Differentiating ischemic stroke patients from healthy subjects using a large-scale, retrospective EEG database and machine learning methods.

OBJECTIVES: We set out to develop a machine learning model capable of distinguishing patients presenting with ischemic stroke from a healthy cohort of subjects. The model relies on a 3-min resting electroencephalogram (EEG) recording from which features can be computed. MATERIALS AND METHODS: Using a large-scale, retrospective database of EEG recordings and matching clinical reports, we were able to construct a dataset of 1385 healthy subjects and 374 stroke patients. With subjects often producing more than one recording per session, the final dataset consisted of 2401 EEG recordings (63% healthy, 37% stroke). RESULTS: Using a rich set of features encompassing both the spectral and temporal domains, our model yielded an AUC of 0.95, with a sensitivity and specificity of 93% and 86%, respectively. Allowing for multiple recordings per subject in the training set boosted sensitivity by 7%, attributable to a more balanced dataset. CONCLUSIONS: Our work demonstrates strong potential for the use of EEG in conjunction with machine learning methods to distinguish stroke patients from healthy subjects. Our approach provides a solution that is not only timely (3-minutes recording time) but also highly precise and accurate (AUC: 0.95).

Quality indicators for osteoarthritis pain management in the primary care setting.

BACKGROUND: Development of valid and feasible quality indicators (QIs) is needed to track quality initiatives for osteoarthritis pain management in primary care settings. METHODS: Literature search identified published guidelines that were reviewed for QI extraction. A panel of 14 experts was assembled, including primary care physicians, rheumatologists, orthopedic surgeons, pain specialists, and outcomes research pharmacists. A screening survey excluded QIs that cannot be reliably extracted from the electronic health record or that are irrelevant for osteoarthritis in primary care settings. A validity screening survey used a 9-point Likert scale to rate the validity of each QI based on predefined criteria. During expert panel discussions, stakeholders revised QI wording, added new QIs, and voted to include or exclude each QI. A priority survey used a 9-point Likert scale to prioritize the included QIs. RESULTS: Literature search identified 520 references published from January 2015 to March 2021 and 4 additional guidelines from professional/governmental websites. The study included 41 guidelines. Extraction of 741 recommendations yielded 115 candidate QIs. Feasibility screening excluded 28 QIs. Validity screening and expert panel discussion excluded 73 QIs and added 1 QI. The final set of 15 prioritized QIs focused on pain management safety, education, weight-management, psychological wellbeing, optimizing first-line medications, referral, and imaging. CONCLUSION: This multi-disciplinary expert panel established consensus on QIs for osteoarthritis pain management in primary care settings by combining scientific evidence with expert opinion. The resulting list of 15 prioritized, valid, and feasible QIs can be used to track quality initiatives for osteoarthritis pain management.

Impact of automated alerts on discharge opioid overprescribing after general surgery.

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: The objectives of this study were to identify the most performed surgical procedures associated with the highest rates of discharge opioid overprescribing and to implement an electronic health record (EHR) alert to reduce discharge opioid overprescribing. METHODS: This quality improvement, before-and-after study included patients undergoing one of the identified target procedures-laparoscopic cholecystectomy, unilateral open inguinal hernia repair, and laparoscopic appendectomy-at an academic medical center. The alert notified providers when the prescribed opioid quantity exceeded guideline recommendations. The preimplementation cohort included surgical encounters from January 2020 to December 2021. The EHR alert was implemented in May 2022 following provider education via email and in-person presentations. The postimplementation cohort included surgical encounters from May to August 2022. The primary outcome was the proportion of patients with a discharge opioid supply exceeding guideline recommendations (overprescribing). RESULTS: A total of 1,478 patients were included in the preimplementation cohort, and 141 patients were included in the postimplementation cohort. The rate of discharge opioid overprescribing decreased from 48% in the preimplementation cohort to 3% in the postimplementation cohort, with an unadjusted absolute reduction of 45% (95% confidence interval, 41% to 49%; P < 0.001) and an adjusted odds ratio of 0.03 (95% confidence interval, 0.01 to 0.08; P < 0.001). Among patients who received opioids, the mean (SD) opioid supply at discharge decreased from 92 (43) oral morphine milligram equivalents (MME) (before implementation) to 57 (20) MME (after implementation) (P < 0.001). The proportion of patients who received additional opioid prescriptions within 1 to 14 days of hospital discharge did not change (P = 0.76). CONCLUSION: Implementation of an EHR alert along with provider education can reduce discharge opioid overprescribing following general surgery.

What Will the Mobile Stroke Unit of the Future Look Like, and Will EEG Have a Role?

There have been major advances in prehospital evaluation and care of stroke patients in the past 2 decades. Because about half of patients experiencing stroke arrive to the emergency department (ED) by ambulance, emergency medical service providers are in a unique position to positively affect stroke outcomes. One development of great interest is the implementation of mobile stroke units (MSUs), large ambulances outfitted with mobile CT scanners, point-of-care laboratories, and access to clinical stroke expertise (either in-person or remotely).1.

