Effect of exercise on fatigue and depression in breastcancer women undergoing chemotherapy: a systematic review and meta-analysis.

This meta-analysis examined the effectiveness of exercise interventions in reducing fatigue and depression among women undergoing chemotherapy for breast cancer. The study followed PRISMA guidelines and analysed seven randomized controlled trials between 2016 and 2022. The results showed that exercise can substantially reduce fatigue levels (MD: -0.40, CI: -0.66, -0.14, P: 0.003), a common side effect of chemotherapy. Although depression did not significantly change (MD: -0.39, CI: -0.98, 0.20, P: 0.19), this study highlights the positive impact of exercise on mental health outcomes. The control group also experienced decreased quality of life (MD: 0.18, CI: 0.01-0.35, P: 0.03), emphasizing the importance of incorporating exercise interventions to improve overall well-being during breast cancer treatment. In addition to primary outcomes, the study revealed that exercise positively affected secondary aspects such as cognitive fatigue, social function, physical function, constipation, and dyspnoea.

Transforming Hypertension Diagnosis and Management in The Era of Artificial Intelligence: A 2023 National Heart, Lung, and Blood Institute (NHLBI) Workshop Report.

Hypertension is among the most important risk factors for cardiovascular disease, chronic kidney disease, and dementia. The artificial intelligence (AI) field is advancing quickly, and there has been little discussion on how AI could be leveraged for improving the diagnosis and management of hypertension. AI technologies, including machine learning tools, could alter the way we diagnose and manage hypertension, with potential impacts for improving individual and population health. The development of successful AI tools in public health and health care systems requires diverse types of expertise with collaborative relationships between clinicians, engineers, and data scientists. Unbiased data sources, management, and analyses remain a foundational challenge. From a diagnostic standpoint, machine learning tools may improve the measurement of blood pressure and be useful in the prediction of incident hypertension. To advance the management of hypertension, machine learning tools may be useful to find personalized treatments for patients using analytics to predict response to antihypertension medications and the risk for hypertension-related complications. However, there are real-world implementation challenges to using AI tools in hypertension. Herein, we summarize key findings from a diverse group of stakeholders who participated in a workshop held by the National Heart, Lung, and Blood Institute in March 2023. Workshop participants presented information on communication gaps between clinical medicine, data science, and engineering in health care; novel approaches to estimating BP, hypertension risk, and BP control; and real-world implementation challenges and issues.

Novel quinoline substituted autophagy inhibitors attenuate Zika virus replication in ocular cells.

Zika virus (ZIKV) is a re-emerging RNA virus that is known to cause ocular and neurological abnormalities in infants. ZIKV exploits autophagic processes in infected cells to enhance its replication and spread. Thus, autophagy inhibitors have emerged as a potent therapeutic target to combat RNA viruses, with Hydroxychloroquine (HCQ) being one of the most promising candidates. In this study, we synthesized several novel small-molecule quinoline derivatives, assessed their antiviral activity, and determined the underlying molecular mechanisms. Among the nine synthesized analogs, two lead candidates, labeled GL-287 and GL-382, significantly attenuated ZIKV replication in human ocular cells, primarily by inhibiting autophagy. These two compounds surpassed the antiviral efficacy of HCQ and other existing autophagy inhibitors, such as ROC-325, DC661, and GNS561. Moreover, unlike HCQ, these novel analogs did not exhibit cytotoxicity in the ocular cells. Treatment with compounds GL-287 and GL-382 in ZIKV-infected cells increased the abundance of LC3 puncta, indicating the disruption of the autophagic process. Furthermore, compounds GL-287 and GL-382 effectively inhibited the ZIKV-induced innate inflammatory response in ocular cells. Collectively, our study demonstrates the safe and potent antiviral activity of novel autophagy inhibitors against ZIKV.

Concordance With Screening and Treatment Guidelines for Chronic Kidney Disease in Type 2 Diabetes.

