Identification of pre-diagnostic lipid sets associated with liver cancer risk using untargeted lipidomics and chemical set analysis: A nested case-control study within the ATBC cohort.

In pre-disposed individuals, a reprogramming of the hepatic lipid metabolism may support liver cancer initiation. We conducted a high-resolution mass spectrometry based untargeted lipidomics analysis of pre-diagnostic serum samples from a nested case-control study (219 liver cancer cases and 219 controls) within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. Out of 462 annotated lipids, 158 (34.2%) were associated with liver cancer risk in a conditional logistic regression analysis at a false discovery rate (FDR) <0.05. A chemical set enrichment analysis (ChemRICH) and co-regulatory set analysis suggested that 22/28 lipid classes and 47/83 correlation modules were significantly associated with liver cancer risk (FDR <0.05). Strong positive associations were observed for monounsaturated fatty acids (MUFA), triacylglycerols (TAGs) and phosphatidylcholines (PCs) having MUFA acyl chains. Negative associations were observed for sphingolipids (ceramides and sphingomyelins), lysophosphatidylcholines, cholesterol esters and polyunsaturated fatty acids (PUFA) containing TAGs and PCs. Stearoyl-CoA desaturase enzyme 1 (SCD1), a rate limiting enzyme in fatty acid metabolism and ceramidases seems to be critical in this reprogramming. In conclusion, our study reports pre-diagnostic lipid changes that provide novel insights into hepatic lipid metabolism reprogramming may contribute to a pro-cell growth and anti-apoptotic tissue environment and, in turn, support liver cancer initiation.

Efficient risk-based collection of biospecimens in cohort studies: Designing a prospective study of diagnostic performance for multicancer detection tests.

In cohort studies, it can be infeasible to collect specimens on an entire cohort. For example, to estimate sensitivity of multiple Multi-Cancer Detection (MCD) assays, we desire an extra 80mL of cell-free DNA (cfDNA) blood, but this much extra blood is too expensive for us to collect on everyone. We propose a novel epidemiologic study design that efficiently oversamples those at highest baseline disease risk from whom to collect specimens, to increase the number of future cases with cfDNA blood collection. The variance reduction ratio from our risk-based subsample versus a simple random (sub)sample (SRS) depends primarily on the ratio of risk model sensitivity to the fraction of the cohort selected for specimen collection subject to constraining the risk model specificity. In a simulation where we chose 34% of Prostate, Lung, Colorectal, and Ovarian Screening Trial cohort at highest risk of lung cancer for cfDNA blood collection, we could enrich the number of lung cancers 2.42-fold and the standard deviation of lung-cancer MCD sensitivity was 31-33% reduced versus SRS. Risk-based collection of specimens on a subsample of the cohort could be a feasible and efficient approach to collecting extra specimens for molecular epidemiology.

Most Fanconi anemia heterozygotes are not at increased cancer risk: A genome-first DiscovEHR cohort population study.

PURPOSE: Fanconi anemia (FA) is a bone marrow failure and cancer predisposition syndrome caused primarily by biallelic pathogenic variants in 1 of 22 genes involved in DNA interstrand cross-link repair. An enduring question concerns cancer risk of those with a single pathogenic FA gene variant. To investigate all FA genes, this study utilized the DiscovEHR cohort of 170,503 individuals with exome sequencing and electronic health data. METHODS: 5822 subjects with a single pathogenic variant in an FA gene were identified. Two control groups were used in primary analysis deriving cancer risk signals. Secondary exploratory analysis was conducted using the UK Biobank and The Cancer Genome Atlas. RESULTS: Signals for elevated cancer risk were found in all 5 known cancer predisposition genes. Among the remaining 15 genes associated with autosomal recessive inheritance cancer risk signals were found for 4 cancers across 3 genes in the primary cohort but were not validated in secondary cohorts. CONCLUSION: To our knowledge, this is the first and largest FA heterozygote study to use genomic ascertainment and validates well-established cancer predispositions in 5 genes, whereas finding insufficient evidence of predisposition in 15 others. Our findings inform clinical surveillance given how common pathogenic FA variants are in the population.

