A prospective, observational validation of HRAD±, a novel pediatric affect and cooperation scale.

STUDY OBJECTIVE: HRAD± was developed to quickly assess pediatric perioperative affect and cooperation. HRAD± represents: Happy, Relaxed, Anxious, Distressed, with a yes/no answer to cooperativity. The primary aim of this study was to investigate the clinical utility of HRAD± as an affect and cooperation assessment tool for inhalational mask induction. Secondary aims examined inter-rater reliability (IRR) of HRAD± and predictive validity of induction HRAD± with emergence delirium. DESIGN: This was a prospective observational investigation. SETTING: We conducted this investigation at Lucile Packard Children's Hospital Stanford, an academic, quaternary care children's hospital in Northern California. PATIENTS: A total of 197 patients were included in this investigation. Children 1-14 years of age, who underwent daytime procedures with inhalational induction of anesthesia and American Society of Anesthesiologists physical status I-III were eligible. INTERVENTIONS: During mask induction, two trained research assistants (RAs) independently scored the patient's affect and cooperation. After extubation, the same investigators observed the patient's emergence. MEASUREMENTS: RAs scored each mask induction using the following scales: HRAD±, modified Yale Preoperative Anxiety Scale (mYPAS), Observation Scale of Behavioral Distress (OSBD), and Induction Compliance Checklist (ICC). Correlations were calculated to HRAD±. IRR of HRAD± between the RAs as well as predictive validity of HRAD± to Pediatric Anesthesia Emergence Delirium (PAED), Watcha and Cravero scales were calculated. MAIN RESULTS: HRAD± scores strongly correlated with mYPAS (r = 0.840, p < 0.0001) with moderate correlation to OSBD (r = 0.685, p < 0.0001) and ICC (-0.663, p < 0.0001). IRR was moderate for the affect and cooperation portion of the HRAD± scale, respectively (κ = 0.595 [p < 0.0001], κ = 0.478 [p < 0.0001]). A weak correlation was observed with PAED (r = 0.134 [p = 0.0597]) vs HRAD±. No correlations were observed between Watcha (r = 0.013 [p = 0.8559]) and Cravero and HRAD± scales (r = 0.002 [p = 0.9767]). CONCLUSIONS: HRAD± is a clinically useful and simple scale for evaluating pediatric affect and cooperation during inhalational mask induction. Results demonstrate correlation with commonly utilized research assessment scales.

Evidence-based clinical practice guideline for the pharmacologic management of acute dental pain in adolescents, adults, and older adults: A report from the American Dental Association Science and Research Institute, the University of Pittsburgh, and the University of Pennsylvania.

BACKGROUND: A panel convened by the American Dental Association Science and Research Institute, the University of Pittsburgh, and the University of Pennsylvania conducted systematic reviews and meta-analyses and formulated evidence-based recommendations for the pharmacologic management of acute dental pain after simple and surgical tooth extraction(s) and for the temporary management (ie, definitive dental treatment not immediately available) of toothache associated with pulp and periapical diseases in adolescents, adults, and older adults. TYPES OF STUDIES REVIEWED: The panel conducted 4 systematic reviews to determine the effect of opioid and nonopioid analgesics, local anesthetics, corticosteroids, and topical anesthetics on acute dental pain. The panel used the Grading of Recommendations, Assessment, Development and Evaluation approach to assess the certainty of the evidence and the Grading of Recommendations, Assessment, Development and Evaluation Evidence-to-Decision Framework to formulate recommendations. RESULTS: The panel formulated recommendations and good practice statements using the best available evidence. There is a beneficial net balance favoring the use of nonopioid medications compared with opioid medications. In particular, nonsteroidal anti-inflammatory drugs alone or in combination with acetaminophen likely provide superior pain relief with a more favorable safety profile than opioids. CONCLUSIONS AND PRACTICAL IMPLICATIONS: Nonopioid medications are first-line therapy for managing acute dental pain after tooth extraction(s) and the temporary management of toothache. The use of opioids should be reserved for clinical situations when the first-line therapy is insufficient to reduce pain or there is contraindication of nonsteroidal anti-inflammatory drugs. Clinicians should avoid the routine use of just-in-case prescribing of opioids and should exert extreme caution when prescribing opioids to adolescents and young adults.