Importance: Chronic kidney disease (CKD) is an often-asymptomatic complication of type 2 diabetes (T2D) that requires annual screening to diagnose. Patient-level factors linked to inadequate screening and treatment can inform implementation strategies to facilitate guideline-recommended CKD care. Objective: To identify risk factors for nonconcordance with guideline-recommended CKD screening and treatment in patients with T2D. Design, Setting, and Participants: This retrospective cohort study was performed at 20 health care systems contributing data to the US National Patient-Centered Clinical Research Network. To evaluate concordance with CKD screening guidelines, adults with an outpatient clinician visit linked to T2D diagnosis between January 1, 2015, and December 31, 2020, and without known CKD were included. A separate analysis reviewed prescription of angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) and sodium-glucose cotransporter 2 (SGLT2) inhibitors in adults with CKD (estimated glomerular filtration rate [eGFR] of 30-90 mL/min/1.73 m2 and urinary albumin-to-creatinine ratio [UACR] of 200-5000 mg/g) and an outpatient clinician visit for T2D between October 1, 2019, and December 31, 2020. Data were analyzed from July 8, 2022, through June 22, 2023. Exposures: Demographics, lifestyle factors, comorbidities, medications, and laboratory results. Main Outcomes and Measures: Screening required measurement of creatinine levels and UACR within 15 months of the index visit. Treatment reflected prescription of ACEIs or ARBs and SGLT2 inhibitors within 12 months before or 6 months following the index visit. Results: Concordance with CKD screening guidelines was assessed in 316 234 adults (median age, 59 [IQR, 50-67] years), of whom 51.5% were women; 21.7%, Black; 10.3%, Hispanic; and 67.6%, White. Only 24.9% received creatinine and UACR screening, 56.5% received 1 screening measurement, and 18.6% received neither. Hispanic ethnicity was associated with lack of screening (relative risk [RR], 1.16 [95% CI, 1.14-1.18]). In contrast, heart failure, peripheral arterial disease, and hypertension were associated with a lower risk of nonconcordance. In 4215 patients with CKD and albuminuria, 3288 (78.0%) received an ACEI or ARB; 194 (4.6%), an SGLT2 inhibitor; and 885 (21.0%), neither therapy. Peripheral arterial disease and lower eGFR were associated with lack of CKD treatment, while diuretic or statin prescription and hypertension were associated with treatment. Conclusions and Relevance: In this cohort study of patients with T2D, fewer than one-quarter received recommended CKD screening. In patients with CKD and albuminuria, 21.0% did not receive an SGLT2 inhibitor or an ACEI or an ARB, despite compelling indications. Patient-level factors may inform implementation strategies to improve CKD screening and treatment in people with T2D.

Data Interoperability for Ambulatory Monitoring of Cardiovascular Disease: A Scientific Statement From the American Heart Association.

Wearable devices are increasingly used by a growing portion of the population to track health and illnesses. The data emerging from these devices can potentially transform health care. This requires an interoperability framework that enables the deployment of platforms, sensors, devices, and software applications within diverse health systems, aiming to facilitate innovation in preventing and treating cardiovascular disease. However, the current data ecosystem includes several noninteroperable systems that inhibit such objectives. The design of clinically meaningful systems for accessing and incorporating these data into clinical workflows requires strategies to ensure the quality of data and clinical content and patient and caregiver accessibility. This scientific statement aims to address the best practices, gaps, and challenges pertaining to data interoperability in this area, with considerations for (1) data integration and the scope of measures, (2) application of these data into clinical approaches/strategies, and (3) regulatory/ethical/legal issues.

Binding selectivity analysis of new delhi metallo-beta-lactamase-1 inhibitors using molecular dynamics simulations: Exploring possibilities for decoding antimicrobial drug resistance.

