Risks of peri- and postoperative complications with glucagon-like peptide-1 receptor agonists.

AIM: To assess whether adults with diabetes on oral hypoglycaemic agents undergoing general endotracheal anaesthesia during nine common surgical procedures who are glucagon-like peptide-1 receptor agonist (GLP1-RA) users, compared with non-users, are at increased risk of six peri- and post-procedure complications. MATERIALS AND METHODS: A retrospective observational cohort analysis of over 130 million deidentified US adults with diabetes (defined as being on oral hypoglycaemic agents) from a nationally representative electronic health dataset between 1 January 2015 and 1 April 2023 was analysed. Cohorts were matched by high-dimensionality propensity scoring. We compared the odds of six peri- and postoperative complications in GLP1-RA users and non-users. A sensitivity analysis compared these odds in GLP1-RA users to non-users with diabetes and obesity. We measured the odds of (a) a composite outcome of postoperative decelerated gastric emptying, including antiemetic use, ileus within 7 days post-procedure, gastroparesis diagnosis, gastric emptying study; (b) postoperative aspiration or pneumonitis; (c) severe respiratory failure; (d) postoperative hypoglycaemia; (e) inpatient mortality; and (f) 30-day mortality. RESULTS: Among 13 361 adults with diabetes, 16.5% were treated with a GLP1-RA. In the high-dimensionality propensity score-matched cohort, GLP1-RA users had a lower risk of peri- and postoperative complications for decelerated gastric emptying and antiemetic use compared with non-users. The risk of ileus within 7 days, aspiration/pneumonitis, hypoglycaemia and 30-day mortality were not different. A sensitivity analysis showed similar findings in patients with diabetes and obesity. CONCLUSION: No increased risk of peri- and postoperative complications in GLP1-RA users undergoing surgery with general endotracheal anaesthesia was identified.

Antipsychotic medications associated with increased length of hospital stay in autoimmune encephalitis and multiple sclerosis: A retrospective study.

BACKGROUND: Antipsychotic medications (APMs) and selective serotonin reuptake inhibitors (SSRIs) are frequently utilized in patients with neuroinflammatory disorders, such as autoimmune encephalitis and multiple sclerosis (MS). This retrospective study investigates how in-hospital treatment with APMs and SSRIs in patients with these neuroinflammatory diseases are associated with differences in hospital length-of-stay (LOS) and mortality. METHODS: We evaluated all the inpatients in the Stanford University Hospital from 2008 to 2023 diagnosed with either non-infectious encephalitis or MS and subdivided them into those who did or did not receive APMs or SSRIs while hospitalized. We then analyzed whether hospital LOS and mortality differed with these medications. RESULTS: Among inpatients with non-infectious encephalitis (n = 114), those who were exposed to APMs had a significantly increased mean LOS (11.8 vs 20.9 days, p < 0.01). For inpatients with MS (n = 1095), treatment with an APM was associated with a significant increase in mean LOS (2.8 vs. 7.1, p < 0.00001). When comparing typical to atypical APMs given to subjects with MS, those who received atypical APMs showed a significant increase in LOS (4.3 vs 10.5, p < 0.01), although typical APMs showed significantly increased risk of mortality (p < 0.05). For inpatients with MS and SSRI use, there was a significant increase in mean hospital LOS (3.5 vs 5.3, p < 0.01), with a significant difference found in those who received fluoxetine or citalopram, but not sertraline or escitalopram. Finally, several healthcare disparities were found, including that Black patients were more likely to receive APMs, and those with MS were more likely to receive typical rather than atypical APMs. Conversely, Black patients with MS were less likely to receive SSRI treatment. CONCLUSIONS: There was a statistically significant increase in LOS associated with APM use in non-infectious encephalitis and MS, as well as with SSRI use in MS. These data reflect the importance of these medications in these neuroinflammatory disorders and suggest that further investigation into their risks and benefits would be warranted.

A widely distributed gene cluster compensates for uricase loss in hominids.

