Bacteria-to-Human Protein Networks Reveal Origins of Endogenous DNA Damage.

DNA damage provokes mutations and cancer and results from external carcinogens or endogenous cellular processes. However, the intrinsic instigators of endogenous DNA damage are poorly understood. Here, we identify proteins that promote endogenous DNA damage when overproduced: the DNA "damage-up" proteins (DDPs). We discover a large network of DDPs in Escherichia coli and deconvolute them into six function clusters, demonstrating DDP mechanisms in three: reactive oxygen increase by transmembrane transporters, chromosome loss by replisome binding, and replication stalling by transcription factors. Their 284 human homologs are over-represented among known cancer drivers, and their RNAs in tumors predict heavy mutagenesis and a poor prognosis. Half of the tested human homologs promote DNA damage and mutation when overproduced in human cells, with DNA damage-elevating mechanisms like those in E. coli. Our work identifies networks of DDPs that provoke endogenous DNA damage and may reveal DNA damage-associated functions of many human known and newly implicated cancer-promoting proteins.

Gamblers: An Antibiotic-Induced Evolvable Cell Subpopulation Differentiated by Reactive-Oxygen-Induced General Stress Response.

Antibiotics can induce mutations that cause antibiotic resistance. Yet, despite their importance, mechanisms of antibiotic-promoted mutagenesis remain elusive. We report that the fluoroquinolone antibiotic ciprofloxacin (cipro) induces mutations by triggering transient differentiation of a mutant-generating cell subpopulation, using reactive oxygen species (ROS). Cipro-induced DNA breaks activate the Escherichia coli SOS DNA-damage response and error-prone DNA polymerases in all cells. However, mutagenesis is limited to a cell subpopulation in which electron transfer together with SOS induce ROS, which activate the sigma-S (σS) general-stress response, which allows mutagenic DNA-break repair. When sorted, this small σS-response-"on" subpopulation produces most antibiotic cross-resistant mutants. A U.S. Food and Drug Administration (FDA)-approved drug prevents σS induction, specifically inhibiting antibiotic-promoted mutagenesis. Further, SOS-inhibited cell division, which causes multi-chromosome cells, promotes mutagenesis. The data support a model in which within-cell chromosome cooperation together with development of a "gambler" cell subpopulation promote resistance evolution without risking most cells.

The Safety of Inpatient Health Care.

BACKGROUND: Adverse events during hospitalization are a major cause of patient harm, as documented in the 1991 Harvard Medical Practice Study. Patient safety has changed substantially in the decades since that study was conducted, and a more current assessment of harm during hospitalization is warranted. METHODS: We conducted a retrospective cohort study to assess the frequency, preventability, and severity of patient harm in a random sample of admissions from 11 Massachusetts hospitals during the 2018 calendar year. The occurrence of adverse events was assessed with the use of a trigger method (identification of information in a medical record that was previously shown to be associated with adverse events) and from review of medical records. Trained nurses reviewed records and identified admissions with possible adverse events that were then adjudicated by physicians, who confirmed the presence and characteristics of the adverse events. RESULTS: In a random sample of 2809 admissions, we identified at least one adverse event in 23.6%. Among 978 adverse events, 222 (22.7%) were judged to be preventable and 316 (32.3%) had a severity level of serious (i.e., caused harm that resulted in substantial intervention or prolonged recovery) or higher. A preventable adverse event occurred in 191 (6.8%) of all admissions, and a preventable adverse event with a severity level of serious or higher occurred in 29 (1.0%). There were seven deaths, one of which was deemed to be preventable. Adverse drug events were the most common adverse events (accounting for 39.0% of all events), followed by surgical or other procedural events (30.4%), patient-care events (which were defined as events associated with nursing care, including falls and pressure ulcers) (15.0%), and health care-associated infections (11.9%). CONCLUSIONS: Adverse events were identified in nearly one in four admissions, and approximately one fourth of the events were preventable. These findings underscore the importance of patient safety and the need for continuing improvement. (Funded by the Controlled Risk Insurance Company and the Risk Management Foundation of the Harvard Medical Institutions.).

The Safety of Outpatient Health Care : Review of Electronic Health Records.

