Adi V. Gundlapalli

Germline Mutations in NFKB2 Implicate the Noncanonical NF-κB Pathway in the Pathogenesis of Common Variable Immunodeficiency

Common variable immunodeficiency (CVID) is a heterogeneous disorder characterized by antibody deficiency, poor humoral response to antigens, and recurrent infections. To investigate the molecular cause of CVID, we carried out exome sequence analysis of a family diagnosed with CVID and identified a heterozygous frameshift mutation, c.2564delA (p.Lys855Serfs(∗)7), in NFKB2 affecting the C terminus of NF-κB2 (also known as p100/p52 or p100/p49). Subsequent screening of NFKB2 in 33 unrelated CVID-affected individuals uncovered a second heterozygous nonsense mutation, c.2557C>T (p.Arg853(∗)), in one simplex case. Affected individuals in both families presented with an unusual combination of childhood-onset hypogammaglobulinemia with recurrent infections, autoimmune features, and adrenal insufficiency. NF-κB2 is the principal protein involved in the noncanonical NF-κB pathway, is evolutionarily conserved, and functions in peripheral lymphoid organ development, B cell development, and antibody production. In addition, Nfkb2 mouse models demonstrate a CVID-like phenotype with hypogammaglobulinemia and poor humoral response to antigens. Immunoblot analysis and immunofluorescence microscopy of transformed B cells from affected individuals show that the NFKB2 mutations affect phosphorylation and proteasomal processing of p100 and, ultimately, p52 nuclear translocation. These findings describe germline mutations in NFKB2 and establish the noncanonical NF-κB signaling pathway as a genetic etiology for this primary immunodeficiency syndrome.

Dissemination and sustainability of a hospital-wide hand hygiene program emphasizing positive reinforcement.

OBJECTIVE To increase and sustain hospital-wide compliance with hand hygiene through a long-term ongoing multidimensional improvement program emphasizing behavioral factors. DESIGN Quasi-experimental short study (August 2000-November 2001) and descriptive time series (April 2003-December 2006). SETTING A 450-bed teaching tertiary-care hospital. INTERVENTIONS An initial intervention bundle was introduced in pilot locations that addressed cognitive behavioral factors, which included access to alcohol sanitizer, education, and ongoing audit and feedback. The bundle was subsequently disseminated hospital-wide, along with a novel approach focused on behavior modification through positive reinforcement and annually changing incentives. RESULTS A total of 36,123 hand hygiene opportunities involving all categories of healthcare workers from 12 inpatient units were observed from October 2000 to October 2006. The rate of compliance with hand hygiene significantly improved after the intervention in 2 cohorts over the first year (from 40% to 64% of opportunities and from 34% to 49% of opportunities;P <.001, compared with the control group). Mean compliance rates ranged from 19% to 41% of 4174 opportunities (at baseline), increased to the highest levels of 73%-84% of 6,420 opportunities 2 years after hospital-wide dissemination, and remained improved at 59%-81% of 4,990 opportunities during year 6 of the program. CONCLUSION This interventional cohort study used a behavioral change approach and is one of the earliest and largest institution-wide programs promoting alcohol sanitizer from the United States that has shown significant and sustained improvements in hand hygiene compliance. This creative campaign used ongoing frequent audit and feedback with novel use of immediate positive reinforcement at an acceptable cost to the institution.

Perspectives and concerns regarding antimicrobial agent shortages among infectious disease specialists

Antimicrobial shortages have made treating certain infections more difficult. A web-based survey asking about experience with antimicrobial drug shortages was distributed in 2011 to 1328 infectious diseases physician members of the Emerging Infectious Diseases Network of the Infectious Diseases Society of America. A majority (78%) of 627 respondents reported needing to modify antimicrobial choices because of drug shortages within the past 2 years. Antimicrobials most often reported as not available or available but in short supply were trimethoprim-sulfamethoxazole injection (by 65% of respondents), amikacin (by 58%), aztreonam (by 31%), and foscarnet (by 22%). Most respondents (55%) reporting a shortage indicated that the shortage adversely affected patient outcomes and that they were forced to use alternative and second line agents which were either less effective, more toxic, or more costly. Most (70%) indicated that they learned about the shortage from contact with the pharmacy after trying to prescribe a drug in short supply. More effective means of informing physicians about drug shortages is critical to lessen the impact on patient care.

Developing a manually annotated clinical document corpus to identify phenotypic information for inflammatory bowel disease.

