Trajectory assessment is useful when day-to-day esophageal acid exposure varies in prolonged wireless pH monitoring.

Acid exposure time commonly varies from day-to-day in prolonged wireless pH monitoring. Thus, diagnosis based on the number of days with abnormal acid burden may be misleading or inconclusive. We hypothesize that assessing longitudinal patterns of acid exposure may be diagnostically useful. Therefore, this study aims to describe acid exposure trajectories and evaluate agreement between identified trajectory patterns and conventional grouping. In this retrospective cohort study, we assessed patients with nonresponse to proton pump inhibitor therapy who underwent wireless pH monitoring (≥72 h) off therapy between August 2010 and September 2016. The primary outcome was esophageal acid exposure time. Subjects were grouped as 0, 1, 2, and 3+ days positive based on number of days with an acid exposure time >5.0%. Latent class group-based mixture model identified distinct longitudinal acid exposure trajectory groups. Of 212 subjects included 44%, 18%, 14%, and 24% had 0, 1, 2, 3+ days positive, respectively. Group-based modeling identified three significantly stable acid exposure trajectories: low (64%), middle (28%), and high (8%). Trajectory grouping and days positive grouping agreed substantially (weighted K 0.69; 95% CI: 0.63-0.76). Trajectory grouping identified 62% of subjects with conventionally inconclusive studies (one or two days positive) into the low trajectory. Agreement between trajectory groups when using three versus four days of monitoring was substantial (K 0.70; CI: 0.61-0.78). In summary, we found that patients with nonresponse to proton pump inhibitors follow three acid exposure trajectories over prolonged pH-monitoring periods: low, middle, and high. Compared to conventional day positive grouping, the trajectory modeling identified the majority of inconclusive days positive into the low trajectory group. Analyzing prolonged wireless pH data according to trajectories may be a complimentary method to conventional grouping, and may increase precision and accuracy in identifying acid burden.

Pilot validation of blood-based biomarkers during pregnancy and postpartum in women with prior or current depression.

Major depressive disorder (MDD) is more common in women than in men, and evidence of gender-related subtypes of depression is emerging. Previously identified blood-based transcriptomic biomarkers distinguished male and female subjects with MDD from those without the disorder. In the present pilot study, we investigated the performance of these biomarkers in pregnant and postpartum women with prior major depressive episodes, some of whom had current symptomatology. The symptom scores of 13 pregnant and 15 postpartum women were identified by the Inventory of Depressive Symptoms (IDS-SR-30) at the time of blood sampling. Blood levels of the 20 transcriptomic biomarkers and that of estrogen receptor 2 (ESR2), membrane progesterone receptor alpha and beta (mPRα, mPRß) were measured. In pregnant women, transcript levels of ADCY3, ASAH1, ATP11C, CDR2, ESR2, FAM46A, mPRß, NAGA, RAPH1, TLR7, and ZNF291/SCAPER showed significant association with IDS-SR-30 scores, of which ADCY3, FAM46A, RAPH1, and TLR7 were identified in previous studies for their diagnostic potential for major depression. ASAH1 and ATP11C were previously also identified as potential markers of treatment efficacy. In postpartum women, transcript levels of CAT, CD59, and RAPH1 demonstrated a trend of association with IDS-SR-30 scores. Transcript levels of ADCY3, ATP11C, FAM46A, RAPH1, and ZNF291/SCAPER correlated with ESR2 and mPRß expressions in pregnant women, whereas these associations only existed for mPRß in postpartum women. These results suggest that a blood biomarker panel can identify depression symptomatology in pregnant women and that expression of these biomarker genes are affected by estrogen and/or progesterone binding differently during pregnancy and postpartum.

Rationale and design for an investigation to optimize selective serotonin reuptake inhibitor treatment for pregnant women with depression.

The physiological changes of pregnancy can affect the pharmacokinetics of a drug, thereby affecting its dose requirements. Because pharmacokinetic (PK) studies in pregnant women have rarely been conducted, evidence-based dosing adjustments are seldom available. In particular, despite the fact that the use of antidepressants has become increasingly common, pregnancy-associated PK changes of the selective serotonin reuptake inhibitors (SSRIs) are largely unknown.

High-resolution impedance manometry measurement of bolus flow time in achalasia and its correlation with dysphagia.

BACKGROUND: We assessed whether a high-resolution impedance manometry (HRIM) metric, bolus flow time (BFT) across the esophagogastric junction (EGJ), was abnormal in achalasia patients subtyped by the Chicago Classification and compared BFT to other HRM metrics. METHODS: HRIM studies were performed in 60 achalasia patients (14 type I, 36 type II and 10 type III) and 15 healthy controls. Studies were analyzed with a MATLAB program to calculate BFT using a virtual HRIM sleeve. Integrated relaxation pressure (IRP) and basal end-expiratory EGJ pressure were also calculated. The relationship between BFT and dysphagia symptom scores was assessed using the impaction dysphagia questionnaire (IDQ). KEY RESULTS: Median BFT was significantly lower in achalasia patients (0.5 s, range 0.0-3.5 s) compared to controls (3.5 s, range 2.0-5.0 s; p < 0.05). BFT was significantly lower in types I and II than in type III achalasia in both the supine and upright positions (p < 0.0001). BFT was the only HRIM metric significantly associated with IDQ score in both the supine (R(2)  = 0.20, p = 0.0046) and upright positions (R(2)  = 0.27, p = 0.0002). CONCLUSIONS & INFERENCES: BFT was significantly reduced in all subtypes of achalasia and complementary to the IRP as a diagnostic discriminant in equivocal achalasia cases. Additionally, BFT had a more robust correlation with dysphagia severity compared to other metrics of EGJ function.