Breast Cancer is Increased in Women with Primary Ovarian Insufficiency.

CONTEXT: DNA damage/repair gene variants are associated with both primary ovarian insufficiency (POI) and cancer risk. OBJECTIVE: We hypothesized that a subset of women with POI and family members would have increased risk for cancer. DESIGN: Case-control population-based study using records from 1995-2022. SETTING: Two major Utah academic healthcare systems serving 85% of the state. SUBJECTS: Women with POI (n=613) were identified using ICD codes and reviewed for accuracy. Relatives were linked using the Utah Population Database. INTERVENTION: Cancer diagnoses were identified using the Utah Cancer Registry. MAIN OUTCOME MEASURES: The relative risk of cancer in women with POI and relatives was estimated by comparison to population rates. Whole genome sequencing was performed on a subset of women. RESULTS: Breast cancer was increased in women with POI (OR [95%CI] 2.20 [1.30, 3.47]; p=0.0023) and there was a nominally significant increase in ovarian cancer. Probands with POI were 36.5±4.3 years and 59.5±12.7 years when diagnosed with POI and cancer, respectively. Causal and candidate gene variants for cancer and POI were identified.Among second-degree relatives of these women, there was an increased risk of breast (1.28 [1.08, 1.52]; p=0.0078) and colon cancer (1.50 [1.14, 1.94]; p=0.0036). Prostate cancer was increased in first- (1.64 [1.18, 2.23]; p=0.0026), second- (1.54 [1.32, 1.79]; p<0.001), and third-degree relatives (1.33 [1.20, 1.48]; p<0.001). CONCLUSIONS: Data suggest common genetic risk for POI and reproductive cancers. Tools are needed to predict cancer risk in women with POI and potentially to counsel about risks of hormone replacement therapy.

Defining blood hematology reference values in female pig-tailed macaques (Macaca nemestrina) using the Isolation Forest algorithm.

BACKGROUND: Pig-tailed macaques (PTMs) are commonly used as preclinical models to assess antiretroviral drugs for HIV prevention research. Drug toxicities and disease pathologies are often preceded by changes in blood hematology. To better assess the safety profile of pharmaceuticals, we defined normal ranges of hematological values in PTMs using an Isolation Forest (iForest) algorithm. METHODS: Eighteen female PTMs were evaluated. Blood was collected 1-24 times per animal for a total of 159 samples. Complete blood counts were performed, and iForest was used to analyze the hematology data to detect outliers. RESULTS: Median, IQR, and ranges were calculated for 13 hematology parameters. From all samples, 22 outliers were detected. These outliers were excluded from the reference index. CONCLUSIONS: Using iForest, we defined a normal range for hematology parameters in female PTMs. This reference index can be a valuable tool for future studies evaluating drug toxicities in PTMs.

Time and Note Characteristic Effects of an Electronic Health Record Template for Internal Medicine Resident Notes.

Background Inpatient internal medicine (IM) residents spend most of their time on indirect patient care activities such as clinical documentation. Objective We developed optimized electronic health record (EHR) templates for IM resident admission and progress notes, with the objective to reduce note-writing time, shorten note length, and decrease the percentage of progress note text that was copy-forwarded from prior notes. Methods In 2022, a multidisciplinary team created, over an 8-month period, optimized EHR templates for IM resident admission and progress notes. A retrospective analysis was performed to assess differences in resident time spent writing notes, note length in characters, and percentage of progress note text that was copy-forwarded. All 94 residents in the IM residency program had the opportunity to use the novel templates. Results Following implementation of the novel templates, residents spent on average 3.6 minutes less per progress note compared to pre-intervention (P=.008; 95% CI of the difference: 1.1-6.0 minutes). Notes in the post-intervention period were shorter for admission notes (mean reduction of 1041 characters; P<.001; 95% CI of the difference: 448-1634 characters) and progress notes (mean reduction of 764 characters; P<.001; 95% CI of the difference: 103-1426 characters). Progress notes also saw an average 22% decrease of copy-forwarded text (P<.001, 95% CI of the difference: 18.7%-25.4%). Conclusions The optimized note templates led to a reduction in resident progress note-writing time, shortened note length, and a lower percentage of copy-forwarded text.

Candida auris outbreak at a tertiary care hospital during the COVID-19 pandemic.

BACKGROUND: Candida auris (C auris) is a fungal pathogen that has the potential for environmental persistence leading to outbreaks in health care settings. There has been a worldwide surge in C auris outbreaks during the COVID-19 pandemic. In this report, we describe an outbreak of C auris, its control, patient outcomes, and lessons learned. METHODS: The outbreak occurred in a 600-bed adult academic tertiary care hospital. Contact tracing was initiated immediately after identification of the index case and surveillance testing for C auris was obtained from patients who were exposed to the index case. Infection prevention measures were closely followed. RESULTS: A total of 560 cultures were performed on 453 unique patients between August 2021 and December 2021. Of those, 31 cultures (5.5%) were positive for C auris; 27 (87.1%) were colonized with C auris, while 4 patients developed a clinical infection (12.9%). The secondary attack rate was 6.8% (31/453). The 30-day all-cause mortality rate for all patients who tested positive for C auris was 9.7%. DISCUSSION: C auris can cause protracted outbreaks that result in colonization and invasive infections. Multidisciplinary work to improve adherence to infection prevention measures as well as targeted admission screening are essential to limit outbreaks.