BACKGROUND: New Delhi metallo-beta-lactamase-1 (NDM1) confers resistance to several bacterial species against a broad range of beta-lactam antibiotics and turning them into superbugs that pose a significant threat to healthcare systems worldwide. As such, it is a potentially relevant biological target for counteracting bacterial infections. Given the lack of effective treatment options against NDM1 producing bacteria, finding a reliable inhibitor for the NDM1 enzyme is crucial. METHODS: Using molecular dynamics simulations, the binding selectivities and affinities of three ligands, viz. PNK, 3S0, and N1G were investigated against NDM1. RESULTS: The results indicate that N1G binds with more affinity to NDM1 than PNK and 3S0. The binding energy decomposition analysis revealed that residues I35, W93, H189, K211, and N220 showed significant binding energies with PNK, 3S0, and N1G, and hence are crucially involved in the binding of the ligands to NDM1. Molecular dynamics trajectory analysis further elicited that the ligands influence dynamic flexibility of NDM1 morphology, which contributes to the partial selectivities of PNK, 3S0, and N1G. CONCLUSIONS: This in silico study offers a vital information for developing potential NDM1 inhibitors with high selectivity. Nevertheless, in vitro and in vivo experimental validation is mandated to extend the possible applications of these ligands as NDM1 inhibitors that succor in combating antimicrobial resistance.

Breaking Bad: Spontaneous Rupture of Incisional Hernia.

Spontaneous bowel evisceration from a ruptured, long-standing abdominal wall hernia is a very rare complication with significant morbidity and mortality, usually occurring in incisional or recurrent groin hernias. In this case report, we elucidate an unexpected scenario of spontaneous incisional hernia rupture leading to bowel evisceration, detailing the clinical presentation, diagnostic workup, and surgical management. By highlighting this rare complication, we emphasise the significance of vigilance in monitoring hernia patients and the necessity of expedited surgical intervention to prevent complications, optimise outcomes, and minimise morbidity.

Performance of risk models to predict mortality risk for patients with heart failure: evaluation in an integrated health system.

BACKGROUND: Referral of patients with heart failure (HF) who are at high mortality risk for specialist evaluation is recommended. Yet, most tools for identifying such patients are difficult to implement in electronic health record (EHR) systems. OBJECTIVE: To assess the performance and ease of implementation of Machine learning Assessment of RisK and EaRly mortality in Heart Failure (MARKER-HF), a machine-learning model that uses structured data that is readily available in the EHR, and compare it with two commonly used risk scores: the Seattle Heart Failure Model (SHFM) and Meta-Analysis Global Group in Chronic (MAGGIC) Heart Failure Risk Score. DESIGN: Retrospective, cohort study. PARTICIPANTS: Data from 6764 adults with HF were abstracted from EHRs at a large integrated health system from 1/1/10 to 12/31/19. MAIN MEASURES: One-year survival from time of first cardiology or primary care visit was estimated using MARKER-HF, SHFM, and MAGGIC. Discrimination was measured by the area under the receiver operating curve (AUC). Calibration was assessed graphically. KEY RESULTS: Compared to MARKER-HF, both SHFM and MAGGIC required a considerably larger amount of data engineering and imputation to generate risk score estimates. MARKER-HF, SHFM, and MAGGIC exhibited similar discriminations with AUCs of 0.70 (0.69-0.73), 0.71 (0.69-0.72), and 0.71 (95% CI 0.70-0.73), respectively. All three scores showed good calibration across the full risk spectrum. CONCLUSIONS: These findings suggest that MARKER-HF, which uses readily available clinical and lab measurements in the EHR and required less imputation and data engineering than SHFM and MAGGIC, is an easier tool to identify high-risk patients in ambulatory clinics who could benefit from referral to a HF specialist.

SARS-CoV-2 infects cells lining the blood-retinal barrier and induces a hyperinflammatory immune response in the retina via systemic exposure.