Reducing Preoperative Caregiver Anxiety With Virtual Reality: A Pragmatic, Randomized Controlled Study.

Pediatric patients and their caregivers often experience perioperative anxiety. Interventions reduce caregiver anxiety improve cooperation and contribute to an improved patient experience. This study seeks to evaluate the efficacy of virtual reality (VR)-assisted mindfulness on perioperative caregiver anxiety. Participants were randomized into a standard of care (SOC) group, which included snacks but no technology-based distractions, or a VR group, which included snacks and a VR-guided meditation. Caregiver anxiety was measured before and after the intervention using the Visual Analogue Scale for Anxiety (VAS-A). Secondary aims explored participants' baseline anxiety with the State-Trait Anxiety Inventory (STAI). VR group participants completed a satisfaction survey. Linear regression models of VAS-A and STAI were used to compare group differences. Satisfaction survey results were reported with descriptive statistics. 26 participants were included, with 12 randomized to the SOC group and 14 to the VR group. VAS-A scores in the VR group were lower than those in the SOC group (p = .002). The STAI found no change in participants' state of anxiety in the SOC group (p = .7108), compared to a significant reduction (p = .014) in the VR group when controlling for anxiety traits. 12 of 14 caregivers in the VR group expressed satisfaction or strong satisfaction. This study supports the implementation of VR mindfulness as a method to reduce caregiver anxiety. VR use in the pediatric healthcare setting is safe and inexpensive, and the intervention had a high degree of participant satisfaction.

Predicting pediatric healthcare provider use of virtual reality using a technology acceptance model.

Objective: The primary aim of this study was to apply a novel technology acceptance model (TAM) for virtual reality (VR) in healthcare. The secondary aim was to assess reliability of this model to evaluate factors that predict the intentions of pediatric health providers' use of VR as an anxiolytic for hospitalized pediatric patients. Materials and Methods: Healthcare providers that interacted with pediatric patients participated in a VR experience available as anxiolysis for minor procedures and then completed a survey evaluating attitudes, behaviors, and technology factors that influence adoption of new technologies. Results: Reliability for all domain measurements were good, and all confirmatory factor analysis models demonstrated good fit. Usefulness, ease of use, curiosity, and enjoyment of the VR experience all strongly predict intention to use and purchase VR technologies. Age of providers, past use, and cost of technology did not influence future purchase or use, suggesting that VR technologies may be broadly adopted in the pediatric healthcare setting. Discussion: Previous VR-TAM models in non-healthcare consumers formulated that age, past use, price willing to pay, and curiosity impacted perceived ease of use. This study established that age, past use, and cost may not influence use in healthcare. Future studies should be directed at evaluating the social influences and facilitating conditions within healthcare that play a larger influence on technology adoption. Conclusion: The VR-TAM model demonstrated validity and reliability for predicting intent to use VR in a pediatric hospital.

Evidence-based clinical practice guideline for the pharmacologic management of acute dental pain in children: A report from the American Dental Association Science and Research Institute, the University of Pittsburgh School of Dental Medicine, and the Center for Integrative Global Oral Health at the University of Pennsylvania.

