Use of diuretics and risk of incident gout: a population-based case-control study

OBJECTIVE Use of diuretics has been associated with an increased risk of gout. Data on different types of diuretics are scarce. We undertook this study to investigate the association between use of loop diuretics, thiazide or thiazide-like diuretics, and potassium-sparing agents and the risk of developing incident gout. METHODS We conducted a retrospective population-based case-control analysis using the General Practice Research Database established in the UK. We identified case patients who were diagnosed as having incident gout between 1990 and 2010. One control patient was matched to each case patient for age, sex, general practice, calendar time, and years of active history in the database. We used conditional logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs), and we adjusted for potential confounders. RESULTS We identified 91,530 incident cases of gout and the same number of matched controls. Compared to past use of diuretics from each respective drug class, adjusted ORs for current use of loop diuretics, thiazide diuretics, thiazide-like diuretics, and potassium-sparing diuretics were 2.64 (95% CI 2.47-2.83), 1.70 (95% CI 1.62-1.79), 2.30 (95% CI 1.95-2.70), and 1.06 (95% CI 0.91-1.23), respectively. Combined use of loop diuretics and thiazide diuretics was associated with the highest relative risk estimates of gout (adjusted OR 4.65 [95% CI 3.51-6.16]). Current use of calcium channel blockers or losartan slightly attenuated the risk of gout in patients who took diuretics. CONCLUSION Use of loop diuretics, thiazide diuretics, and thiazide-like diuretics was associated with an increased risk of incident gout, although use of potassium-sparing agents was not.

Poorly controlled type 2 diabetes mellitus is associated with a decreased risk of incident gout: a population-based case-control study

OBJECTIVE The aim of this study was to explore the risk of incident gout in patients with type 2 diabetes mellitus (T2DM) in association with diabetes duration, diabetes severity and antidiabetic drug treatment. METHODS We conducted a case-control study in patients with T2DM using the UK-based Clinical Practice Research Datalink (CPRD). We identified case patients aged ≥18 years with an incident diagnosis of gout between 1990 and 2012. We matched to each case patient one gout-free control patient. We used conditional logistic regression analysis to calculate adjusted ORs (adj. ORs) with 95% CIs and adjusted our analyses for important potential confounders. RESULTS The study encompassed 7536 T2DM cases with a first-time diagnosis of gout. Compared to a diabetes duration <1 year, prolonged diabetes duration (1-3, 3-6, 7-9 and ≥10 years) was associated with decreased adj. ORs of 0.91 (95% CI 0.79 to 1.04), 0.76 (95% CI 0.67 to 0.86), 0.70 (95% CI 0.61 to 0.86), and 0.58 (95% CI 0.51 to 0.66), respectively. Compared to a reference A1C level of <7%, the risk estimates of increasing A1C levels (7.0-7.9, 8.0-8.9 and ≥9%) steadily decreased with adj. ORs of 0.79 (95% CI 0.72 to 0.86), 0.63 (95% CI 0.55 to 0.72), and 0.46 (95% CI 0.40 to 0.53), respectively. Neither use of insulin, metformin, nor sulfonylureas was associated with an altered risk of incident gout. CONCLUSIONS Increased A1C levels, but not use of antidiabetic drugs, was associated with a decreased risk of incident gout among patients with T2DM.

Cancer risk and use of protease inhibitor or nonnucleoside reverse transcriptase inhibitor-based combination antiretroviral therapy: the d: a: d study.

BACKGROUND The association between combination antiretroviral therapy (cART) and cancer risk, especially regimens containing protease inhibitors (PIs) or nonnucleoside reverse transcriptase inhibitors (NNRTIs), is unclear. METHODS Participants were followed from the latest of D:A:D study entry or January 1, 2004, until the earliest of a first cancer diagnosis, February 1, 2012, death, or 6 months after the last visit. Multivariable Poisson regression models assessed associations between cumulative (per year) use of either any cART or PI/NNRTI, and the incidence of any cancer, non-AIDS-defining cancers (NADC), AIDS-defining cancers (ADC), and the most frequently occurring ADC (Kaposi sarcoma, non-Hodgkin lymphoma) and NADC (lung, invasive anal, head/neck cancers, and Hodgkin lymphoma). RESULTS A total of 41,762 persons contributed 241,556 person-years (PY). A total of 1832 cancers were diagnosed [incidence rate: 0.76/100 PY (95% confidence interval: 0.72 to 0.79)], 718 ADC [0.30/100 PY (0.28-0.32)], and 1114 NADC [0.46/100 PY (0.43-0.49)]. Longer exposure to cART was associated with a lower ADC risk [adjusted rate ratio: 0.88/year (0.85-0.92)] but a higher NADC risk [1.02/year (1.00-1.03)]. Both PI and NNRTI use were associated with a lower ADC risk [PI: 0.96/year (0.92-1.00); NNRTI: 0.86/year (0.81-0.91)]. PI use was associated with a higher NADC risk [1.03/year (1.01-1.05)]. Although this was largely driven by an association with anal cancer [1.08/year (1.04-1.13)], the association remained after excluding anal cancers from the end point [1.02/year (1.01-1.04)]. No association was seen between NNRTI use and NADC [1.00/year (0.98-1.02)]. CONCLUSIONS Cumulative use of PIs may be associated with a higher risk of anal cancer and possibly other NADC. Further investigation of biological mechanisms is warranted.

