Temporal Development of Depression and Anxiety in a Large Facial Palsy Cohort.

INTRODUCTION: Diagnosis with facial palsy (FP) has been linked to increased psychosocial distress and communication disorders, but limited data exist on the temporal development of depression and anxiety after diagnosis. In a large cohort of FP patients, we characterize the rates of depression and anxiety at several timepoints post-FP diagnosis. METHODS: A de-identified database of all FP patients who presented to a single healthcare system over 22 years was created using Epic SlicerDicer. Demographics and comorbidities were collected and depression and anxiety diagnosis rates at three timepoints (non-inclusive lower bounds) post-FP diagnosis were examined. RESULTS: 3,910 FP patients were identified, with a median age of 59. 56% were female and 51% were white. At 0-6, 6-12-, and 12-36-month post-FP diagnosis, 156 (4%), 58 (1.4%), and 205 (5.2%) individuals were diagnosed with depression, and 171 (4.4%), 84 (2.1%), and 237 (6.1%) were diagnosed with anxiety. At each time point, the median time between FP and depression diagnosis (2.1, 3.4, and 11.4 months) or anxiety diagnosis (2.5, 4.0, and 11.1 months) was similar. Dual depression and anxiety diagnoses were observed in 52 (1.3%), 32 (0.8%), and 122 (3.1%) patients at each time point. Compared to the overall cohort, more patients with anxiety were female (65 vs. 56%, p < 0.001) and younger (57 vs. 59, p = 0.002), and more depressed patients were Black (7.3 vs. 3.3%, p = 0.02). CONCLUSIONS: Facial palsy may lead to increased risk of depression and/or anxiety in the first year after diagnosis as demonstrated here in one of the largest FP cohorts to date. We report high rates of depression (5.5%), anxiety (6.5%), and comorbid depression and anxiety (2.1%) occurring within 1 year after FP diagnosis. Of these, the majority occurred within the first 6 months (72%, 67%, 62%, respectively). Anxiety was more common in young female patients and depression more common in Black patients, which can inform targeted mental health resources within the first 6 months post-FP diagnosis.

The Rate of Occult Lesion Diagnosis in a Large Bell's Palsy Cohort.

OBJECTIVES: We characterize occult lesion diagnosis rates after initial Bell's palsy diagnoses. METHODS: A de-identified database of all facial palsy patients who presented to an extensive health care system across 22 years was created using Epic SlicerDicer. Among patients with Bell's palsy diagnoses, we extracted demographic and any subsequent occult lesion diagnosis data across various clinical sites. Descriptive and multivariable regression analyses comparing patients with occult lesion diagnoses made at different time points were included. RESULTS: Among the total 3912 facial palsy patients, 2240 had Bell's palsy diagnoses, of which 217 (9.7%) had subsequent lesion diagnoses at a median (IQR) of 12.3 (4.2, 23.8) months, consisting of cranial nerve neoplasms (62.2%), parotid gland neoplasms (34.1%), and cholesteatomas (3.7%). Although a large proportion of total lesions were diagnosed within the first 3 months (19.8%), 69.5% were diagnosed after 6 months. There were no demographic differences among patients diagnosed with different lesion types, but Asian patients were more likely to be diagnosed with occult lesions after 12 months after Bell's palsy diagnosis compared with white patients (odds ratio = 6.2, p = 0.001). CONCLUSIONS: In one of the largest Bell's palsy cohorts to date, we identified a 9.7% occult lesion diagnosis rate at a median of 12.3 months after Bell's palsy diagnosis. These data underscore the importance of timely workup for occult lesions in cases of facial palsy with no signs of recovery after 3-4 months. LEVEL OF EVIDENCE: 4 Laryngoscope, 134:911-918, 2024.

A Window of Opportunity: Understanding Pediatric Falls Using Area Deprivation Index.

INTRODUCTION: The purpose of our study is to assess neighborhood socioeconomic disadvantage (NSD) as a risk factor for window falls (WF) in children. METHODS: A single institution retrospective review was performed of patients ≤18 years old with fall injuries treated at a Level I trauma center between 2018 and 2021. Demographic, injury, and NSD characteristics which were collected from a trauma registry were analyzed and compared between WF versus non-window falls. Area Deprivation Index (ADI) was used to measure NSD levels based on patients' home address 9-digit zip code, with greater NSD being defined as ADI quintiles 4 and 5. Property type was used to compare falls that took place at single-family homes versus apartment buildings. RESULTS: Among 1545 pediatric fall injuries, 194 were WF, of which 60 % were male and 46 % were Hispanic. WF patients were younger than NWF patients (median age WF 3.2 vs. age 4.3, p<0.047). WF patients were more likely to have a depressed Glasgow Coma Scale (GCS score ≤12, WF 9 % vs. 3 %) and sustain greater head/neck injuries (median AIS 3vs. AIS 2, p<0.001) when compared to NWF. WF patients had longer hospital and ICU lengths of stay than NWF patients (p<0.001 and p<0.001, respectively). WF patients were more likely to live in areas of greater NSD than NWF patients (53 % vs. 35 %, p<0.001), and 73 % of all WF patients lived in apartments or condominiums. CONCLUSIONS: Window fall injuries were associated with lower GCS, greater severity of head/neck injuries, and longer hospital and ICU length of stay than non-window falls. ADI research can provide meaningful data for targeted injury prevention programs in areas where children are at higher risk of window falls. STUDY TYPE: Retrospective review. LEVEL OF EVIDENCE: III.

