Background. Legionnaires' disease cannot be clinically or radiographically distinguished from other causes of pneumonia, and specific tests are required to make the diagnosis. Currently, testing ...occurs erratically and, instead, clinicians rely on empiric treatment strategies and ignore public health implications of the diagnosis. We aimed to measure the increase in case detection of Legionnaires' disease following the introduction of routine polymerase chain reaction (PCR) testing of respiratory specimens. PCR is the most sensitive diagnostic tool for Legionnaires' disease. Methods. In a quasi-experimental study in Christchurch, New Zealand, we compared the number of cases of Legionnaires' disease requiring hospitalization diagnosed during a 2-year period before the introduction of a routine PCR testing strategy (November 2008–October 2010) with a similar period after the introduction (November 2010–October 2012). With this testing strategy, all respiratory specimens from hospitalized patients with pneumonia sent to the region's sole tertiary-level laboratory were tested for Legionella by PCR, whether requested or not. Results. During November 2008 to October 2010, there were 22 cases of Legionnaires' disease compared with 92 during November 2010 to October 2012. Of 1834 samples tested since November 2010, 1 in 20 was positive, increasing to 1 in 9 during peak Legionella season (November to January). Increasing bacterial load was associated with increasing disease severity. Conclusions. In our region, the burden of Legionnaires' disease is much greater than was previously recognized. Routine PCR testing provides results within a clinically relevant time frame and enables improved characterization of the regional epidemiology of Legionnaires' disease.
Aims
This study examined how family, peer and school factors are related to different trajectories of adolescent alcohol use at key developmental periods.
Design
Latent class growth analysis was used ...to identify trajectories based on five waves of data (from grade 6, age 12 to grade 11, age 17), with predictors at grades 5, 7 and 9 included as covariates.
Setting
Adolescents completed surveys during school hours.
Participants
A total of 808 students in Victoria, Australia.
Measurements
Alcohol use trajectories were based on self‐reports of 30‐day frequency of alcohol use. Predictors included sibling alcohol use, attachment to parents, parental supervision, parental attitudes favourable to adolescent alcohol use, peer alcohol use and school commitment.
Findings
A total of 8.2% showed steep escalation in alcohol use. Relative to non‐users, steep escalators were predicted by age‐specific effects for low school commitment at grade 7 (P = 0.031) and parental attitudes at grade 5 (P = 0.003), and age‐generalized effects for sibling alcohol use (Ps = 0.001, 0.012, 0.033 at grades 5, 7 and 9, respectively) and peer alcohol use (Ps = 0.041, < 0.001, < 0.001 at grades 5, 7 and 9, respectively). Poor parental supervision was associated with steep escalators at grade 9 (P < 0.001) but not the other grades. Attachment to parents was unrelated to alcohol trajectories.
Conclusions
Parental disapproval of alcohol use before transition to high school, low school commitment at transition to high school, and sibling and peer alcohol use during adolescence are associated with a higher risk of steep escalations in alcohol use.
Reply to Boethel et al Murdoch, David R.; Podmore, Roslyn G.; Anderson, Trevor P. ...
Clinical infectious diseases,
11/2014, Letnik:
59, Številka:
10
Journal Article
Abstract Background Lyme disease (LD) is the fifth most reported notifiable disease in the US, but the true disease burden remains unknown due to inconsistent reporting. Claims-based algorithms ...estimate a ≥10-fold higher incidence compared to notifiable-disease surveillance, but these algorithms are unvalidated. Methods We evaluated a claims-based LD algorithm based on ICD codes (ICD-9-CM 088.81 or ICD-10-CM A69.2X) and a ≥7-day course of an antibiotic used to treat LD dispensed ±30 days of diagnosis. We applied the LD algorithm to Harvard Pilgrim Health Care (HPHC) claims data for Massachusetts (MA) residents. We sought health records for patients who met the algorithm between Jan 2015 and June 2019 and received care within the Massachusetts General Brigham (MGB) system at diagnosis. Three clinicians received training on case classification and conducted chart abstractions and adjudications. Cases were classified as confirmed, probable, suspect, or ruled out using 2017 CDC case definitions. To assess inter-rater reliability, the clinicians abstracted and adjudicated the same 20 charts; we computed the mean of kappa for each clinician-pair. We calculated the positive predictive value (PPV) of the algorithm for identifying confirmed, probable, or suspect LD cases, all of which required at least erythema migrans (EM) or clinical diagnosis with confirmatory serology and antibiotics prescription. Results We identified 11,823 HPHC members who met the LD algorithm. Of these members, 171 cases occurred within the study period among MGB patients; we obtained 128 (75%) patients’ charts for review. The average weighted kappa statistic of adjudicator agreement was 0.94. Of the reviewed charts, 103 (80.5%) were adults ≥ 18 years old. 71 patients (55.5%) were clinically diagnosed with LD, among whom 62 (48.4%) presented with EM rash. 24 reviewed cases (18.8%) had laboratory-confirmed LD. LD was ruled out for 8 cases. The overall algorithm PPV was 93.8% (95% CI 89.6-97.9%). Limited to confirmed and probable cases only, the PPV was 66.4% (95% CI 57.5-74.5%). Conclusion A claims-based algorithm combining diagnosis codes and antibiotic prescriptions identified LD cases in MA with high PPV. This algorithm could be used to describe the incidence of LD in regions with similar diagnostic, treatment, and coding practices. Disclosures Sheryl A. Kluberg, PhD, SM, GlaxoSmithKline: Grant/Research Support|Pfizer, Inc.: Support for the project described in the abstract Sarah J. Willis, PhD, MPH, Pfizer: Employment|Pfizer: Conducted Pfizer funded research while employed by Harvard Pilgrim Health Care Institute Noelle M. Cocoros, DSc, MPH, Pfizer: PI on study Bradford D. Gessner, M.D., M.P.H., Pfizer Inc.: Employee|Pfizer Inc.: Stocks/Bonds Sarah J. Pugh, PhD, MPH, Pfizer, Inc: Employee|Pfizer, Inc: Stocks/Bonds James H. Stark, PhD, Pfizer: Employee|Pfizer: Stocks/Bonds Chanu Rhee, MD, MPH, Cytovale: Advisor/Consultant|Pfizer: Advisor/Consultant|UpToDate, Inc.: Royalties.
Exhaled breath contains more than 1000 constituents at trace level concentrations, with a wide variety of these compounds potentially serving as biomarkers for specific diseases, physiologic status, ...or therapeutic progress. Some of the compounds in exhaled breath (EB) are well studied, and their relationship with disease pathologies is well established. However, molecularly specific analysis of such biomarkers in EB at clinically relevant levels remains an analytical and practical challenge due to the low levels of such biomarkers frequently below the ppb (v/v) range in EB. In this contribution, mid-infrared (MIR) spectroscopic sensing techniques are reviewed for potential application in breath diagnostics. While the spectral regime from 3-20 ¿m has already been utilized for fundamental studies on breath analysis, significant further improvements are in demand for substantiating MIR spectroscopy and sensing techniques as a suitable candidate for clinically deployable breath analyzers. Several advantageous features including inherent molecular selectivity, real-time monitoring capability, comparable ease of operation, potentially low costs, and a compact device footprint promise reliable optical diagnostics in the MIR. Hence, while the application of MIR spectroscopy and sensing systems to breath analysis yet appear in their infancy, recent progress on advanced MIR light sources, waveguides, and device concepts forecasts next-generation optical sensing platforms suitable for addressing the challenges of in situ breath diagnostics.
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