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.

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.

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.

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.

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.

Big data modeling to predict platelet usage and minimize wastage in a tertiary care system.

Maintaining a robust blood product supply is an essential requirement to guarantee optimal patient care in modern health care systems. However, daily blood product use is difficult to anticipate. Platelet products are the most variable in daily usage, have short shelf lives, and are also the most expensive to produce, test, and store. Due to the combination of absolute need, uncertain daily demand, and short shelf life, platelet products are frequently wasted due to expiration. Our aim is to build and validate a statistical model to forecast future platelet demand and thereby reduce wastage. We have investigated platelet usage patterns at our institution, and specifically interrogated the relationship between platelet usage and aggregated hospital-wide patient data over a recent consecutive 29-mo period. Using a convex statistical formulation, we have found that platelet usage is highly dependent on weekday/weekend pattern, number of patients with various abnormal complete blood count measurements, and location-specific hospital census data. We incorporated these relationships in a mathematical model to guide collection and ordering strategy. This model minimizes waste due to expiration while avoiding shortages; the number of remaining platelet units at the end of any day stays above 10 in our model during the same period. Compared with historical expiration rates during the same period, our model reduces the expiration rate from 10.5 to 3.2%. Extrapolating our results to the ∼2 million units of platelets transfused annually within the United States, if implemented successfully, our model can potentially save ∼80 million dollars in health care costs.

Clostridium difficile PCR Cycle Threshold Predicts Free Toxin.

There is no stand-alone Clostridium difficile diagnostic that can sensitively and rapidly detect fecal free toxins. We investigated the performance of the C. difficile PCR cycle threshold (CT ) for predicting free toxin status. Consecutive stool samples (n = 312) positive for toxigenic C. difficile by the GeneXpert C. difficile/Epi tcdB PCR assay were tested with the rapid membrane C. Diff Quik Chek Complete immunoassay (RMEIA). RMEIA toxin-negative samples were tested with the cell cytotoxicity neutralization assay (CCNA) and tgcBIOMICS enzyme-linked immunosorbent assay (ELISA). Using RMEIA alone or in combination with CCNA and/or ELISA as the reference method, the accuracy of CT was measured at different CT cutoffs. Using RMEIA as the reference method, a CT cutoff of 26.35 detected toxin-positive samples with a sensitivity, specificity, positive predictive value, and negative predictive value of 96.0% (95% confidence interval [CI], 90.2% to 98.9%), 65.9% (95% CI, 59.0% to 72.2%), 57.4% (95% CI, 52.7% to 62%), and 97.1% (95% CI, 92.8% to 98.9), respectively. Inclusion of CCNA in the reference method improved CT specificity to 78.0% (95% CI, 70.7% to 84.2%). Intercartridge lot CT variability measured as the average coefficient of variation was 2.8% (95% CI, 1.2% to 3.2%). Standardizing the input stool volume did not improve CT toxin specificity. The median CT values were not significantly different between stool samples with Bristol scores of 5, 6, and 7, between pediatric and adult samples, or between presumptive 027 and non-027 strains. In addition to sensitively detecting toxigenic C. difficile in stool, on-demand PCR may also be used to accurately predict toxin-negative stool samples, thus providing additional results in PCR-positive stool samples to guide therapy.

Real-Time Electronic Tracking of Diarrheal Episodes and Laxative Therapy Enables Verification of Clostridium difficile Clinical Testing Criteria and Reduction of Clostridium difficile Infection Rates.