SARS-CoV-2 has been shown to cause wide-ranging ocular abnormalities and vision impairment in COVID-19 patients. However, there is limited understanding of SARS-CoV-2 in ocular transmission, tropism, and associated pathologies. The presence of viral RNA in corneal/conjunctival tissue and tears, along with the evidence of viral entry receptors on the ocular surface, has led to speculation that the eye may serve as a potential route of SARS-CoV-2 transmission. Here, we investigated the interaction of SARS-CoV-2 with cells lining the blood-retinal barrier (BRB) and the role of the eye in its transmission and tropism. The results from our study suggest that SARS-CoV-2 ocular exposure does not cause lung infection and moribund illness in K18-hACE2 mice despite the extended presence of viral remnants in various ocular tissues. In contrast, intranasal exposure not only resulted in SARS-CoV-2 spike (S) protein presence in different ocular tissues but also induces a hyperinflammatory immune response in the retina. Additionally, the long-term exposure to viral S-protein caused microaneurysm, retinal pigmented epithelium (RPE) mottling, retinal atrophy, and vein occlusion in mouse eyes. Notably, cells lining the BRB, the outer barrier, RPE, and the inner barrier, retinal vascular endothelium, were highly permissive to SARS-CoV-2 replication. Unexpectedly, primary human corneal epithelial cells were comparatively resistant to SARS-CoV-2 infection. The cells lining the BRB showed induced expression of viral entry receptors and increased susceptibility towards SARS-CoV-2-induced cell death. Furthermore, hyperglycemic conditions enhanced the viral entry receptor expression, infectivity, and susceptibility of SARS-CoV-2-induced cell death in the BRB cells, confirming the reported heightened pathological manifestations in comorbid populations. Collectively, our study provides the first evidence of SARS-CoV-2 ocular tropism via cells lining the BRB and that the virus can infect the retina via systemic permeation and induce retinal inflammation.

Effect of Microwave-Based Dry Blanching on Drying of Potato Slices: A Comparative Study.

Microwave (MW)-based dry blanching can inactivate oxidative enzymes like peroxidase (POD) and polyphenol oxidase (PPO) rapidly and retain a higher amount of water-soluble nutrients, like ascorbic acid. This study compared the MW-based dry blanching of potato slices of various thicknesses (5, 8, and 10 mm) with conventional methods (water and steam blanching). The time required for water and steam blanching was longer than that required for MW blanching. Potato slices of 10 mm thickness required a longer blanching duration compared with slices of a lesser thickness (5 and 8 mm). The MW-blanched samples (77.37-83.5%) retained a higher content of ascorbic acid, followed by steam-blanched (69.15-74.92%) and water-blanched (67.18-71.54%) samples. The Page, modified Page, Midilli-Kucuk, and Hii, Law, and Cloke models predicted the thin layer drying of potato slices (5 mm thickness) better with a higher coefficient of determination values (0.9607-0.9976) compared to Fick's and Exponential models (0.8942-0.9444).

The multifaceted functions of long non-coding RNA HOTAIR in neuropathologies and its potential as a prognostic marker and therapeutic biotarget.

Long non-coding RNAs (lncRNAs) are progressively being perceived as prominent molecular agents controlling multiple aspects of neuronal (patho)physiology. Amongst these is the HOX transcript antisense intergenic RNA, often abbreviated as HOTAIR. HOTAIR epigenetically regulates its target genes via its interaction with two different chromatin-modifying agents; histone methyltransferase polycomb-repressive complex 2 and histone demethylase lysine-specific demethylase 1. Parenthetically, HOTAIR elicits trans-acting sponging function against multiple micro-RNA species. Oncological research studies have confirmed the pathogenic functions of HOTAIR in multiple cancer types, such as gliomas and proposed it as a pro-oncological lncRNA. In fact, its expression has been suggested to be a predictor of the severity/grade of gliomas, and as a prognostic biomarker. Moreover, a propound influence of HOTAIR in other aspects of brain heath and disease states is just beginning to be unravelled. The objective of this review is to recapitulate all the relevant data pertaining to the regulatory roles of HOTAIR in neuronal (patho)physiology. To this end, we discuss the pathogenic mechanisms of HOTAIR in multiple neuronal diseases, such as neurodegeneration, traumatic brain injury and neuropsychiatric disorders. Finally, we also summarize the results from the studies incriminating HOTAIR in the pathogeneses of gliomas and other brain cancers. Implications of HOTAIR serving as a suitable therapeutic target in neuropathologies are also discussed.