Copeptin Is Associated with Kidney Length, Renal Function, and Prevalence of Simple Cysts in a Population-Based Study.

Arginine vasopressin (AVP) has a key role in osmoregulation by facilitating water transport in the collecting duct. Recent evidence suggests that AVP may have additional effects on renal function and favor cyst growth in polycystic kidney disease. Whether AVP also affects kidney structure in the general population is unknown. We analyzed the association of copeptin, an established surrogate for AVP, with parameters of renal function and morphology in a multicentric population-based cohort. Participants from families of European ancestry were randomly selected in three Swiss cities. We used linear multilevel regression analysis to explore the association of copeptin with renal function parameters as well as kidney length and the presence of simple renal cysts assessed by ultrasound examination. Copeptin levels were log-transformed. The 529 women and 481 men had median copeptin levels of 3.0 and 5.2 pmol/L, respectively (P<0.001). In multivariable analyses, the copeptin level was associated inversely with eGFR (β=-2.1; 95% confidence interval [95% CI], -3.3 to -0.8; P=0.002) and kidney length (β=-1.2; 95% CI, -1.9 to -0.4; P=0.003) but positively with 24-hour urinary albumin excretion (β=0.11; 95% CI, 0.01 to 0.20; P=0.03) and urine osmolality (β=0.08; 95% CI, 0.05 to 0.10; P<0.001). A positive association was found between the copeptin level and the presence of renal cysts (odds ratio, 1.6; 95% CI, 1.1 to 2.4; P=0.02). These results suggest that AVP has a pleiotropic role in renal function and may favor the development of simple renal cysts.

New anthropometry-based age- and sex-specific reference values for urinary 24-hour creatinine excretion based on the adult Swiss population.

BACKGROUND Urinary creatinine excretion is used as a marker of completeness of timed urine collections, which are a keystone of several metabolic evaluations in clinical investigations and epidemiological surveys. The current reference values for 24-hour urinary creatinine excretion rely on observations performed in the 1960s and 1970s in relatively small and mostly selected groups, and may thus poorly fit to the present-day general European population. The aim of this study was to establish and validate anthropometry-based age- and sex-specific reference values of the 24-hour urinary creatinine excretion on adult populations with preserved renal function. METHODS We used data from two independent Swiss cross-sectional population-based studies with standardised 24-hour urinary collection and measured anthropometric variables. Only data from adults of European descent, with estimated glomerular filtration rate (eGFR) ≥60 ml/min/1.73 m(2) and reported completeness of the urinary collection were retained. A linear regression model was developed to predict centiles of the 24-hour urinary creatinine excretion in 1,137 participants from the Swiss Survey on Salt and validated in 994 participants from the Swiss Kidney Project on Genes in Hypertension. RESULTS The mean urinary creatinine excretion was 193 ± 41 μmol/kg/24 hours in men and 151 ± 38 μmol/kg/24 hours in women in the Swiss Survey on Salt. The values were inversely correlated with age and body mass index (BMI). Based on current reference values (177 to 221 μmol/kg/24 hours in men and 133 to 177 μmol/kg/24 hours in women), 56% of the urinary collections in the whole population and 67% in people >60 years old would have been considered as inaccurate. A linear regression model with sex, BMI and age as predictor variables was found to provide the best prediction of the observed values and showed a good fit when applied to the validation population. CONCLUSIONS We propose a validated prediction equation for 24-hour urinary creatinine excretion in the general European population, based on readily available variables such as age, sex and BMI, and a few derived normograms to ease its clinical application. This should help healthcare providers to interpret the completeness of a 24-hour urine collection in daily clinical practice and in epidemiological population studies.

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.

Associations between mood, anxiety or substance use disorders and inflammatory markers after adjustment for multiple covariates in a population-based study.

