RESUMEN
BACKGROUND: Social determinants of health (SDOH) influence access to health care and are associated with inequities in patient outcomes, yet few studies have explored SDOH among pediatric EMS patients. The objective of this study was to examine the presence of SDOH in EMS clinician free text notes and quantify the association of SDOH with EMS pediatric transport decisions. METHODS: This was a retrospective analysis of primary 9-1-1 responses for patients ages 0-17 years from the 2019 ESO Data Collaborative research dataset. We excluded cardiac arrests and patients in law enforcement custody. Using natural language processing (NLP) we extracted the following SDOH categories: income insecurity, food insecurity, housing insecurity, insurance insecurity, poor social support, and child protective services. Univariate and multivariable associations between the presence of SDOH in EMS records and EMS transport decisions were assessed using logistic regression. RESULTS: We analyzed 325,847 pediatric EMS encounters, of which 35% resulted in non-transport. The median age was 10 years and 52% were male. Slightly over half (53%) were White, 31% were Black, and 11% were Hispanic. Child protective services (n = 2,620) and housing insecurity (n = 1,136) were the most common SDOH categories found in the EMS free text narratives. In the multivariable model, child protective services involvement (odds ratio (OR)=2.04 [95% confidence interval (CI) 1.84-2.05]), housing insecurity (OR = 1.46 [95% CI 1.26-1.70]), insurance security (OR = 2.44 [95% CI 1.93-3.09]), and poor social support (OR = 10.48 [95% CI 1.42-77.29]) were associated with greater odds of EMS transport. CONCLUSIONS: SDOH documentation in the EMS narrative was rare among pediatric encounters; however, children with documented SDOH were more likely to be transported. Additional exploration of the root causes and outcomes associated with SDOH among children encountered by EMS are warranted.
Asunto(s)
Servicios Médicos de Urgencia , Determinantes Sociales de la Salud , Humanos , Niño , Masculino , Recién Nacido , Lactante , Preescolar , Adolescente , Femenino , Estudios Retrospectivos , Procesamiento de Lenguaje Natural , Atención a la SaludRESUMEN
BACKGROUND: The goal of our investigation was to describe the incidence of serious bacterial infection (SBI, defined as bacteremia, urinary tract infection (UTI), or meningitis) in young infants with and without documented viral pathogens. METHODS: This was a retrospective cross-sectional study (1/2016-12/2017) in 3 emergency departments (EDs). Previously healthy 0-60-day-old infants were included if at least respiratory viral testing and a blood culture was obtained. The frequency of SBI, the primary outcome, was compared among infants with/without respiratory viral infections using the Pearson Chi-square test (or Fisher's Exact Test) and unadjusted odds ratios (OR). RESULTS: The median age of the 597-infant cohort was 32 days (interquartile range: 20-45 days); 42% were female. Eighty-three percent were well appearing in the ED and 72% were admitted. ED triage vitals commonly revealed tachypnea (68%), pyrexia (45%), and tachycardia (28%); hypoxemia (5%) was uncommon. Twenty-eight percent had positive viral testing, most commonly RSV (93/169, 55%), parainfluenza (29, 17%), and influenza A (23, 14%). Eighty-three infants (13.9%) had SBI: 8.4% (n = 50) had UTI alone, 2.8% (n = 17) had bacteremia alone, 1.2% (n = 7) had bacteremia + UTI, 1.0% (n = 6) had bacteremia + meningitis, and 0.5% (n = 3) had meningitis alone. Infants with documented respiratory viral pathogens were less likely to have any SBI (OR: 0.23; 95% CI: 0.11-0.50), UTI (OR 0.22, 95% CI: 0.09-0.56), or bacteremia (OR 0.27, 95% CI: 0.08-0.9) than infants with negative viral testing. There was no difference in meningitis frequency based on viral status (OR: 0.13, 95% CI: 0.008-2.25). CONCLUSIONS: The frequency of bacteremia and UTI was lower in young infants with respiratory viral infections compared to infants with negative respiratory viral testing.