Gum Ghatti: A Comprehensive Review on Production, Processing, Remarkable Properties, and Diverse Applications.

Gum ghatti, popularly known as Indian gum and obtained from Anogeissus latifolia, is a complex high-molecular-weight, water-soluble, and swellable nonstarch polysaccharide comprised of magnesium and calcium salts of ghattic acids and multiple monosugars. Unlike other nontimber forest produce, gums ghatti is a low-volume but high-value product. It has several applications and is widely used as food, in pharmaceuticals, and for wastewater treatment and hydrogel formation, and it has attracted a great deal of attention in the fields of energy, environmental science, and nanotechnology. Industrial applications of gum ghatti are primarily due to its excellent emulsification, stabilization, thickening, heat tolerance, pH stability, carrier, and biodegradable properties. However, utilization of gum ghatti is poorly explored and implemented due to a lack of knowledge of its production, processing, and properties. Nevertheless, there has been interest among investigators in recent times for exploring its production, processing, molecular skeleton, and functional properties. This present review focuses on production scenarios, processing aspects, structural and functional properties, and potential applications in the food, pharmaceuticals, nonfood, and other indigenous and industrial usages.

Neuroprotective, Anti-Inflammatory and Antifibrillogenic Offerings by Emodin against Alzheimer's Dementia: A Systematic Review.

Background: Alzheimer's disease (AD) is among the major causes of dementia in the elderly and exerts tremendous clinical, psychological and socio-economic constraints. Currently, there are no effective disease-modifying/retarding anti-AD agents. Emodin is a bioactive phytochemical with potent multimodal anti-inflammatory, antioxidant, and antifibrillogenic properties. In particular, emodin may result in significant repression of the pathogenic mechanisms underlying AD. The purpose of this review is to accumulate and summarize all the primary research data evaluating the therapeutic actions of emodin in AD pathogenesis. Methodology: The search, selection, and retrieval of pertinent primary research articles were systematically performed using a methodically designed approach. A variety of keyword combinations were employed on online scholarly web-databases. Strict preset inclusion and exclusion criteria were used to select the retrieved studies. Data from the individual studies were summarized and compiled into different sections, based upon their findings. Results: Cellular and animal research indicates that emodin exerts robust multimodal neuroprotection in AD. While emodin effectively prevents tau and amyloid-beta (Aß) oligomerization, it also mitigates their neurotoxicity by attenuating neuroinflammatory, oxidative, and bioenergetic defects. Evidences for emodin-mediated enhancements in memory, learning, and cognition were also found in the literature. Conclusion: Emodin is a potential anti-AD dietary supplement; however, further studies are warrantied to thoroughly understand its target players and mechanisms. Moreover, human clinical data on emodin-mediated amelioration of AD phenotype is largely lacking, and must be addressed in the future. Lastly, the safety of exogenously supplemented emodin must be thoroughly evaluated.

Multirole of the internet of medical things (IoMT) in biomedical systems for managing smart healthcare systems: An overview of current and future innovative trends.

