Associations between commonly used patient-reported outcome tools in postpartum depression clinical practice and the Hamilton Rating Scale for Depression

Increasing postpartum depression screening and resources in pediatric primary care: A quality improvement project to enhance provider confidence

BACKGROUND

Unidentified and untreated postpartum depression (PPD) can have a negative impact on children. This Quality Improvement (QI) project aimed to increase PPD screening through provider education and enhancing pediatric primary care provider (PCP) confidence in using the Edinburg Postnatal Depression Screening (EPDS) tool, discussing PPD with mothers, and providing resources.

DESIGN AND METHODS

PCPs and staff were educated on the project. Providers were surveyed prior to and after implementation to assess confidence with screening for and addressing PPD. Mothers of infants 0-6 months were screened using the EPDS at well-care visits. Discussion of PPD and resource support was provided if needed.

RESULTS

A total of 273 mothers met criteria for screening, and of those 65% (n = 178) had a documented score. 12.4% of mothers had a score of 10 or greater, indicating high risk for PPD. Results from PCPs were compared both pre- and post-project. Screening for PPD increased from 3 to 4.5, using the EPDS tool from 2.25 to 4.75, discussing PPD with mothers from 2.75 to 4.25, and providing resources from 2.25 to 4.25.

CONCLUSIONS

PPD screening increased, and provider confidence with using the EPDS, discussing PPD with mothers, and providing resources in pediatric primary care increased.

PRACTICE IMPLICATIONS

Educating PCPs on the importance of PPD screening and providing resources for at-risk mothers can increase identification of PPD in the primary care setting. Enhancing the confidence of providers to discuss PPD with mothers and offer resources to those in need can lead to better outcomes for pediatric patients and their families.

Indirect comparisons of relative efficacy estimates of zuranolone and selective serotonin reuptake inhibitors for postpartum depression

AIMS

Estimate relative efficacy of zuranolone, a novel oral, Food and Drug Administration-approved treatment for postpartum depression (PPD) in adults vs. selective serotonin reuptake inhibitors (SSRIs) and combination therapies used for PPD in the United States.

MATERIALS AND METHODS

Randomized controlled trials (RCTs) for zuranolone and SSRIs, identified from systematic review, were used to construct evidence networks, linking via common comparator arms. Due to heterogeneity in placebo responses, matching-adjusted indirect comparison (MAIC) was applied, statistically weighting the zuranolone treatment arm of Phase 3 SKYLARK Study (NCT04442503) to the placebo arm of RCTs investigating SSRIs for PPD. MAIC outputs were applied in Bucher indirect treatment comparisons (ITCs) and network meta-analysis (NMA), using Edinburgh Postnatal Depression Scale (EPDS) and 17-item Hamilton Rating Scale for Depression (HAMD-17) change from baseline (CFB) on Days 3, 15, 28 (Month 1), 45, and last observation (Day 45, Week 12/18).

RESULTS

Larger EPDS CFB was observed among zuranolone-treated vs. SSRI-treated patients from Day 15 onward. Zuranolone-treated (vs. SSRI-treated) patients exhibited 4.22-point larger reduction in EPDS by Day 15 (95% confidence interval: -6.16, -2.28) and 7.43-point larger reduction at Day 45 (-9.84, -5.02) with Bucher ITC. NMA showed EPDS reduction for zuranolone was 4.52 (-6.40, -2.65) points larger than SSRIs by Day 15 and 7.16 (-9.47, -4.85) larger at Day 45. Lack of overlap between study populations substantially reduced effective sample size post-matching, making HAMD-17 CFB analysis infeasible.

LIMITATIONS

Limited population overlap between SKYLARK Study and RCTs reduced feasibility of undertaking HAMD-17 CFB ITCs and may introduce uncertainty to EPDS CFB ITC results.

CONCLUSIONS

Analysis showed zuranolone-treated patients with PPD experienced greater symptom improvement than SSRI-treated patients from Day 15 onward, with largest mean difference at Day 45. Adjusting for differences between placebo arms, zuranolone may be associated with greater PPD symptom improvement (measured by EPDS) vs. SSRIs.

Feasibility and acceptability of a novel telepsychiatry-delivered precision prescribing intervention for anxiety and depression

BACKGROUND

Major Depressive Disorder and Generalized Anxiety Disorder are pervasive and debilitating conditions, though treatment is often inaccessible and based on trial-and-error prescribing methods. The present observational study seeks to describe the use of a proprietary precision prescribing algorithm piloted during routine clinical practice as part of Brightside's telepsychiatry services. The primary aim is to determine the feasibility and acceptability of implementing this intervention. Secondary aims include exploring remission and symptom improvement rates.

METHODS

Participants were adult patients enrolled in Brightside who completed at least 12 weeks of treatment for depression and/or anxiety and received a prescription for at least one psychiatric medication. A prescription recommendation was made by Brightside's algorithm at treatment onset and was utilized for clinical decision support. Participants received baseline screening surveys of the PHQ-9 and GAD-7, and at weeks 2,4,6,8,10 and 12. Intent-to-treat (ITT) sensitivity analyses were conducted. Feasibility of the implementation was measured by the platform's ability to enroll and engage participants in timely psychiatric care, as well as offer high touch-point treatment options. Acceptability was measured by patient responses to a 5-star satisfaction rating.

