Prenatal Exposure to Nonpersistent Environmental Chemicals and Postpartum Depression.

Importance: Postpartum depression (PPD) affects up to 20% of childbearing individuals, and a significant limitation in reducing its morbidity is the difficulty in modifying established risk factors. Exposure to synthetic environmental chemicals found in plastics and personal care products, such as phenols, phthalates, and parabens, are potentially modifiable and plausibly linked to PPD and have yet to be explored. Objective: To evaluate associations of prenatal exposure to phenols, phthalates, parabens, and triclocarban with PPD symptoms. Design, Setting, and Participants: This was a prospective cohort study from 5 US sites, conducted from 2006 to 2020, and included pooled data from 5 US birth cohorts from the National Institutes of Health Environmental Influences on Child Health Outcomes (ECHO) consortium. Participants were pregnant individuals with data on urinary chemical concentrations (phenols, phthalate metabolites, parabens, or triclocarban) from at least 1 time point in pregnancy and self-reported postnatal depression screening assessment collected between 2 weeks and 12 months after delivery. Data were analyzed from February to May 2022. Exposures: Phenols (bisphenols and triclosan), phthalate metabolites, parabens, and triclocarban measured in prenatal urine samples. Main Outcomes and Measures: Depression symptom scores were assessed using the Edinburgh Postnatal Depression Scale (EPDS) or the Center for Epidemiologic Studies Depression Scale (CES-D), harmonized to the Patient-Reported Measurement Information System (PROMIS) Depression scale. Measures of dichotomous PPD were created using both sensitive (EPDS scores ≥10 and CES-D scores ≥16) and specific (EPDS scores ≥13 and CES-D scores ≥20) definitions. Results: Among the 2174 pregnant individuals eligible for analysis, nearly all (>99%) had detectable levels of several phthalate metabolites and parabens. PPD was assessed a mean (SD) of 3 (2.5) months after delivery, with 349 individuals (16.1%) and 170 individuals (7.8%) screening positive for PPD using the sensitive and specific definitions, respectively. Linear regression results of continuous PROMIS depression T scores showed no statistically significant associations with any chemical exposures. Models examining LMW and HMW phthalates and di (2-ethylhexyl) phthalate had estimates in the positive direction whereas all others were negative. A 1-unit increase in log-transformed LMW phthalates was associated with a 0.26-unit increase in the PROMIS depression T score (95% CI, -0.01 to 0.53; P = .06). This corresponded to an odds ratio (OR) of 1.08 (95% CI, 0.98-1.19) when modeling PPD as a dichotomous outcome and using the sensitive PPD definition. HMW phthalates were associated with increased odds of PPD (OR, 1.11; 95% CI, 1.00-1.23 and OR, 1.10; 95% CI, 0.96-1.27) for the sensitive and specific PPD definitions, respectively. Sensitivity analyses produced stronger results. Conclusions and Relevance: Phthalates, ubiquitous chemicals in the environment, may be associated with PPD and could serve as important modifiable targets for preventive interventions. Future studies are needed to confirm these observations.

Incidence and Trends of Progressive Supranuclear Palsy and Corticobasal Syndrome: A Population-Based Study.

BACKGROUND: Few studies have investigated the incidence of PSP and CBS in the population. OBJECTIVE: To examine the incidence of and trends in progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) in a population-based cohort of residents of Olmsted County, MN. METHODS: We used the 1991-2005 population-based, Olmsted County Parkinsonism-cohort study, defined via the Rochester Epidemiology Project. A movement-disorder specialist reviewed medical records, to confirm PSP and CBS diagnoses. RESULTS: We identified 21 patients with these diagnoses 1991-2005 : 18 (85.7%), PSP; 3 (14.3%), CBS. The median diagnosis age was 78 (range: 66-88). 13/21 (62.0%) were male. MRI was performed pre-diagnosis in 11 patients (8 PSP and 3 CBD); 10 showed atrophy consistent with clinical diagnoses. We observed concordance between clinical and pathological diagnoses in two PSP patients who underwent autopsy. Combined incidence for PSP and CBS in Olmsted County was 3.1 per 100,000 person-years (2.6 per 100,000 person-years, PSP; 0.4 per 100,000 person-years, CBS). Incidence was higher in men (4.5, 95% CI, 2.0-7.0) than women (1.8, 95% CI, 0.5-2.9). A combined, significant trend of increasing incidence was observed between 1991 and 2005 (B=0.69, 95% CI 0.42, 0.96, p<0.001). Median time from symptom onset to death among both groups was 6 years (range PSP, 1-10 years; range CBS, 3-8 years). CONCLUSIONS: The combined incidence for PSP and CBS was 3.1 per 100,000 person-years, higher in men than women. We observed a significant increase in both PSP and CBS, likely due to advancing imaging technology and improved diagnostic ability among physicians.

