.6% underwent nonroutine discharge, and 24.9% incurred elevated total hospital charges. Decreasing Karnofsky Performance Status (KPS) (P = 0.004), increasing modified 5-factor frailty (mFI-5) index (P = 0.012), lower surgeon experience (P = 0.005), emergent surgery (P < 0.0001), and larger tumor volume (P < 0.0001) predicted extended LOS. Independent predictors of nonroutine discharge included older age (P = 0.02), decreasing KPS (P < 0.0001), and emergent surgery (P = 0.048). Nonprivate insurance (P = 0.011), decreasing KPS (P = 0.029), emergent surgery (P < 0.0001), and larger tumor volume (P = 0.004) predicted elevated hospital charges. These models were incorporated into an open-access online calculator (https://neurooncsurgery3.shinyapps.io/gbm_calculator/).

CONCLUSIONS

Several factors were independent predictors for at least 1 high-value care outcome, with lower KPS and emergent admission associated with each outcome. These models and our calculator may help clinicians provide individualized postoperative risk assessment to glioblastoma patients.

Future of machine learning in paediatrics

Machine learning (ML) is a branch of artificial intelligence (AI) that enables computers to learn without being explicitly programmed, through a combination of statistics and computer science. It encompasses a variety of techniques used to analyse and interpret extremely large amounts of data, which can then be applied to create predictive models. Such applications of this technology are now ubiquitous in our day-to-day lives: predictive text, spam filtering, and recommendation systems in social media, streaming video and e-commerce to name a few examples. It is only more recently that ML has started to be implemented against the vast amount of data generated in healthcare. The emerging role of AI in refining healthcare delivery was recently highlighted in the 'National Health Service Long Term Plan 2019'. In paediatrics, workforce challenges, rising healthcare attendance and increased patient complexity and comorbidity mean that demands on paediatric services are also growing. As healthcare moves into this digital age, this review considers the potential impact ML can have across all aspects of paediatric care from improving workforce efficiency and aiding clinical decision-making to precision medicine and drug development.

Effects of the COVID-19 pandemic on pediatric trauma in Southern California

PURPOSE

The COVID-19 pandemic resulted in increased penetrating trauma and decreased length of stay (LOS) amongst the adult trauma population, findings important for resource allocation. Studies regarding the pediatric trauma population are sparse and mostly single-center. This multicenter study examined pediatric trauma patients, hypothesizing increased penetrating trauma and decreased LOS after the 3/19/2020 stay-at-home (SAH) orders.

METHODS

A multicenter retrospective analysis of trauma patients ≤ 17 years old presenting to 11 centers in California was performed. Demographic data, injury characteristics, and outcomes were collected. Patients were divided into three groups based on injury date: 3/19/2019-6/30/2019 (CONTROL), 1/1/2020-3/18/2020 (PRE), 3/19/2020-6/30/2020 (POST). POST was compared to PRE and CONTROL in separate analyses.

RESULTS

1677 patients were identified across all time periods (CONTROL: 631, PRE: 479, POST: 567). POST penetrating trauma rates were not significantly different compared to both PRE (11.3 vs. 9.0%, p = 0.219) and CONTROL (11.3 vs. 8.2%, p = 0.075), respectively. POST had a shorter mean LOS compared to PRE (2.4 vs. 3.3 days, p = 0.002) and CONTROL (2.4 vs. 3.4 days, p = 0.002). POST was also not significantly different than either group regarding intensive care unit (ICU) LOS, ventilator days, and mortality (all p > 0.05).

CONCLUSIONS

This multicenter retrospective study demonstrated no difference in penetrating trauma rates among pediatric patients after SAH orders but did identify a shorter LOS.