Palmer N, Beam A, Agniel D, Eran A, Manrai A, Spettell C, Steinberg G, Mandl K, Fox K, Nelson SF, et al. Association of Sex With Recurrence of Autism Spectrum Disorder Among Siblings. JAMA Pediatr. 2017;171 (11) :1107-1112.
AbstractImportance: Autism spectrum disorder (ASD) is known to be more prevalent among males than females in the general population. Although overall risk of recurrence of ASD among siblings has been estimated to be between 6.1% and 24.7%, information on sex-specific recurrence patterns is lacking.
Objective: To estimate high-confidence sex-specific recurrence rates of ASD among siblings.
Design, Setting, and Participants: This observational study used an administrative database to measure the incidence of ASD among children in 1 583 271 families (37 507 with at least 1 diagnosis of ASD) enrolled in commercial health care insurance plans at a large US managed health care company from January 1, 2008, through February 29, 2016. Families in the study had 2 children who were observed for at least 12 months between 4 and 18 years of age.
Main Outcomes and Measures: The primary measure of ASD recurrence was defined as the diagnosis of ASD in a younger sibling of an older sibling with an ASD diagnosis.
Results: Among the 3 166 542 children (1 547 266 females and 1 619 174 males; mean [SD] age, 11.2 [4.7] years) in the study, the prevalence of ASD was 1.96% (95% CI, 1.94%-1.98%) among males and 0.50% (95% CI, 0.49%-0.51%) among females. When a male was associated with risk in the family, ASD was diagnosed in 4.2% (95% CI, 3.8%-4.7%) of female siblings and 12.9% (95% CI, 12.2%-13.6%) of male siblings. When a female was associated with risk in the family, ASD was diagnosed in 7.6% (95% CI, 6.5%-8.9%) of female siblings and 16.7% (95% CI, 15.2%-18.4%) of male siblings.
Conclusions and Relevance: These findings are in agreement with the higher rates of ASD observed among males than among females in the general population. Our study provides more specific guidance for the screening and counseling of families and may help inform future investigations into the environmental and genetic factors that confer risk of ASD.
Miron O, Beam AL, Kohane IS.
Auditory brainstem response in infants and children with autism spectrum disorder: A meta-analysis of wave V. Autism Res. 2017.
AbstractInfants with autism spectrum disorder (ASD) were recently found to have prolonged auditory brainstem response (ABR); however, at older ages, findings are contradictory. We compared ABR differences between participants with ASD and controls with respect to age using a meta-analysis. Data sources included MEDLINE, EMBASE, Web of Science, Google Scholar, HOLLIS, and ScienceDirect from their inception to June 2016. The 25 studies that were included had a total of 1349 participants (727 participants with ASD and 622 controls) and an age range of 0-40 years. Prolongation of the absolute latency of wave V in ASD had a significant negative correlation with age (R2 = 0.23; P = 0.01). The 22 studies below age 18 years showed a significantly prolonged wave V in ASD (Standard Mean Difference = 0.6 [95% CI, 0.5-0.8]; P < 0.001). The 3 studies above 18 years of age showed a significantly shorter wave V in ASD (SMD = -0.6 [95% CI, -1.0 to -0.2]; P = 0.004). Prolonged ABR was consistent in infants and children with ASD, suggesting it can serve as an ASD biomarker at infancy. As the ABR is routinely used to screen infants for hearing impairment, the opportunity for replication studies is extensive. Autism Res 2017. © 2017 The Authors Autism Research published by International Society for Autism Research and Wiley Periodicals, Inc.
LAY SUMMARY: Our analysis of previous studies showed that infants and children with autism spectrum disorder (ASD) have a slower brain response to sound, while adults have a faster brain response to sound. This suggests that slower brain response in infants may predict ASD risk. Brain response to sound is routinely tested on newborns to screen hearing impairment, which has created large data sets to afford replication of these results.
Nitzschke S, Offodile AC, Cauley RP, Frankel JE, Beam A, Elias KM, Gibbons FK, Salim A, Christopher KB.
Long term mortality in critically ill burn survivors. Burns. 2017;43 (6) :1155-1162.