Application of a Machine Learning Algorithm in Prediction of Abusive Head Trauma in Children.

PURPOSE: We explored the application of a machine learning algorithm for the timely detection of potential abusive head trauma (AHT) using the first free-text note of an encounter and demographic information. METHODS: First free-text physician notes and demographic information were collected for children under 5 years of age at a Level 1 Trauma Center. The control group, which included patients with head/neck injury, was compared to those with AHT diagnosed by the Child Protective Team. Differential scores accounted for words overrepresented in AHT patient vs. control notes. Sentiment scores were reflective of note positivity/negativity and subjectivity scores accounted for note subjectivity/objectivity. The composite scores reflected the patient's differential score modified by the subjectivity score. Composite, sentiment, and subjectivity scores combined with demographic information trained a Random Forest (RF) machine learning algorithm to predict AHT. RESULTS: Final composite scores with demographic information were highly associated with AHT in a test dataset. The control group included 587 patients and the test group included 193 patients. Combining composite scores with demographic information into the RF model improved AHT classification area under the curve (AUC) from 0.68 to 0.78, with an overall accuracy of 84%. Feature importance analysis of our RF model revealed that composite score, sentiment, age, and subjectivity were the most impactful predictors of AHT. The sentiment was not significantly different between control and AHT notes (p = 0.87), while subjectivity trended higher for AHT notes (p = 0.081). CONCLUSION: We conclude that a machine learning algorithm can recognize patterns within free-text notes and demographic information that aid in AHT detection in children. LEVEL OF EVIDENCE: III.

Evaluating pediatric car safety compliance in motor vehicle collisions: Identifying high-risk groups for improper restraint usage.

PURPOSE: To identify patient factors associated with improper restraint usage and worse trauma outcomes for pediatric patients involved in motor vehicle collisions (MVCs). METHODS: Retrospective study performed at a Level I pediatric trauma center for patients (≤18 yr) evaluated after MVC between 2008 and 2018. The Area Deprivation Index (ADI) was used to measure neighborhood socioeconomic disadvantage (NSD) levels based on the patient's home address. Trauma registry data was correlated to ADI and used to analyze appropriate restraint usage by NSD. Proper restraint practices were defined based on national guidelines and state laws. Demographics and clinical outcomes were also analyzed. Chi-square analysis with Bonferroni corrections was used to assess the association of ADI, race, and ethnicity with proper restraint usage. RESULTS: Among 1152 patients included, approximately 50% were male, the median age was 7 years [IQR 4-10], and 53% were of Hispanic ethnicity. Hispanic patients comprised 73% of children in ADI quintile 5 (greatest NSD), yet only 26% of children in ADI quintile 1 (least NSD). No differences were observed across clinical data and outcomes. Hispanic children <8 yr were significantly less likely to be in a car seat/booster seat compared to non-Hispanic children (OR 0.69, 95% CI 0.50-0.95, p = 0.025). Furthermore, those with greatest NSD (ADI quintile 5) had the largest proportion of unrestrained patients (21%, see Fig. 1). CONCLUSION: Hispanic children, especially those who require infant or booster seats (<8 yr), and children living in areas with greater neighborhood socioeconomic disadvantage demonstrated poorer restraint practices. ADI can successfully identify high-risk groups for targeted injury prevention programs and improved compliance in the most vulnerable neighborhoods. TYPE OF STUDY: Retrospective Study.

Integrating traffic safety data with area deprivation index: A method to better understand the causes of pediatric pedestrian versus automobile collisions.

