Search

Abstract: Bone marrow microenvironment plays an important role in promoting growth and survival of multiple myeloma (MM) cells. The tumor-promoting immune microenvironment is augmented while antitumor immune responses are inhibited. Although clinical and genomic markers of high-risk MM have been described, the immune status is just being recognized as a potential mediator of disease behavior. This is even more important with the development of a number of immune-based therapies. Based on these considerations, we evaluated peripheral blood absolute lymphocyte count (ALC) as an easily accessible marker representing immune microenvironment at diagnosis and after treatment of MM. We retrospectively evaluated 11 427 patients diagnosed with MM between 2000 and 2019 at Veterans Administration hospitals using ALC obtained closest to diagnosis and up to 2.5 years thereafter. Patients were stratified into 3 ALC categories: severely low, low, and normal (1.5 × 103/μL, respectively). Lymphopenia (including severely low and low ALC) was present in 53% of patients at MM diagnosis and was associated with inferior overall survival (OS). The median OS for patients with severely low, low, and normal ALC at diagnosis was 2.7, 3.3, and 4.2 years (P < .001), respectively. Moreover, persistent or new development of lymphopenia during treatment and follow-up was also associated with inferior OS. Our findings support the use of ALC as a biomarker for risk stratification in MM.

Abstract Background: COVID-associated pulmonary aspergillosis (CAPA) was described early in the pandemic as a complication of SARS-CoV-2. Data about incidence of aspergillosis and characteristics of affected patients after mid-2021 are limited. Methods: A retrospective, nationwide cohort of US Veterans with SARS-CoV-2 from 1/1/2020 to 2/7/2024 was created. Potential cases of aspergillosis ≤12 weeks of a SARS-CoV-2 test were flagged electronically (based on testing results indicative of invasive fungal infection, antifungal therapy, and/or ICD-10 codes), followed by manual review to establish the clinical diagnosis of pulmonary aspergillosis. Incidence rates were calculated per 10,000 SARS-CoV-2 cases. Selected clinical characteristics included age >70, receipt of immune-compromising drugs, hematologic malignancy, chronic respiratory disease, vaccination status, and vaccine era. Multivariate logistic regression was used to estimate the independent effects of these variables via adjusted odds ratios (aOR). Results: Among 674,343 Veterans with SARS-CoV-2, 165 were electronically flagged for review. Of these, 66 were judged to be cases of aspergillosis. Incidence proportions ranged from 0.30/10,000 among patients with zero risk factors to 34/10,000 among those with ≥3 risk factors; rates were similar in the pre- and post-vaccination eras. The 90-day mortality among aspergillosis cases was 50%. In the multivariate analysis, immune suppression (aOR 6.47, CI 3.84–10.92), chronic respiratory disease (aOR 3.57, CI 2.10–6.14), and age >70 (aOR 2.78, CI 1.64–4.80) were associated with aspergillosis. Conclusions: Patients with underlying risk factors for invasive aspergillosis continue to be at some risk despite SARS-CoV-2 immunization. Risk in patients without immune suppression or preexisting lung disease is very low.

Background: Cancer-associated thrombosis (CAT) is a leading cause of death in patients diagnosed with cancer. However, pharmacologic thromboprophylaxis use in cancer patients must be carefully evaluated due to a 2-fold increased risk of experiencing a major bleeding event within this population. The electronic health record CAT (EHR-CAT) risk assessment model (RAM) was recently developed, and reports improved performance over the widely used Khorana score. Extensive RAM external validation is crucial to determine accuracy across diverse patient populations prior to clinical utilization. Objectives: To externally validate EHR-CAT using data from 2103 patients with cancer at the Boston Medical Center (BMC), New England’s largest safety-net hospital, and to compare this RAM with the Khorana score. Methods: We conducted a retrospective study of BMC cancer patients diagnosed between January 2014 and December 2022 using data from the BMC tumor registry and EHR system. We validated the RAM using measures of discrimination and calibration. Results: The EHR-CAT score exhibited a strong ability to discriminate the risk of CAT (C statistic, 0.67), which was substantially higher than the classic Khorana score (C statistic, 0.58). This increased discrimination power reflects the 20% of patients that were reclassified into high or low risk by the expanded score. Model calibration was also strong in this dataset. Conclusion: In our external validation, the recently published EHR-CAT score showed clear and improved separation of patients at high and low risk for CAT. The utilization of this expanded CAT score could facilitate improved targeting of at-risk cancer patients for prophylactic therapy.