Acute and chronic kidney injury during therapy for pediatric acute leukemia: A report from the Leukemia Electronic Abstraction of Records Network (LEARN).

Children with acute leukemia are at increased risk of kidney injury. Using electronic health record data from three centers between 2010 and 2018, this study retrospectively described acute kidney injury (AKI) and chronic kidney disease (CKD) prevalence in children with acute lymphoblastic or myeloid leukemia (ALL, AML) using Common Terminology Criteria for Adverse Events (CTCAE) and Kidney Disease Improving Global Outcomes (KDIGO) definitions. AKI during therapy was 25% (ALL) and 32% (AML) using CTCAE, versus 84% (ALL) and 74% (AML) using KDIGO. CKD prevalence was low and Grade 1/Stage 2. Further investigation is needed to optimally define kidney injury in acute leukemia.

Absolute lymphocyte count recovery following initial acute myelogenous leukemia therapy: Implications for adoptive cell therapy.

BACKGROUND: An adequate absolute lymphocyte count (ALC) is an essential first step in autologous chimeric antigen receptor (CAR) T-cell manufacturing. For patients with acute myelogenous leukemia (AML), the intensity of chemotherapy received may affect adequate ALC recovery required for CAR T-cell production. We sought to analyze ALC following each course of upfront therapy as one metric for CAR T-cell manufacturing feasibility in children and young adults with AML. PROCEDURE: ALC data were collected from an observational study of patients with newly diagnosed AML between the ages of 1 month and 21 years who received treatment between the years of 2006 and 2018 at one of three hospitals in the Leukemia Electronic Abstraction of Records Network (LEARN) consortium. RESULTS: Among 193 patients with sufficient ALC data for analysis, the median ALC following induction 1 was 1715 cells/µl (interquartile range: 1166-2388), with successive decreases in ALC with each subsequent course. Similarly, the proportion of patients achieving an ALC >400 cells/µl decreased following each course, ranging from 98.4% (190/193) after course 1 to 66.7% (22/33) for patients who received a fifth course of therapy. CONCLUSIONS: There is a successive decline of ALC recovery with subsequent courses of chemotherapy. Despite this decline, ALC values are likely sufficient to consider apheresis prior to the initiation of each course of upfront therapy for the majority of newly diagnosed pediatric AML patients, thereby providing a window of opportunity for T-cell collection for those patients identified at high risk of relapse or with refractory disease.

Incidence and risk factors for hypoglycemia during maintenance chemotherapy in pediatric acute lymphoblastic leukemia.

BACKGROUND: Fasting hypoglycemia is a recognized occurrence among pediatric patients with acute lymphoblastic leukemia (ALL) during maintenance therapy. Existing publications describing this finding are limited to small studies and case reports. Our objective was to determine the incidence of hypoglycemia during maintenance chemotherapy and to investigate the association of age, as well as other potential risk factors, with this outcome in pediatric patients with ALL. PROCEDURE: This retrospective cohort study included individuals 1 to 21 years of age with ALL treated with antimetabolite-containing maintenance chemotherapy at a large children's hospital between January 2011 and December 2014. The primary endpoint was time to first documented episode of hypoglycemia during maintenance therapy, defined as single measurement of plasma glucose <60 mg/dL. Cox regression was used to evaluate the association with age and identify other potential risk factors. RESULTS: We identified 126 eligible patients, of whom 63% were documented as White, non-Hispanic, 28% as non-White, non-Hispanic, and 9% as Hispanic. Twenty-eight children (22%) had documented hypoglycemia during maintenance therapy. Younger age at the start of maintenance and hepatotoxicity documented during chemotherapy prior to maintenance initiation were associated with hypoglycemia (adjusted HR age = 0.88; 95% CI, 0.78-0.99; adjusted HR prior hepatotoxicity = 3.50; 95% CI, 1.47-8.36). CONCLUSIONS: Nearly one quarter of children in our cohort had hypoglycemia documented during maintenance chemotherapy. Younger age at maintenance initiation and hepatotoxicity during chemotherapy prior to maintenance initiation emerged as risk factors. These findings highlight the importance of counseling about the risk of, and monitoring for, hypoglycemia, particularly in young children.