Incidence of frontotemporal disorders in Olmsted County: A population-based study.

INTRODUCTION: Frontotemporal dementia disorders (FTDs) are heterogeneous phenotypical behavioral and language disorders usually associated with frontal and/or temporal lobe degeneration. We investigated their incidence in a population-based cohort. METHODS: Using a records-linkage system, we identified all patients with a diagnostic code for dementia in Olmsted County, MN, 1995-2010, and confirmed the diagnosis of FTD. A behavioral neurologist verified the clinical diagnosis and determined phenotypes. RESULTS: We identified 35 FTDs cases. Overall, the incidence of FTDs was 4.3/100,000/year (95% CI: 2.9, 5.7). Incidence was higher in men (6.3/100,000, 95% CI 3.6, 9.0) than women (2.9/100,000; 95% CI: 1.3, 4.5); we observed an increased trend over time (B = 0.83, 95% CI: 0.54, 1.11, P < .001). At autopsy, clinical diagnosis was confirmed in eight (72.7%) cases. DISCUSSION: We observed an increased incidence and trends of FTDs over time. This may reflect a better recognition by clinicians and improvement of clinical criteria and diagnostic tools.

Episodic and Chronic Migraine in Primary Care.

OBJECTIVE: To inform migraine care model development by assessing differences between patients with chronic migraine (CM) and episodic migraine (EM) in the current state of treatment, disability, patient satisfaction, and quality improvement opportunities. BACKGROUND: Efficient and focused use of scarce resources will be needed to address challenges within large populations of migraine patients. METHODS: We deployed a cross-sectional survey study of randomly selected migraine patients within a community primary care practice. RESULTS: There were 516 survey respondents (516/1804 [30%] response rate). CM patients were more likely than EM patients to report care from a neurologist (76/110 [69%] vs 229/406 [56%]; P = .0026), and higher disability according to the Migraine Disability Assessment and Headache Impact Test - 6 questionnaires (P < .0001). CM patients were less likely than EM patients to report overall satisfaction with care (16/110 [38%] vs 156/406 [66%], P = .0002), satisfaction with access to care (17/110 [33%] vs 176/406 [68%], P < .0001), and advice they needed (16/110 [31%] vs 160/406 [62%], P < .0001). Most patients with migraine had been offered triptan medications 377/516 (78%). Overall, 156/516 (31%) of individuals were currently taking any medication for migraine prevention, and 208/516 (40%) including botulinum toxin injections. CM patients were more likely to be taking preventive medication (39/110 [36%] vs 117/406 [29%], P = .0191) and report familiarity with the diagnosis of medication-overuse headache than patients with EM (80/110 [81%] vs 256/406 [69%], P = .0178). CONCLUSIONS: We observed differences between patients with chronic and EM and expected care delivery improvement opportunities for migraine patients in primary care. CM patients report higher levels of disability and less satisfaction with access to perceived needed medical advice and care. These findings support the need to further develop and study novel care models to efficiently and effectively deliver high-quality care and expertise in limited supply to a diverse migraine population.

Measuring the impact of ambulatory red blood cell transfusion on home functional status: study protocol for a pilot randomized controlled trial.