Approximately 15% of US adults have circulating levels of uric acid above its solubility limit, which is causally linked to the disease gout. In most mammals, uric acid elimination is facilitated by the enzyme uricase. However, human uricase is a pseudogene, having been inactivated early in hominid evolution. Though it has long been known that uric acid is eliminated in the gut, the role of the gut microbiota in hyperuricemia has not been studied. Here, we identify a widely distributed bacterial gene cluster that encodes a pathway for uric acid degradation. Stable isotope tracing demonstrates that gut bacteria metabolize uric acid to xanthine or short chain fatty acids. Ablation of the microbiota in uricase-deficient mice causes severe hyperuricemia, and anaerobe-targeted antibiotics increase the risk of gout in humans. These data reveal a role for the gut microbiota in uric acid excretion and highlight the potential for microbiome-targeted therapeutics in hyperuricemia.

Initial development and testing of an exhaled microRNA detection strategy for lung cancer case-control discrimination.

For detecting field carcinogenesis non-invasively, early technical development and case-control testing of exhaled breath condensate microRNAs was performed. In design, human lung tissue microRNA-seq discovery was reconciled with TCGA and published tumor-discriminant microRNAs, yielding a panel of 24 upregulated microRNAs. The airway origin of exhaled microRNAs was topographically "fingerprinted", using paired EBC, upper and lower airway donor sample sets. A clinic-based case-control study (166 NSCLC cases, 185 controls) was interrogated with the microRNA panel by qualitative RT-PCR. Data were analyzed by logistic regression (LR), and by random-forest (RF) models. Feasibility testing of exhaled microRNA detection, including optimized whole EBC extraction, and RT and qualitative PCR method evaluation, was performed. For sensitivity in this low template setting, intercalating dye-based URT-PCR was superior to fluorescent probe-based PCR (TaqMan). In application, adjusted logistic regression models identified exhaled miR-21, 33b, 212 as overall case-control discriminant. RF analysis of combined clinical + microRNA models showed modest added discrimination capacity (1.1-2.5%) beyond clinical models alone: all subjects 1.1% (p = 8.7e-04)); former smokers 2.5% (p = 3.6e-05); early stage 1.2% (p = 9.0e-03), yielding combined ROC AUC ranging from 0.74 to 0.83. We conclude that exhaled microRNAs are qualitatively measureable, reflect in part lower airway signatures; and when further refined/quantitated, can potentially help to improve lung cancer risk assessment.

Predicting lymph node metastasis from primary tumor histology and clinicopathologic factors in colorectal cancer using deep learning.

BACKGROUND: Presence of lymph node metastasis (LNM) influences prognosis and clinical decision-making in colorectal cancer. However, detection of LNM is variable and depends on a number of external factors. Deep learning has shown success in computational pathology, but has struggled to boost performance when combined with known predictors. METHODS: Machine-learned features are created by clustering deep learning embeddings of small patches of tumor in colorectal cancer via k-means, and then selecting the top clusters that add predictive value to a logistic regression model when combined with known baseline clinicopathological variables. We then analyze performance of logistic regression models trained with and without these machine-learned features in combination with the baseline variables. RESULTS: The machine-learned extracted features provide independent signal for the presence of LNM (AUROC: 0.638, 95% CI: [0.590, 0.683]). Furthermore, the machine-learned features add predictive value to the set of 6 clinicopathologic variables in an external validation set (likelihood ratio test, p < 0.00032; AUROC: 0.740, 95% CI: [0.701, 0.780]). A model incorporating these features can also further risk-stratify patients with and without identified metastasis (p < 0.001 for both stage II and stage III). CONCLUSION: This work demonstrates an effective approach to combine deep learning with established clinicopathologic factors in order to identify independently informative features associated with LNM. Further work building on these specific results may have important impact in prognostication and therapeutic decision making for LNM. Additionally, this general computational approach may prove useful in other contexts.

When colorectal cancers spread to the lymph nodes, it can indicate a poorer prognosis. However, detecting lymph node metastasis (spread) can be difficult and depends on a number of factors such as how samples are taken and processed. Here, we show that machine learning, which involves computer software learning from patterns in data, can predict lymph node metastasis in patients with colorectal cancer from the microscopic appearance of their primary tumor and the clinical characteristics of the patients. We also show that the same approach can predict patient survival. With further work, our approach may help clinicians to inform patients about their prognosis and decide on appropriate treatments.