Adaptive local false discovery rate procedures for highly spiky data and their application RNA sequencing data of yeast SET4 deletion mutants.

Chromatin dynamics are central to the regulation of gene expression and genome stability. In order to improve understanding of the factors regulating chromatin dynamics, the genes encoding these factors are deleted and the differential gene expression profiles are determined using approaches such as RNA sequencing. Here, we analyzed a gene expression dataset aimed at uncovering the function of the relatively uncharacterized chromatin regulator, Set4, in the model system Saccharomyces cerevisiae (budding yeast). The main theme of this paper focuses on identifying the highly differentially expressed genes in cells deleted for Set4 (referred to as Set4 Δ mutant dataset) compared to the wild-type yeast cells. The Set4 Δ mutant data produce a spiky distribution on the log-fold changes of their expressions, and it is reasonably assumed that genes which are not highly differentially expressed come from a mixture of two normal distributions. We propose an adaptive local false discovery rate (FDR) procedure, which estimates the null distribution of the log-fold changes empirically. We numerically show that, unlike existing approaches, our proposed method controls FDR at the aimed level (0.05) and also has competitive power in finding differentially expressed genes. Finally, we apply our procedure to analyzing the Set4 Δ mutant dataset.

Identification of Pediatric Sepsis for Epidemiologic Surveillance Using Electronic Clinical Data.

OBJECTIVES: A method to identify pediatric sepsis episodes that is not affected by changing diagnosis and claims-based coding practices does not exist. We derived and validated a surveillance algorithm to identify pediatric sepsis using routine clinical data and applied the algorithm to study longitudinal trends in sepsis epidemiology. DESIGN: Retrospective observational study. SETTING: Single academic children's hospital. PATIENTS: All emergency and hospital encounters from January 2011 to January 2019, excluding neonatal ICU and cardiac center. EXPOSURE: Sepsis episodes identified by a surveillance algorithm using clinical data to identify infection and concurrent organ dysfunction. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A surveillance algorithm was derived and validated in separate cohorts with suspected sepsis after clinician-adjudication of final sepsis diagnosis. We then applied the surveillance algorithm to determine longitudinal trends in incidence and mortality of pediatric sepsis over 8 years. Among 93,987 hospital encounters and 1,065 episodes of suspected sepsis in the derivation period, the surveillance algorithm yielded sensitivity 78% (95% CI, 72-84%), specificity 76% (95% CI, 74-79%), positive predictive value 41% (95% CI, 36-46%), and negative predictive value 94% (95% CI, 92-96%). In the validation period, the surveillance algorithm yielded sensitivity 84% (95% CI, 77-92%), specificity of 65% (95% CI, 59-70%), positive predictive value 43% (95% CI, 35-50%), and negative predictive value 93% (95% CI, 90-97%). Notably, most "false-positives" were deemed clinically relevant sepsis cases after manual review. The hospital-wide incidence of sepsis was 0.69% (95% CI, 0.67-0.71%), and the inpatient incidence was 2.8% (95% CI, 2.7-2.9%). Risk-adjusted sepsis incidence, without bias from changing diagnosis or coding practices, increased over time (adjusted incidence rate ratio per year 1.07; 95% CI, 1.06-1.08; p < 0.001). Mortality was 6.7% and did not change over time (adjusted odds ratio per year 0.98; 95% CI, 0.93-1.03; p = 0.38). CONCLUSIONS: An algorithm using routine clinical data provided an objective, efficient, and reliable method for pediatric sepsis surveillance. An increased sepsis incidence and stable mortality, free from influence of changes in diagnosis or billing practices, were evident.

Pediatric asthma hospitalizations among urban minority children and the continuity of primary care.

