Seasonal Testing, Results, and Effect of the Pandemic on Coxsackievirus Serum Studies.

Coxsackieviruses (CVs) are common causes of infections and can be life-threatening. Unfortunately, rigorous studies guiding the clinician in interpreting CV serum antibody titer testing is lacking. To explore the epidemiology of circulating CVs and the serological test utility in aiding diagnosis of CV infections in our community, we obtained results of CV immunologic diagnostic tests between 2018 and 2022 from a regional healthcare database. For CV type A, rare individuals had positive CF (complement fixation) tests whereas all 16 individuals with IFA testing showed at least one positive serotype. For CV type B CF testing, 52.2% of 222 patients had at least one serotype positive, with B5 being most common and also the most common with higher titers (14.8% with ≥1:32). We found a significant reduction in seropositivity rate during the pandemic in 2020 compared to 2018, which continued through 2022 (OR: 0.2, 95% CI: 0.08-0.49, p-value < 0.001). During the pandemic, the seasonal pattern of positive tests varied from the pre-pandemic pattern. Testing for CVs was increased after the first year of the pandemic. Overall, the variability by month and seasonal change in our data support that CF testing can be used to identify recent CVB infection.

Fall risk classification with posturographic parameters in community-dwelling older adults: a machine learning and explainable artificial intelligence approach.

BACKGROUND: Computerized posturography obtained in standing conditions has been applied to classify fall risk for older adults or disease groups. Combining machine learning (ML) approaches is superior to traditional regression analysis for its ability to handle complex data regarding its characteristics of being high-dimensional, non-linear, and highly correlated. The study goal was to use ML algorithms to classify fall risks in community-dwelling older adults with the aid of an explainable artificial intelligence (XAI) approach to increase interpretability. METHODS: A total of 215 participants were included for analysis. The input information included personal metrics and posturographic parameters obtained from a tracker-based posturography of four standing postures. Two classification criteria were used: with a previous history of falls and the timed-up-and-go (TUG) test. We used three meta-heuristic methods for feature selection to handle the large numbers of parameters and improve efficacy, and the SHapley Additive exPlanations (SHAP) method was used to display the weights of the selected features on the model. RESULTS: The results showed that posturographic parameters could classify the participants with TUG scores higher or lower than 10 s but were less effective in classifying fall risk according to previous fall history. Feature selections improved the accuracy with the TUG as the classification label, and the Slime Mould Algorithm had the best performance (accuracy: 0.72 to 0.77, area under the curve: 0.80 to 0.90). In contrast, feature selection did not improve the model performance significantly with the previous fall history as a classification label. The SHAP values also helped to display the importance of different features in the model. CONCLUSION: Posturographic parameters in standing can be used to classify fall risks with high accuracy based on the TUG scores in community-dwelling older adults. Using feature selection improves the model's performance. The results highlight the potential utility of ML algorithms and XAI to provide guidance for developing more robust and accurate fall classification models. Trial registration Not applicable.

Application of biomaterials and nanotechnology in corneal tissue engineering.

Corneal diseases are among the most common causes of blindness worldwide. Regardless of the etiology, corneal opacity- or globe integrity-threatening conditions may necessitate corneal replacement procedures. Several procedure types are currently available to address these issues, based on the complexity and extent of injury. Corneal allograft or keratoplasty is considered to be first-line treatment in many cases. However, a significant proportion of the world's population are reported to have no access to this option due to limitations in donor preparation. Thus, providing an appropriate, safe, and efficient synthetic implant (e.g., artificial cornea) may revolutionize this field. Nanotechnology, with its potential applications, has garnered a lot of recent attention in this area, however, there is seemingly a long way to go. This narrative review provides a brief overview of the therapeutic interventions for corneal pathologies, followed by a summary of current biomaterials used in corneal regeneration and a discussion of the nanotechnologies that can aid in the production of superior implants.

Monitoring trends in lacrimator exposures using the National Poison Data System: 2000-2021.