BackgroundNatural Language Processing (NLP) systems can be used for specific Information Extraction (IE) tasks such as extracting phenotypic data from the electronic medical record (EMR). These data are useful for translational research and are often found only in free text clinical notes. A key required step for IE is the manual annotation of clinical corpora and the creation of a reference standard for (1) training and validation tasks and (2) to focus and clarify NLP system requirements. These tasks are time consuming, expensive, and require considerable effort on the part of human reviewers.MethodsUsing a set of clinical documents from the VA EMR for a particular use case of interest we identify specific challenges and present several opportunities for annotation tasks. We demonstrate specific methods using an open source annotation tool, a customized annotation schema, and a corpus of clinical documents for patients known to have a diagnosis of Inflammatory Bowel Disease (IBD). We report clinician annotator agreement at the document, concept, and concept attribute level. We estimate concept yield in terms of annotated concepts within specific note sections and document types.ResultsAnnotator agreement at the document level for documents that contained concepts of interest for IBD using estimated Kappa statistic (95% CI) was very high at 0.87 (0.82, 0.93). At the concept level, F-measure ranged from 0.61 to 0.83. However, agreement varied greatly at the specific concept attribute level. For this particular use case (IBD), clinical documents producing the highest concept yield per document included GI clinic notes and primary care notes. Within the various types of notes, the highest concept yield was in sections representing patient assessment and history of presenting illness. Ancillary service documents and family history and plan note sections produced the lowest concept yield.ConclusionChallenges include defining and building appropriate annotation schemas, adequately training clinician annotators, and determining the appropriate level of information to be annotated. Opportunities include narrowing the focus of information extraction to use case specific note types and sections, especially in cases where NLP systems will be used to extract information from large repositories of electronic clinical note documents.

It Takes a Village: A Multidisciplinary Model for the Acute Illness Aftercare of Individuals Experiencing Homelessness

Homeless individuals are often uninsured and are more likely than the housed to utilize acute health care services and experience longer hospitalizations. Currently in the United States, there are fragmented services available for the aftercare of these patients to ensure continuum of care, promote healing, and avoid re-entry into the acute care system. The Fourth Street Clinic Respite Program was created to address these issues. Patients are referred to the program from local hospitals and other service providers. Based on the acuity of illness and need for nursing care, patients are admitted to one of four programs: (1) Shelter-based Day Bed Program, (2) Temporary Emergency Housing (Motel) Program, (3) Tuberculosis Housing Program, or (4) Nursing Home Program. Aftercare patients receive medical, social, and behavioral health services and are discharged to local shelters when stable. The aftercare program provides a safe refuge for recovery from acute illnesses for those experiencing homelessness.

Quantitative Models of the Dose-Response and Time Course of Inhalational Anthrax in Humans

Anthrax poses a community health risk due to accidental or intentional aerosol release. Reliable quantitative dose-response analyses are required to estimate the magnitude and timeline of potential consequences and the effect of public health intervention strategies under specific scenarios. Analyses of available data from exposures and infections of humans and non-human primates are often contradictory. We review existing quantitative inhalational anthrax dose-response models in light of criteria we propose for a model to be useful and defensible. To satisfy these criteria, we extend an existing mechanistic competing-risks model to create a novel Exposure–Infection–Symptomatic illness–Death (EISD) model and use experimental non-human primate data and human epidemiological data to optimize parameter values. The best fit to these data leads to estimates of a dose leading to infection in 50% of susceptible humans (ID50) of 11,000 spores (95% confidence interval 7,200–17,000), ID10 of 1,700 (1,100–2,600), and ID1 of 160 (100–250). These estimates suggest that use of a threshold to human infection of 600 spores (as suggested in the literature) underestimates the infectivity of low doses, while an existing estimate of a 1% infection rate for a single spore overestimates low dose infectivity. We estimate the median time from exposure to onset of symptoms (incubation period) among untreated cases to be 9.9 days (7.7–13.1) for exposure to ID50, 11.8 days (9.5–15.0) for ID10, and 12.1 days (9.9–15.3) for ID1. Our model is the first to provide incubation period estimates that are independently consistent with data from the largest known human outbreak. This model refines previous estimates of the distribution of early onset cases after a release and provides support for the recommended 60-day course of prophylactic antibiotic treatment for individuals exposed to low doses.

Modeling the variations in pediatric respiratory syncytial virus seasonal epidemics

BackgroundSeasonal respiratory syncytial virus (RSV) epidemics occur annually in temperate climates and result in significant pediatric morbidity and increased health care costs. Although RSV epidemics generally occur between October and April, the size and timing vary across epidemic seasons and are difficult to predict accurately. Prediction of epidemic characteristics would support management of resources and treatment.MethodsThe goals of this research were to examine the empirical relationships among early exponential growth rate, total epidemic size, and timing, and the utility of specific parameters in compartmental models of transmission in accounting for variation among seasonal RSV epidemic curves. RSV testing data from Primary Childrens Medical Center were collected on children under two years of age (July 2001-June 2008). Simple linear regression was used explore the relationship between three epidemic characteristics (final epidemic size, days to peak, and epidemic length) and exponential growth calculated from four weeks of daily case data. A compartmental model of transmission was fit to the data and parameter estimated used to help describe the variation among seasonal RSV epidemic curves.ResultsThe regression results indicated that exponential growth was correlated to epidemic characteristics. The transmission modeling results indicated that start time for the epidemic and the transmission parameter co-varied with the epidemic season.ConclusionsThe conclusions were that exponential growth was somewhat empirically related to seasonal epidemic characteristics and that variation in epidemic start date as well as the transmission parameter over epidemic years could explain variation in seasonal epidemic size. These relationships are useful for public health, health care providers, and infectious disease researchers.