OBJECTIVE: To examine the effect of ambulatory health care processes on asthma hospitalizations. METHODS: A retrospective cohort study using electronic health records was completed. Patients aged 2-18 years receiving health care from 1 of 5 urban practices between Jan 1, 2004 and Dec 31, 2008 with asthma documented on their problem list were included. Independent variables were modifiable health care processes in the primary care setting: (1) use of asthma controller medications; (2) regular assessment of asthma symptoms; (3) use of spirometry; (4) provision of individualized asthma care plans; (5) timely influenza vaccination; (6) access to primary healthcare; and (7) use of pay for performance physician incentives. Occurrence of one or more asthma hospitalizations was the primary outcome of interest. We used a log linear model (Poisson regression) to model the association between the factors of interest and number of asthma hospitalizations. RESULTS: 5,712 children with asthma were available for analysis. 96% of the children were African American. The overall hospitalization rate was 64 per 1,000 children per year. None of the commonly used asthma-specific indicators of high quality care were associated with fewer asthma hospitalizations. Children with documented asthma who experienced a lack of primary health care (no more than one outpatient visit at their primary care location in the 2 years preceding hospitalization) were at higher risk of hospitalization compared to those children with a greater number of visits (incidence rate ratio 1.39; 95% CI 1.09-1.78). CONCLUSIONS: In children with asthma, more frequent primary care visits are associated with reduced asthma hospitalizations.

A genome-first approach to characterize DICER1 pathogenic variant prevalence, penetrance and cancer, thyroid, and other phenotypes in 2 population-scale cohorts.

Purpose: Population-scale, exome-sequenced cohorts with linked electronic health records (EHR) permit genome-first exploration of phenotype. Phenotype and cancer risk are well-characterized in children with a pathogenic DICER1 (HGNC ID:17098) variant. Here, the prevalence, penetrance and phenotype of pathogenic germline DICER1 variants in adults was investigated in two population-scale cohorts. Methods: Variant pathogenicity was classified using published DICER1 ClinGen criteria in the UK Biobank (469,787 exomes; unrelated: 437,663) and Geisinger (170,503 exomes; unrelated: 109,789) cohorts. In the UK Biobank cohort, cancer diagnoses in the EHR, cancer and death registry were queried. For the Geisinger cohort, the Geisinger Cancer Registry and EHR were queried. Results: In the UK Biobank, there were 46 unique pathogenic DICER1 variants in 57 individuals (1:8,242;95%CI:1:6,362-1:10,677). In Geisinger, there were 16 unique pathogenic DICER1 variants (including one microdeletion) in 21 individuals (1:8,119;95%CI:1:5,310-1:12,412). Cohorts were well-powered to find larger effect sizes for common cancers. Cancers were not significantly enriched in DICER1 heterozygotes; however, there was a ~4-fold increased risk for thyroid disease in both cohorts. There were multiple ICD10 codes enriched >2-fold in both cohorts. Conclusion: Estimates of pathogenic germline DICER1 prevalence, thyroid disease penetrance and cancer phenotype from genomically ascertained adults are determined in two large cohorts.

The use of azithromycin and pyrimethamine for treatment of cerebral toxoplasmosis in human immunodeficiency virus-infected patients: a systematic review.

Purpose: Toxoplasma gondii is a parasite that is widely distributed around the globe and can cause brain inflammation, particularly in immunosuppressed patients such as those diagnosed with human immunodeficiency virus (HIV). This paper reviews the efficacy of azithromycin and pyrimethamine combination therapy for cerebral toxoplasmosis in patients with HIV. Methods: The scope of the studies included in this review was limited from 1992 to 2022, with studies primarily being randomized, controlled clinical trials available on online scientific journal databases. The authors screened eligible records for review, removing those that did not fit the inclusion and exclusion criteria. The risk of bias of the extracted data was analyzed through the Cochrane risk-of-bias tool for randomized trials. Results: A broad search of major online databases such as PubMed, Medline, Google Scholar, and Cochrane using keywords, limit fields, and Boolean operators yielded 3,130 articles. After thoroughly screening the search results, two studies were included in this review. Results from the studies included in the review demonstrate that the combination therapy of azithromycin and pyrimethamine is favorable for cerebral toxoplasmosis. However, the net response is less effective than the standard treatment regimen (pyrimethamine and sulfadiazine). Conclusion: The combination therapy of azithromycin and pyrimethamine is less effective than the standard treatment regimen for maintenance therapy for cerebral toxoplasmosis; thus, administering these medications for this indication must be met with caution.