Health care-onset health care facility-associated Clostridium difficile infection (HO-CDI) is overdiagnosed for several reasons, including the high prevalence of C. difficile colonization and the inability of hospitals to limit testing to patients with clinically significant diarrhea. We conducted a quasiexperimental study from 22 June 2015 to 30 June 2016 on consecutive inpatients with C. difficile test orders at an academic hospital. Real-time electronic patient data tracking was used by the laboratory to enforce testing criteria (defined as the presence of diarrhea [≥3 unformed stools in 24 h] and absence of laxative intake in the prior 48 h). Outcome measures included C. difficile test utilization, HO-CDI incidence, oral vancomycin utilization, and clinical complications. During the intervention, 7.1% (164) and 9.1% (211) of 2,321 C. difficile test orders were canceled due to absence of diarrhea and receipt of laxative therapy, respectively. C. difficile test utilization decreased upon implementation from an average of 208.8 tests to 143.0 tests per 10,000 patient-days (P < 0.001). HO-CDI incidence rate decreased from an average of 13.0 cases to 9.7 cases per 10,000 patient-days (P = 0.008). Oral vancomycin days of therapy decreased from an average of 13.8 days to 9.4 days per 1,000 patient-days (P = 0.009). Clinical complication rates were not significantly different in patients with 375 canceled orders compared with 869 episodes with diarrhea but negative C. difficile results. Real-time electronic clinical data tracking is an effective tool for verification of C. difficile clinical testing criteria and safe reduction of inflated HO-CDI rates.

Epigenetics decouples mutational from environmental robustness. Did it also facilitate multicellularity?

The evolution of ever increasing complex life forms has required innovations at the molecular level in order to overcome existing barriers. For example, evolving processes for cell differentiation, such as epigenetic mechanisms, facilitated the transition to multicellularity. At the same time, studies using gene regulatory network models, and corroborated in single-celled model organisms, have shown that mutational robustness and environmental robustness are correlated. Such correlation may constitute a barrier to the evolution of multicellularity since cell differentiation requires sensitivity to cues in the internal environment during development. To investigate how this barrier might be overcome, we used a gene regulatory network model which includes epigenetic control based on the mechanism of histone modification via Polycomb Group Proteins, which evolved in tandem with the transition to multicellularity. Incorporating the Polycomb mechanism allowed decoupling of mutational and environmental robustness, thus allowing the system to be simultaneously robust to mutations while increasing sensitivity to the environment. In turn, this decoupling facilitated cell differentiation which we tested by evaluating the capacity of the system for producing novel output states in response to altered initial conditions. In the absence of the Polycomb mechanism, the system was frequently incapable of adding new states, whereas with the Polycomb mechanism successful addition of new states was nearly certain. The Polycomb mechanism, which dynamically reshapes the network structure during development as a function of expression dynamics, decouples mutational and environmental robustness, thus providing a necessary step in the evolution of multicellularity.

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.

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.

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.

Comprehensive microRNA profiling in B-cells of human centenarians by massively parallel sequencing.

BACKGROUND: MicroRNAs (miRNAs) are small, non-coding RNAs that regulate gene expression and play a critical role in development, homeostasis, and disease. Despite their demonstrated roles in age-associated pathologies, little is known about the role of miRNAs in human aging and longevity. RESULTS: We employed massively parallel sequencing technology to identify miRNAs expressed in B-cells from Ashkenazi Jewish centenarians, i.e., those living to a hundred and a human model of exceptional longevity, and younger controls without a family history of longevity. With data from 26.7 million reads comprising 9.4 × 108 bp from 3 centenarian and 3 control individuals, we discovered a total of 276 known miRNAs and 8 unknown miRNAs ranging several orders of magnitude in expression levels, a typical characteristics of saturated miRNA-sequencing. A total of 22 miRNAs were found to be significantly upregulated, with only 2 miRNAs downregulated, in centenarians as compared to controls. Gene Ontology analysis of the predicted and validated targets of the 24 differentially expressed miRNAs indicated enrichment of functional pathways involved in cell metabolism, cell cycle, cell signaling, and cell differentiation. A cross sectional expression analysis of the differentially expressed miRNAs in B-cells from Ashkenazi Jewish individuals between the 50th and 100th years of age indicated that expression levels of miR-363* declined significantly with age. Centenarians, however, maintained the youthful expression level. This result suggests that miR-363* may be a candidate longevity-associated miRNA. CONCLUSION: Our comprehensive miRNA data provide a resource for further studies to identify genetic pathways associated with aging and longevity in humans.

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.

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.