Inflammation is one possible mechanism underlying the associations between mental disorders and cardiovascular diseases (CVD). However, studies on mental disorders and inflammation have yielded inconsistent results and the majority did not adjust for potential confounding factors. We examined the associations of several pro-inflammatory cytokines (IL-1β, IL-6 and TNF-α) and high sensitive C-reactive protein (hsCRP) with lifetime and current mood, anxiety and substance use disorders (SUD), while adjusting for multiple covariates. The sample included 3719 subjects, randomly selected from the general population, who underwent thorough somatic and psychiatric evaluations. Psychiatric diagnoses were made with a semi-structured interview. Major depressive disorder was subtyped into "atypical", "melancholic", "combined atypical-melancholic" and "unspecified". Associations between inflammatory markers and psychiatric diagnoses were assessed using multiple linear and logistic regression models. Lifetime bipolar disorders and atypical depression were associated with increased levels of hsCRP, but not after multivariate adjustment. After multivariate adjustment, SUD remained associated with increased hsCRP levels in men (β = 0.13 (95% CI: 0.03,0.23)) but not in women. After multivariate adjustment, lifetime combined and unspecified depression were associated with decreased levels of IL-6 (β = -0.27 (-0.51,-0.02); β = -0.19 (-0.34,-0.05), respectively) and TNF-α (β = -0.16 (-0.30,-0.01); β = -0.10 (-0.19,-0.02), respectively), whereas current combined and unspecified depression were associated with decreased levels of hsCRP (β = -0.20 (-0.39,-0.02); β = -0.12 (-0.24,-0.01), respectively). Our data suggest that the significant associations between increased hsCRP levels and mood disorders are mainly attributable to the effects of comorbid disorders, medication as well as behavioral and physical CVRFs.

Survival after somatostatin based radiopeptide therapy with (90)Y-DOTATOC vs. (90)Y-DOTATOC plus (177)Lu-DOTATOC in metastasized gastrinoma.

We aimed to explore the effects of (90)Y-DOTATOC and (90)Y-DOTATOC plus (177)Lu-DOTATOC on survival of patients with metastasized gastrinoma. Patients with progressive metastasized gastrinoma were treated with repeated cycles of (90)Y-DOTATOC or with cycles alternating between (90)Y-DOTATOC and (177)Lu-DOTATOC until tumor progression or permanent toxicity. Multivariable Cox regression analyses were used to study predictors of survival. A total of 36 patients were enrolled; 30 patients received (90)Y-DOTATOC (median activity per patient 11.8GBq; range: 6.1-62.2GBq) and 6 patients received (90)Y-DOTATOC plus (177)Lu-DOTATOC (median activity per patient: 14.8GBq; range: 7.4-14.8GBq). Response was found in 26 patients (72.2%), including morphological (n=12, 33.3%), biochemical (n=14, 38.9%) and/or clinical response (n=6, 16.2%). A total of 21 patients (58.3%) experienced hematotoxicity grade 1/2, while 1 patient (2.8%) experienced hematotoxicity grade 3; no grade 4 hematotoxicity occurred. Furthermore, 2 patients (5.6%) developed grade 4 renal toxicity; no grade 5 renal toxicity occurred. Responders had a significantly longer median survival from time of enrollment than non-responders (45.1 months, range: 37.1-53.1 months vs. 12.6 months, range: 11.0-14.2, hazard ratio: 0.12 (0.027-0.52), p=0.005). Additionally, there was a trend towards longer median survival with (90)Y-DOTATOC plus (177)Lu-DOTATOC as compared to (90)Y-DOTATOC alone (60.2 months, range: 19.8-100.6 months vs. 27.0 months, range: 4.0-50.0, hazard ratio: 0.21 (0.01-3.98), p=0.16). Response to (90)Y-DOTATOC and (90)Y-DOTATOC plus (177)Lu-DOTATOC therapy is associated with a longer survival in patients with metastasized gastrinoma. Both treatment regimens are promising tools for management of progressive gastrinoma.

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.

A Passive WiFi Source Localization System based on Fine-grained Power-based Trilateration

Indoor localization systems become more interesting for researchers because of the attractiveness of business cases in various application fields. A WiFi-based passive localization system can provide user location information to third-party providers of positioning services. However, indoor localization techniques are prone to multipath and Non-Line Of Sight (NLOS) propagation, which lead to significant performance degradation. To overcome these problems, we provide a passive localization system for WiFi targets with several improved algorithms for localization. Through Software Defined Radio (SDR) techniques, we extract Channel Impulse Response (CIR) information at the physical layer. CIR is later adopted to mitigate the multipath fading problem. We propose to use a Nonlinear Regression (NLR) method to relate the filtered power information to propagation distances, which significantly improves the ranging accuracy compared to the commonly used log-distance path loss model. To mitigate the influence of ranging errors, a new trilateration algorithm is designed as well by combining Weighted Centroid and Constrained Weighted Least Square (WC-CWLS) algorithms. Experiment results show that our algorithm is robust against ranging errors and outperforms the linear least square algorithm and weighted centroid algorithm.