BACKGROUND: Despite considerable emphasis on delivering safe care, substantial patient harm occurs. Although most care occurs in the outpatient setting, knowledge of outpatient adverse events (AEs) remains limited. OBJECTIVE: To measure AEs in the outpatient setting. DESIGN: Retrospective review of the electronic health record (EHR). SETTING: 11 outpatient sites in Massachusetts in 2018. PATIENTS: 3103 patients who received outpatient care. MEASUREMENTS: Using a trigger method, nurse reviewers identified possible AEs and physicians adjudicated them, ranked severity, and assessed preventability. Generalized estimating equations were used to assess the association of having at least 1 AE with age, sex, race, and primary insurance. Variation in AE rates was analyzed across sites. RESULTS: The 3103 patients (mean age, 52 years) were more often female (59.8%), White (75.1%), English speakers (90.8%), and privately insured (70.4%) and had a mean of 4 outpatient encounters in 2018. Overall, 7.0% (95% CI, 4.6% to 9.3%) of patients had at least 1 AE (8.6 events per 100 patients annually). Adverse drug events were the most common AE (63.8%), followed by health care-associated infections (14.8%) and surgical or procedural events (14.2%). Severity was serious in 17.4% of AEs, life-threatening in 2.1%, and never fatal. Overall, 23.2% of AEs were preventable. Having at least 1 AE was less often associated with ages 18 to 44 years than with ages 65 to 84 years (standardized risk difference, -0.05 [CI, -0.09 to -0.02]) and more often associated with Black race than with Asian race (standardized risk difference, 0.09 [CI, 0.01 to 0.17]). Across study sites, 1.8% to 23.6% of patients had at least 1 AE and clinical category of AEs varied substantially. LIMITATION: Retrospective EHR review may miss AEs. CONCLUSION: Outpatient harm was relatively common and often serious. Adverse drug events were most frequent. Rates were higher among older adults. Interventions to curtail outpatient harm are urgently needed. PRIMARY FUNDING SOURCE: Controlled Risk Insurance Company and the Risk Management Foundation of the Harvard Medical Institutions.

Looking Under the Lamppost: The Search for New Cancer Targets in the Human Kinome.

The number of cancer drugs is increasing as new chemical entities are developed to target molecules, often protein kinases, driving cancer progression. In 2009, Fedorov et al. identified that of the protein kinases in the human kinome, most of the focus has been on a small subset. They highlighted that many poorly investigated protein kinases were cancer drivers, but there was no relationship between publications and involvement in cancer development or progression. Since 2009, there has been a doubling in the number of publications, patents, and drugs targeting the kinome. To determine whether this was an expansion in knowledge of well-studied targets-searching in the light under the lamppost-or an explosion of investigations into previously poorly investigated targets, we searched the literature for publications on each kinase, updating Federov et al.'s assessment of the druggable kinome. The proportion of papers focusing on the 50 most-studied kinases had not changed, and the makeup of those 50 had barely changed. The majority of new drugs (80%) were against the same group of 50 kinases identified as targets 10 years ago, and the proportion of studies investigating previously poorly investigated kinases (<1%) was unchanged. With three exceptions [p38 mitogenactivated protein kinase (p38a), AMP-activated protein kinase catalytic α-subunit 1,2, and B-Raf proto-oncogene (BRAF) serine/threonine kinase], >95% of publications addressing kinases still focused on a relatively small proportion (<50%) of the human kinome independently of their involvement as cancer drivers. There is, therefore, still extensive scope for discovery of therapeutics targeting different protein kinases in cancer and still a bias toward well-characterized targets over the innovative searchlight into the unknown. SIGNIFICANCE STATEMENT: This study presents evidence that drug discovery efforts in cancer are still to some extent focused on a narrow group of well-studied kinases 10 years after the identification of multiple novel cancer targets in the human kinome. This suggests that there is still room for researchers in academia, industry, and the not-for-profit sector to develop new and diverse therapies targeting kinases for cancer.

Heparanase inhibition as a systemic approach to protect the endothelial glycocalyx and prevent microvascular complications in diabetes.