BACKGROUND: A guideline panel convened by the American Dental Association Council on Scientific Affairs, American Dental Association Science and Research Institute, University of Pittsburgh School of Dental Medicine, and Center for Integrative Global Oral Health at the University of Pennsylvania conducted a systematic review and meta-analyses and formulated evidence-based recommendations for the pharmacologic management of acute dental pain after 1 or more simple and surgical tooth extractions and the temporary management of toothache (that is, when definitive dental treatment not immediately available) associated with pulp and furcation or periapical diseases in children (< 12 years). TYPES OF STUDIES REVIEWED: The authors conducted a systematic review to determine the effect of analgesics and corticosteroids in managing acute dental pain. They used the Grading of Recommendations Assessment, Development and Evaluation approach to assess the certainty of the evidence and the Grading of Recommendations Assessment, Development and Evaluation Evidence to Decision framework to formulate recommendations. RESULTS: The panel formulated 7 recommendations and 5 good practice statements across conditions. There is a small beneficial net balance favoring the use of nonsteroidal anti-inflammatory drugs alone or in combination with acetaminophen compared with not providing analgesic therapy. There is no available evidence regarding the effect of corticosteroids on acute pain after surgical tooth extractions in children. CONCLUSIONS AND PRACTICAL IMPLICATIONS: Nonopioid medications, specifically nonsteroidal anti-inflammatory drugs like ibuprofen and naproxen alone or in combination with acetaminophen, are recommended for managing acute dental pain after 1 or more tooth extractions (that is, simple and surgical) and the temporary management of toothache in children (conditional recommendation, very low certainty). According to the US Food and Drug Administration, the use of codeine and tramadol in children for managing acute pain is contraindicated.

Spatiotemporally resolved transcriptomics reveals the subcellular RNA kinetic landscape.

Spatiotemporal regulation of the cellular transcriptome is crucial for proper protein expression and cellular function. However, the intricate subcellular dynamics of RNA remain obscured due to the limitations of existing transcriptomics methods. Here, we report TEMPOmap-a method that uncovers subcellular RNA profiles across time and space at the single-cell level. TEMPOmap integrates pulse-chase metabolic labeling with highly multiplexed three-dimensional in situ sequencing to simultaneously profile the age and location of individual RNA molecules. Using TEMPOmap, we constructed the subcellular RNA kinetic landscape in various human cells from transcription and translocation to degradation. Clustering analysis of RNA kinetic parameters across single cells revealed 'kinetic gene clusters' whose expression patterns were shaped by multistep kinetic sculpting. Importantly, these kinetic gene clusters are functionally segregated, suggesting that subcellular RNA kinetics are differentially regulated in a cell-state- and cell-type-dependent manner. Spatiotemporally resolved transcriptomics provides a gateway to uncovering new spatiotemporal gene regulation principles.

Transcription factor induction of vascular blood stem cell niches in vivo.

The hematopoietic niche is a supportive microenvironment composed of distinct cell types, including specialized vascular endothelial cells that directly interact with hematopoietic stem and progenitor cells (HSPCs). The molecular factors that specify niche endothelial cells and orchestrate HSPC homeostasis remain largely unknown. Using multi-dimensional gene expression and chromatin accessibility analyses in zebrafish, we define a conserved gene expression signature and cis-regulatory landscape that are unique to sinusoidal endothelial cells in the HSPC niche. Using enhancer mutagenesis and transcription factor overexpression, we elucidate a transcriptional code that involves members of the Ets, Sox, and nuclear hormone receptor families and is sufficient to induce ectopic niche endothelial cells that associate with mesenchymal stromal cells and support the recruitment, maintenance, and division of HSPCs in vivo. These studies set forth an approach for generating synthetic HSPC niches, in vitro or in vivo, and for effective therapies to modulate the endogenous niche.

Prospective Real-Time Validation of a Lung Ultrasound Deep Learning Model in the ICU.