A chrysophyte-based quantitative reconstruction of winter severity from varved lake sediments in NE Poland during the past millennium and its relationship to natural climate variability

Chrysophyte cysts are recognized as powerful proxies of cold-season temperatures. In this paper we use the relationship between chrysophyte assemblages and the number of days below 4 °C (DB4 °C) in the epilimnion of a lake in northern Poland to develop a transfer function and to reconstruct winter severity in Poland for the last millennium. DB4 °C is a climate variable related to the length of the winter. Multivariate ordination techniques were used to study the distribution of chrysophytes from sediment traps of 37 low-land lakes distributed along a variety of environmental and climatic gradients in northern Poland. Of all the environmental variables measured, stepwise variable selection and individual Redundancy analyses (RDA) identified DB4 °C as the most important variable for chrysophytes, explaining a portion of variance independent of variables related to water chemistry (conductivity, chlorides, K, sulfates), which were also important. A quantitative transfer function was created to estimate DB4 °C from sedimentary assemblages using partial least square regression (PLS). The two-component model (PLS-2) had a coefficient of determination of View the MathML sourceRcross2 = 0.58, with root mean squared error of prediction (RMSEP, based on leave-one-out) of 3.41 days. The resulting transfer function was applied to an annually-varved sediment core from Lake Żabińskie, providing a new sub-decadal quantitative reconstruction of DB4 °C with high chronological accuracy for the period AD 1000–2010. During Medieval Times (AD 1180–1440) winters were generally shorter (warmer) except for a decade with very long and severe winters around AD 1260–1270 (following the AD 1258 volcanic eruption). The 16th and 17th centuries and the beginning of the 19th century experienced very long severe winters. Comparison with other European cold-season reconstructions and atmospheric indices for this region indicates that large parts of the winter variability (reconstructed DB4 °C) is due to the interplay between the oscillations of the zonal flow controlled by the North Atlantic Oscillation (NAO) and the influence of continental anticyclonic systems (Siberian High, East Atlantic/Western Russia pattern). Differences with other European records are attributed to geographic climatological differences between Poland and Western Europe (Low Countries, Alps). Striking correspondence between the combined volcanic and solar forcing and the DB4 °C reconstruction prior to the 20th century suggests that winter climate in Poland responds mostly to natural forced variability (volcanic and solar) and the influence of unforced variability is low.

Migration and population expansion of Abies, Fagus, Picea, and Quercus since 15000 years in and across the Alps, based on pollen-percentage threshold values

Aims: The aim of this study is to explore the migration (colonization of new areas) and subsequent population expansion (within an area) since 15 ka cal BP of Abies, Fagus, Picea, and Quercus into and through the Alps solely on the basis of high-quality pollen data. Methods: Chronologies of 101 pollen sequences are improved or created. Data from the area delimited by 45.5–48.1°N and 6–14°E are summarized in three ways: (1) in a selection of pollen-percentage threshold maps (thresholds 0.5%, 1%, 2%, 4%, 8%, 16%, and 32% of land pollen); (2) in graphic summaries of 250-year time slices and geographic segments (lengthwise and transverse in relation to the main axis of the Alps) as pollen-percentage curves, pollen-percentage difference curves, and pollen-percentage threshold ages cal BP graphed against both the length and the transverse Alpine axes; and (3) in tables showing statistical relationships of either pollen-percentage threshold ages cal BP or pollen expansion durations (=time lapse between different pollen-percentage threshold ages cal BP) with latitude, longitude, and elevation; to establish these relationships we used both simple linear regression and multiple linear regression after stepwise-forward selection. Results: The statistical results indicate that (a) the use of pollen-percentage thresholds between 0.5% and 8% yield mostly similar directions of tree migration, so the method is fairly robust, (b) Abies migrated northward, Fagus southward, Picea westward, and Quercus northward; more detail does not emerge due to an extreme scarcity of high-quality data especially along the southern foothills of the Alps and in the eastern Alps. This scarcity allows the reconstruction of one immigration route only of Abies into the southern Alps. The speed of population expansion (following arrival) of Abies increased and of Picea decreased during the Holocene, of Fagus it decreased especially during the later Holocene, and of Quercus it increased especially at the start of the Holocene.