BACKGROUND: Diabetes mellitus is a chronic disease which is detrimental to cardiovascular health, often leading to secondary microvascular complications, with huge global health implications. Therapeutic interventions that can be applied to multiple vascular beds are urgently needed. Diabetic retinopathy (DR) and diabetic kidney disease (DKD) are characterised by early microvascular permeability changes which, if left untreated, lead to visual impairment and renal failure, respectively. The heparan sulphate cleaving enzyme, heparanase, has previously been shown to contribute to diabetic microvascular complications, but the common underlying mechanism which results in microvascular dysfunction in conditions such as DR and DKD has not been determined. METHODS: In this study, two mouse models of heparan sulphate depletion (enzymatic removal and genetic ablation by endothelial specific Exotosin-1 knock down) were utilized to investigate the impact of endothelial cell surface (i.e., endothelial glycocalyx) heparan sulphate loss on microvascular barrier function. Endothelial glycocalyx changes were measured using fluorescence microscopy or transmission electron microscopy. To measure the impact on barrier function, we used sodium fluorescein angiography in the eye and a glomerular albumin permeability assay in the kidney. A type 2 diabetic (T2D, db/db) mouse model was used to determine the therapeutic potential of preventing heparan sulphate damage using treatment with a novel heparanase inhibitor, OVZ/HS-1638. Endothelial glycocalyx changes were measured as above, and microvascular barrier function assessed by albumin extravasation in the eye and a glomerular permeability assay in the kidney. RESULTS: In both models of heparan sulphate depletion, endothelial glycocalyx depth was reduced and retinal solute flux and glomerular albumin permeability was increased. T2D mice treated with OVZ/HS-1638 had improved endothelial glycocalyx measurements compared to vehicle treated T2D mice and were simultaneously protected from microvascular permeability changes associated with DR and DKD. CONCLUSION: We demonstrate that endothelial glycocalyx heparan sulphate plays a common mechanistic role in microvascular barrier function in the eye and kidney. Protecting the endothelial glycocalyx damage in diabetes, using the novel heparanase inhibitor OVZ/HS-1638, effectively prevents microvascular permeability changes associated with DR and DKD, demonstrating a novel systemic approach to address diabetic microvascular complications.

Patterns of Social Needs Predict Quality-of-Life and Healthcare Utilization Outcomes in Patients from a Large Hospital System.

BACKGROUND: Unmet social needs (SNs) often coexist in distinct patterns within specific population subgroups, yet these patterns are understudied. OBJECTIVE: To identify patterns of social needs (PSNs) and characterize their associations with health-related quality-of-life (HRQoL) and healthcare utilization (HCU). DESIGN: Observational study using data on SNs screening, HRQoL (i.e., low mental and physical health), and 90-day HCU (i.e., emergency visits and hospital admission). Among patients with any SNs, latent class analysis was conducted to identify unique PSNs. For all patients and by race and age subgroups, compared with no SNs, we calculated the risks of poor HRQoL and time to first HCU following SNs screening for each PSN. PATIENTS: Adult patients undergoing SNs screening at the Mass General Brigham healthcare system in Massachusetts, United States, between March 2018 and January 2023. MAIN MEASURES: SNs included: education, employment, family care, food, housing, medication, transportation, and ability to pay for household utilities. HRQoL was assessed using the Patient-Reported Outcomes Measurement Information System Global-10. KEY RESULTS: Six unique PSNs were identified: "high number of social needs," "food and utility access," "employment needs," "interested in education," "housing instability," and "transportation barriers." In 14,230 patients with HRQoL data, PSNs increased the risks of poor mental health, with risk ratios ranging from 1.07(95%CI:1.01-1.13) to 1.80(95%CI:1.74-1.86). Analysis of poor physical health yielded similar findings, except that the "interested in education" showed a mild protective effect (0.97[95%CI:0.94-1.00]). In 105,110 patients, PSNs increased the risk of 90-day HCU, with hazard ratios ranging from 1.09(95%CI:0.99-1.21) to 1.70(95%CI:1.52-1.90). Findings were generally consistent in subgroup analyses by race and age. CONCLUSIONS: Certain SNs coexist in distinct patterns and result in poorer HRQoL and more HCU. Understanding PSNs allows policymakers, public health practitioners, and social workers to identify at-risk patients and implement integrated, system-wide, and community-based interventions.

COVID-19 outbreaks surveillance through text mining applied to electronic health records.

BACKGROUND: The COVID-19 pandemic has caused significant disruptions to everyday life and has had social, political, and financial consequences that will persist for years. Several initiatives with intensive use of technology were quickly developed in this scenario. However, technologies that enhance epidemiological surveillance in contexts with low testing capacity and healthcare resources are scarce. Therefore, this study aims to address this gap by developing a data science model that uses routinely generated healthcare encounter records to detect possible new outbreaks early in real-time. METHODS: We defined an epidemiological indicator that is a proxy for suspected cases of COVID-19 using the health records of Emergency Care Unit (ECU) patients and text mining techniques. The open-field dataset comprises 2,760,862 medical records from nine ECUs, where each record has information about the patient's age, reported symptoms, and the time and date of admission. We also used a dataset where 1,026,804 cases of COVID-19 were officially confirmed. The records range from January 2020 to May 2022. Sample cross-correlation between two finite stochastic time series was used to evaluate the models. RESULTS: For patients with age 18 years, we find time-lag () = 72 days and cross-correlation () ~ 0.82, = 25 days and ~ 0.93, and = 17 days and ~ 0.88 for the first, second, and third waves, respectively. CONCLUSIONS: In conclusion, the developed model can aid in the early detection of signs of possible new COVID-19 outbreaks, weeks before traditional surveillance systems, thereby anticipating in initiating preventive and control actions in public health with a higher likelihood of success.