OBJECTIVES: To evaluate the accuracy of a bedside, real-time deployment of a deep learning (DL) model capable of distinguishing between normal (A line pattern) and abnormal (B line pattern) lung parenchyma on lung ultrasound (LUS) in critically ill patients. DESIGN: Prospective, observational study evaluating the performance of a previously trained LUS DL model. Enrolled patients received a LUS examination with simultaneous DL model predictions using a portable device. Clip-level model predictions were analyzed and compared with blinded expert review for A versus B line pattern. Four prediction thresholding approaches were applied to maximize model sensitivity and specificity at bedside. SETTING: Academic ICU. PATIENTS: One-hundred critically ill patients admitted to ICU, receiving oxygen therapy, and eligible for respiratory imaging were included. Patients who were unstable or could not undergo an LUS examination were excluded. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 100 unique ICU patients (400 clips) were enrolled from two tertiary-care sites. Fifty-six patients were mechanically ventilated. When compared with gold standard expert annotation, the real-time inference yielded an accuracy of 95%, sensitivity of 93%, and specificity of 96% for identification of the B line pattern. Varying prediction thresholds showed that real-time modification of sensitivity and specificity according to clinical priorities is possible. CONCLUSIONS: A previously validated DL classification model performs equally well in real-time at the bedside when platformed on a portable device. As the first study to test the feasibility and performance of a DL classification model for LUS in a dedicated ICU environment, our results justify further inquiry into the impact of employing real-time automation of medical imaging into the care of the critically ill.

CIViCdb 2022: evolution of an open-access cancer variant interpretation knowledgebase.

CIViC (Clinical Interpretation of Variants in Cancer; civicdb.org) is a crowd-sourced, public domain knowledgebase composed of literature-derived evidence characterizing the clinical utility of cancer variants. As clinical sequencing becomes more prevalent in cancer management, the need for cancer variant interpretation has grown beyond the capability of any single institution. CIViC contains peer-reviewed, published literature curated and expertly-moderated into structured data units (Evidence Items) that can be accessed globally and in real time, reducing barriers to clinical variant knowledge sharing. We have extended CIViC's functionality to support emergent variant interpretation guidelines, increase interoperability with other variant resources, and promote widespread dissemination of structured curated data. To support the full breadth of variant interpretation from basic to translational, including integration of somatic and germline variant knowledge and inference of drug response, we have enabled curation of three new Evidence Types (Predisposing, Oncogenic and Functional). The growing CIViC knowledgebase has over 300 contributors and distributes clinically-relevant cancer variant data currently representing >3200 variants in >470 genes from >3100 publications.

Sequencing of medical therapy in heart failure with a reduced ejection fraction.

The management of heart failure with a reduced ejection fraction is a true success story of modern medicine. Evidence from randomised clinical trials provides the basis for an extensive catalogue of disease-modifying drug treatments that improve both symptoms and survival. These treatments have undergone rigorous scrutiny by licensing and guideline development bodies to make them eligible for clinical use. With an increasing number of drug therapies however, it has become a complex management challenge to ensure patients receive these treatments in a timely fashion and at recommended doses. The tragedy is that, for a condition with many life-prolonging drug therapies, there remains a potentially avoidable mortality risk associated with delayed treatment. Heart failure therapeutic agents have conventionally been administered to patients in the chronological order they were tested in clinical trials, in line with the aggregate benefit observed when added to existing background treatment. We review the evidence for simultaneous expedited initiation of these disease-modifying drug therapies and how these strategies may focus the heart failure clinician on a time-defined smart goal of drug titration, while catering for patient individuality. We highlight the need for adequate staffing levels, especially heart failure nurse specialists and pharmacists, in a structure to provide the capacity to deliver this care. Finally, we propose a heart failure clinic titration schedule and novel practical treatment score which, if applied at each heart failure patient contact, could tackle treatment inertia by a constant assessment of attainment of optimal medical therapy.

Dysphagia Worsens With Increasing Ineffective Swallows Among Patients With Ineffective Esophageal Motility.