BACKGROUND: Red blood cell (RBC) transfusion is frequently employed in both ambulatory and hospital environments with the aim of improving patient functional status. In the ambulatory setting, this practice is particularly common in patients with malignancy due to anemia associated with their cancer therapy. Increasingly, the efficacy of this US$10.5 billion per year practice has been called into question. While it is often standard of care for patients with chemotherapy-induced anemia to receive ambulatory RBC transfusions, it is unclear to what extent such transfusions affect home functional status. It is also unclear whether or not changes in functional status in this population can be objectively quantified using wearable activity monitors. We propose to directly measure the impact of outpatient RBC transfusions on at-home functional status by recording several physiological parameters and quantifiable physical activity metrics, e.g., daily energy expenditure and daily total step count, using the ActiGraph wGT3X-BT. This device is an accelerometer-based wearable activity monitor similar in size to a small watch and is worn at the waist. Study participants will wear the device during the course of their daily activities giving us quantifiable insight into activity levels in the home environment. METHODS/DESIGN: This will be a randomized crossover pilot clinical trial with a participant study duration of 28 days. The crossover nature allows each patient to serve as their own control. Briefly, patients presenting at a tertiary medical center's Ambulatory Infusion Center (AIC) will be randomized to either: (1) receive an RBC transfusion as scheduled (transfusion) or (2) abstain from the scheduled transfusion (no transfusion). After an appropriate washout period, participants will crossover from the transfusion arm to the no-transfusion arm or vice versa. Activity levels will be recorded continuously throughout the study using an accelerometry monitor. In addition to device data, functional status and health outcomes will be collected via a weekly telephone interview. The primary outcome measure will be daily energy expenditure. Performance metrics, such as step count changes, will also be evaluated. Additional secondary outcome measures will include daily sedentary time and Patient-reported Outcomes Measurement Information System (PROMIS) Global 10 Survey scores. DISCUSSION: This trial will provide important information on the feasibility and utility of using accelerometry monitors to directly assess the impact of RBC transfusion on patients' functional status. The results of the study will inform the merit and methods of a more definitive future trial evaluating the impact of ambulatory RBC transfusions in the target population. TRIAL REGISTRATION: ClinicalTrials.gov, identifier: NCT02835937 . Registered on 15 July 2016.

Effects of Plasma Transfusion on Perioperative Bleeding Complications: A Machine Learning Approach.

Perioperative bleeding (PB) is associated with increased patient morbidity and mortality, and results in substantial health care resource utilization. To assess bleeding risk, a routine practice in most centers is to use indicators such as elevated values of the International Normalized Ratio (INR). For patients with elevated INR, the routine therapy option is plasma transfusion. However, the predictive accuracy of INR and the value of plasma transfusion still remains unclear. Accurate methods are therefore needed to identify early the patients with increased risk of bleeding. The goal of this work is to apply advanced machine learning methods to study the relationship between preoperative plasma transfusion (PPT) and PB in patients with elevated INR undergoing noncardiac surgery. The problem is cast under the framework of causal inference where robust meaningful measures to quantify the effect of PPT on PB are estimated. Results show that both machine learning and standard statistical methods generally agree that PPT negatively impacts PB and other important patient outcomes. However, machine learning methods show significant results, and machine learning boosting methods are found to make less errors in predicting PB.

Ensemble learning approaches to predicting complications of blood transfusion.

Of the 21 million blood components transfused in the United States during 2011, approximately 1 in 414 resulted in complication [1]. Two complications in particular, transfusion-related acute lung injury (TRALI) and transfusion-associated circulatory overload (TACO), are especially concerning. These two alone accounted for 62% of reported transfusion-related fatalities in 2013 [2]. We have previously developed a set of machine learning base models for predicting the likelihood of these adverse reactions, with a goal towards better informing the clinician prior to a transfusion decision. Here we describe recent work incorporating ensemble learning approaches to predicting TACO/TRALI. In particular we describe combining base models via majority voting, stacking of model sets with varying diversity, as well as a resampling/boosting combination algorithm called RUSBoost. We find that while the performance of many models is very good, the ensemble models do not yield significantly better performance in terms of AUC.