AbstractINTRODUCTION: Little is known about long term survival risk factors in critically ill burn patients who survive hospitalization. We hypothesized that patients with major burns who survive hospitalization would have favorable long term outcomes.
METHODS: We performed a two center observational cohort study in 365 critically ill adult burn patients who survived to hospital discharge. The exposure of interest was major burn defined a priori as >20% total body surface area burned [TBSA]. The modified Baux score was determined by age + %TBSA+ 17(inhalational injury). The primary outcome was all-cause 5year mortality based on the US Social Security Administration Death Master File. Adjusted associations were estimated through fitting of multivariable logistic regression models. Our final model included adjustment for inhalational injury, presence of 3rd degree burn, gender and the acute organ failure score, a validated ICU risk-prediction score derived from age, ethnicity, surgery vs. medical patient type, comorbidity, sepsis and acute organ failure covariates. Time-to-event analysis was performed using Cox proportional hazard regression.
RESULTS: Of the cohort patients studied, 76% were male, 29% were non white, 14% were over 65, 32% had TBSA >20%, and 45% had inhalational injury. The mean age was 45, 92% had 2nd degree burns, 60% had 3rd degree burns, 21% received vasopressors, and 26% had sepsis. The mean TBSA was 20.1%. The mean modified Baux score was 72.8. Post hospital discharge 5year mortality rate was 9.0%. The 30day hospital readmission rate was 4%. Patients with major burns were significantly younger (41 vs. 47 years) had a significantly higher modified Baux score (89 vs. 62), and had significantly higher comorbidity, acute organ failure, inhalational injury and sepsis (all P<0.05). There were no differences in gender and the acute organ failure score between major and non-major burns. In the multivariable logistic regression model, major burn was associated with a 3 fold decreased odds of 5year post-discharge mortality compared to patients with TBSA<20% [OR=0.29 (95%CI 0.11-0.78; P=0.014)]. The adjusted model showed good discrimination [AUC 0.81 (95%CI 0.74-0.89)] and calibration (Hosmer-Lemeshow χ2 P=0.67). Cox proportional hazard multivariable regression modeling, adjusting for inhalational injury, presence of 3rd degree burn, gender and the acute organ failure score, showed that major burn was predictive of lower mortality following hospital admission [HR=0.34 (95% CI 0.15-0.76; P=0.009)]. The modified Baux score was not predictive for mortality following hospital discharge [OR 5year post-discharge mortality=1.00 (95%CI 0.99-1.02; P=0.74); HR for post-discharge mortality=1.00 (95% CI 0.99-1.02; P=0.55)].
CONCLUSIONS: Critically ill patients with major burns who survive to hospital discharge have decreased 5year mortality compared to those with less severe burns. ICU Burn unit patients who survive to hospital discharge are younger with less comorbidities. The observed relationship is likely due to the relatively higher physiological reserve present in those who survive a Burn ICU course which may provide for a survival advantage during recovery after major burn.
Beam AL, Kartoun U, Pai JK, Chatterjee AK, Fitzgerald TP, Shaw SY, Kohane IS.
Predictive Modeling of Physician-Patient Dynamics That Influence Sleep Medication Prescriptions and Clinical Decision-Making. Sci Rep. 2017;7 :42282.
AbstractInsomnia remains under-diagnosed and poorly treated despite its high economic and social costs. Though previous work has examined how patient characteristics affect sleep medication prescriptions, the role of physician characteristics that influence this clinical decision remains unclear. We sought to understand patient and physician factors that influence sleep medication prescribing patterns by analyzing Electronic Medical Records (EMRs) including the narrative clinical notes as well as codified data. Zolpidem and trazodone were the most widely prescribed initial sleep medication in a cohort of 1,105 patients. Some providers showed a historical preference for one medication, which was highly predictive of their future prescribing behavior. Using a predictive model (AUC = 0.77), physician preference largely determined which medication a patient received (OR = 3.13; p = 3 × 10(-37)). In addition to the dominant effect of empirically determined physician preference, discussion of depression in a patient's note was found to have a statistically significant association with receiving a prescription for trazodone (OR = 1.38, p = 0.04). EMR data can yield insights into physician prescribing behavior based on real-world physician-patient interactions.