INTRODUCTION: Ineffective esophageal motility (IEM) is the most common motility disorder identified on esophageal high-resolution manometry (HRM), but patients with this finding may be asymptomatic. Therefore, we aimed to identify specific HRM findings predictive of symptoms in IEM. METHODS: Adult patients (≥18 y) who underwent HRM between March 2016 and July 2019 were retrospectively evaluated and reclassified according to Chicago Classification 4.0 (CC4.0). Demographic information, HRM parameters, and gastroesophageal reflux disease Health-Related Quality of Life Questionnaire responses were captured among those with normal manometry or IEM. We evaluated the association between heartburn, regurgitation, and dysphagia, with respect to HRM findings including ineffective swallows. RESULTS: Of 379 patients, 243 (64.1%) had a normal manometry, 136 (35.9%) were on IEM spectrum, and 73 (19.3%) had conclusive IEM by CC4.0. Mean dysphagia scores were significantly higher in those with conclusive IEM compared with those with normal HRM (2.00 vs. 1.36, P =0.002), as was the percentage of individuals reporting dysphagia affecting daily activities (21.9% vs. 11.4%, P =0.02). Heartburn and regurgitation symptoms did not differ between groups. In a multivariable model of IEM patients, the percentage of ineffective swallows independently predicted a higher dysphagia burden (ß regression coefficient: 0.032, P =0.04). CONCLUSIONS: Applying the CC4.0 definition for conclusive IEM identifies a group of patients with worse dysphagia symptoms. Within this group, the percentage of ineffective swallows was an independent predictor of dysphagia severity. These findings may help practitioners and patients contextualize the heterogeneous diagnosis of IEM.

Enhancing Annotation Efficiency with Machine Learning: Automated Partitioning of a Lung Ultrasound Dataset by View.

BACKGROUND: Annotating large medical imaging datasets is an arduous and expensive task, especially when the datasets in question are not organized according to deep learning goals. Here, we propose a method that exploits the hierarchical organization of annotating tasks to optimize efficiency. METHODS: We trained a machine learning model to accurately distinguish between one of two classes of lung ultrasound (LUS) views using 2908 clips from a larger dataset. Partitioning the remaining dataset by view would reduce downstream labelling efforts by enabling annotators to focus on annotating pathological features specific to each view. RESULTS: In a sample view-specific annotation task, we found that automatically partitioning a 780-clip dataset by view saved 42 min of manual annotation time and resulted in 55±6 additional relevant labels per hour. CONCLUSIONS: Automatic partitioning of a LUS dataset by view significantly increases annotator efficiency, resulting in higher throughput relevant to the annotating task at hand. The strategy described in this work can be applied to other hierarchical annotation schemes.

Accurate assessment of the lung sliding artefact on lung ultrasonography using a deep learning approach.

Pneumothorax is a potentially life-threatening condition that can be rapidly and accurately assessed via the lung sliding artefact generated using lung ultrasound (LUS). Access to LUS is challenged by user dependence and shortage of training. Image classification using deep learning methods can automate interpretation in LUS and has not been thoroughly studied for lung sliding. Using a labelled LUS dataset from 2 academic hospitals, clinical B-mode (also known as brightness or two-dimensional mode) videos featuring both presence and absence of lung sliding were transformed into motion (M) mode images. These images were subsequently used to train a deep neural network binary classifier that was evaluated using a holdout set comprising 15% of the total data. Grad-CAM explanations were examined. Our binary classifier using the EfficientNetB0 architecture was trained using 2535 LUS clips from 614 patients. When evaluated on a test set of data uninvolved in training (540 clips from 124 patients), the model performed with a sensitivity of 93.5%, specificity of 87.3% and an area under the receiver operating characteristic curve (AUC) of 0.973. Grad-CAM explanations confirmed the model's focus on relevant regions on M-mode images. Our solution accurately distinguishes between the presence and absence of lung sliding artefacts on LUS.

3D Ultrasound-Guided Photoacoustic Imaging to Monitor the Effects of Suboptimal Tyrosine Kinase Inhibitor Therapy in Pancreatic Tumors.