Abstract Background The global COVID-19 pandemic is an opportunity to evaluate factors associated with high levels of adoption of different therapeutics in a real-world setting. The aim of this nationwide, retrospective cohort study was to evaluate the diffusion and adoption of novel therapeutics with an emerging evidence basis and to identify factors that influenced physicians’ treatment decisions. Methods Cohort creation: A cohort of Veteran patients with a microbiologically confirmed diagnosis of SARS-CoV2 were identified, and cases were classified by disease severity (outpatient, inpatient with mild and severe disease, intensive care unit ICU]). After classification of disease severity, the proportion of cases (outpatients) and admissions (inpatients) in each category receiving each type of medication were plotted as a function of time. Identification of milestones and guidance changes: Key medications used for the management of COVID-19 milestones in the release of primary research results in various forms (e.g. via press release, preprint or publication in a traditional medical journal), policy events and dates of key guidelines were identified and plotted as a timeline. After a timeline was created, time points were compared to changes in medication use, and factors potentially impacting the magnitude (i.e. proportion of patients who received the treatment) and the speed (i.e. the slope of the change in use) of practice changes were evaluated. Results Dexamethasone and remdesivir, the first two medications with clinical trial data to support their use, underwent the most rapid, complete and sustained diffusion and adoption; the majority of practice changes occurred after press releases and preprints were available and prior to guideline changes, although some additional uptake occurred following guideline updates. Medications that were not “first in class”, that were identified later in the pandemic, and that had higher perceived risk had slower and less complete uptake regardless of the strength and quality of the evidence supporting the intervention. Conclusions Our findings suggest that traditional and social media platforms and preprint releases were major catalysts of practice change, particularly prior to the identification of effective treatments. The “first available treatment in class” impact appeared to be the single most important factor determining the speed and scope of diffusion.

Abstract Background Older patients with non‐small cell lung cancer (NSCLC) are a heterogeneous population with varying degrees of frailty. An electronic frailty index such as the Veterans Affairs Frailty Index (VA‐FI) can potentially help identify vulnerable patients at high risk of poor outcomes. Methods NSCLC patients ≥65 years old and diagnosed in 2002–2017 were identified using the VA Central Cancer Registry. The VA‐FI was calculated using administrative codes from VA electronic health records data linked with Medicare and Medicaid data. We assessed associations between the VA‐FI and times to mortality, hospitalization, and emergency room (ER) visit following diagnosis by Kaplan–Meier analysis and multivariable stratified Cox models. We also evaluated the change in discrimination and calibration of reference prognostic models after adding VA‐FI. Results We identified a cohort of 42,204 older NSCLC VA patients, in which 55.5% were classified as frail (VA‐FI >0.2). After adjustment, there was a strong association between VA‐FI and the risk of mortality (HR = 1.23 for an increase of four deficits or, equivalently, an increase of 0.129 on VA‐FI, p

Cases for a disease can be defined broadly using diagnostic codes, or narrowly using gold-standard confirmation that often is not available in large administrative datasets. These different definitions can have significant impacts on the results and conclusions of studies. We conducted this study to assess how using melanoma phecodes versus histologic confirmation for invasive or in situ melanoma impacts the results of a genome-wide association study (GWAS) using the Million Veteran Program. Melanoma status was determined three ways: (1) by the presence of two or more phecodes, (2) histologically-confirmed invasive melanoma, and (3) histologically-confirmed melanoma in situ. We conducted a GWAS for variants with minor allele frequencies of 1% or greater. There were 45,665 cases in the phecode cohort, 5364 cases in the confirmed invasive melanoma cohort, and 4792 cases in the confirmed melanoma in situ cohort. There were 20,457 variants significant at the genome-wide level in the phecode cohort, 2582 in the invasive melanoma cohort, and 1989 in the melanoma in situ cohort. Most of the variants identified in the phecode cohort did not replicate in the histologically-confirmed cohorts. The different case definitions led to large differences in sample size and variants associated at the genome-wide level. Unvalidated and imprecise case definitions can lead to less accurate results. Investigators should use validated phenotypes when gold-standard definitions are not available. [ABSTRACT FROM AUTHOR]

Natural language processing of medical records offers tremendous potential to improve the patient experience. Sentiment analysis of clinical notes has been performed with mixed results, often highlighting the issue that dictionary ratings are not domain specific. Here, for the first time, we re-calibrate the labMT sentiment dictionary on 3.5M clinical notes describing 10,000 patients diagnosed with lung cancer at the Department of Veterans Affairs. The sentiment score of notes was calculated for two years after date of diagnosis and evaluated against a lab test (platelet count) and a combination of data points (treatments). We found that the oncology specific labMT dictionary, after re-calibration for the clinical oncology domain, produces a promising signal in notes that can be detected based on a comparative analysis to the aforementioned parameters.