Optimization of Opioid Discharge Prescriptions Following Thyroid and Parathyroid Surgery.

OBJECTIVE: To evaluate the impact of a quality improvement bundle on opioid discharge prescribing following thyroidectomy and parathyroidectomy. METHODS: This before-and-after study included patients undergoing thyroidectomy or parathyroidectomy at an academic medical center. The quality improvement bundle included a patient education flyer, electronic health record order sets with multimodal analgesia regimens, and provider education. The preimplementation cohort included patients treated from January 2018 to December 2019. The postimplementation cohort included patients treated from June 2021 to August 2021. The primary outcome was the proportion of patients who received new opioid discharge prescriptions. RESULTS: A total of 160 patients were included in the preimplementation cohort, and the first 80 patients treated after bundle implementation were included in the postimplementation cohort. Patients receiving new opioid discharge prescriptions decreased from 80% (128/160) in the preimplementation cohort to 35% (28/80) in the postimplementation cohort with an unadjusted absolute reduction of 45% (95% CI, 33%-57%; P < .001; number needed to treat = 3) and an adjusted odds ratio (OR) of 0.08 (95% CI, 0.04-0.19; P < .001). The bundle was associated with reductions in opioid discharge prescriptions that exceeded 112.5 oral morphine milligram equivalents (33% pre- vs 10% postimplementation; adjusted OR, 0.20; P = .001) or 5 days of therapy (17% pre- vs 6% postimplementation; adjusted OR, 0.34; P = .049). DISCUSSION: Implementation of a pain management quality improvement bundle reduced opioid discharge prescribing following thyroidectomy and parathyroidectomy. IMPLICATIONS FOR PRACTICE: Unnecessary opioid prescriptions generate unused opioids in patients' homes that can lead to opioid misuse. We believe that this bundle reduced the risk for opioid misuse in our community. REGISTRATION: The study was registered at ClinicalTrials.gov (NCT04955444) before implementation.

A Persistent Positive Antibody Test in a Patient with No History of COVID-19 Infection.

Antibody testing for SARS-CoV-2 has been established as a tool with broad utility in the surveillance and control of the COVID-19 pandemic. However, because of limited knowledge about the duration of humoral immunity to COVID-19 and the existence of unique individual immune responses, the potential role of antibody testing in the diagnosis of current and past infections of COVID-19 remains ambiguous. Herein, we describe a unique case of an asymptomatic patient showing a persistent positive total antibody test for SARS-CoV-2 while testing negative for SARS-CoV-2 RNA and IgG-specific antibodies. This case study shows how a combination of tests can be employed to identify a false positive and draw conclusions about a patient's COVID-19 status. It also highlights the complexity of using antibody testing for the diagnosis of COVID-19.

Quality indicators to measure the effect of opioid stewardship interventions in hospital and emergency department settings.

PURPOSE: The purpose of this project was to develop a set of valid and feasible quality indicators used to track opioid stewardship efforts in hospital and emergency department settings. METHODS: Candidate quality indicators were extracted from published literature. Feasibility screening excluded quality indicators that cannot be reliably extracted from the electronic health record or that are irrelevant to pain management in the hospital and emergency department settings. Validity screening used an electronic survey of key stakeholders including pharmacists, nurses, physicians, administrators, and researchers. Stakeholders used a 9-point Likert scale to rate the validity of each quality indicator based on predefined criteria. During expert panel discussions, stakeholders revised quality indicator wording, added new quality indicators, and voted to include or exclude each quality indicator. Priority ranking used a second electronic survey and a 9-point Likert scale to prioritize the included quality indicators. RESULTS: Literature search yielded 76 unique quality indicators. Feasibility screening excluded 9 quality indicators. The validity survey was completed by 46 (20%) of 228 stakeholders. Expert panel discussions yielded 19 valid and feasible quality indicators. The top 5 quality indicators by priority were: the proportion of patients with (1) naloxone administrations, (2) as needed opioids with duplicate indications, and (3) long acting or extended release opioids if opioid-naïve, (4) the average dose of morphine milligram equivalents administered per day, and (5) the proportion of opioid discharge prescriptions exceeding 7 days. CONCLUSION: Multi-professional stakeholders across a health system participated in this consensus process and developed a set of 19 valid and feasible quality indicators for opioid stewardship interventions in the hospital and emergency department settings.

Small-fiber neuropathy: answering the burning questions.

Small-fiber neuropathy is a peripheral nerve disease that most commonly presents in middle-aged and older people, who develop burning pain in their feet. Although it can be caused by disorders of metabolism such as diabetes, chronic infections (such as with human immunodeficiency virus), genetic abnormalities, toxicity from various drugs, and autoimmune diseases, the cause often remains a mystery because standard electrophysiologic tests for nerve injury do not detect small-fiber function. Inadequate ability to test for and diagnose small-fiber neuropathies has impeded patient care and research, but new tools offer promise. Infrequently, the underlying cause of small-fiber dysfunction is identified and disease-modifying therapy can be instituted. More commonly, the treatments for small-fiber neuropathy involve symptomatic treatment of neuropathic pain.