Inverse association for diagnosis of Alzheimer's disease subsequent to both melanoma and non-melanoma skin cancers in a large, urban, single-centre, Midwestern US patient population.

BACKGROUND: Although literature demonstrates a decreased risk of Alzheimer's disease (AD) in individuals with various cancers, including squamous cell cancers (SCC) and basal cell cancers (BCC) comprising non-melanoma skin cancers (NMSC), there is a paucity of literature to substantiate an association between malignant melanoma (MM) and AD. OBJECTIVE: The aim of this study was to determine whether an association exists between MM and AD as well as for NMSC and AD. METHODS: A large urban, Midwestern, US, single-centre, medical record (EMR) data repository was searched between January 2001 and December 2015, to identify all patients at age ≥60 and <89 years with a clinic follow-up of at least 1 year and no diagnosis for AD, MM or NMSC at the time of the study entry. Data collected included age, gender, race and duration of follow-up. MM and NMSC were detected by ICD-9 codes and ICD-10 codes. Incident diagnosis of AD was also detected by ICD-9 and ICD-10 codes. Logistic regression analysis was utilized to obtain crude and adjusted odds ratios (ORs). RESULTS: Data for a total of 82 925 patients with known race and gender and were detected. After adjusting for confounding factors (race, gender, age, cerebrovascular disease, peripheral vascular disease and diabetes), there was a significant decreased risk of subsequent AD in patients with MM (OR: 0.39; 95% CI: 0.16-0.96; P = 0.042) as well as in patients with BCC (OR: 0.18; 95% CI: 0.08-0.45; P < 0.0001) and for patients with SCC (OR: 0.08; 95% CI: 0.01-0.56; P = 0.013). CONCLUSION: These findings add to the growing body of evidence for a decreased risk of AD in patients with various cancers and highlight the need for ongoing research to elucidate both neurologic and biologic mechanisms that may underlie this apparent inverse association.

Validation of International Classification of Disease Ninth Revision codes for atopic dermatitis.

BACKGROUND: Evaluation of large-scale data sets is needed to better understand the epidemiology, cost, and burden of atopic dermatitis (AD). We sought to validate the use of ICD-9-CM codes for identifying AD. METHODS: Patients from a large metropolitan quaternary care medical center with a diagnostic code of either 691.8 (AD) or 692.9 (eczema and contact dermatitis) were queried. Medical records were reviewed for demographics, Hanifin & Rajka (H&R) and United Kingdom Working Party (UKWP) criteria. Sensitivity, specificity, and positive predictive values (PPV) of the codes were calculated. RESULTS: Of 43 278 patients identified with associated ICD-9 codes of 691.8 or 692.9, 519 and 253 with 691.8 and 692.9 were randomly selected for chart review. There was extensive overlap: 34.3% had ≥1 occurrences of 691.8 and 692.9 and 25.6% had multiple occurrences of both codes. Among patients with ≥1 occurrence of 691.8, 29.9% and 30.8% met the H&R and UKWP criteria, respectively. Similarly, among patients with ≥1 occurrence of 692.9, 33.7% and 32.2% met the H&R and UKWP criteria. Increased PPV was associated with concomitant diagnoses of asthma, hay fever, and food allergy and increased disease severity. CONCLUSIONS: In the outpatient setting, the ICD-9-CM codes 691.8 and 692.9 alone have poor PPV. Incorporation of diagnoses of asthma, hay fever, and food allergy improves PPV and specificity. In the inpatient setting, a primary discharge diagnosis of 691.8 had excellent PPV. Although ICD-10 has been adopted in Europe and more recently in the USA, the same systematic errors would likely occur unless providers standardize their coding.

The relationship of lithology and watershed characteristics to fine sediment deposition in streams of the Oregon coast range.

Lithology is one of many factors influencing the amount, grain size distribution, and location of fine sediment deposition on the bed of mountain stream channels. In the Oregon Coast Range, 18 pool-riffle stream reaches with similar slope and intact riparian area and relatively unaffected by logjams were surveyed for assessment of fine sediment deposition. Half of the streams were in watersheds underlain by relatively erodible sandstone. The other half were underlain by a more resistant basalt. Channel morphology, hydraulic variables, particle size, relative pool volume of fine sediment (V*), and wood characteristics were measured in the streams. A significantly higher amount of fine sediment was deposited in the sandstone channels than in the basalt channels, as indicated by V*. Grab samples of sediment from pools also were significantly finer grained in the sandstone channels. Geographic information systems (GIS) software was used to derive several variables that might correlate with fine sediment deposition. These variables were combined with those derived from field data to create multiple linear regression models to be used for further exploration of the type and relative influence of factors affecting fine sediment deposition. Lithology appeared to be significant in some of these models, but usually was not the primary driver. The results from these models indicate that V* at the reach scale is best explained by stream power per unit area and by the volume of wood perpendicular to the flow per channel area (R(2) = 0.46). Findings show that V* is best explained using only watershed scale variables, including negative correlations with relief ratio and basin precipitation index, and positive correlations with maximum slope and circularity.