Background Vascular function is compromised in Alzheimer disease (AD) years before amyloid and tau pathology are detected and a substantial body of work shows abnormal platelet activation states in patients with AD. The aim of our study was to investigate whether platelet function in middle age is independently associated with future risk of AD. Methods and Results We examined associations of baseline platelet function with incident dementia risk in the community‐based FHS (Framingham Heart Study) longitudinal cohorts. The association between platelet function and risk of dementia was evaluated using the cumulative incidence function and inverse probability weighted Cox proportional cause‐specific hazards regression models, with adjustment for demographic and clinical covariates. Platelet aggregation response was measured by light transmission aggregometry. The final study sample included 1847 FHS participants (average age, 53.0 years; 57.5% women). During follow‐up (median, 20.5 years), we observed 154 cases of incident dementia, of which 121 were AD cases. Results from weighted models indicated that platelet aggregation response to adenosine diphosphate 1.0 µmol/L was independently and positively associated with dementia risk, and it was preceded in importance only by age and hypertension. Sensitivity analyses showed associations with the same directionality for participants defined as adenosine diphosphate hyper‐responders, as well as the platelet response to 0.1 µmol/L epinephrine. Conclusions Our study shows individuals free of antiplatelet therapy with a higher platelet response are at higher risk of dementia in late life during a 20‐year follow‐up, reinforcing the role of platelet function in AD risk. This suggests that platelet phenotypes may be associated with the rate of dementia and potentially have prognostic value.

Objective: Active neutrophils are important contributors to Alzheimer’s disease (AD) pathology through the formation of capillary stalls that compromise cerebral blood flow (CBF) and through aberrant neutrophil signaling that advances disease progression. The neutrophil to lymphocyte ratio (NLR) is a proxy of neutrophil-mediated inflammation, and higher NLR is found in persons diagnosed with clinical AD. The objective of this study was to investigate whether increased NLR in older adults is independently associated with the risk of subsequent dementia.Methods: We examined associations of baseline NLR with incident dementia risk in the community-based Framingham Heart Study (FHS) longitudinal cohorts. The association between NLR and risk of dementia was evaluated using the cumulative incidence function (CIF) and inverse probability-weighted Cox proportional cause-specific hazards regression models, with adjustment for age, sex, body mass index (BMI), systolic and diastolic blood pressure, diabetes, current smoking status, low-density lipoprotein (LDH), high-density lipoprotein (LDL), total cholesterol, triglycerides, and history of cardiovascular disease (CVD). Random forest survival models were used to evaluate the relative predictive value of the model covariates on dementia risk.Results: The final study sample included 1,648 participants with FHS (average age, 69 years; 56% women). During follow-up (median, 5.9 years), we observed 51 cases of incident dementia, of which 41 were AD cases. Results from weighted models suggested that the NLR was independently associated with incident dementia, and it was preceded in predictive value only by age, history of CVD, and blood pressure at baseline.Conclusion: Our study shows that individuals with higher NLR are at a greater risk of subsequent dementia during a 5.9-year follow-up period. Further evaluating the role of neutrophil-mediated inflammation in AD progression may be warranted.

INTRODUCTION: The use of antidepressants in major depressive disorder (MDD) has been reported to influence long‐term risk of Alzheimer's disease (AD) and AD‐related dementias (AD/ADRD), but studies are conflicting. METHODS: We used inverse probability weighted (IPW) Cox models with time‐varying covariates in a retrospective cohort study among midlife veterans with MDD within the US Veterans Affairs healthcare system from January 1, 2000 to June 1, 2022. RESULTS: A total of 35,200 patients with MDD were identified. No associations were seen regarding the effect of being exposed to any antidepressant versus no exposure on AD/ADRD risk (events = 1,056, hazard ratio = 0.94, 95% confidence interval: 0.81 to 1.09) or the exposure to specific antidepressant classes versus no exposure. A risk reduction was observed for female patients in a stratified analysis; however, the number of cases was small. DISCUSSION: Our study suggests that antidepressant exposure has no effect on AD/ADRD risk. The association in female patients should be interpreted with caution and requires further attention. Highlights: We studied whether antidepressant use was associated with future dementia risk.We specifically focused on patients after their first‐ever diagnosis of depression.We used IPW Cox models with time‐varying covariates and a large observation window.Our study did not identify an effect of antidepressant use on dementia risk.A risk reduction was observed in female patients, but the number of cases was small. [ABSTRACT FROM AUTHOR]