CONTEXT: Lacrimators are used by individuals for personal defense and by police for crowd control during periods of civil unrest. Increased public awareness about their use has raised concerns about their application and safety. OBJECTIVE: To characterize patterns of lacrimator exposures in the United States, we describe temporal trends of calls to poison centers by demographics, substances, medical outcomes, exposure sites, and scenarios. METHODS: A retrospective data analysis was performed for all single-substance lacrimator exposures in the United States reported to the National Poison Data System between 2000 and 2021. Descriptive analyses were performed to examine demographic characteristics, geographic distribution, product types and medical outcomes associated with lacrimator exposures. RESULTS: A total of 107,149 lacrimator exposure calls were identified. There was an overall decrease in calls per year, from 6,521 calls in 2000 to 2,520 in 2020, followed by an increase to 3,311 calls in 2021. A declining trend was observed independent of total poison center call volume. Oleoresin capsicum was the most commonly reported substance (81,990, 76.5%). Individuals ages 19 years and younger accounted for 62% of calls, but adults ages 20 and over were more likely to develop major clinical effects (odds ratio 3.03; 95% confidence interval 1.91-4.81; P < 0.0001). The most common exposure site was "own residence," followed by schools. School exposures accounted for 15.8% of exposures in children ages 6-12 years and 37.7% in adolescents. Among calls with documented scenarios, 19.7% involved unintentional exposures due to children accessing lacrimators. CONCLUSION: Lacrimator exposure calls to United States poison centers decreased from 2000 to 2021. Most calls pertain to oleoresin capsicum and individuals ages 19 and younger. Improper storage allowing children to have access to these chemicals, is a common scenario. Public safety interventions such as education about safe storage and use of lacrimators, improved product design, or regulatory changes may prevent unintentional exposures.

Decreased Clinical Severity of Pediatric Acute COVID-19 and MIS-C and Increase of Incidental Cases during the Omicron Wave in Comparison to the Delta Wave.

This study describes differences in clinical presentation in hospitalized children with acute COVID-19 and MIS-C between the Delta and Omicron (BA.1.1) waves in a tertiary children's hospital. This retrospective cohort study with case adjudication of hospitalized children with SARS-CoV-2-positive testing or MIS-C diagnosis occurred during the Delta and Omicron waves, from August 2021 until February 2022. There were no differences noted by race, but both waves disproportionally affected black children (24% and 25%). Assigned by a three-person expert panel, incidental diagnoses were higher in the Omicron wave (34% versus 19%). Hospitalization rates of non-incidental cases were higher during Omicron (3.8 versus 5.9 per 1000 PCR-positive community cases). Respiratory-related admissions were prominent during Delta, while Omicron clinical presentations varied, including a high number of cases of croup and seizures. Length of stay and ICU use during Omicron was significantly less than Delta for MIS-C and acute cases. Estimation of vaccination efficacy for preventing hospital admissions was 85.1-91.7% in the early Omicron period. Our estimates suggest that a protective role for vaccination continues into the Omicron wave. The high rate of incidental cases during the Omicron wave should be considered when reviewing more cursory summative data sets. This study emphasizes the need for continued clinical suspicion of COVID-19 even when lower respiratory symptoms are not dominant.

Applications of mesenchymal stem cells in ocular surface diseases: sources and routes of delivery.

INTRODUCTION: Mesenchymal stem cells (MSCs) are novel, promising agents for treating ocular surface disorders. MSCs can be isolated from several tissues and delivered by local or systemic routes. They produce several trophic factors and cytokines, which affect immunomodulatory, transdifferentiating, angiogenic, and pro-survival pathways in their local microenvironment via paracrine secretion. Moreover, they exert their therapeutic effect through a contact-dependent manner. AREAS COVERED: In this review, we discuss the characteristics, sources, delivery methods, and applications of MSCs in ocular surface disorders. We also explore the potential application of MSCs to inhibit senescence at the ocular surface. EXPERT OPINION: Therapeutic application of MSCs in ocular surface disorders are currently under investigation. One major research area is corneal epitheliopathies, including chemical or thermal burns, limbal stem cell deficiency, neurotrophic keratopathy, and infectious keratitis. MSCs can promote corneal epithelial repair and prevent visually devastating sequelae of non-healing wounds. However, the optimal dosages and delivery routes have yet to be determined and further clinical trials are needed to address these fundamental questions.

Morbidity and Mortality of Unintentional Carbon Monoxide Poisoning: United States 2005 to 2018.