Patient-reported outcome measures for primary hyperparathyroidism: a systematic review of measurement properties.

BACKGROUND: The quality of patient-reported outcome measures (PROMs) used to assess the outcomes of primary hyperparathyroidism (PHPT), a common endocrine disorder that can negatively affect patients' health-related quality of life due to chronic symptoms, has not been rigorously examined. This systematic review aimed to summarize and evaluate evidence on the measurement properties of PROMs used in adult patients with PHPT, and to provide recommendations for appropriate measure selection. METHODS: After PROSPERO registration (CRD42023438287), Medline, EMBASE, CINAHL Complete, Web of Science, PsycINFO, and Cochrane Trials were searched for full-text articles in English investigating PROM development, pilot studies, or evaluation of at least one PROM measurement property in adult patients with any clinical form of PHPT. Two reviewers independently identified studies for inclusion and conducted the review following the Consensus-Based Standards for the Selection of Health Measurement Instruments (COSMIN) Methodology to assess risk of bias, evaluate the quality of measurement properties, and grade the certainty of evidence. RESULTS: From 4989 records, nine PROM development or validation studies were identified for three PROMs: the SF-36, PAS, and PHPQoL. Though the PAS demonstrated sufficient test-retest reliability and convergent validity, and the PHPQoL sufficient test-retest reliability, convergent validity, and responsiveness, the certainty of evidence was low-to-very low due to risk of bias. All three PROMs lacked sufficient evidence for content validity in patients with PHPT. CONCLUSIONS: Based upon the available evidence, the SF-36, PAS, and PHPQoL cannot currently be recommended for use in research or clinical care, raising important questions about the conclusions of studies using these PROMs. Further validation studies or the development of more relevant PROMs with strong measurement properties for this patient population are needed.

Psoralen mapping reveals a bacterial genome supercoiling landscape dominated by transcription.

DNA supercoiling is a key regulator of all DNA metabolic processes including replication, transcription, and recombination, yet a reliable genomic assay for supercoiling is lacking. Here, we present a robust and flexible method (Psora-seq) to measure whole-genome supercoiling at high resolution. Using this tool in Escherichia coli, we observe a supercoiling landscape that is well correlated to transcription. Supercoiling twin-domains generated by RNA polymerase complexes span 25 kb in each direction - an order of magnitude farther than previous measurements in any organism. Thus, ribosomal and many other highly expressed genes strongly affect the topology of about 40 neighboring genes each, creating highly integrated gene circuits. Genomic patterns of supercoiling revealed by Psora-seq could be aptly predicted from modeling based on gene expression levels alone, indicating that transcription is the major determinant of chromosome supercoiling. Large-scale supercoiling patterns were highly symmetrical between left and right chromosome arms (replichores), indicating that DNA replication also strongly influences supercoiling. Skew in the axis of symmetry from the natural ori-ter axis supports previous indications that the rightward replication fork is delayed several minutes after initiation. Implications of supercoiling on DNA replication and chromosome domain structure are discussed.

A qualitative study of leaders' experiences of handling challenges and changes induced by the COVID-19 pandemic in rural nursing homes and homecare services.

BACKGROUND: The COVID-19 pandemic had a major impact on healthcare services globally. In care settings such as small rural nursing homes and homes care services leaders were forced to confront, and adapt to, both new and ongoing challenges to protect their employees and patients and maintain their organization's operation. The aim of this study was to assess how healthcare leaders, working in rural primary healthcare services, led nursing homes and homecare services during the COVID-19 pandemic. Moreover, the study sought to explore how adaptations to changes and challenges induced by the pandemic were handled by leaders in rural nursing homes and homecare services. METHODS: The study employed a qualitative explorative design with individual interviews. Nine leaders at different levels, working in small, rural nursing homes and homecare services in western Norway were included. RESULTS: Three main themes emerged from the thematic analysis: "Navigating the role of a leader during the pandemic," "The aftermath - management of COVID-19 in rural primary healthcare services", and "The benefits and drawbacks of being small and rural during the pandemic." CONCLUSIONS: Leaders in rural nursing homes and homecare services handled a multitude of immediate challenges and used a variety of adaptive strategies during the COVID-19 pandemic. While handling their own uncertainty and rapidly changing roles, they also coped with organizational challenges and adopted strategies to maintain good working conditions for their employees, as well as maintain sound healthcare management. The study results establish the intricate nature of resilient leadership, encompassing individual resilience, personality, governance, resource availability, and the capability to adjust to organizational and employee requirements, and how the rural context may affect these aspects.

