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Using Electronic Health Record Data to Determine the Safety of Aqueous Humor Liquid Biopsies for Molecular Analyses

Purpose

Knowing the surgical safety of anterior chamber liquid biopsies will support the increased use of proteomics and other molecular analyses to better understand disease mechanisms and therapeutic responses in patients and clinical trials. Manual review of operative notes from different surgeons and procedures in electronic health records (EHRs) is cumbersome, but free-text software tools could facilitate efficient searches.

Design

Retrospective case series.

Participants

A total of 1418 aqueous humor liquid biopsies from patients undergoing intraocular surgery.

Methods

Free-text EHR searches were performed using the Stanford Research Repository cohort discovery tool to identify complications associated with anterior chamber paracentesis and subsequent endophthalmitis. Complications of the surgery unrelated to the biopsy were not reviewed.

Main Outcome Measures

Biopsy-associated intraoperative complications and endophthalmitis.

Results

A total of 1418 aqueous humor liquid biopsies were performed by 17 experienced surgeons. EHR free-text searches were 100% error-free for surgical complications, >99% for endophthalmitis (<1% false positive), and >93.6% for anesthesia type, requiring manual review for only a limited number of cases. More than 85% of cases were performed under local anesthesia without ocular muscle akinesia. Although the most common indication was cataract (50.1%), other diagnoses included glaucoma, diabetic retinopathy, uveitis, age-related macular degeneration, endophthalmitis, retinitis pigmentosa, and uveal melanoma. A 50- to 100-μL sample was collected in all cases using either a 30-gauge needle or a blunt cannula via a paracentesis. The median follow-up was >7 months. There was only one minor complication (0.07%) identified: a case of a small tear in Descemet membrane without long-term sequelae. No other complications occurred, including other corneal injuries, lens or iris trauma, hyphema, or suprachoroidal hemorrhage. There was no case of postoperative endophthalmitis.

Conclusions

Anterior chamber liquid biopsy during intraocular surgery is a safe procedure and may be considered for large-scale collection of aqueous humor samples for molecular analyses. Free-text EHR searches are an efficient approach to reviewing intraoperative procedures.

Financial Disclosures

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

The Problem of Pain in Lupus: Epidemiological Profiles of Patients Attending Multidisciplinary Pain Clinics

INTRODUCTION

Patients with systemic lupus erythematosus (SLE) bear a significant burden of pain. We aimed to identify factors that distinguish patients with SLE referred to comprehensive pain clinics and those who are not. Characterizing this patient population will identify unmet needs in SLE management and inform efforts to improve pain care in rheumatology.

METHODS

Among patients with SLE with ≥2 rheumatology clinic visits in a large hospital system from 1998 to 2023 (n = 1319), we examined factors that distinguished those who had at least one visit to multidisciplinary pain clinics (n = 77, 5.8%) from those who did not have any visits (n = 1242, 94.2%) with a focus on biopsychosocial and socioeconomic characteristics. We extracted demographic data and ICD-9/ICD-10 codes from the EHR.

RESULTS

Patients with SLE attending the pain clinics exhibited characteristics including average older age (mean age ± SD: 54.1 ± 17.9 vs. 48.4 ± 19.9), a higher likelihood of relying on public health insurance (50.7% vs. 34.2%), and a greater representation of Black patients (9.1% vs. 4.4%) compared to SLE patients not seen in pain clinics. Nearly all patients seen at the pain clinics presented with at least one chronic overlapping pain condition (96.1% vs. 58.6%), demonstrated a higher likelihood of having a mental health diagnosis (76.7% vs. 42.4%), and exhibited a greater number of comorbidities (mean ± SD: 6.0 ± 3.0 vs. 2.9 ± 2.6) compared to those not attending the pain clinic.

CONCLUSION

We found notable sociodemographic and clinical differences between these patient populations. Patients presenting with multiple comorbidities might benefit from further pain screening and referral to pain clinics to provide comprehensive care, and earlier referral could mitigate the development and progression of multimorbidities.

Initiating medical abortion in an emergency department in the United States

OBJECTIVES

The primary objective of this study was to assess the feasibility of initiating medical abortions in a large, academic emergency department (ED) in the United States.

METHODS

A retrospective case series analysis was conducted to evaluate a protocol for initiating medical abortion in the ED implemented from January 2020 to October 2023 at an academic, tertiary care hospital in California, USA. Participants included ED patients diagnosed with pregnancies in the first trimester that were undesired and who opted for medical abortion. The medical abortion protocol was collaboratively designed by a multidisciplinary team and follow-up was conducted by our institution's gynaecology department. Data were sourced from a data repository of electronic health records and subjected to descriptive statistical analysis.

RESULTS

A total of 27 eligible patients initiated medical abortions in the ED during the study period. The cohort was diverse in terms of racial and ethnic backgrounds and almost evenly split between private and public insurance. No patients had significant complications identified in the medical record. Two patients required uterine aspiration by the gynaecology team; one patient in clinic and one during a return visit to the ED.

CONCLUSIONS

Data from this case series suggest that initiating medical abortion in the ED is feasible. The ED may be considered as an additional access point for abortion care services, especially in areas where other care options are not readily available. Educational, legal and regulatory frameworks that allow emergency physicians to take a greater role in providing this care should be considered.

Race, Sex, and Age Disparities in the Performance of ECG Deep Learning Models Predicting Heart Failure

BACKGROUND

Deep learning models may combat widening racial disparities in heart failure outcomes through early identification of individuals at high risk. However, demographic biases in the performance of these models have not been well-studied.

METHODS

This retrospective analysis used 12-lead ECGs taken between 2008 and 2018 from 326 518 patient encounters referred for standard clinical indications to Stanford Hospital. The primary model was a convolutional neural network model trained to predict incident heart failure within 5 years. Biases were evaluated on the testing set (160 312 ECGs) using the area under the receiver operating characteristic curve, stratified across the protected attributes of race, ethnicity, age, and sex.

RESULTS

There were 59 817 cases of incident heart failure observed within 5 years of ECG collection. The performance of the primary model declined with age. There were no significant differences observed between racial groups overall. However, the primary model performed significantly worse in Black patients aged 0 to 40 years compared with all other racial groups in this age group, with differences most pronounced among young Black women. Disparities in model performance did not improve with the integration of race, ethnicity, sex, and age into model architecture, by training separate models for each racial group, or by providing the model with a data set of equal racial representation. Using probability thresholds individualized for race, age, and sex offered substantial improvements in F1 scores.

CONCLUSIONS

The biases found in this study warrant caution against perpetuating disparities through the development of machine learning tools for the prognosis and management of heart failure. Customizing the application of these models by using probability thresholds individualized by race, ethnicity, age, and sex may offer an avenue to mitigate existing algorithmic disparities.