Investigating the genetic contribution in febrile infection-related epilepsy syndrome and refractory status epilepticus.

Introduction: Febrile infection-related epilepsy syndrome (FIRES) is a severe childhood epilepsy with refractory status epilepticus after a typically mild febrile infection. The etiology of FIRES is largely unknown, and outcomes in most individuals with FIRES are poor. Methods: Here, we reviewed the current state-of-the art genetic testing strategies in individuals with FIRES. We performed a systematic computational analysis to identify individuals with FIRES and characterize the clinical landscape using the Electronic Medical Records (EMR). Among 25 individuals with a confirmed FIRES diagnosis over the last decade, we performed a comprehensive review of genetic testing and other diagnostic testing. Results: Management included use of steroids and intravenous immunoglobulin (IVIG) in most individuals, with an increased use of immunomodulatory agents, including IVIG, plasma exchange (PLEX) and immunosuppressants such as cytokine inhibitors, and the ketogenic diet after 2014. Genetic testing was performed on a clinical basis in almost all individuals and was non-diagnostic in all patients. We compared FIRES with both status epilepticus (SE) and refractory status epilepticus (RSE) as a broader comparison cohort and identified genetic causes in 36% of patients with RSE. The difference in genetic signatures between FIRES and RSE suggest distinct underlying etiologies. In summary, despite the absence of any identifiable etiologies in FIRES, we performed an unbiased analysis of the clinical landscape, identifying a heterogeneous range of treatment strategies and characterized real-world clinical practice. Discussion: FIRES remains one of the most enigmatic conditions in child neurology without any known etiologies to date despite significant efforts in the field, suggesting a clear need for further studies and novel diagnostic and treatment approaches.

Automated Ascertainment of Typhlitis From the Electronic Health Record.

PURPOSE: Adverse events (AEs) on Children's Oncology Group (COG) trials are manually ascertained using Common Terminology Criteria for Adverse Events. Despite significant effort, we previously demonstrated that COG typhlitis reporting sensitivity was only 37% when compared with gold standard physician chart abstraction. This study tested an automated typhlitis identification algorithm using electronic health record data. METHODS: Electronic health record data from children with leukemia age 0-22 years treated at a single institution from 2006 to 2019 were included. Patients were divided into derivation and validation cohorts. Rigorous chart abstraction of validation cohort patients established a gold standard AE data set. We created an automated algorithm to identify typhlitis matching Common Terminology Criteria for Adverse Events v5 that included antibiotics, neutropenia, and non-negated mention of typhlitis in a note. We iteratively refined the algorithm using the derivation cohort and then applied the algorithm to the validation cohort; performance was compared with the gold standard. For patients on trial AAML1031, COG AE report performance was compared with the gold standard. RESULTS: The derivation cohort included 337 patients. The validation cohort included 270 patients (961 courses). Chart abstraction identified 16 courses with typhlitis. The algorithm identified 37 courses with typhlitis; 13 were true positives (sensitivity 81.3%, positive predictive value 35.1%). For patients on AAML1031, chart abstraction identified nine courses with typhlitis, and COG reporting correctly identified 4 (sensitivity 44.4%, positive predictive value 100.0%). CONCLUSION: The automated algorithm identified true cases of typhlitis with higher sensitivity than COG reporting. The algorithm identified false positives but reduced the number of courses needing manual review by 96% (961 to 37) by detecting potential typhlitis. This algorithm could provide a useful screening tool to reduce manual effort required for typhlitis AE reporting.

Rates of laboratory adverse events by course in paediatric leukaemia ascertained with automated electronic health record extraction: a retrospective cohort study from the Children's Oncology Group.