Barriers and enablers for externally and internally driven implementation processes in healthcare: a qualitative cross-case study.

BACKGROUND: Quality in healthcare is a subject in need of continuous attention. Quality improvement (QI) programmes with the purpose of increasing service quality are therefore of priority for healthcare leaders and governments. This study explores the implementation process of two different QI programmes, one externally driven implementation and one internally driven, in Norwegian nursing homes and home care services. The aim for the study was to identify enablers and barriers for externally and internally driven implementation processes in nursing homes and homecare services, and furthermore to explore if identified enablers and barriers are different or similar across the different implementation processes. METHODS: This study is based on an exploratory qualitative methodology. The empirical data was collected through the 'Improving Quality and Safety in Primary Care - Implementing a Leadership Intervention in Nursing Homes and Homecare' (SAFE-LEAD) project. The SAFE-LEAD project is a multiple case study of two different QI programmes in primary care in Norway. A large externally driven implementation process was supplemented with a tracer project involving an internally driven implementation process to identify differences and similarities. The empirical data was inductively analysed in accordance with grounded theory. RESULTS: Enablers for both external and internal implementation processes were found to be technology and tools, dedication, and ownership. Other more implementation process specific enablers entailed continuous learning, simulation training, knowledge sharing, perceived relevance, dedication, ownership, technology and tools, a systematic approach and coordination. Only workload was identified as coincident barriers across both externally and internally implementation processes. Implementation process specific barriers included turnover, coping with given responsibilities, staff variety, challenges in coordination, technology and tools, standardizations not aligned with work, extensive documentation, lack of knowledge sharing. CONCLUSION: This study provides understanding that some enablers and barriers are present in both externally and internally driven implementation processes, while other are more implementation process specific. Dedication, engagement, technology and tools are coinciding enablers which can be drawn upon in different implementation processes, while workload acted as the main barrier in both externally and internally driven implementation processes. This means that some enablers and barriers can be expected in implementation of QI programmes in nursing homes and home care services, while others require contextual understanding of their setting and work.

Targeted chromosomal Escherichia coli:dnaB exterior surface residues regulate DNA helicase behavior to maintain genomic stability and organismal fitness.

Helicase regulation involves modulation of unwinding speed to maintain coordination of DNA replication fork activities and is vital for replisome progression. Currently, mechanisms for helicase regulation that involve interactions with both DNA strands through a steric exclusion and wrapping (SEW) model and conformational shifts between dilated and constricted states have been examined in vitro. To better understand the mechanism and cellular impact of helicase regulation, we used CRISPR-Cas9 genome editing to study four previously identified SEW-deficient mutants of the bacterial replicative helicase DnaB. We discovered that these four SEW mutations stabilize constricted states, with more fully constricted mutants having a generally greater impact on genomic stress, suggesting a dynamic model for helicase regulation that involves both excluded strand interactions and conformational states. These dnaB mutations result in increased chromosome complexities, less stable genomes, and ultimately less viable and fit strains. Specifically, dnaB:mut strains present with increased mutational frequencies without significantly inducing SOS, consistent with leaving single-strand gaps in the genome during replication that are subsequently filled with lower fidelity. This work explores the genomic impacts of helicase dysregulation in vivo, supporting a combined dynamic regulatory mechanism involving a spectrum of DnaB conformational changes and relates current mechanistic understanding to functional helicase behavior at the replication fork.

Straight to the point: evaluation of a Point of Care Information (POCI) resource in answering disease-related questions.