Internet of Medical Things (IoMT) is an emerging subset of Internet of Things (IoT), often called as IoT in healthcare, refers to medical devices and applications with internet connectivity, is exponentially gaining researchers' attention due to its wide-ranging applicability in biomedical systems for Smart Healthcare systems. IoMT facilitates remote health biomedical system and plays a crucial role within the healthcare industry to enhance precision, reliability, consistency and productivity of electronic devices used for various healthcare purposes. It comprises a conceptualized architecture for providing information retrieval strategies to extract the data from patient records using sensors for biomedical analysis and diagnostics against manifold diseases to provide cost-effective medical solutions, quick hospital treatments, and personalized healthcare. This article provides a comprehensive overview of IoMT with special emphasis on its current and future trends used in biomedical systems, such as deep learning, machine learning, blockchains, artificial intelligence, radio frequency identification, and industry 5.0.

Roles of HOTAIR Long Non-coding RNA in Gliomas and Other CNS Disorders.

HOX transcript antisense intergenic RNA (HOTAIR) is a long non-coding RNA (lncRNA) which is increasingly being perceived as a tremendous molecular mediator of brain pathophysiology at multiple levels. Epigenetic regulation of target gene expression carried out by HOTAIR is thorough modulation of chromatin modifiers; histone methyltransferase polycomb repressive complex 2 (PRC2) and histone demethylase lysine-specific demethylase 1 (LSD1). Incidentally, HOTAIR was the first lncRNA shown to elicit sponging of specific microRNA (miRNA or miR) species in a trans-acting manner. It has been extensively studied in various cancers, including gliomas and is regarded as a prominent pro-tumorigenic and pro-oncogenic lncRNA. Indeed, the expression of HOTAIR may serve as glioma grade predictor and prognostic biomarker. The objective of this timely review is not only to outline the multifaceted pathogenic roles of HOTAIR in the development and pathophysiology of gliomas and brain cancers, but also to delineate the research findings implicating it as a critical regulator of overall brain pathophysiology. While the major focus is on neuro-oncology, wherein HOTAIR represents a particularly potent underlying pathogenic player and a suitable therapeutic target, mechanisms underlying the regulatory actions of HOTAIR in neurodegeneration, traumatic, hypoxic and ischemic brain injuries, and neuropsychiatric disorders are also presented.

Ineffective ventilation in a very low birth weight infant with H-type Tracheoesophageal Fistula with bilateral chemical pneumonitis. A lesson learned.

Tracheoesophageal fistula (TEF) with or without associated esophageal atresia (EA) in the neonate is challenging to diagnose and manage its complications like aspiration, respiratory distress, and other associated anomalies. To stabilize, ventilate and prepare for surgical correction, understanding the H-nature of disease and anticipation of problems and their management will improve survival. We present a newborn with tracheoesophageal fistula without atresia from resource-limited settings and lessons we learned from the case.

Mind Matters: Exploring the Intersection of Psychological Factors and Cognitive Abilities of University Students by Using ANN Model.

Purpose: While previous studies have suggested close association of psychological variables of students withtheir higher-order cognitive abilities, such studies have largely been lacking for third world countries like India, with their unique socio-economic-cultural set of challenges. We aimed to investigate the relationship between psychological variables (depression, anxiety and stress) and cognitive functions among Indian students, and to predict cognitive performance as a function of these variables. Patients and Methods: Four hundred and thirteen university students were systematically selected using purposive sampling. Widely used and validated offline questionnaires were used to assess their psychological and cognitive statuses. Correlational analyses were conducted to examine the associations between these variables. An Artificial Neural Network (ANN) model was applied to predict cognitive levels based on the scores of psychological variables. Results: Correlational analyses revealed negative correlations between emotional distress and cognitive functioning. Principal Component Analysis (PCA) reduced the dimensionality of the input data, effectively capturing the variance with fewer features. The feature weight analysis indicated a balanced contribution of each mental health symptom, with particular emphasis on one of the symptoms. The ANN model demonstrated moderate predictive performance, explaining a portion of the variance in cognitive levels based on the psychological variables. Conclusion: The study confirms significant associations between emotional statuses of university students with their cognitive abilities. Specifically, we provide evidence for the first time that in Indian students, self-reported higher levels of stress, anxiety, and depression are linked to lower performance in cognitive tests. The application of PCA and feature weight analysis provided deeper insights into the structure of the predictive model. Notably, use of the ANN model provided insights into predicting these cognitive domains as a function of the emotional attributes. Our results emphasize the importance of addressing mental health concerns and implementing interventions for the enhancement of cognitive functions in university students.