BACKGROUND: Adverse events are often misreported in clinical trials, leading to an incomplete understanding of toxicities. We aimed to test automated laboratory adverse event ascertainment and grading (via the ExtractEHR automated package) to assess its scalability and define adverse event rates for children with acute myeloid leukaemia and acute lymphoblastic leukaemia. METHODS: For this retrospective cohort study from the Children's Oncology Group (COG), we included patients aged 0-22 years treated for acute myeloid leukaemia or acute lymphoblastic leukaemia at Children's Healthcare of Atlanta (Atlanta, GA, USA) from Jan 1, 2010, to Nov 1, 2018, at the Children's Hospital of Philadelphia (Philadelphia, PA, USA) from Jan 1, 2011, to Dec 31, 2014, and at the Texas Children's Hospital (Houston, TX, USA) from Jan 1, 2011, to Dec 31, 2014. The ExtractEHR automated package acquired, cleaned, and graded laboratory data as per Common Terminology Criteria for Adverse Events (CTCAE) version 5 for 22 commonly evaluated grade 3-4 adverse events (fatal events were not evaluated) with numerically based CTCAE definitions. Descriptive statistics tabulated adverse event frequencies. Adverse events ascertained by ExtractEHR were compared to manually reported adverse events for patients enrolled in two COG trials (AAML1031, NCT01371981; AALL0932, NCT02883049). Analyses were restricted to protocol-defined chemotherapy courses (induction I, induction II, intensification I, intensification II, and intensification III for acute myeloid leukaemia; induction, consolidation, interim maintenance, delayed intensification, and maintenance for acute lymphoblastic leukaemia). FINDINGS: Laboratory adverse event data from 1077 patients (583 from Children's Healthcare of Atlanta, 200 from the Children's Hospital of Philadelphia, and 294 from the Texas Children's Hospital) who underwent 4611 courses (549 for acute myeloid leukaemia and 4062 for acute lymphoblastic leukaemia) were extracted, processed, and graded. Of the 166 patients with acute myeloid leukaemia, 86 (52%) were female, 80 (48%) were male, 96 (58%) were White, and 132 (80%) were non-Hispanic. Of the 911 patients with acute lymphoblastic leukaemia, 406 (45%) were female, 505 (55%) were male, 596 (65%) were White, and 641 (70%) were non-Hispanic. Patients with acute myeloid leukaemia had the most adverse events during induction I and intensification II. Hypokalaemia (one [17%] of six to 75 [48%] of 156 courses) and alanine aminotransferase (ALT) increased (13 [10%] of 134 to 27 [17%] of 156 courses) were the most prevalent non-haematological adverse events in patients with acute myeloid leukaemia, as identified by ExtractEHR. Patients with acute lymphoblastic leukaemia had the greatest number of adverse events during induction and maintenance (eight adverse events with prevalence ≥10%; induction and maintenance: anaemia, platelet count decreased, white blood cell count decreased, neutrophil count decreased, lymphocyte count decreased, ALT increased, and hypocalcaemia; induction: hypokalaemia; maintenance: aspartate aminotransferase [AST] increased and blood bilirubin increased), as identified by ExtractEHR. 187 (85%) of 220 total comparisons in 22 adverse events in four AAML1031 and six AALL0923 courses were substantially higher with ExtractEHR than COG-reported adverse event rates for adverse events with a prevalence of at least 2%. INTERPRETATION: ExtractEHR is scalable and accurately defines laboratory adverse event rates for paediatric acute leukaemia; moreover, ExtractEHR seems to detect higher rates of laboratory adverse events than those reported in COG trials. These rates can be used for comparisons between therapies and to counsel patients treated on or off trials about the risks of chemotherapy. ExtractEHR-based adverse event ascertainment can improve reporting of laboratory adverse events in clinical trials. FUNDING: US National Institutes of Health, St Baldrick's Foundation, and Alex's Lemonade Stand Foundation.

Set4 regulates stress response genes and coordinates histone deacetylases within yeast subtelomeres.