Background: Patients taking immune‐suppressive drugs are at increased risk of severe coronavirus disease 2019 (COVID‐19), not fully ameliorated by vaccination. We assessed the contributions of clinical and demographic factors to the risk of severe disease despite vaccination in patients taking immune‐suppressive medications for solid organ transplantation (SOT), rheumatoid arthritis (RA), inflammatory bowel disease (IBD), or psoriasis. Methods: Veterans Health Administration electronic health records were used to identify patients diagnosed with RA, IBD, psoriasis, or SOT who had been vaccinated against severe acute respiratory syndrome coronavirus 2, were subsequently infected, and had received immune‐suppressive drugs within 3 months before infection. The association of severe (defined as hypoxemia, mechanical ventilation, dexamethasone use, or death) versus non‐severe COVID‐19 with the use of immune‐suppressive and antiviral drugs and clinical covariates was assessed by multivariable logistic regression. Results: Severe COVID‐19 was more common in patients with SOT (230/1011, 22.7%) than RA (173/1355, 12.8%), IBD (51/742, 6.9%), or psoriasis (82/1125, 7.3%). Age was strongly associated with severe COVID‐19, adjusted odds ratio (aOR) of 1.04 (CI 1.03–1.05) per year. Comorbidities indicating chronic brain, heart, lung, or kidney damage were also associated with severity, aOR 1.35–2.38. The use of glucocorticoids was associated with increased risk (aOR 1.66, CI 1.39–2.18). Treatment with antivirals was associated with reduced severity, for example, aOR 0.28 (CI 0.13–0.62) for nirmatrelvir/ritonavir. Conclusion: The risk of severe COVID‐19 despite vaccination is substantial in patients taking immune‐suppressive drugs, more so in patients with SOT than in patients with inflammatory diseases. Age and severe comorbidities contribute to risk, as in the general population. Oral antivirals were very beneficial but not widely used. [ABSTRACT FROM AUTHOR]

Antiviral drugs reduce the rate of progression to severe COVID-19 when given to patients with mild-to-moderate disease within 5 days of symptom onset. Despite being recommended for patients at high risk for progression to severe COVID-19 because of age or chronic conditions, reported antiviral use among the general adult population has been ≤35%. To ascertain reasons for underuse of antiviral medications to prevent severe COVID-19 and propose interventions accordingly, a detailed review was conducted of 110 Veterans Health Administration patients with mild-to-moderate infection at high risk for progression because of underlying conditions (organ transplantation or hematologic malignancies) who did not receive an antiviral drug. Among these 110 patients, all of whom had received COVID-19 vaccine, 22 (20.0%) were offered treatment but declined, and 88 (80.0%) were not offered treatment. Among the 88 patients not offered treatment, provider reasons included symptom duration of >5 days (22.7%), concern about possible drug interactions (5.7%), or absence of symptoms (22.7%); however, among nearly one half (43 of 88; 48.9%) of these patients, no reason other than mild symptoms was given. Among 24 (55.8%) of those 43 patients, follow-up was limited to telephone calls to report test results and inquire about symptom evolution, with no documentation of treatment being offered. These findings suggest that education of patients, providers, and medical personnel tasked with follow-up calls, combined with advance planning in the event of a positive test result, might improve the rate of recommended antiviral medication use to prevent severe COVID-19-associated illness, including death. [ABSTRACT FROM AUTHOR]