Utilities of Isolated Nerve Terminals in Ex Vivo Analyses of Protein Translation in (Patho)physiological Brain States: Focus on Alzheimer's Disease.

Synapses are the cellular substrates of higher-order brain functions, and their dysfunction is an early and primary pathogenic mechanism across several neurological disorders. In particular, Alzheimer's disease (AD) is categorized by prodromal structural and functional synaptic deficits, prior to the advent of classical behavioral and pathological features. Recent research has shown that the development, maintenance, and plasticity of synapses depend on localized protein translation. Synaptosomes and synaptoneurosomes are biochemically isolated synaptic terminal preparations which have long been used to examine a variety of synaptic processes ex vivo in both healthy and pathological conditions. These ex vivo preparations preserve the mRNA species and the protein translational machinery. Hence, they are excellent in organello tools for the study of alterations in mRNA levels and protein translation in neuropathologies. Evaluation of synapse-specific basal and activity-driven de novo protein translation activity can be conveniently performed in synaptosomal/synaptoneurosomal preparations from both rodent and human brain tissue samples. This review gives a quick overview of the methods for isolating synaptosomes and synaptoneurosomes before discussing the studies that have utilized these preparations to study localized synapse-specific protein translation in (patho)physiological situations, with an emphasis on AD. While the review is not an exhaustive accumulation of all the studies evaluating synaptic protein translation using the synaptosomal model, the aim is to assemble the most relevant studies that have done so. The hope is to provide a suitable research platform to aid neuroscientists to utilize the synaptosomal/synaptoneurosomal models to evaluate the molecular mechanisms of synaptic dysfunction within the specific confines of mRNA localization and protein translation research.

Comparative antimicrobial use in coronavirus disease 2019 (COVID-19) and non-COVID-19 inpatients from 2019 to 2020: A multicenter ecological study.

OBJECTIVE: We sought to determine whether increased antimicrobial use (AU) at the onset of the coronavirus disease 2019 (COVID-19) pandemic was driven by greater AU in COVID-19 patients only, or whether AU also increased in non-COVID-19 patients. DESIGN: In this retrospective observational ecological study from 2019 to 2020, we stratified inpatients by COVID-19 status and determined relative percentage differences in median monthly AU in COVID-19 patients versus non-COVID-19 patients during the COVID-19 period (March-December 2020) and the pre-COVID-19 period (March-December 2019). We also determined relative percentage differences in median monthly AU in non-COVID-19 patients during the COVID-19 period versus the pre-COVID-19 period. Statistical significance was assessed using Wilcoxon signed-rank tests. SETTING: The study was conducted in 3 acute-care hospitals in Chicago, Illinois. PATIENTS: Hospitalized patients. RESULTS: Facility-wide AU for broad-spectrum antibacterial agents predominantly used for hospital-onset infections was significantly greater in COVID-19 patients versus non-COVID-19 patients during the COVID-19 period (with relative increases of 73%, 66%, and 91% for hospitals A, B, and C, respectively), and during the pre-COVID-19 period (with relative increases of 52%, 64%, and 66% for hospitals A, B, and C, respectively). In contrast, facility-wide AU for all antibacterial agents was significantly lower in non-COVID-19 patients during the COVID-19 period versus the pre-COVID-19 period (with relative decreases of 8%, 7%, and 8% in hospitals A, B, and C, respectively). CONCLUSIONS: AU for broad-spectrum antimicrobials was greater in COVID-19 patients compared to non-COVID-19 patients at the onset of the pandemic. AU for all antibacterial agents in non-COVID-19 patients decreased in the COVID-19 period compared to the pre-COVID-19 period.