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  • 1
    In: Diabetes Care, American Diabetes Association, Vol. 44, No. 5 ( 2021-05-01), p. 1219-1227
    Abstract: In observational data, lower levels of lipoprotein(a) have been associated with greater prevalence of type 2 diabetes. Whether pharmacologic lowering of lipoprotein(a) influences incident type 2 diabetes is unknown. We determined the relationship of lipoprotein(a) concentration with incident type 2 diabetes and effects of treatment with alirocumab, a PCSK9 inhibitor. RESEARCH DESIGN AND METHODS In the ODYSSEY OUTCOMES trial alirocumab was compared with placebo in patients with acute coronary syndrome. Incident diabetes was determined from laboratory, medication, and adverse event data. RESULTS Among 13,480 patients without diabetes at baseline, 1,324 developed type 2 diabetes over a median 2.7 years. Median baseline lipoprotein(a) was 21.9 mg/dL. With placebo, 10 mg/dL lower baseline lipoprotein(a) was associated with hazard ratio 1.04 (95% CI 1.02−1.06, P & lt; 0.001) for incident type 2 diabetes. Alirocumab reduced lipoprotein(a) by a median 23.2% with greater absolute reductions from higher baseline levels and no overall effect on incident type 2 diabetes (hazard ratio 0.95, 95% CI 0.85–1.05). At low baseline lipoprotein(a) levels, alirocumab tended to reduce incident type 2 diabetes, while at high baseline lipoprotein(a) alirocumab tended to increase incident type 2 diabetes compared with placebo (treatment–baseline lipoprotein(a) interaction P = 0.006). In the alirocumab group, a 10 mg/dL decrease in lipoprotein(a) from baseline was associated with hazard ratio 1.07 (95% CI 1.03−1.12; P = 0.0002) for incident type 2 diabetes. CONCLUSIONS In patients with acute coronary syndrome, baseline lipoprotein(a) concentration associated inversely with incident type 2 diabetes. Alirocumab had neutral overall effect on incident type 2 diabetes. However, treatment-related reductions in lipoprotein(a), more pronounced from high baseline levels, were associated with increased risk of incident type 2 diabetes. Whether these findings pertain to other therapies that reduce lipoprotein(a) is undetermined.
    Type of Medium: Online Resource
    ISSN: 0149-5992 , 1935-5548
    Language: English
    Publisher: American Diabetes Association
    Publication Date: 2021
    detail.hit.zdb_id: 1490520-6
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  • 2
    In: The Lancet Diabetes & Endocrinology, Elsevier BV, Vol. 7, No. 8 ( 2019-08), p. 618-628
    Type of Medium: Online Resource
    ISSN: 2213-8587
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2019
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  • 3
    In: Journal of the American College of Cardiology, Elsevier BV, Vol. 78, No. 5 ( 2021-08), p. 421-433
    Type of Medium: Online Resource
    ISSN: 0735-1097
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 1468327-1
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  • 4
    In: Circulation, Ovid Technologies (Wolters Kluwer Health), Vol. 146, No. 9 ( 2022-08-30), p. 657-672
    Abstract: Apolipoprotein B (apoB) provides an integrated measure of atherogenic risk. Whether apoB levels and apoB lowering hold incremental predictive information on residual risk after acute coronary syndrome beyond that provided by low-density lipoprotein cholesterol is uncertain. Methods: The ODYSSEY OUTCOMES trial (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab) compared the proprotein convertase subtilisin/kexin type 9 inhibitor alirocumab with placebo in 18 924 patients with recent acute coronary syndrome and elevated atherogenic lipoproteins despite optimized statin therapy. Primary outcome was major adverse cardiovascular events (MACE; coronary heart disease death, nonfatal myocardial infarction, fatal/nonfatal ischemic stroke, hospitalization for unstable angina). Associations between baseline apoB or apoB at 4 months and MACE were assessed in adjusted Cox proportional hazards and propensity score–matched models. Results: Median follow-up was 2.8 years. In proportional hazards analysis in the placebo group, MACE incidence increased across increasing baseline apoB strata (3.2 [95% CI, 2.9–3.6], 4.0 [95% CI, 3.6–4.5] , and 5.5 [95% CI, 5.0–6.1] events per 100 patient-years in strata 〈 75, 75– 〈 90, ≥90 mg/dL, respectively; P trend 〈 0.0001) and after adjustment for low-density lipoprotein cholesterol ( P trend =0.035). Higher baseline apoB stratum was associated with greater relative ( P trend 〈 0.0001) and absolute reduction in MACE with alirocumab versus placebo. In the alirocumab group, the incidence of MACE after month 4 decreased monotonically across decreasing achieved apoB strata (4.26 [95% CI, 3.78–4.79], 3.09 [95% CI, 2.69–3.54] , and 2.41 [95% CI, 2.11–2.76] events per 100 patient-years in strata ≥50, 〉 35– 〈 50, and ≤35 mg/dL, respectively). Compared with propensity score–matched patients from the placebo group, treatment hazard ratios for alirocumab also decreased monotonically across achieved apoB strata. Achieved apoB was predictive of MACE after adjustment for achieved low-density lipoprotein cholesterol or non–high-density lipoprotein cholesterol but not vice versa. Conclusions: In patients with recent acute coronary syndrome and elevated atherogenic lipoproteins, MACE increased across baseline apoB strata. Alirocumab reduced MACE across all strata of baseline apoB, with larger absolute reductions in patients with higher baseline levels. Lower achieved apoB was associated with lower risk of MACE, even after accounting for achieved low-density lipoprotein cholesterol or non–high-density lipoprotein cholesterol, indicating that apoB provides incremental information. Achievement of apoB levels as low as ≤35 mg/dL may reduce lipoprotein-attributable residual risk after acute coronary syndrome. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01663402.