STUDY OBJECTIVE: Centers for Disease Control and Prevention conducts case surveillance through the National Notifiable Diseases Surveillance System (NNDSS). This study aimed to provide surveillance report of unintentional carbon monoxide poisoning across multiple data sources to provide baseline data for the new NNDSS carbon monoxide poisoning surveillance. METHODS: For the period 2005 to 2018, we used 4 data sources to describe unintentional carbon monoxide poisoning: exposures reported by poison centers, emergency department (ED) visits, hospitalizations, and deaths. We conducted descriptive analyses by the cause of exposure (fire, nonfire, or unknown), age, sex, season, and US census region. Additional analyses were conducted using poison center exposure case data focusing on the reported signs and symptoms, management site, and medical outcome. RESULTS: Annually, we observed 39.5 poison center exposure calls (per 1 million, nationally), 56.5 ED visits (per 1 million, across 17 states), 7.3 hospitalizations (per 1 million, in 26 states), and 3.3 deaths (per 1 million, nationally) due to unintentional carbon monoxide poisoning. For 2005 to 2018, there was a decrease in the crude rate for non-fire-related carbon monoxide poisonings from hospital, and death data. Non-fire-related cases comprised 74.0% of ED visits data, 60.1% of hospitalizations, and 40.9% of deaths compared with other unintentional causes. Across all data sources, unintentional carbon monoxide poisonings were most often reported during the winter season, notably in January and December. Children aged 0 to 9 years had the highest reported rates in poison center exposure case data and ED visits (54.1 and 70.5 per 1 million, respectively); adults older than 80 years had the highest rates of hospitalization and deaths (20.2 and 9.9 per 1 million, respectively); and deaths occurred more often among men and in the Midwest region. Poison center exposure call data revealed that 45.9% of persons were treated at a health care facility. Headaches, nausea, and dizziness/vertigo were the most reported symptoms. CONCLUSION: The crude rates in non-fire-related carbon monoxide poisonings from hospitalizations, and mortality significantly decreased over the study period (ie, 2005 to 2018). This surveillance report provides trends and characteristics of unintentional carbon monoxide poisoning and the baseline morbidities and mortality data for the Centers for Disease Control and Prevention national surveillance system of carbon monoxide poisoning.

Predicting Intravenous Immunoglobulin Resistance Among North American Children Hospitalized With Kawasaki Disease.

OBJECTIVE: The Kobayashi score (KS) is the most widely used tool for predicting intravenous immunoglobulin (IVIG) resistance in Kawasaki disease (KD). The KS has shown good sensitivity (86%) and specificity (68%) in Japanese children; however, its use is limited outside of Japan. No models accurately predict IVIG resistance of children with KD in the United States. We sought to develop and test a novel scoring system to predict IVIG resistance in hospitalized children with KD. METHODS: A retrospective chart review was conducted of all children diagnosed with KD from January 2000 to December 2015. Subjects were divided into 2 groups: IVIG susceptible or resistant. Variables that differed between the groups were identified and used to create a "new score" to predict resistance to IVIG. The new score was then compared with the KS and performance characteristics were determined. RESULTS: A total of 208 subjects were reviewed. White blood cell count, neutrophil percentage, age, and serum albumin were used in the new score with equal weighting. Overall, the new score achieved improved sensitivity (54% vs 26%) and similar specificity (69% vs 74%) compared with the KS in predicting IVIG resistance in hospitalized children diagnosed with KD. CONCLUSIONS: Predicting IVIG resistance in children diagnosed with KD remains challenging. The KS has low sensitivity in predicting IVIG resistance in children with KD in the United States. The new score resulted in improved sensitivity, but many children with true IVIG resistance may be missed. Further research is needed to improve IVIG resistance prediction.

Humoral cross-coronavirus responses against the S2 region in children with Kawasaki disease.

Multisystem Inflammatory Syndrome in Children (MIS-C), a post infectious complication of SARS CoV-2 infection, shares enough features with Kawasaki Disease (KD) that some have hypothesized cross-coronavirus (CoV) immunity may explain the shared pathology. Recent studies have shown that humoral cross-reactivity of the CoVs, particularly of OC43, is focused on the S2 region of the Spike protein. Due to efforts utilizing CoV S2 regions to produce a cross-CoV vaccine, we wished to assess SARS-CoV-2 S2 reactivity in children with KD and assess if cardiac involvement in KD correlated with S2 CoV antibody targeting. The presence of cross-reactivity does not distinguish KD from febrile controls and does not correlate with cardiac involvement in KD. These findings support that, in relation to cardiac vascular inflammation, vaccines targeting the S2 region appear to be a safe approach, but there is disparity in the ability of CoV species to raise cross-reactive S2 targeted antibodies.