The yeast chromatin protein Set4 is a member of the Set3-subfamily of SET domain proteins which play critical roles in the regulation of gene expression in diverse developmental and environmental contexts. We previously reported that Set4 promotes survival during oxidative stress and regulates expression of stress response genes via stress-dependent chromatin localization. In this study, global gene expression analysis and investigation of histone modification status identified a role for Set4 in maintaining gene repressive mechanisms within yeast subtelomeres under both normal and stress conditions. We show that Set4 works in a partially overlapping pathway to the SIR complex and the histone deacetylase Rpd3 to maintain proper levels of histone acetylation and expression of stress response genes encoded in subtelomeres. This role for Set4 is particularly critical for cells under hypoxic conditions, where the loss of Set4 decreases cell fitness and cell wall integrity. These findings uncover a new regulator of subtelomeric chromatin that is key to stress defense pathways and demonstrate a function for Set4 in regulating repressive, heterochromatin-like environments.

Sex-based prevalence of growth faltering in an urban pediatric population.

OBJECTIVE: To determine the sex-based prevalence of growth faltering in a pediatric primary care setting. STUDY DESIGN: A total of 33 476 children attending 4 urban pediatric primary care practices affiliated with a tertiary pediatric hospital between July 2002 and June 2005 were studied. Growth faltering was defined as height <5th percentile or a drop in height z-score by >or= 1.5 standard deviations (SD) before age 18 months or by >or= 1 SD thereafter. The growth-faltering and nonfaltering groups were compared in terms of sex, race, age, number of clinic visits, and insurance, and by US census tract, socioeconomic status and parental education. Similar comparisons were made for children with height z-scores below -2.25 SD. RESULTS: Growth faltering was present in 3007 of the children studied (9%). Univariate and multivariate logistic regression analyses identified significant associations between growth faltering and younger age (P< .0001), Caucasian race (P< .0001), fewer clinic visits (P< .0001), and Medicaid insurance (P< .005), but not with sex nor by residential census tract, median income or proportion with less than high school education. Height below -2.25 SD was associated with male sex (P< .01), Medicaid insurance (P< .01), and more primary care visits (P< .0005). CONCLUSIONS: The sex disparity in subspecialty growth center referrals (2:1 male:female) is not due to male predominance in growth faltering among children in the urban primary care setting.

Assessment of myocardial viability: review of the clinical significance.

The identification of myocardial viability in patients with coronary artery disease and left ventricular dysfunction (LVD) has important clinical and prognostic implications. Two terms commonly used to define clinical conditions of potentially reversible contractile dysfunction are stunned myocardium and hibernating myocardium. Stunned myocardium refers to transient depression of contractile function secondary to an acute ischemic insult. Hibernating myocardium is a form of contractile dysfunction of living myocytes in the setting of chronic ischemia or chronically reduced flow reserve. Numerous observational studies have shown improved clinical outcomes after revascularization of patients with LVD and evidence of myocardial viability, although patients with nonviable myocardium have not been shown to have the same benefits. The use of noninvasive techniques to determine myocardial viability provides important information to guide clinicians in deciding which patients with LVD are likely to receive benefit from a revascularization procedure. Positron emission tomography, single-photon emission computed tomography, dobutamine echocardiography, and cardiac magnetic resonance imaging each have advantages and limitations.

Eosinophilic Esophagitis Is a Late Manifestation of the Allergic March.