BACKGROUND: The purpose of this study was to identify clinical and traffic factors that influence pediatric pedestrian versus automobile collisions (P-ACs) with an emphasis on health care disparities. METHODS: A retrospective review was performed of pediatric (18 years or younger) P-ACs treated at a Level I pediatric trauma center from 2008 to 2018. Demographic, clinical, and traffic scene data were analyzed. Area deprivation index (ADI) was used to measure neighborhood socioeconomic disadvantage (NSD) based on home addresses. Traffic scene data from the California Statewide Integrated Traffic Records System were matched to clinical records. Traffic safety was assessed by the streetlight coverage, the proximity of the collision to home addresses, and sidewalk coverage. Descriptive statistics and univariate analysis for key variables and outcomes were calculated using Kruskal-Wallis, Wilcoxon, χ 2 , or Fisher's exact tests. Statistical significance was attributed to p values of <0.05. RESULTS: Among 770 patients, the majority were male (65%) and Hispanic (54%), with a median age of 8 years (interquartile range, 4-12 years). Hispanic patients were more likely to live in more disadvantaged neighborhoods than non-Hispanic patients (67% vs. 45%, p < 0.01). There were no differences in clinical characteristics or outcomes across ADI quintiles. Using the Statewide Integrated Traffic Records System (n = 272), patients with more NSD were more likely injured during dark streetlight conditions (15% vs. 4% least disadvantaged; p = 0.04) and within 0.5 miles from home ( p < 0.01). Pedestrian violations were common (65%). During after-school hours, 25% were pedestrian violations, compared with 12% driver violations ( p = 0.02). CONCLUSION: A larger proportion of Hispanic children injured in P-ACs lived in neighborhoods with more socioeconomic disadvantage. Hispanic ethnicity and NSD are each independently associated with P-ACs. Poor streetlight conditions and close proximity to home were associated with the most socioeconomically disadvantaged neighborhoods. This research may support targeted prevention programs to improve pedestrian safety in children. LEVEL OF EVIDENCE: Prognostic/Epidemiological; Level IV.

Bike Helmet Usage in the Most Disadvantaged Neighborhoods: A Focused Area for Trauma Prevention.

INTRODUCTION: There is a paucity of data to describe how neighborhood socioeconomic disadvantage (NSD) correlates with childhood injuries and outcomes. This study assesses the relationship of NSD to bicycle safety and trauma outcomes among pediatric bicycle versus automobile injuries. METHODS: Between 2008 and 2018, patients ≤18 y old with bicycle versus automobile injuries from a Level I pediatric trauma center were evaluated. Area Deprivation Index (ADI) was used to measure NSD. Patient demographics, injury, clinical data characteristics, and bike safety were analyzed. Traffic scene data from the Statewide Integrated Traffic Records System were matched to clinical records. Multivariate logistic regression was used to assess demographic characteristics related to helmet usage. RESULTS: Among 321 patients, 84% were male with a median age of 12 y [interquartile range 9-13], and 44% were of Hispanic ethnicity. Hispanic ethnicity was greater in the most disadvantaged ADI groups (P < 0.001). Mortality occurred in two patients, and most (96%) were discharged home. Of Statewide Integrated Traffic Records System matched traffic records, 81% were at locations without a bike lane. No differences were found in GCS, intensive care unit admission, or length of stay by ADI. Hispanic ethnicity and the highest deprivation group were independently associated with lower odds of wearing a helmet (AOR 0.35, 95% confidence interval 0.1-0.9, P = 0.03; AOR 0.33 95% confidence interval 0.17-0.62; P = 0.001), while patient age and sex were unrelated to helmet usage. CONCLUSIONS: Outcomes for bike versus auto trauma remains similar across ADI groups. However, bike helmet usage is significantly lower among Hispanic children and those from neighborhoods with greater socioeconomic disadvantage.

Differential expression of nuclear genes encoding mitochondrial proteins from urban and rural populations in Morocco.

Urbanization in low-income countries represents an important inflection point in the epidemiology of disease, with rural populations experiencing high rates of chronic and recurrent infections and urban populations displaying a profile of noncommunicable diseases. To investigate if urbanization alters the expression of genes encoding mitochondrial proteins, we queried gene microarray data from rural and urban populations living in Morocco (GSE17065). The R Bioconductor packages edgeR and limma were used to identify genes with different expression. The experimental design was modeled upon location and sex. Nuclear genes encoding mitochondrial proteins were identified from the MitoCarta2.0 database. Of the 1158 genes listed in the MitoCarta2.0 database, 847 genes (73%) were available for analysis in the Moroccan dataset. The urban-rural comparison with the greatest environmental differences showed that 76.5% of the MitoCarta2.0 genes were differentially expressed, with 97% of the genes having an increased expression in the urban area. Enrichment analysis revealed 367 significantly enriched pathways (adjusted p value < 0.05), with oxidative phosphorylation, insulin secretion and glucose regulations (adj.p values = 6.93E-16) being the top three. Four significantly perturbed KEGG disease pathways were associated with urbanization-three degenerative neurological diseases (Huntington's, Alzheimer's, and Parkinson's diseases) and herpes simplex infection (false discover rate corrected p value (PGFdr) < 0.2). Mitochondrial RNA metabolic processing and translational elongation were the biological processes that had the greatest enrichment (enrichment ratios 14.0 and 14.8, respectively, FDR < 0.5). Our study links urbanization in Morocco with changes in the expression of the nuclear genes encoding mitochondrial proteins.