Objective: To evaluate the ability of DynaMedex, an evidence-based drug and disease Point of Care Information (POCI) resource, in answering clinical queries using keyword searches. Methods: Real-world disease-related questions compiled from clinicians at an academic medical center, DynaMedex search query data, and medical board review resources were categorized into five clinical categories (complications & prognosis, diagnosis & clinical presentation, epidemiology, prevention & screening/monitoring, and treatment) and six specialties (cardiology, endocrinology, hematology-oncology, infectious disease, internal medicine, and neurology). A total of 265 disease-related questions were evaluated by pharmacist reviewers based on if an answer was found (yes, no), whether the answer was relevant (yes, no), difficulty in finding the answer (easy, not easy), cited best evidence available (yes, no), clinical practice guidelines included (yes, no), and level of detail provided (detailed, limited details). Results: An answer was found for 259/265 questions (98%). Both reviewers found an answer for 241 questions (91%), neither found the answer for 6 questions (2%), and only one reviewer found an answer for 18 questions (7%). Both reviewers found a relevant answer 97% of the time when an answer was found. Of all relevant answers found, 68% were easy to find, 97% cited best quality of evidence available, 72% included clinical guidelines, and 95% were detailed. Recommendations for areas of resource improvement were identified. Conclusions: The resource enabled reviewers to answer most questions easily with the best quality of evidence available, providing detailed answers and clinical guidelines, with a high level of replication of results across users.

Targeting alternative splicing as a new cancer immunotherapy-phosphorylation of serine arginine-rich splicing factor (SRSF1) by SR protein kinase 1 (SRPK1) regulates alternative splicing of PD1 to generate a soluble antagonistic isoform that prevents T cell exhaustion.

BACKGROUND: Regulation of alternative splicing is a new therapeutic approach in cancer. The programmed cell death receptor 1 (PD-1) is an immunoinhibitory receptor expressed on immune cells that binds to its ligands, PD-L1 and PD-L2 expressed by cancer cells forming a dominant immune checkpoint pathway in the tumour microenvironment. Targeting this pathway using blocking antibodies (nivolumab and pembrolizumab) is the mainstay of anti-cancer immunotherapies, restoring the function of exhausted T cells. PD-1 is alternatively spliced to form isoforms that are either transmembrane signalling receptors (flPD1) that mediate T cell death by binding to the ligand, PD-L1 or an alternatively spliced, soluble, variant that lacks the transmembrane domain. METHODS: We used PCR and western blotting on primary peripheral blood mononuclear cells (PBMCs) and Jurkat T cells, IL-2 ELISA, flow cytometry, co-culture of melanoma and cholangiocarcinoma cells, and bioinformatics analysis and molecular cloning to examine the mechanism of splicing of PD1 and its consequence. RESULTS: The soluble form of PD-1, generated by skipping exon 3 (∆Ex3PD1), was endogenously expressed in PBMCs and T cells and prevents cancer cell-mediated T cell repression. Multiple binding sites of SRSF1 are adjacent to PD-1 exon 3 splicing sites. Overexpression of phosphomimic SRSF1 resulted in preferential expression of flPD1. Inhibition of SRSF1 phosphorylation both by SRPK1 shRNA knockdown and by a selective inhibitor, SPHINX31, resulted in a switch in splicing to ∆Ex3PD1. Cholangiocarcinoma cell-mediated repression of T cell IL-2 expression was reversed by SPHINX31 (equivalent to pembrolizumab). CONCLUSIONS: These results indicate that switching of the splicing decision from flPD1 to ∆Ex3PD1 by targeting SRPK1 could represent a potential novel mechanism of immune checkpoint inhibition in cancer.

Extramural Venous Invasion and Tumor Deposit at Diffusion-weighted MRI in Patients after Neoadjuvant Treatment for Rectal Cancer.

Background Diffusion-weighted (DW) imaging is useful in detecting tumor in the primary tumor bed in locally advanced rectal cancer (LARC) after neoadjuvant therapy, but its value in detecting extramural venous invasion (EMVI) and tumor deposit is not well validated. Purpose To evaluate diagnostic accuracy and association with patient prognosis of viable EMVI and tumor deposit on DW images in patients with LARC after neoadjuvant therapy using whole-mount pathology specimens. Materials and Methods This retrospective study included patients who underwent neoadjuvant therapy and surgery from 2018 to 2021. Innovative five-point Likert scale was used by two radiologists to independently evaluate the likelihood of viable EMVI and tumor deposit on restaging DW MRI scans in four axial quadrants (12 to 3 o'clock, 3 to 6 o'clock, 6 to 9 o'clock, and 9 to 12 o'clock). Diagnostic accuracy was assessed at both the per-quadrant and per-patient level, with whole-mount pathology as the reference standard. Weighted κ values for interreader agreement and Cox regression models for disease-free survival and overall survival analyses were used. Results A total of 117 patients (mean age, 56 years ± 12 [SD]; 70 male, 47 female) were included. Pathologically proven viable EMVI and tumor deposit was detected in 29 of 117 patients (25%) and in 44 of 468 quadrants (9.4%). Per-quadrant analyses showed an area under the receiver operating characteristics curve of 0.75 (95% CI: 0.68, 0.83), with sensitivity and specificity of 55% and 96%, respectively. Good interreader agreement was observed between the radiologists (κ = 0.62). Per-patient analysis showed sensitivity and specificity of 62% and 93%, respectively. The presence of EMVI and tumor deposit on restaging DW MRI scans was associated with worse disease-free survival (hazard ratio [HR], 5.6; 95% CI: 2.4, 13.3) and overall survival (HR, 8.9; 95% CI: 1.6, 48.5). Conclusion DW imaging using the five-point Likert scale showed high specificity and moderate sensitivity in the detection of viable extramural venous invasion and tumor deposits in LARC after neoadjuvant therapy, and its presence on restaging DW MRI scans is associated with worse prognosis. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Méndez and Ayuso in this issue.