Pancreatic cancer is a disease with an incredibly poor survival rate. As only about 20% of patients are eligible for surgical resection, neoadjuvant treatments that can relieve symptoms and shrink tumors for surgical resection become critical. Many forms of treatments rely on increased vulnerability of cancerous cells, but tumors or regions within the tumors that may be hypoxic could be drug resistant. Particularly for neoadjuvant therapies such as the tyrosine kinase inhibitors utilized to shrink tumors, it is critical to monitor changes in vascular function and hypoxia to predict treatment efficacy. Current clinical imaging modalities used to obtain structural and functional information regarding hypoxia or oxygen saturation (StO2) do not provide sufficient depth penetration or require the use of exogenous contrast agents. Recently, ultrasound-guided photoacoustic imaging (US-PAI) has garnered significant popularity, as it can noninvasively provide multiparametric information on tumor vasculature and function without the need for contrast agents. Here, we built upon existing literature on US-PAI and demonstrate the importance of changes in StO2 values to predict treatment response, particularly tumor growth rate, when the outcomes are suboptimal. Specifically, we image xenograft mouse models of pancreatic adenocarcinoma treated with suboptimal doses of a tyrosine kinase inhibitor cabozantinib. We utilize the US-PAI data to develop a multivariate regression model that demonstrates that a therapy-induced reduction in tumor growth rate can be predicted with 100% positive predictive power and a moderate (58.33%) negative predictive power when a combination of pretreatment tumor volume and changes in StO2 values pretreatment and immediately posttreatment was employed. Overall, our study indicates that US-PAI has the potential to provide label-free surrogate imaging biomarkers that can predict tumor growth rate in suboptimal therapy.

Evaluating the Quality of Latent Tuberculosis Infection Screening in Ireland: A Single-Centre Retrospective Cohort Study.

Ireland is a country with a low incidence of tuberculosis (TB) (5.6 cases per 100,000 population in 2019) that should be aiming for TB elimination (fewer than 1 case per million of population). To achieve TB elimination in low-incidence countries, programmatic latent tuberculosis infection (LTBI) management is important. This requires high-quality latent tuberculosis infection (LTBI) screening. AIM: To assess the quality of LTBI screening in a tertiary centre in Ireland using a framework. METHODS: A retrospective review of the health care records of patients screened for TB in a tertiary centre in Ireland using an interferon-gamma release assay (IGRA) between 2016 and 2018 was performed. Three domains from the Institute of Medicine framework for health care quality, effectiveness, efficiency, and equity, were applied to measure the quality of LTBI screening. RESULTS: Forty patients had LTBI and an indication for treatment, of whom 20% (8/40) were not offered treatment by the health care provider, 2.5% (1/40) did not accept treatment, and 10% (4/40) did not complete treatment. Seventy-five percent (6/8) of patients not offered treatment were non-Irish. The cost of screening per LTBI case identified was EUR 2048. CONCLUSIONS: This study evaluated the quality of LTBI screening using a framework and identified that LTBI screening in this tertiary centre needs to be scaled and expanded, and that treatment initiation needs to be improved, particularly among non-Irish nationals.

Mechanical phenotyping reveals unique biomechanical responses in retinoic acid-resistant acute promyelocytic leukemia.

All-trans retinoic acid (ATRA) is an essential therapy in the treatment of acute promyelocytic leukemia (APL), but nearly 20% of patients with APL are resistant to ATRA. As there are no biomarkers for ATRA resistance that yet exist, we investigated whether cell mechanics could be associated with this pathological phenotype. Using mechano-node-pore sensing, a single-cell mechanical phenotyping platform, and patient-derived APL cell lines, we discovered that ATRA-resistant APL cells are less mechanically pliable. By investigating how different subcellular components of APL cells contribute to whole-cell mechanical phenotype, we determined that nuclear mechanics strongly influence an APL cell's mechanical response. Moreover, decondensing chromatin with trichostatin A is especially effective in softening ATRA-resistant APL cells. RNA-seq allowed us to compare the transcriptomic differences between ATRA-resistant and ATRA-responsive APL cells and highlighted gene expression changes that could be associated with mechanical changes. Overall, we have demonstrated the potential of "physical" biomarkers in identifying APL resistance.