Etiology and utility of hospital-onset bacteremia as a safety metric for targeted harm reduction.

BACKGROUND: Hospital acquired infections (HAIs) are a major driver of morbidity and cost in health systems. Central line-associated bloodstream infections (CLABSIs) require intensive surveillance and review. All-cause hospital-onset bacteremia (HOB) may be a simpler reporting metric, correlates with CLABSI, and is viewed positively by HAI experts. Despite the ease in the collection, the proportion of HOBs that are actionable and preventable is unknown. Moreover, quality improvement strategies targeting it may be more challenging. In this study, we describe the bedside provider-perceived sources of HOB in order to provide insight into this new metric as a target for HAI prevention. METHODS: All cases of HOBs in 2019 from an academic tertiary care hospital were retrospectively reviewed. Information was collected to assess provider-perceived etiology and associated clinical factors (microbiology, severity, mortality, and management). HOB was categorized as preventable or not preventable based on the perceived source from the care team and management decisions. Preventable causes included device-associated bacteremias, pneumonias, surgical complications, and contaminated blood cultures. RESULTS: Of the 392 instances of HOB, 56.0% (n = 220) had episodes that were determined not preventable by providers. Excluding blood culture contaminates, the most common cause of preventable HOB was secondary to CLABSIs (9.9%, n = 39). Of the HOBs that were not preventable, the most common sources were gastrointestinal and abdominal (n = 62), neutropenic translocation (n = 37), and endocarditis (n = 23). Patients with HOB were generally medically complex with an average Charlson comorbidity index of 4.97. This translated into a higher average length of stay (29.23 vs 7.56, P < .001) and higher inpatient mortality (odds ratio 8.3, confidence interval [6.32-10.77]) when compared to admissions without HOB. CONCLUSIONS: The majority of HOBs were not preventable and the HOB metric may be a marker of a sicker patient population making it a less actionable target for quality improvement. Standardization across the patient mix is important if the metric becomes linked to reimbursement. If the HOB metric were to be used in lieu of CLABSI, large tertiary care health systems that house sicker patients may be unfairly financially penalized for caring for more medically complex patients.

A Deep Learning Decision Support Tool to Improve Risk Stratification and Reduce Unnecessary Biopsies in BI-RADS 4 Mammograms.

Purpose: To evaluate the performance of a biopsy decision support algorithmic model, the intelligent-augmented breast cancer risk calculator (iBRISK), on a multicenter patient dataset. Materials and Methods: iBRISK was previously developed by applying deep learning to clinical risk factors and mammographic descriptors from 9700 patient records at the primary institution and validated using another 1078 patients. All patients were seen from March 2006 to December 2016. In this multicenter study, iBRISK was further assessed on an independent, retrospective dataset (January 2015-June 2019) from three major health care institutions in Texas, with Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions. Data were dichotomized and trichotomized to measure precision in risk stratification and probability of malignancy (POM) estimation. iBRISK score was also evaluated as a continuous predictor of malignancy, and cost savings analysis was performed. Results: The iBRISK model's accuracy was 89.5%, area under the receiver operating characteristic curve (AUC) was 0.93 (95% CI: 0.92, 0.95), sensitivity was 100%, and specificity was 81%. A total of 4209 women (median age, 56 years [IQR, 45-65 years]) were included in the multicenter dataset. Only two of 1228 patients (0.16%) in the "low" POM group had malignant lesions, while in the "high" POM group, the malignancy rate was 85.9%. iBRISK score as a continuous predictor of malignancy yielded an AUC of 0.97 (95% CI: 0.97, 0.98). Estimated potential cost savings were more than $420 million. Conclusion: iBRISK demonstrated high sensitivity in the malignancy prediction of BI-RADS 4 lesions. iBRISK may safely obviate biopsies in up to 50% of patients in low or moderate POM groups and reduce biopsy-associated costs.Keywords: Mammography, Breast, Oncology, Biopsy/Needle Aspiration, Radiomics, Precision Mammography, AI-augmented Biopsy Decision Support Tool, Breast Cancer Risk Calculator, BI-RADS 4 Mammography Risk Stratification, Overbiopsy Reduction, Probability of Malignancy (POM) Assessment, Biopsy-based Positive Predictive Value (PPV3) Supplemental material is available for this article. Published under a CC BY 4.0 license.See also the commentary by McDonald and Conant in this issue.