Associations of Tinnitus Incidence with Use of Tumor Necrosis Factor-Alpha Inhibitors among Patients with Autoimmune Conditions.

Tumor necrosis factor-alpha (TNFα) may promote neuroinflammation prompting tinnitus. This retrospective cohort study evaluated whether anti-TNFα therapy influences incident tinnitus risk among adults with autoimmune disorders and no baseline tinnitus selected from a US electronic health records database (Eversana; 1 January 2010-27 January 2022). Patients with anti-TNFα had ≥90-day history pre-index (first autoimmune disorder diagnosis) and ≥180-day follow-up post-index. Random samples (n = 25,000) of autoimmune patients without anti-TNFα were selected for comparisons. Tinnitus incidence was compared among patients with or without anti-TNFα therapy, overall and among at-risk age groups or by anti-TNFα category. High-dimensionality propensity score (hdPS) matching was used to adjust for baseline confounders. Compared with patients with no anti-TNFα, anti-TNFα was not associated with tinnitus risk overall (hdPS-matched HR [95% CI]: 1.06 [0.85, 1.33]), or between groups stratified by age (30-50 years: 1 [0.68, 1.48]; 51-70 years: 1.18 [0.89, 1.56]) or anti-TNFα category (monoclonal antibody vs. fusion protein: 0.91 [0.59, 1.41]). Anti-TNFα was not associated with tinnitus risk among those treated for ≥6 months (hdPS-matched HR [95% CI]: 0.96 [0.69, 1.32]) or ≥12 (1.03 [0.71, 1.5]), or those with RA (1.16 [0.88, 1.53]). Thus, in this US cohort study, anti-TNFα therapy was not associated with tinnitus incidence among patients with autoimmune disorders.

Alterations in Gut Microbiome Composition and Function in Irritable Bowel Syndrome and Increased Probiotic Abundance with Daily Supplementation.

Irritable bowel syndrome (IBS) is characterized by abdominal discomfort and irregular bowel movements and stool consistency. As such, the gut microbiome has been posited as being influential for the syndrome. However, identifying microbial features associated with IBS symptom heterogeneity is difficult without large cohorts. Our aim was to identify microbial features associated with IBS and IBS subtypes compared to healthy controls and to determine if a synbiotic supplementation intervention could decrease the proportion of those microbial features. Stool samples from 490 individuals with IBS (including all dominant subtypes) and 122 individuals without IBS were analyzed with metagenomic sequencing. One hundred thirty-four IBS subjects were followed over time while receiving daily synbiotic supplementation, the composition of which varied between participants. IBS participants had significantly lower alpha diversity, an enrichment in Gram-negative bacteria, and a reduction in pathways associated with short-chain fatty acid and vitamin synthesis. Shigella species were significantly associated with IBS, while Eubacterium rectale and Faecalibacterium prausnitzii were associated with healthy controls. Random forest identified unique and overlapping microbial features associated with each IBS subtype. Longitudinal assessment of 134 IBS subjects receiving synbiotic supplements demonstrated a significant difference in microbial features and an increase in probiotic abundance across time. We identified microbial features that differentiate healthy and IBS subtypes. Synbiotic supplementation in IBS subjects did not result in alpha diversity change in the microbiome but did demonstrate changes in microbial features. Future work is needed to determine if the observed microbiome changes are associated with IBS symptom improvement. IMPORTANCE An estimated 35 million people in the United States and 11.5% of the population globally are affected by IBS. Immunity, genetics, environment, diet, small intestinal bacterial overgrowth (SIBO), and the gut microbiome are all factors that contribute to the onset or triggers of IBS. With strong supporting evidence that the gut microbiome may influence symptoms associated with IBS, elucidating the important microbes that contribute to the symptoms and severity is important to make decisions for targeted treatment. As probiotics have become more common in treating IBS symptoms, identifying effective probiotics may help inform future studies and treatment.