MRI Assessment of Extramural Venous Invasion Before and After Total Neoadjuvant Therapy for Locally Advanced Rectal Cancer and Its Association with Disease-Free and Overall Survival.

BACKGROUND: Extramural venous invasion (EMVI) on baseline MRI is associated with poor prognosis in patients with locally advanced rectal cancer. This study investigated the association of persistent EMVI after total neoadjuvant therapy (TNT) (chemoradiotherapy and systemic chemotherapy) with survival. METHODS: Baseline MRI, post-TNT MRI, and surgical pathology data from 175 patients with locally advanced rectal cancer who underwent TNT and total mesorectal excision between 2010 and 2017 were retrospectively analyzed for evidence of EMVI. Two radiologists assessed EMVI status with disagreement adjudicated by a third. Pathologic EMVI status was assessed per departmental standards. Cox regression models evaluated the associations between EMVI and disease-free and overall survival. RESULTS: EMVI regression on both post-TNT MRI and surgical pathology was associated with disease-free survival (hazard ratio, 0.17; 95% confidence interval (CI), 0.04-0.64) and overall survival (hazard ratio, 0.11; 95% CI, 0.02-0.68). In an exploratory analysis of 35 patients with EMVI on baseline MRI, only six had EMVI on pathology compared with 18 on post-TNT MRI; these findings were not associated (p = 0.2). Longer disease-free survival was seen with regression on both modalities compared with remaining positive. Regression on pathology alone, independent of MRI EMVI status, was associated with similar improvements in survival. CONCLUSIONS: Baseline EMVI is associated with poor prognosis even after TNT. EMVI regression on surgical pathology is common even with persistent EMVI on post-TNT MRI. EMVI regression on surgical pathology is associated with improved DFS, while the utility of post-TNT MRI EMVI persistence for decision-making and prognosis remains unclear.

Physician Note Composition Patterns and Time on the EHR Across Specialty Types: a National, Cross-sectional Study.

BACKGROUND: The burden of clinical documentation in electronic health records (EHRs) has been associated with physician burnout. Numerous tools (e.g., note templates and dictation services) exist to ease documentation burden, but little evidence exists regarding how physicians use these tools in combination and the degree to which these strategies correlate with reduced time spent on documentation. OBJECTIVE: To characterize EHR note composition strategies, how these strategies differ in time spent on notes and the EHR, and their distribution across specialty types. DESIGN: Secondary analysis of physician-level measures of note composition and EHR use derived from Epic Systems' Signal data warehouse. We used k-means clustering to identify documentation strategies, and ordinary least squares regression to analyze the relationship between documentation strategies and physician time spent in the EHR, on notes, and outside scheduled hours. PARTICIPANTS: A total of 215,207 US-based ambulatory physicians using the Epic EHR between September 2020 and May 2021. MAIN MEASURES: Percent of note text derived from each of five documentation tools: SmartTools, copy/paste, manual text, NoteWriter, and voice recognition and transcription; average total and after-hours EHR time per visit; average time on notes per visit. KEY RESULTS: Six distinct note composition strategies emerged in cluster analyses. The most common strategy was predominant SmartTools use (n=89,718). In adjusted analyses, physicians using primarily transcription and dictation (n=15,928) spent less time on notes than physicians with predominant Smart Tool use. (b=-1.30, 95% CI=-1.62, -0.99, p<0.001; average 4.8 min per visit), while those using mostly copy/paste (n=23,426) spent more time on notes (b=2.38, 95% CI=1.92, 2.84, p<0.001; average 13.1 min per visit). CONCLUSIONS: Physicians' note composition strategies have implications for both time in notes and after-hours EHR use, suggesting that how physicians use EHR-based documentation tools can be a key lever for institutions investing in EHR tools and training to reduce documentation time and alleviate EHR-associated burden.