Robust humoral immune response after boosting in children with Multisystem Inflammatory Syndrome in Children.

The exact pathogenesis of Multisystem Inflammatory Syndrome in Children (MIS-C) is unknown. Reports on response to vaccination in children who had MIS-C are lacking. Using prospectively enrolled children, we report on humoral immune responses prior to and after SARS-CoV-2 immune rechallenge. Recurrent auricular chondritis was also noted in one child.

VCNet: Hybrid Deep Learning Model for Detection and Classification of Lung Carcinoma Using Chest Radiographs.

Detection of malignant lung nodules from Computed Tomography (CT) images is a significant task for radiologists. But, it is time-consuming in nature. Despite numerous breakthroughs in studies on the application of deep learning models for the identification of lung cancer, researchers and doctors still face challenges when trying to deploy the model in clinical settings to achieve improved accuracy and sensitivity on huge datasets. In most situations, deep convolutional neural networks are used for detecting the region of the main nodule of the lung exclusive of considering the neighboring tissues of the nodule. Although the accuracy achieved through CNN is good enough but this models performance degrades when there are variations in image characteristics like: rotation, tiling, and other abnormal image orientations. CNN does not store relative spatial relationships among features in scanned images. As CT scans have high spatial resolution and are sensitive to misalignments during the scanning process, there is a requirement of a technique which helps in considering spatial information of image features also. In this paper, a hybrid model named VCNet is proposed by combining the features of VGG-16 and capsule network (CapsNet). VGG-16 model is used for object recognition and classification. CapsNet is used to address the shortcomings of convolutional neural networks for image rotation, tiling, and other abnormal image orientations. The performance of VCNeT is verified on the Lung Image Database Consortium (LIDC) image collection dataset. It achieves higher testing accuracy of 99.49% which is significantly better than MobileNet, Xception, and VGG-16 that has achieved an accuracy of 98, 97.97, and 96.95%, respectively. Therefore, the proposed hybrid VCNet framework can be used for the clinical purpose for nodule detection in lung carcinoma detection.

A Survey on Machine Learning and Internet of Medical Things-Based Approaches for Handling COVID-19: Meta-Analysis.

Early diagnosis, prioritization, screening, clustering, and tracking of patients with COVID-19, and production of drugs and vaccines are some of the applications that have made it necessary to use a new style of technology to involve, manage, and deal with this epidemic. Strategies backed by artificial intelligence (A.I.) and the Internet of Things (IoT) have been undeniably effective to understand how the virus works and prevent it from spreading. Accordingly, the main aim of this survey is to critically review the ML, IoT, and the integration of IoT and ML-based techniques in the applications related to COVID-19, from the diagnosis of the disease to the prediction of its outbreak. According to the main findings, IoT provided a prompt and efficient approach to tracking the disease spread. On the other hand, most of the studies developed by ML-based techniques aimed at the detection and handling of challenges associated with the COVID-19 pandemic. Among different approaches, Convolutional Neural Network (CNN), Support Vector Machine, Genetic CNN, and pre-trained CNN, followed by ResNet have demonstrated the best performances compared to other methods.

Clonal expansion and markers of directed mutation of IGHV4-34 B cells in plasmablasts during Kawasaki disease.

Kawasaki disease (KD) is the leading cause of acquired heart disease in children. The cause remains unknown; however, epidemiologic and demographic data support a single preceding infectious agent may lead to KD. A variety of pathophysiologic responses have been proposed, including direct invasion of the coronary arteries, a superantigen response, and a post-infectious autoimmune phenomenon. A role for B cell responses during KD are supported by numerous findings including B cell specific markers identified in genome wide association studies. We have recently published data showing children with KD have similar plasmablast (PB) responses to children with infections. Since during other infections, cells expressing antibodies against the preceding infection are enriched in PBs, we sought to explore the specific antibodies encoded by PBs during KD. In one child we see a massive expansion in IGHV4-34 utilizing antibodies, which has been associated with autoimmunity in the past. We further explored this expansion of IGHV4-34 utilization during the peripheral PB rise with next generation sequencing (NGS) analysis and utilizing newer techniques of chromium chip single cell separation (10x Genomics®). We also utilized peptide array screening to attempt to identify an antigen to the most prolific clones.