Serum Testosterone Levels and Symptom-Based Depression Subtypes in Men

The main objective of this preliminary study was to further clarify the association between testosterone (T) levels and depression by investigating symptom-based depression subtypes in a sample of 64 men. The data were taken from the ZInEP epidemiology survey. Gonadal hormones of a melancholic (n  = 25) and an atypical (n = 14) depression subtype, derived from latent class analysis, were compared with those of healthy controls (n  = 18). Serum T was assayed using an enzyme-linked immunosorbent assay procedure. Analysis of variance, analysis of covariance, non-parametrical tests, and generalized linear regression models were performed to examine group differences. The atypical depressive subtype showed significantly lower T levels compared with the melancholic depressives. While accumulative evidence indicates that, beyond psychosocial characteristics, the melancholic and atypical depressive subtypes are also distinguishable by biological correlates, the current study expanded this knowledge to include gonadal hormones. Further longitudinal research is warranted to disclose causality by linking the multiple processes in pathogenesis of depression.

Inactive Matrix Gla-Protein Is Associated With Arterial Stiffness in an Adult Population-Based Study

Increased pulse wave velocity (PWV) is a marker of aortic stiffness and an independent predictor of mortality. Matrix Gla-protein (MGP) is a vascular calcification inhibitor that needs vitamin K to be activated. Inactive MGP, known as desphospho-uncarboxylated MGP (dp-ucMGP), can be measured in plasma and has been associated with various cardiovascular markers, cardiovascular outcomes, and mortality. In this study, we hypothesized that high levels of dp-ucMGP are associated with increased PWV. We recruited participants via a multicenter family-based cross-sectional study in Switzerland. Dp-ucMGP was quantified in plasma by sandwich ELISA. Aortic PWV was determined by applanation tonometry using carotid and femoral pulse waveforms. Multiple regression analysis was performed to estimate associations between PWV and dp-ucMGP adjusting for age, renal function, and other cardiovascular risk factors. We included 1001 participants in our analyses (475 men and 526 women). Mean values were 7.87±2.10 m/s for PWV and 0.43±0.20 nmol/L for dp-ucMGP. PWV was positively associated with dp-ucMGP both before and after adjustment for sex, age, body mass index, height, systolic and diastolic blood pressure (BP), heart rate, renal function, low- and high-density lipoprotein, glucose, smoking status, diabetes mellitus, BP and cholesterol lowering drugs, and history of cardiovascular disease (P≤0.01). In conclusion, high levels of dp-ucMGP are independently and positively associated with arterial stiffness after adjustment for common cardiovascular risk factors, renal function, and age. Experimental studies are needed to determine whether vitamin K supplementation slows arterial stiffening by increasing MGP carboxylation.

Evidence for chronic low-grade systemic inflammation in individuals with agoraphobia from a population-based prospective study.

BACKGROUND Anxiety disorders have been linked to an increased risk of incident coronary heart disease in which inflammation plays a key pathogenic role. To date, no studies have looked at the association between proinflammatory markers and agoraphobia. METHODS In a random Swiss population sample of 2890 persons (35-67 years, 53% women), we diagnosed a total of 124 individuals (4.3%) with agoraphobia using a validated semi-structured psychiatric interview. We also assessed socioeconomic status, traditional cardiovascular risk factors (i.e., body mass index, hypertension, blood glucose levels, total cholesterol/high-density lipoprotein-cholesterol ratio), and health behaviors (i.e., smoking, alcohol consumption, and physical activity), and other major psychiatric diseases (other anxiety disorders, major depressive disorder, drug dependence) which were treated as covariates in linear regression models. Circulating levels of inflammatory markers, statistically controlled for the baseline demographic and health-related measures, were determined at a mean follow-up of 5.5 ± 0.4 years (range 4.7 - 8.5). RESULTS Individuals with agoraphobia had significantly higher follow-up levels of C-reactive protein (p = 0.007) and tumor-necrosis-factor-α (p = 0.042) as well as lower levels of the cardioprotective marker adiponectin (p = 0.032) than their non-agoraphobic counterparts. Follow-up levels of interleukin (IL)-1β and IL-6 did not significantly differ between the two groups. CONCLUSIONS Our results suggest an increase in chronic low-grade inflammation in agoraphobia over time. Such a mechanism might link agoraphobia with an increased risk of atherosclerosis and coronary heart disease, and needs to be tested in longitudinal studies.