Restless legs syndrome (RLS) affects about 20% of all pregnant women. RLS symptoms are usually moderate to severe in intensity during pregnancy and can result in insomnia, depression, and other adverse outcomes. Although iron deficiency has been implicated as a potential etiological factor, other mechanisms can also play a role. Nonpharmacologic methods are the primary recommended form of treatment for RLS in pregnancy and lactation. Iron supplementation may be considered when the serum ferritin is low; however, several patients are unable to tolerate iron or have severe symptoms despite oral iron replacement. Here, we describe a case of severe RLS in pregnancy and illustrate the dilemmas in diagnosis and management. We review the literature on the prevalence, diagnosis, course, possible underlying pathophysiologic mechanisms and complications of RLS in pregnancy. We describe current best evidence on the efficacy, and safety of nonpharmacologic therapies, oral and intravenous iron supplementation, as well as other medication treatments for RLS in pregnancy and lactation. We highlight gaps in the literature and provide a practical guide for the clinical management of RLS in pregnancy and during breastfeeding.

Study Objectives: Patients presenting with excessive sleepiness are frequently using antidepressant medication(s). While practice parameters recommend discontinuation of antidepressants prior to multiple sleep latency testing (MSLT), data examining the impact of tapering these medications on MSLT results are limited. Methods: Adult patients who underwent MSLT at Mayo Clinic Rochester, Minnesota, between 2014 and 2018 were included. Clinical and demographic characteristics, medications, including use of rapid eye movement-suppressing antidepressants (REMS-ADs) at assessment and during testing, actigraphy, and polysomnography data were manually abstracted. The difference in number of sleep-onset rapid eye movement periods (SOREMs), proportion with ≥2 SOREMs, and mean sleep latency in patients who were using REMS-ADs and discontinued prior to testing versus those who remained on REMS-ADs were examined. At our center, all antidepressants are discontinued 2 weeks prior to MSLT, wherever feasible; fluoxetine is stopped 6 weeks prior. Regression analyses accounting for demographic, clinical, and other medication-related confounders were performed. Results: A total of 502 patients (age = 38.18 ± 15.90 years; 67% female) underwent MSLT; 178 (35%) were taking REMS-ADs at the time of assessment. REMS-AD was discontinued prior to MSLT in 121/178 (70%) patients. Patients whose REMS-AD was discontinued prior to MSLT were more likely to have ≥2 SOREMs (odds ratio: 12.20; 95% confidence interval: 1.60-92.94) compared with patients on REMS-ADs at MSLT. They also had shorter mean sleep latency (8.77 ± 0.46 vs 10.21 ± 0.28 minutes; P > .009) and higher odds of having ≥2 SOREMs (odds ratio: 2.22; 95% confidence interval: 1.23-3.98) compared with patients not taking REMS-ADs at initial assessment. These differences persisted after regression analyses accounting for confounders. Conclusions: Patients who taper off REMS-ADs prior to MSLT are more likely to demonstrate ≥2 SOREMs and have a shorter mean sleep latency. Pending further prospective investigations, clinicians should preferably withdraw REMS-ADs before MSLT. If this is not done, the test interpretation should include a statement regarding the potential effect of the drugs on the results.

Context: Identifying patients with needs related to Social Determinants of Health (SDOH) and connecting them with appropriate resources in an effective, efficient, and timely way can prove challenging. Primary care clinicians (PCC's) interact with the EHR thousands of times daily; this engagement can be leveraged to better address the SDOH. Objective: To understand our health system PCC's use of the EHR to identify adult patients who are experiencing adverse SDOH. Study Design: Descriptive study conducted by a learning collaborative (LC). Setting: A large health system including urban and rural regions in Minnesota, Wisconsin, Iowa, Florida, and Arizona. Population studied: Community-based physicians, nurse practitioners, and physician assistants practicing in family medicine, general internal medicine, or pediatrics. Instrument: A brief intranet survey was sent to members of the system's primary care learning collaborative. The survey included multiple-choice questions, with additional space provided for optional narrative responses. Outcome Measures: Assess PCC's practice patterns for addressing the SDOH through utilization of the EHR tools. Results: 87 responses were received out of 192 surveys issued (45%). Most PCC's see patients who are negatively impacted by SDOH either daily (85%) or weekly (92%). Fifty-six percent review the patient specific SDOH information in the EHR at the time of the clinical encounter, while 29% do not review the information at all. Of those who review the SDOH in the EHR, 63% refer the patient to someone else to manage the identified needs; 78% use social workers, 44% use nursing staff, and 24% use case managers. Only 11% rated the EHR as very useful in identifying SDOH, 55% find it somewhat useful and 32% do not find it helpful at all. Most (78%) were unaware of how to use the EHR to refer a patient to a community-based organization. Forty-four percent of PCC's were interested in learning, in written or webinar form, more about using the EHR to screen and intervene on the SDOH. Conclusion: PCC's frequently see patients with needs related to the SDOH. While the EHR is a tool to screen patients for barriers to optimal health, it is not currently being well utilized by PCCs to intervene on these barriers. PCCs tend to engage ancillary team members to address the complex care needs of their patients. There is interest in learning ways to use the EHR to identify and intervene when adverse SDOH are identified.