RESULTS

Brightside accessed and treated 6248 patients from October 2018 to April 2021, treating a majority of patients within 4-days of enrollment. The average plan cost was $115/month. 89% of participants utilized Brightside's core medication plan at a cost of $95/month. 13.4% of patients in the study rated Brightside's services as highly satisfactory, averaging a 4.6-star rating. Furthermore, 90% of 6248 patients experienced a MCID in PHQ-9 or GAD-7 score. Remission rates were 75% (final PHQ-9 or GAD-7 score < 10) for the study sample and 59% for the ITT sample. 69.3% of Brightside patients were treated with the medication initially prescribed at intake.

CONCLUSIONS

Results suggest that the present intervention may be feasible and acceptable within the assessed population. Exploratory analyses suggest that Brightside's course of treatment, guided by precision recommendations, improved patients' symptoms of anxiety and depression.

The effect of intravenous ketamine on depressive symptoms after surgery: A systematic review

STUDY OBJECTIVE

The development of depressive symptoms is an important complication experienced by patients postoperatively and is associated with poor clinical outcomes. Ketamine is a feasible treatment option for depressive symptoms after surgery due to its known antidepressant effect. This meta-analysis aimed to evaluate the current body of research regarding the effects of intravenous ketamine on depressive symptoms after surgery.

DESIGN

A meta-analysis of randomized controlled trials.

SETTING

Perioperative care area.

PATIENTS

Adult surgical patients.

MEASUREMENTS

Systematic literature search was performed in the CENTRAL, MEDLINE, and EMBASE databases, for randomized controlled trials comparing the effect of intravenous ketamine versus placebo on postoperative depressive symptoms as the primary outcome, with no language restrictions. Two independent reviewers screened records for inclusion, extracted data, and assessed risk of bias. Random effects models were used to pool overall estimates. Postoperative pain intensity was also examined. The GRADE approach was used to assess the quality of evidence.

MAIN RESULTS

Out of 834 records screened, 9 studies met our inclusion criteria, comprising a total of 2468 patients. Compared with the control group, ketamine provided significant reduction of postoperative depression scale scores, by a standardized mean difference (SMD) of -0.89 (95% CI [-1.23, -0.73], P = 0.33, I² = 13%; 4 studies) on postoperative day (POD) 1, SMD -0.51 (95% CI [-0.99, -0.04], P < 0.001, I² = 93%; 4 studies) on POD 3, suggesting clinically relevant reduction in postoperative depressive symptoms. Postoperative depression scale scores on POD 7 were also reduced in patients receiving ketamine compared to the control group, with SMD -0.33 (95% CI [-0.52, -0.14], P = 0.36, I² = 2%; 3 studies), but the minimal clinical difference of 0.5 SMD was not reached. No significant difference was observed in the postoperative depression scale over the long term at 30 days' follow-up (SMD -0.13, 95% CI [-0.25, 0.00], P = 0.07, I² = 52%; 5 studies). A significant reduction of postoperative pain intensity on POD 1 was identified in patients following ketamine administration (SMD -1.29, 95% CI [-2.57, -0.01], P = 0.05, I² = 98%; 5 studies). However, administration of ketamine resulted in a significantly increased risk of nausea and vomiting (RR 1.71, 95% CI [1.25, 2.33], P = 0.17, I² = 35%; 6 studies), headache (RR 4.88, 95% CI [1.97, 12.06], P = 0.83, I² = 0%; 4 studies), and hallucination (RR 34.94, 95% CI [8.59, 142.17], P = 0.44, I² = 0%; 4 studies).

CONCLUSIONS

The current evidence supports intravenous ketamine administration for the treatment of depressive symptoms after surgery. While ketamine administration has clinically significant side effects, future studies are needed in surgical populations at high risk of complications.

Semi-supervised random forest regression model based on co-training and grouping with information entropy for evaluation of depression symptoms severity

Semi-supervised learning has always been a hot topic in machine learning. It uses a large number of unlabeled data to improve the performance of the model. This paper combines the co-training strategy and random forest to propose a novel semi-supervised regression algorithm: semi-supervised random forest regression model based on co-training and grouping with information entropy (E-CoGRF), and applies it to the evaluation of depression symptoms severity. The algorithm inherits the ensemble characteristics of random forest, and combines well with co-training. In order to balance the accuracy and diversity of co-training random forests, the algorithm proposes a grouping strategy to decision trees. Moreover, the information entropy is used to measure the confidence, which avoids unnecessary repeated training and improves the efficiency of the model. In the practical application of evaluation of depression symptoms severity, we collect cognitive behavioral data of emotional conflict based on the depressive affective disorder. And on this basis, feature construction and normalization preprocessing are carried out. Finally, the test is conducted on 35 labeled and 80 unlabeled depression patients. The result shows that the proposed algorithm obtains MAE (Mean Absolute Error) = 3.63 and RMSE (Root Mean Squared Error) = 4.50, which is better than other semi-supervised regression algorithms. The proposed method effectively solves the modeling difficulties caused by insufficient labeled samples, and has important reference value for the diagnosis of depression symptoms severity.