Adherence to Urgent Eye Visits during the COVID-19 Pandemic: A Population Characteristics Study.

PURPOSE: To explore individual and community factors associated with adherence to physician recommended urgent eye visits via a tele-triage system during the COVID-19 pandemic. METHOD: We retrospectively reviewed acute visit requests and medical exam data between April 6, 2020 and June 6, 2020. Patient demographics and adherence to visit were examined. Census tract level community characteristics from the U.S. Census Bureau and zip code level COVID-19 related death data from the Cook County Medical Examiner's Office were appended to each geocoded patient address. Descriptive statistics, t-tests, and logistic regression analyses were performed to explore the effects of individual and community variables on adherence to visit. RESULTS: Of 229 patients recommended an urgent visit, 216 had matching criteria on chart review, and 192 (88.9%) adhered to their visit. No difference in adherence was found based on individual characteristics including: age (p = .24), gender (p = .94), race (p = .56), insurance (p = .28), nor new versus established patient status (p = .20). However, individuals who did not adhere were more likely to reside in neighborhoods with a greater proportion of Blacks (59.4% vs. 33.4%; p = .03), greater unemployment rates (17.5% vs. 10.7%; p < .01), and greater cumulative deaths from COVID-19 (56 vs. 31; p = .01). Unemployment rate continued to be statistically significant after controlling for race and cumulative deaths from COVID-19 (p = .04). CONCLUSION: We found that as community unemployment rate increases, adherence to urgent eye visits decreases, after controlling for relevant neighborhood characteristics. Unemployment rates were highest in predominantly Black neighborhoods early in the pandemic, which may have contributed to existing racial disparities in eye care.

Assessment of a novel ophthalmology tele-triage system during the COVID-19 pandemic.

BACKGROUND: In response to the COVID-19 pandemic, a web-based tele-triage system was created to prioritize in-person clinic visits and ensure safety at the University of Illinois at Chicago Department of Ophthalmology and Visual Sciences during a statewide shelter-in-place order. The aim of this study is to evaluate the impact of the tele-triage system on urgent visit volume and explore the characteristics of acute visit requests at a tertiary referral eye center. METHODS: This retrospective study analyzed acute visit requests between April 6, 2020 and June 6, 2020. Descriptive statistics, chi-square tests, ANOVA, and bivariate logistic regression were used to compare variables with a p-value of 0.05. RESULTS: Three hundred fifty-eight surveys were completed. Mean age was 49.7 ± 18.8 years (range 2-91). The majority of requests were determined as urgent (63.0%) or emergent (0.8%). Forty-nine patients had recent eye trauma (13.7%), and the most common reported symptoms were new onset eye pain (25.7%) and photophobia (22.9%). Most patients were self-referred (63.7%), though provider referral was more common in patients with symptoms of new onset lid swelling (p < 0.01), diplopia (p < 0.01), flashing lights (p = 0.02), or droopy eyelid (p < 0.01). Patients presenting with symptom onset within 48 h tended to be younger (45.8 years) versus those with symptom duration of 48 h to 1 week (49.6 years), or more than 1 week (52.6 years; p < 0.01). CONCLUSION: This novel tele-triage system screened out one-third of acute visit requests as non-urgent, which limited in-person visits during the initial shelter-in-place period of the pandemic. Tele-triage systems should be implemented in eye care practices for future emergency preparedness.

COVID-19 associated Multisystem Inflammatory Syndrome in Children (MIS-C) guidelines; revisiting the Western New York approach as the pandemic evolves.

Multisystem inflammatory syndrome of children (MIS-C) continues to be a highly concerning diagnosis in those recently infected with SARS-CoV-2. The diagnosis of MIS-C cases will likely become even more challenging as vaccine uptake and natural immunity in previously infected persons leads to lower circulating rates of SARS-CoV-2 infection and will make cases sporadic. Febrile children presenting with cardiac dysfunction, symptoms overlapping Kawasaki disease or significant gastrointestinal complaints warrant a thorough screen in emergency departments, urgent care centers, and outpatient pediatric or family medicine practices. An increased index of suspicion and discussion regarding higher level of care (transferring to pediatric tertiary care centers or to intensive care) continues to be recommended. Herein we outline a broad approach with a multidisciplinary team for those meeting the case definition and believe such an approach is crucial for successful outcomes.