Node-Pore Sensing for Characterizing Cells and Extracellular Vesicles.

Node-Pore Sensing, NPS, is an extremely versatile and powerful technique for the analysis of cells and the detection of extracellular vesicles (EVs). NPS involves measuring the modulated current pulse caused by a cell transiting a microfluidic channel that has been segmented by a series of inserted nodes. As the current pulse reflects the number of nodes and segments of the channel, NPS can achieve exquisite sensitivity. Thus, when used as a Coulter counter, NPS can measure the sub-micron size increase of antibody-coated colloids to which EVs are specifically bound. By simply inserting between two nodes a "contraction" channel through which cells can squeeze, one can mechanically phenotype cells. We discuss the details of performing these two NPS applications.

Dilated cardiomyopathy: the role of genetics, highlighted in a family with Filamin C (FLNC) variant.

Dilated cardiomyopathy (DCM) is a heterogenous group of disorders characterised by left ventricular dilatation and dysfunction, in the absence of factors affecting loading conditions such as hypertension or valvular disease, or significant coronary artery disease. The prevalence of idiopathic DCM is estimated between 1:250 and 1:500 individuals. Determining the aetiology of DCM can be challenging, particularly when evaluating an individual and index case with no classical history or investigations pointing towards an obvious acquired cause, or no clinical clues in the family history to suggest a genetic cause. We present a family affected by DCM associated with Filamin C variant, causing sudden cardiac death at a young age and heart failure due to severe left ventricular impairment and myocardial scarring. We review the diagnosis and treatment of DCM, its genetic associations and potential acquired causes. Thorough assessment is mandatory to risk stratify and identify patients who may benefit from primary prevention implantable cardioverter defibrillator therapy according to international guidelines. Genetic testing has some limitations, and is positive in only 20%-35% of DCM, but should be considered in specific cases to identify families who may benefit from cascade screening after appropriate counselling. The management of often complex familial cardiomyopathy requires specialist input for every case, and the appropriate infrastructure to coordinate investigations.

High Rates of Mortality in Geriatric Patients Admitted for Inflammatory Bowel Disease Management.

GOAL: The goal of this study was to evaluate the inpatient mortality risk among geriatric patients with inflammatory bowel disease (IBD). BACKGROUND: The challenges of caring for elderly patients with IBD will increase with the aging of the US population. Given the complications of hospitalization, we set to examine if elderly patients age older than 65 were at higher risk of mortality. MATERIALS AND METHODS: All patients with ulcerative colitis (UC) or Crohn's disease (CD) in the National Inpatient Sample (NIS) from 2016 and 2017 as the primary diagnosis or secondary diagnosis with an IBD-related cause of admission were included. Outcomes for patients aged above 65 were compared with below 65 using multivariable survey-adjusted regression. CD and UC were analyzed separately. RESULTS: In 2016-2017, there were an estimated 162,800 admissions for CD and related complications compared with 96,450 for UC. In total, 30% of UC and 20% of CD admissions were geriatric. Geriatric status was associated with higher odds of mortality for CD [odds ratio (OR)=3.47, 95% confidence interval (CI): 2.72-4.44] and UC (OR=2.75, 95% CI: 2.16-3.49) after adjustment for comorbidities, admission type, hospital type, inpatient surgery, and IBD subtype. The cause of death was ∼80% infectious in both CD and UC in all groups. An average of 0.19 days (95% CI: 0.05-0.34) and $2467 (95% CI: 545-4388) increase was seen for geriatric CD patients. No significant change was seen for UC. CONCLUSIONS: Age over 65 was independently associated with higher odds of death in both UC and CD patients, even after appropriate adjustment. Further research is needed to optimize care for this growing patient population.