ACE: the Advanced Cohort Engine for searching longitudinal patient records.

OBJECTIVE: To propose a paradigm for a scalable time-aware clinical data search, and to describe the design, implementation and use of a search engine realizing this paradigm. MATERIALS AND METHODS: The Advanced Cohort Engine (ACE) uses a temporal query language and in-memory datastore of patient objects to provide a fast, scalable, and expressive time-aware search. ACE accepts data in the Observational Medicine Outcomes Partnership Common Data Model, and is configurable to balance performance with compute cost. ACE's temporal query language supports automatic query expansion using clinical knowledge graphs. The ACE API can be used with R, Python, Java, HTTP, and a Web UI. RESULTS: ACE offers an expressive query language for complex temporal search across many clinical data types with multiple output options. ACE enables electronic phenotyping and cohort-building with subsecond response times in searching the data of millions of patients for a variety of use cases. DISCUSSION: ACE enables fast, time-aware search using a patient object-centric datastore, thereby overcoming many technical and design shortcomings of relational algebra-based querying. Integrating electronic phenotype development with cohort-building enables a variety of high-value uses for a learning health system. Tradeoffs include the need to learn a new query language and the technical setup burden. CONCLUSION: ACE is a tool that combines a unique query language for time-aware search of longitudinal patient records with a patient object datastore for rapid electronic phenotyping, cohort extraction, and exploratory data analyses.

SARS-CoV-2 infection and COVID-19 severity in individuals with prior seasonal coronavirus infection.

We show that individuals with documented history of seasonal coronavirus have a similar SARS-CoV-2 infection rate and COVID-19 severity as those with no prior history of seasonal coronavirus. Our findings suggest prior infection with seasonal coronavirus does not provide immunity to subsequent infection with SARS-CoV-2.

Clinical Accuracy and Impact of Plasma Cell-Free DNA Fungal Polymerase Chain Reaction Panel for Noninvasive Diagnosis of Fungal Infection.

BACKGROUND: Invasive fungal infection (IFI) is a growing cause of morbidity and mortality in oncology and transplant patients. Diagnosis of IFI is often delayed due to need for invasive biopsy and low sensitivity of conventional diagnostic methods. Fungal cell-free DNA (cfDNA) detection in plasma is a novel testing modality for the noninvasive diagnosis of IFI. METHODS: A novel bioinformatic pipeline was created to interrogate fungal genomes and identify multicopy sequences for cfDNA polymerase chain reaction (PCR) targeting. A real-time PCR panel was developed for 12 genera and species most commonly causing IFI. Sensitivity and specificity of the fungal PCR panel were determined using plasma samples from patients with IFI and non-IFI controls. Clinical impact of the fungal PCR panel was evaluated prospectively based on the treating team's interpretation of the results. RESULTS: Overall, the sensitivity and specificity were 56.5% (65/115; 95% confidence interval [CI], 47.4-65.2) and 99.5% (2064/2075; 95% CI, 99.0-99.7), respectively. In the subset of patients with an optimized plasma volume (2 mL), sensitivity was 69.6% (48/69; 95% CI, 57.9-79.2). Sensitivity was 91.7% (11/12; 95% CI, 62.5-100) for detection of Mucorales agents, 56.3% (9/16; 95% CI, 33.2-76.9) for Aspergillus species, and 84.6% (11/13; 95% CI, 56.5-96.9) for Candida albicans. In a prospective evaluation of 226 patients with suspected IFI, cfDNA testing was positive in 47 (20.8%) patients and resulted in a positive impact on clinical management in 20 of 47 (42.6%). CONCLUSIONS: The fungal cfDNA PCR panel offers a noninvasive approach to early diagnosis of IFI, providing actionable results for personalized care.

Occurrence and Timing of Subsequent Severe Acute Respiratory Syndrome Coronavirus 2 Reverse-transcription Polymerase Chain Reaction Positivity Among Initially Negative Patients.