Utility of Fully Automated Body Composition Measures on Pretreatment Abdominal CT for Predicting Survival in Patients With Colorectal Cancer.

BACKGROUND. CT examinations contain opportunistic body composition data with potential prognostic utility. Previous studies have primarily used manual or semiautomated tools to evaluate body composition in patients with colorectal cancer (CRC). OBJECTIVE. The purpose of this article is to assess the utility of fully automated body composition measures derived from pretreatment CT examinations in predicting survival in patients with CRC. METHODS. This retrospective study included 1766 patients (mean age, 63.7 ± 14.4 [SD] years; 862 men, 904 women) diagnosed with CRC between January 2001 and September 2020 who underwent pretreatment abdominal CT. A panel of fully automated artificial intelligence-based algorithms was applied to portal venous phase images to quantify skeletal muscle attenuation at the L3 lumbar level, visceral adipose tissue (VAT) area and subcutaneous adipose tissue (SAT) area at L3, and abdominal aorta Agatston score (aortic calcium). The electronic health record was reviewed to identify patients who died of any cause (n = 848). ROC analyses and logistic regression analyses were used to identify predictors of survival, with attention to highest- and lowest-risk quartiles. RESULTS. Patients who died, compared with patients who survived, had lower median muscle attenuation (19.2 vs 26.2 HU, p < .001), SAT area (168.4 cm2 vs 197.6 cm2, p < .001), and aortic calcium (620 vs 182, p < .001). Measures with highest 5-year AUCs for predicting survival in patients without (n = 1303) and with (n = 463) metastatic disease were muscle attenuation (0.666 and 0.701, respectively) and aortic calcium (0.677 and 0.689, respectively). A combination of muscle attenuation, SAT area, and aortic calcium yielded 5-year AUCs of 0.758 and 0.732 in patients without and with metastases, respectively. Risk of death was increased (p < .05) in patients in the lowest quartile for muscle attenuation (hazard ratio [HR] = 1.55) and SAT area (HR = 1.81) and in the highest quartile for aortic calcium (HR = 1.37) and decreased (p < .05) in patients in the highest quartile for VAT area (HR = 0.79) and SAT area (HR = 0.76). In 423 patients with available BMI, BMI did not significantly predict death (p = .75). CONCLUSION. Fully automated CT-based body composition measures including muscle attenuation, SAT area, and aortic calcium predict survival in patients with CRC. CLINICAL IMPACT. Routine pretreatment body composition evaluation could improve initial risk stratification of patients with CRC.

A deep learning approach for transgender and gender diverse patient identification in electronic health records.

BACKGROUND: Although accurate identification of gender identity in the electronic health record (EHR) is crucial for providing equitable health care, particularly for transgender and gender diverse (TGD) populations, it remains a challenging task due to incomplete gender information in structured EHR fields. OBJECTIVE: Using TGD identification as a case study, this research uses NLP and deep learning to build an accurate patient gender identity predictive model, aiming to tackle the challenges of identifying relevant patient-level information from EHR data and reducing annotation work. METHODS: This study included adult patients in a large healthcare system in Boston, MA, between 4/1/2017 to 4/1/2022. To identify relevant information from massive clinical notes, we compiled a list of gender-related keywords through expert curation, literature review, and expansion via a fine-tuned BioWordVec model. This keyword list was used to pre-screen potential TGD individuals and create two datasets for model training, testing, and validation. Dataset I was a balanced dataset that contained clinician-confirmed TGD patients and cases without keywords. Dataset II contained cases with keywords. The performance of the deep learning model was compared to traditional machine learning and rule-based algorithms. RESULTS: The final keyword list consists of 109 keywords, of which 58 (53.2%) were expanded by the BioWordVec model. Dataset I contained 3,150 patients (50% TGD) while Dataset II contained 200 patients (90% TGD). On Dataset I the deep learning model achieved a F1 score of 0.917, sensitivity of 0.854, and a precision of 0.980; and on Dataset II a F1 score of 0.969, sensitivity of 0.967, and precision of 0.972. The deep learning model significantly outperformed rule-based algorithms. CONCLUSION: This is the first study to show that deep learning-integrated NLP algorithms can accurately identify gender identity using EHR data. Future work should leverage and evaluate additional diverse data sources to generate more generalizable algorithms.