Coronavirus Disease 2019 in a Premature Infant: Vertical Transmission and Antibody Response or Lack Thereof.

With the global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, several reports highlight its effects on pregnant women. Based on scant available data, vertical transmission is considered unlikely. We present here a preterm neonate born to a critically ill mother with SARV-CoV-2 with early evidence of infection with a positive reverse transcription polymerase chain reaction on day 1. Lack of parental contact prior to testing and strict adherence to recommended airborne precautions perinatally suggest vertical transmission of infection. Critical maternal illness and medications may have contributed to the need for extensive resuscitation at birth and highlight the importance of close fetal monitoring. Infant lacked immunoglobulin G antibody response by 3 weeks, presumably secondary to mild clinical course and prematurity. Effects of SARS-CoV-2 in preterm infants, their antibody response and potential for asymptomatic carriage remain uncertain.

Serum Responses of Children With Kawasaki Disease Against Severe Acute Respiratory Syndrome Coronavirus 2 Proteins.

With recent reports showing clinical and laboratory overlap of multisystem inflammatory syndrome in children and Kawasaki disease (KD), we addressed the hypothesis that cross coronavirus humoral immunity leads to a parallel postinfectious phenomenon explaining similar pathologic findings in KD and multisystem inflammatory syndrome in children. We demonstrated no cross-reactivity in children with KD but observed some nonspecific interactions postintravenous immunoglobulin infusion.

Serious Adverse Health Events, Including Death, Associated with Ingesting Alcohol-Based Hand Sanitizers Containing Methanol - Arizona and New Mexico, May-June 2020.

Alcohol-based hand sanitizer is a liquid, gel, or foam that contains ethanol or isopropanol used to disinfect hands. Hand hygiene is an important component of the U.S. response to the emergence of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). If soap and water are not readily available, CDC recommends the use of alcohol-based hand sanitizer products that contain at least 60% ethyl alcohol (ethanol) or 70% isopropyl alcohol (isopropanol) in community settings (1); in health care settings, CDC recommendations specify that alcohol-based hand sanitizer products should contain 60%-95% alcohol (≥60% ethanol or ≥70% isopropanol) (2). According to the Food and Drug Administration (FDA), which regulates alcohol-based hand sanitizers as an over-the-counter drug, methanol (methyl alcohol) is not an acceptable ingredient. Cases of ethanol toxicity following ingestion of alcohol-based hand sanitizer products have been reported in persons with alcohol use disorder (3,4). On June 30, 2020, CDC received notification from public health partners in Arizona and New Mexico of cases of methanol poisoning associated with ingestion of alcohol-based hand sanitizers. The case reports followed an FDA consumer alert issued on June 19, 2020, warning about specific hand sanitizers that contain methanol. Whereas early clinical effects of methanol and ethanol poisoning are similar (e.g., headache, blurred vision, nausea, vomiting, abdominal pain, loss of coordination, and decreased level of consciousness), persons with methanol poisoning might develop severe anion-gap metabolic acidosis, seizures, and blindness. If left untreated methanol poisoning can be fatal (5). Survivors of methanol poisoning might have permanent visual impairment, including complete vision loss; data suggest that vision loss results from the direct toxic effect of formate, a toxic anion metabolite of methanol, on the optic nerve (6). CDC and state partners established a case definition of alcohol-based hand sanitizer-associated methanol poisoning and reviewed 62 poison center call records from May 1 through June 30, 2020, to characterize reported cases. Medical records were reviewed to abstract details missing from poison center call records. During this period, 15 adult patients met the case definition, including persons who were American Indian/Alaska Native (AI/AN). All had ingested an alcohol-based hand sanitizer and were subsequently admitted to a hospital. Four patients died and three were discharged with vision impairment. Persons should never ingest alcohol-based hand sanitizer, avoid use of specific imported products found to contain methanol, and continue to monitor FDA guidance (7). Clinicians should maintain a high index of suspicion for methanol poisoning when evaluating adult or pediatric patients with reported swallowing of an alcohol-based hand sanitizer product or with symptoms, signs, and laboratory findings (e.g., elevated anion-gap metabolic acidosis) compatible with methanol poisoning. Treatment of methanol poisoning includes supportive care, correction of acidosis, administration of an alcohol dehydrogenase inhibitor (e.g., fomepizole), and frequently, hemodialysis.