Using data for 20 912 patients from 2 large academic health systems, we analyzed the frequency of severe acute respiratory syndrome coronavirus 2 reverse-transcription polymerase chain reaction test discordance among individuals initially testing negative by nasopharyngeal swab who were retested on clinical grounds within 7 days. The frequency of subsequent positivity within this window was 3.5% and was similar across institutions.

Association of Systemic Diseases With Surgical Treatment for Obstructive Sleep Apnea Compared With Continuous Positive Airway Pressure.

Importance: The efficacy of surgical treatments for obstructive sleep apnea (OSA) is variable when considering only the Apnea Hypopnea Index as the treatment end point. However, only a few studies have shown an association between these procedures and improved clinically relevant outcomes, such as cardiovascular, endocrine, and neurological sequelae of OSA. Objective: To evaluate the association of surgery for OSA with clinically relevant outcomes. Design, Setting, and Participants: This retrospective cohort study used the Truven MarketScan Database from January 1, 2007, to December 31, 2015, to identify all patients diagnosed with OSA who received a prescription of continuous positive airway pressure (CPAP), were 40 to 89 years of age, and had at least 3 years of data on file. Data were analyzed September 19, 2019. Interventions: Soft tissue and skeletal surgical procedures for the treatment of OSA. Main Outcomes and Measures: The occurrence of cardiovascular, neurological, and endocrine complications was compared in patients who received CPAP alone and those who received surgery. High-dimensionality propensity score matching was used to adjust the models for confounders. Kaplan-Meier survival analysis with a log-rank test was used to compare differences in survival curves. Findings: A total of 54 224 patients were identified (33 405 men [61.6%]; mean [SD] age, 55.1 [9.2] years), including a cohort of 49 823 patients who received CPAP prescription alone (mean [SD] age, 55.5 [9.4] years) and 4269 patients who underwent soft tissue surgery (mean [SD] age, 50.3 [7.0] years). The median follow-up time was 4.47 (interquartile range, 3-8) years after the index CPAP prescription. In the unadjusted model, soft tissue surgery was associated with decreased cardiovascular (hazard ratio [HR], 0.92; 95% CI, 0.86-0.98), neurological (HR, 0.49; 95% CI, 0.39-0.61), and endocrine (HR, 0.80; 95% CI, 0.74-0.86) events. This finding was maintained in the adjusted model (HR for cardiovascular events, 0.91 [95% CI, 0.83-1.00]; HR for neurological events, 0.67 [95% CI, 0.51-0.89]; HR for endocrine events, 0.82 [95% CI, 0.74-0.91]). Skeletal surgery (n = 114) and concomitant skeletal and soft tissue surgery (n = 18) did not demonstrate significant differences in rates of development of systemic complications. Conclusions and Relevance: In this cohort study, soft tissue surgery for OSA was associated with lower rates of development of cardiovascular, neurological, and endocrine systemic complications compared with CPAP prescription in a large convenience sample of the working insured US adult population. These findings suggest that surgery should be part of the early treatment algorithm in patients at high risk of CPAP failure or nonadherence.

High Frequency of SARS-CoV-2 RNAemia and Association With Severe Disease.

BACKGROUND: Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in blood, also known as RNAemia, has been reported, but its prognostic implications are poorly understood. This study aimed to determine the frequency of SARS-CoV-2 RNA in plasma and its association with coronavirus disease 2019 (COVID-19) clinical severity. METHODS: An analytical cross-sectional study was performed in a single-center tertiary care institution and included consecutive inpatients and outpatients with confirmed COVID-19. The prevalence of SARS CoV-2 RNAemia and the strength of its association with clinical severity variables were examined and included intensive care unit (ICU) admission, invasive mechanical ventilation, and 30-day all-cause mortality. RESULTS: Paired nasopharyngeal and plasma samples were included from 85 patients. The median age was 55 years, and individuals with RNAemia were older than those with undetectable SARS-CoV-2 RNA in plasma (63 vs 50 years; P = .04). Comorbidities were frequent including obesity (37.6%), hypertension (30.6%), and diabetes mellitus (22.4%). RNAemia was detected in 28/85 (32.9%) of patients, including 22/28 (78.6%) who required hospitalization. In models adjusted for age, RNAemia was detected more frequently in individuals who developed severe disease including ICU admission (32.1 vs 14.0%; P = .04) and invasive mechanical ventilation (21.4% vs 3.5%; P = .02). All 4 deaths occurred in individuals with detectable RNAemia. An additional 121 plasma samples from 28 individuals with RNAemia were assessed longitudinally, and RNA was detected for a maximum duration of 10 days. CONCLUSIONS: This study demonstrated a high proportion of SARS-CoV-2 RNAemia, and an association between RNAemia and clinical severity suggesting the potential utility of plasma viral testing as a prognostic indicator for COVID-19.