Identifying homelessness among veterans using VA administrative data: Opportunities to expand detection criteria

Researchers at the U.S. Department of Veterans Affairs (VA) have used administrative criteria to identify homelessness among U.S. Veterans. Our objective was to explore the use of these codes in VA health care facilities. We examined VA health records (2002-2012) of Veterans recently separated from the military and identified as homeless using VA conventional identification criteria (ICD-9-CM code V60.0, VA specific codes for homeless services), plus closely allied V60 codes indicating housing instability. Logistic regression analyses examined differences between Veterans who received these codes. Health care services and co-morbidities were analyzed in the 90 days post-identification of homelessness. VA conventional criteria identified 21,021 homeless Veterans from Operations Enduring Freedom, Iraqi Freedom, and New Dawn (rate 2.5%). Adding allied V60 codes increased that to 31,260 (rate 3.3%). While certain demographic differences were noted, Veterans identified as homeless using conventional or allied codes were similar with regards to utilization of homeless, mental health, and substance abuse services, as well as co-morbidities. Differences were noted in the pattern of usage of homelessness-related diagnostic codes in VA facilities nation-wide. Creating an official VA case definition for homelessness, which would include additional ICD-9-CM and other administrative codes for VA homeless services, would likely allow improved identification of homeless and at-risk Veterans. This also presents an opportunity for encouraging uniformity in applying these codes in VA facilities nationwide as well as in other large health care organizations.

Drugs of Last Resort? The Use of Polymyxins and Tigecycline at US Veterans Affairs Medical Centers, 2005–2010

Multidrug-resistant (MDR) and carbapenem-resistant (CR) Gram-negative pathogens are becoming increasingly prevalent around the globe. Polymyxins and tigecycline are among the few antibiotics available to treat infections with these bacteria but little is known about the frequency of their use. We therefore aimed to estimate the parenteral use of these two drugs in Veterans Affairs medical centers (VAMCs) and to describe the pathogens associated with their administration. For this purpose we retrospectively analyzed barcode medication administration data of parenteral administrations of polymyxins and tigecycline in 127 acute-care VAMCs between October 2005 and September 2010. Overall, polymyxin and tigecycline use were relatively low at 0.8 days of therapy (DOT)/1000 patient days (PD) and 1.6 DOT/1000PD, respectively. Use varied widely across facilities, but increased overall during the study period. Eight facilities accounted for three-quarters of all polymyxin use. The same statistic for tigecycline use was twenty-six VAMCs. There were 1,081 MDR or CR isolates during 747 hospitalizations associated with polymyxin use (1.4/hospitalization). For tigecycline these number were slightly lower: 671 MDR or CR isolates during 500 hospitalizations (1.3/hospitalization) (p = 0.06). An ecological correlation between the two antibiotics and combined CR and MDR Gram-negative isolates per 1000PD during the study period was also observed (Pearson’s correlation coefficient r = 0.55 polymyxin, r = 0.19 tigecycline). In summary, while polymyxin and tigecycline use is low in most VAMCs, there has been an increase over the study period. Polymyxin use in particular is associated with the presence of MDR Gram-negative pathogens and may be useful as a surveillance measure in the future.

The role of heterogeneity in contact timing and duration in network models of influenza spread in schools

Influenza poses a significant health threat to children, and schools may play a critical role in community outbreaks. Mathematical outbreak models require assumptions about contact rates and patterns among students, but the level of temporal granularity required to produce reliable results is unclear. We collected objective contact data from students aged 5–14 at an elementary school and middle school in the state of Utah, USA, and paired those data with a novel, data-based model of influenza transmission in schools. Our simulations produced within-school transmission averages consistent with published estimates. We compared simulated outbreaks over the full resolution dynamic network with simulations on networks with averaged representations of contact timing and duration. For both schools, averaging the timing of contacts over one or two school days caused average outbreak sizes to increase by 1–8%. Averaging both contact timing and pairwise contact durations caused average outbreak sizes to increase by 10% at the middle school and 72% at the elementary school. Averaging contact durations separately across within-class and between-class contacts reduced the increase for the elementary school to 5%. Thus, the effect of ignoring details about contact timing and duration in school contact networks on outbreak size modelling can vary across different schools.