Asunto(s)
Bacteriemia/epidemiología , Coinfección/epidemiología , Meningitis/epidemiología , Infecciones del Sistema Respiratorio/epidemiología , Infecciones Urinarias/epidemiología , Virosis/epidemiología , Bacteriemia/diagnóstico , Bacteriemia/virología , Estudios de Casos y Controles , Coinfección/diagnóstico , Coinfección/virología , Estudios Transversales , Servicio de Urgencia en Hospital , Femenino , Humanos , Lactante , Recién Nacido , Masculino , Meningitis/diagnóstico , Meningitis/virología , Gravedad del Paciente , Infecciones del Sistema Respiratorio/diagnóstico , Infecciones del Sistema Respiratorio/virología , Estudios Retrospectivos , Medición de Riesgo , Factores de Riesgo , Texas/epidemiología , Infecciones Urinarias/diagnóstico , Infecciones Urinarias/virología , Virosis/diagnósticoRESUMEN
OBJECTIVE: Patients with occlusive or aneurysmal vascular disease are repeatedly exposed to intravascular (IV) contrast for diagnostic or therapeutic purposes. We sought to determine the long-term impact of cumulative iodinated IV contrast exposure (CIVCE) on renal function; the latter was defined by means of National Kidney Foundation (NKF) criteria. METHODS: We performed a longitudinal study of consecutive patients without renal insufficiency at baseline (NFK stage I or II) who underwent interventions for arterial occlusive or aneurysmal disease. We collected detailed data on any IV iodinated contrast exposure (including diagnostic or therapeutic angiography, cardiac catheterization, IV pyelography, computed tomography with IV contrast, computed tomographic angiography); medication exposure throughout the observation period; comorbidities; and demographics. The primary end point was the development of renal failure (RF) (defined as NFK stage 4 or 5). Analysis was performed with the use of a shared frailty model with clustering at the patient level. RESULTS: Patients (n = 1274) had a mean follow-up of 5.8 (range, 2.2-14) years. In the multivariate model with RF as the dependent variable and after adjusting for the statistically significant covariates of baseline renal function (hazard ratio [HR], 0.95; P < .001), diabetes (HR, 1.8; P = .007), use of an angiotensin-converting enzyme inhibitor (HR, 0.63; P = .03), use of antiplatelets (HR, 0.5; P = .01), cumulative number of open vascular operations performed (HR, 1.2; P = .001), and congestive heart failure (HR, 3.2; P < .001), CIVCE remained an independent predictor for RF development (HR, 1.1; P < .001). In the multivariate survival analysis model and after adjusting for the statistically significant covariates of perioperative myocardial infarction (HR, 3.9; P < .001), age at entry in the cohort (HR, 1.05; P = .035), total number of open operations (HR, 1.51; P < .001), and serum albumin (HR, 0.47; P < .001), CIVCE was an independent predictor of death (HR, 1.07; P < .001). CONCLUSIONS: Cumulative IV contrast exposure is an independent predictor of RF and death in patients with occlusive and aneurysmal vascular disease.
Asunto(s)
Aneurisma/diagnóstico por imagen , Angiografía/efectos adversos , Arteriopatías Oclusivas/diagnóstico por imagen , Medios de Contraste/efectos adversos , Tasa de Filtración Glomerular/efectos de los fármacos , Insuficiencia Renal/inducido químicamente , Medición de Riesgo/métodos , Adulto , Anciano , Anciano de 80 o más Años , Medios de Contraste/administración & dosificación , Femenino , Estudios de Seguimiento , Humanos , Inyecciones Intravenosas , Riñón/efectos de los fármacos , Riñón/fisiopatología , Masculino , Persona de Mediana Edad , Insuficiencia Renal/mortalidad , Insuficiencia Renal/fisiopatología , Estudios Retrospectivos , Factores de Riesgo , Tasa de Supervivencia/tendencias , Texas/epidemiología , Factores de TiempoRESUMEN
BACKGROUND: Little is known about the predictors of anesthetic times and impact of anesthetic and operative times on patient outcomes. METHODS: We documented operative case length, anesthetic induction time length, and anesthetic recovery time length in 1713 consecutive patients who underwent elective vascular surgical interventions. We recorded patient and procedure-related characteristics that might influence the anesthetic time length, including a variable for possible July effect. Multivariate linear regression was used to model the length of anesthetic times. Multivariate logistic regression was used to model the impact of anesthetic and operative time lengths on a composite outcome of perioperative (30-d postoperative) death, myocardial infarction, cardiac arrhythmias, stroke, and congestive heart failure. RESULTS: Statistically significant predictors of anesthetic induction time included body mass index, anesthesia type, and procedure type. Statistically significant predictors of anesthetic recovery time included operative case length, procedure type, and anesthesia type. After adjusting for the statistically significant covariates of total blood transfusion, history of coronary artery disease, and procedure type, there was a trend for increased likelihood of the composite end point as a function of operative time (odds ratio, 1.14; 95% confidence interval, 0.97-1.33; P = 0.09), which did not reach statistical significance. Multivariate analysis showed no association between the anesthetic time and composite end point. CONCLUSIONS: Modeling individually anesthetic induction and recovery time on the basis of operative and anesthetic procedure characteristics is feasible. Anesthetic and operative times do not impact perioperative morbidity and mortality.