Several studies have attempted to overcome the sudden volume expansion of the precursor during sulfurization by the use of oxygen-containing precursors when growing the CZTS absorber. This work demonstrates the influence of precursor stacking orders on the properties of the CZTS thin film absorber layer from DC-sputtered oxygenated precursors for solar cell applications. CZTS absorber layers were prepared from three types of DC-sputtered stacks, namely, Zn-O/Sn/Cu, Sn/Zn-O/Cu, and Sn/Cu/Zn-O. The precursors were sequentially deposited on a soda lime glass (SLG) using DC-magnetron sputtering and annealed in a sulfur and nitrogen ambient. X-ray diffractometry (XRD) and Raman spectroscopy analyses reveal the formation of crystalline kesterite CZTS structure regardless of the precursor stacking order. Atomic force microscope (AFM) analysis showed that CZTS thin films grown from precursor stacks SLG/Zn-O/Sn/Cu and SLG/Sn/Zn-O/Cu had improved morphological properties with densely packed large grains compared to that with stack SLG/Sn/Cu/Zn-O. SLG/Zn-O/Sn/Cu is the best stack among the studied stacking orders since it exhibits large grains in the absorber layer, which is preferential for high-efficiency thin film solar cells. The use of oxygenated precursor with order Sn/Zn-O/Cu promises improved CZTS absorber properties as it exhibits better morphological properties. [ABSTRACT FROM AUTHOR]

Background: Major depressive disorder (MDD) is associated with dementia risk. The use of antidepressants in MDD has been reported to influence long term risk of Alzheimer's disease and related dementias (ADRD), but studies are conflicting. Methods: We used inverse probability weighted Cox models with time‐varying covariates in a retrospective cohort study among Veterans with MDD within the US Veterans Affairs health‐care system from 1/1/2000 to 6/1/2022. We focused on patients receiving their first diagnosis of MDD at the age of 60 or above. Our outcome was incident ADRD and unrelated death was considered as a competing risk event. Exposed intervals were defined using prescription data. Models were weighted for the inverse probability of falling in each of the treatment arms (exposed or not) at the beginning of each treatment period based on demographic and clinical covariates updated with most recent information (1‐year prior). The cumulative effect of antidepressant exposure (No. days) was also studied. Result: A total of 24,964 patients with MDD were identified, of which 45% were on antidepressants (Table 1). Median treatment time was 4.10 years [2.56, 6.10]. No relationship was observed between the number of days on antidepressants and the risk of ADRD (Figure 1). No significant associations were seen for the effect of being exposed to antidepressants (any) vs unexposed (HR = 0.94, 95%; CI: 0.81‐1.09) or exposed to each antidepressant drug classes vs unexposed (SSRI HR = 0.93, 95%; CI: 0.79‐1.10; NDRI HR = 0.80, 95%; CI: 0.42‐1.54; SNRI HR = 0.87, 95%; CI: 0.54‐1.41). (Table II). In sensitivity analysis stratified by sex, a reduction in risk due to antidepressant exposure was suggested in female patients, however the number of cases was small (HR = 0.30, 95%; CI: 0.12‐0.81; P = 0.02)). Conclusion: Our study conducted in a large population and after accounting for confounders shows that antidepressant exposure has no effect on ADRD risk. Our result suggesting an association in female patients should be interpreted with caution due to a small sample size and deserves further attention. Replication of results in an external population with a larger representation of female patients is needed for further validation [ABSTRACT FROM AUTHOR]

Frailty is an important construct to measure in acute myeloid leukemia (AML). We used the Veterans Affairs Frailty Index (VA-FI) – calculated using readily available data within the VA's electronic health records – to measure frailty in U.S. veterans with AML. Of the 1166 newly diagnosed and treated veterans with AML between 2012 and 2022, 722 (62%) veterans with AML were classified as frail (VA-FI > 0.2). At a median follow-up of 252.5 days, moderate-severely frail veterans had significantly worse survival than mildly frail, and non-frail veterans (median survival 179 vs. 306 vs. 417 days, p <.001). Increasing VA-FI severity was associated with higher mortality. A model with VA-FI in addition to the European LeukemiaNet (ELN) risk classification and other covariates statistically outperformed a model containing the ELN risk and other covariates alone (p <.001). These findings support the VA-FI as a tool to expand frailty measurement in research and clinical practice for informing prognosis in veterans with AML. [ABSTRACT FROM AUTHOR]