Large-Scale Testing of Asymptomatic Healthcare Personnel for Severe Acute Respiratory Syndrome Coronavirus 2.

Large-scale, 1-time testing of >12,000 asymptomatic healthcare personnel in California, USA, during April-June 2020 showed that prevalence of severe acute respiratory syndrome coronavirus 2 was low (<1%). Testing might identify asymptomatic and presymptomatic persons, including some with high viral burden, enabling prompt implementation of measures to limit nosocomial spread.

Defining the features and duration of antibody responses to SARS-CoV-2 infection associated with disease severity and outcome.

SARS-CoV-2-specific antibodies, particularly those preventing viral spike receptor binding domain (RBD) interaction with host angiotensin-converting enzyme 2 (ACE2) receptor, can neutralize the virus. It is, however, unknown which features of the serological response may affect clinical outcomes of COVID-19 patients. We analyzed 983 longitudinal plasma samples from 79 hospitalized COVID-19 patients and 175 SARS-CoV-2-infected outpatients and asymptomatic individuals. Within this cohort, 25 patients died of their illness. Higher ratios of IgG antibodies targeting S1 or RBD domains of spike compared to nucleocapsid antigen were seen in outpatients who had mild illness versus severely ill patients. Plasma antibody increases correlated with decreases in viral RNAemia, but antibody responses in acute illness were insufficient to predict inpatient outcomes. Pseudovirus neutralization assays and a scalable ELISA measuring antibodies blocking RBD-ACE2 interaction were well correlated with patient IgG titers to RBD. Outpatient and asymptomatic individuals' SARS-CoV-2 antibodies, including IgG, progressively decreased during observation up to five months post-infection.

SARS-CoV-2 Antibody Responses Correlate with Resolution of RNAemia But Are Short-Lived in Patients with Mild Illness.

SARS-CoV-2-specific antibodies, particularly those preventing viral spike receptor binding domain (RBD) interaction with host angiotensin-converting enzyme 2 (ACE2) receptor, could offer protective immunity, and may affect clinical outcomes of COVID-19 patients. We analyzed 625 serial plasma samples from 40 hospitalized COVID-19 patients and 170 SARS-CoV-2-infected outpatients and asymptomatic individuals. Severely ill patients developed significantly higher SARS-CoV-2-specific antibody responses than outpatients and asymptomatic individuals. The development of plasma antibodies was correlated with decreases in viral RNAemia, consistent with potential humoral immune clearance of virus. Using a novel competition ELISA, we detected antibodies blocking RBD-ACE2 interactions in 68% of inpatients and 40% of outpatients tested. Cross-reactive antibodies recognizing SARS-CoV RBD were found almost exclusively in hospitalized patients. Outpatient and asymptomatic individuals' serological responses to SARS-CoV-2 decreased within 2 months, suggesting that humoral protection may be short-lived.

Estimating the efficacy of symptom-based screening for COVID-19.

There is substantial interest in using presenting symptoms to prioritize testing for COVID-19 and establish symptom-based surveillance. However, little is currently known about the specificity of COVID-19 symptoms. To assess the feasibility of symptom-based screening for COVID-19, we used data from tests for common respiratory viruses and SARS-CoV-2 in our health system to measure the ability to correctly classify virus test results based on presenting symptoms. Based on these results, symptom-based screening may not be an effective strategy to identify individuals who should be tested for SARS-CoV-2 infection or to obtain a leading indicator of new COVID-19 cases.