BACKGROUND: The allergic march describes the natural history of allergic conditions as they develop during childhood. Eosinophilic esophagitis (EoE) is a chronic allergic inflammatory disease that can be triggered by specific foods. Despite its allergic pathophysiology, the epidemiologic relationship between EoE and established members of the allergic march is unknown. OBJECTIVE: We sought to determine whether EoE meets epidemiologic criteria for being considered a member of the allergic march. METHODS: Using a primary care birth cohort of 130,435 children, we determined the natural histories of atopic dermatitis (AD), IgE-mediated food allergy (IgE-FA), asthma, EoE, and allergic rhinitis (AR) in individual patients. We then performed case-control analyses to establish the extent that existing allergic conditions influence the rate of subsequent EoE diagnosis. RESULTS: A total of 139 children developed EoE during the observation period (prevalence of 0.11%). The peak age of EoE diagnosis was 2.6 years, as compared with 0.3 years, 1 year, 1.1 years, and 2.1 years for AD, IgE-FA, asthma, and AR, respectively. The presence of AD (hazard ratio [HR] 3.2, 95% confidence interval [CI] 2.2-4.6), IgE-FA (HR 9.1, 95% CI 6.5-12.6), and asthma (HR 1.9, 95% CI 1.3-2.7) was independently and cumulatively associated with subsequent EoE diagnosis. The presence of AR was associated with subsequent EoE diagnosis (HR 2.8, 95% CI 2.0-3.9), and the presence of EoE was associated with subsequent AR diagnosis (HR 2.5, 95% CI 1.7-3.5). CONCLUSIONS: Allergic comorbidities are positively associated with EoE diagnosis. Together, our findings suggest that EoE is a late manifestation of the allergic march.

Identifying surgical site infections in electronic health data using predictive models.

Objective: The objective was to prospectively derive and validate a prediction rule for detecting cases warranting investigation for surgical site infections (SSI) after ambulatory surgery. Methods: We analysed electronic health record (EHR) data for children who underwent ambulatory surgery at one of 4 ambulatory surgical facilities. Using regularized logistic regression and random forests, we derived SSI prediction rules using 30 months of data (derivation set) and evaluated performance with data from the subsequent 10 months (validation set). Models were developed both with and without data extracted from free text. We also evaluated the presence of an antibiotic prescription within 60 days after surgery as an independent indicator of SSI evidence. Our goal was to exceed 80% sensitivity and 10% positive predictive value (PPV). Results: We identified 234 surgeries with evidence of SSI among the 7910 surgeries available for analysis. We derived and validated an optimal prediction rule that included free text data using a random forest model (sensitivity = 0.9, PPV = 0.28). Presence of an antibiotic prescription had poor sensitivity (0.65) when applied to the derivation data but performed better when applied to the validation data (sensitivity = 0.84, PPV = 0.28). Conclusions: EHR data can facilitate SSI surveillance with adequate sensitivity and PPV.

User Testing an Information Foraging Tool for Ambulatory Surgical Site Infection Surveillance.

BACKGROUND: Surveillance for surgical site infections (SSIs) after ambulatory surgery in children requires a detailed manual chart review to assess criteria defined by the National Health and Safety Network (NHSN). Electronic health records (EHRs) impose an inefficient search process where infection preventionists must manually review every postsurgical encounter (< 30 days). Using text mining and business intelligence software, we developed an information foraging application, the SSI Workbench, to visually present which postsurgical encounters included SSI-related terms and synonyms, antibiotic, and culture orders. OBJECTIVE: This article compares the Workbench and EHR on four dimensions: (1) effectiveness, (2) efficiency, (3) workload, and (4) usability. METHODS: Comparative usability test of Workbench and EHR. Objective test metrics are time per case, encounters reviewed per case, time per encounter, and retrieval of information meeting NHSN definitions. Subjective measures are cognitive load using the National Aeronautics and Space Administration (NASA) Task Load Index (NASA TLX), and a questionnaire on system usability and utility. RESULTS: Eight infection preventionists participated in the test. There was no difference in effectiveness as subjects retrieved information from all cases, using both systems, to meet the NHSN criteria. There was no difference in efficiency in time per case between the Workbench and EHR (8.58 vs. 7.39 minutes, p = 0.36). However, with the Workbench subjects opened fewer encounters per case (3.0 vs. 7.5, p = 0.002), spent more time per encounter (2.23 vs. 0.92 minutes, p = 0.002), rated the Workbench lower in cognitive load (NASA TLX, 24 vs. 33, p = 0.02), and significantly higher in measures of usability. CONCLUSION: Compared with the EHR, the Workbench was more usable, short, and reduced cognitive load. In overall efficiency, the Workbench did not save time, but demonstrated a shift from between-encounter foraging to within-encounter foraging and was rated as significantly more efficient. Our results suggest that infection surveillance can be better supported by systems applying information foraging theory.