Background: Electronic frailty indices (eFIs) can expand measurement of frailty in research and practice and have demonstrated predictive validity in associations with clinical outcomes. However, their construct validity is less well studied. We aimed to assess the construct validity of the VA‐FI, an eFI developed for use in the U.S. Veterans Affairs Healthcare System. Methods: Veterans who underwent comprehensive geriatric assessments between January 31, 2019 and June 6, 2022 at VA Boston and had sufficient data documented for a comprehensive geriatric assessment‐frailty index (CGA‐FI) were included. The VA‐FI, based on diagnostic and procedural codes, and the CGA‐FI, based on geriatrician‐measured deficits, were calculated for each patient. Geriatricians also assessed the Clinical Frailty Scale (CFS), functional status (ADLs and IADLs), and 4‐meter gait speed (4MGS). Results: A total of 132 veterans were included, with median age 81.4 years (IQR 75.8–88.7). Across increasing levels of VA‐FI (<0.2; 0.2–0.4; >0.4), mean CGA‐FI increased (0.24; 0.30; 0.40). The VA‐FI was moderately correlated with the CGA‐FI (r 0.45, p < 0.001). Every 0.1‐unit increase in the VA‐FI was associated with an increase in the CGA‐FI (linear regression beta 0.05; 95% confidence interval [CI] 0.03–0.06), higher CFS category (ordinal regression OR 1.69; 95% CI 1.24–2.30), higher odds of ADL dependency (logistic regression OR 1.59; 95% CI 1.20–2.11), IADL dependency (logistic regression OR 1.68; 95% CI 1.23–2.30), and a decrease in 4MGS (linear regression beta −0.07, 95% CI −0.12 to −0.02). All models were adjusted for age and race, and associations held after further adjustment for the Charlson Comorbidity Index. Conclusion: Our results demonstrate the construct validity of the VA‐FI through its associations with clinical measures of frailty, including summary frailty measures, functional status, and objective physical performance. Our findings complement others' in showing that eFIs can capture functional and mobility domains of frailty beyond just comorbidity and may be useful to measure frailty among populations and individuals. [ABSTRACT FROM AUTHOR]

Veterans are at an increased risk for prostate cancer, a disease with extraordinary clinical and molecular heterogeneity, compared with the general population. However, little is known about the underlying molecular heterogeneity within the veteran population and its impact on patient management and treatment. Using clinical and targeted tumor sequencing data from the National Veterans Affairs health system, we conducted a retrospective cohort study on 45 patients with advanced prostate cancer in the Veterans Precision Oncology Data Commons (VPODC), most of whom were metastatic castration-resistant. Wecharacterized the mutational burden in this cohort and conducted unsupervised clustering analysis to stratify patients by molecular alterations. Veterans with prostate cancer exhibited a mutational landscape broadly similar to prior studies, including KMT2A andNOTCH1 mutations associated with neuroendocrine prostate cancer phenotype, previously reported to be enriched in veterans. We also identified several potential novel mutations in PTEN, MSH6, VHL, SMO, and ABL1. Hierarchical clustering analysis revealed two subgroups containing therapeutically targetable molecular features with novel mutational signatures distinct from those reported in the Catalogue of Somatic Mutations in Cancer database. The clustering approach presented in this study can potentially be used to clinically stratify patients based on their distinct mutational profiles and identify actionable somatic mutations for precision oncology. [ABSTRACT FROM AUTHOR]

Background Death within a specified time window following a positive SARS-CoV-2 test is used by some agencies for attributing death to COVID-19. With Omicron variants, widespread immunity, and asymptomatic screening, there is cause to re-evaluate COVID-19 death attribution methods and develop tools to improve case ascertainment. Methods All patients who died following microbiologically confirmed SARS-CoV-2 in the Veterans Health Administration (VA) and at Tufts Medical Center (TMC) were identified. Records of selected vaccinated VA patients with positive tests in 2022, and of all TMC patients with positive tests in 2021–2022, were manually reviewed to classify deaths as COVID-19–related (either directly caused by or contributed to), focused on deaths within 30 days. Logistic regression was used to develop and validate a surveillance model for identifying deaths in which COVID-19 was causal or contributory. Results Among vaccinated VA patients who died ≤30 days after a positive test in January–February 2022, death was COVID-19–related in 103/150 cases (69%) (55% causal, 14% contributory). In June–August 2022, death was COVID-19–related in 70/150 cases (47%) (22% causal, 25% contributory). Similar results were seen among the 71 patients who died at TMC. A model including hypoxemia, remdesivir, and anti-inflammatory drugs had positive and negative predictive values of 0.82–0.95 and 0.64–0.83, respectively. Conclusions By mid-2022, "death within 30 days" did not provide an accurate estimate of COVID-19–related death in 2 US healthcare systems with routine admission screening. Hypoxemia and use of antiviral and anti-inflammatory drugs—variables feasible for reporting to public health agencies—would improve classification of death as COVID-19–related. [ABSTRACT FROM AUTHOR]