    Type of Medium: Online Resource
    ISSN: 0009-7322 , 1524-4539
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2022
    detail.hit.zdb_id: 1466401-X
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  • 5
    Online Resource
    Online Resource
    American Meteorological Society ; 2021
    In:  Monthly Weather Review Vol. 149, No. 8 ( 2021-08), p. 2755-2776
    In: Monthly Weather Review, American Meteorological Society, Vol. 149, No. 8 ( 2021-08), p. 2755-2776
    Abstract: A complex and underexplored relationship exists between atmospheric rivers (ARs) and mesoscale frontal waves (MFWs). The present study further explores and quantifies the importance of diabatic processes to MFW development and the AR–MFW interaction by simulating two ARs impacting Northern California’s flood-vulnerable Russian River watershed using the Model for Prediction Across Scales-Atmosphere (MPAS-A) with and without the effects of latent heating. Despite the storms’ contrasting characteristics, diabatic processes within the system were critical to the development of MFWs, the timing and magnitude of integrated vapor transport (IVT), and precipitation impacts over the Russian River watershed in both cases. Low-altitude circulations and lower-tropospheric moisture content in and around the MFWs are considerably reduced without latent heating, contributing to a decrease in moisture transport, moisture convergence, and IVT. Differences in IVT are not consistently dynamic (i.e., wind-driven) or thermodynamic (i.e., moisture-driven), but instead vary by case and by time throughout each event. For one event, AR conditions over the watershed persisted for 6 h less and the peak IVT occurred 6 h earlier and was reduced by ~17%; weaker orographic and dynamic precipitation forcings reduced precipitation totals by ~64%. Similarly, turning off latent heating shortened the second event by 24 h and reduced precipitation totals by ~49%; the maximum IVT over the watershed was weakened by ~42% and delayed by 18 h. Thus, sufficient representation of diabatic processes, and by inference, water vapor initial conditions, is critical for resolving MFWs, their feedbacks on AR evolution, and associated precipitation forecasts on watershed scales.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
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  • 6
    In: Journal of Hydrometeorology, American Meteorological Society, Vol. 19, No. 7 ( 2018-07-01), p. 1097-1113
    Abstract: Accurate forecasts of precipitation during landfalling atmospheric rivers (ARs) are critical because ARs play a large role in water supply and flooding for many regions. In this study, we have used hundreds of observations to verify global and regional model forecasts of atmospheric rivers making landfall in Northern California and offshore in the midlatitude northeast Pacific Ocean. We have characterized forecast error and the predictability limit in AR water vapor transport, static stability, onshore precipitation, and standard atmospheric fields. Analysis is also presented that apportions the role of orographic forcing and precipitation response in driving errors in forecast precipitation after AR landfall. It is found that the global model and the higher-resolution regional model reach their predictability limit in forecasting the atmospheric state during ARs at similar lead times, and both present similar and important errors in low-level water vapor flux, moist-static stability, and precipitation. However, the relative contribution of forcing and response to the incurred precipitation error is very different in the two models. It can be demonstrated using the analysis presented herein that improving water vapor transport accuracy can significantly reduce regional model precipitation errors during ARs, while the same cannot be demonstrated for the global model.
    Type of Medium: Online Resource
    ISSN: 1525-755X , 1525-7541
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2018
    detail.hit.zdb_id: 2042176-X
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  • 7
    Online Resource
    Online Resource
    American Meteorological Society ; 2021
    In:  Weather and Forecasting ( 2021-07-13)
    In: Weather and Forecasting, American Meteorological Society, ( 2021-07-13)
    Abstract: Accurate forecasts of atmospheric rivers (ARs) provide advance warning of flood and landslide hazards, as well as greatly aid effective water management. It is therefore critical to evaluate the skill of AR forecasts in numerical weather prediction (NWP) models. A new verification framework is proposed leveraging freely available software and metrics previously used for different applications. Specifically, AR detection and statistics are computed for the first time using the Method for Object-based Diagnostic Evaluation (MODE). In addition, the measure of effectiveness (MoE) is introduced as a new metric for understanding AR forecast skill in terms of size and location. The MoE provides a quantitative measure of the position of an entire forecasted AR compared to observation, regardless of whether the AR is making landfall. In addition, the MoE can provide qualitative information about the evolution of a forecast by lead time with implications about the predictability of an AR. We analyze AR forecast verification and skill using 11 years of cold season forecasts from two NWP models, one global and one regional. Four different thresholds of integrated vapor transport (IVT) are used in the verification revealing differences in forecast skill based on the strength of an AR. In addition to MoE, AR forecast skill is also addressed in terms of intensity error, landfall position error, and contingency table metrics.
    Type of Medium: Online Resource
    ISSN: 0882-8156 , 1520-0434
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 2025194-4
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  • 8
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 19, No. 7 ( 2019-04-03), p. 4193-4210
    Abstract: Abstract. Ice-nucleating particles (INPs) have been found to influence the amount, phase and efficiency of precipitation from winter storms, including atmospheric rivers. Warm INPs, those that initiate freezing at temperatures warmer than −10 ∘C, are thought to be particularly impactful because they can create primary ice in mixed-phase clouds, enhancing precipitation efficiency. The dominant sources of warm INPs during atmospheric rivers, the role of meteorology in modulating transport and injection of warm INPs into atmospheric river clouds, and the impact of warm INPs on mixed-phase cloud properties are not well-understood. In this case study, time-resolved precipitation samples were collected during an atmospheric river in northern California, USA, during winter 2016. Precipitation samples were collected at two sites, one coastal and one inland, which are separated by about 35 km. The sites are sufficiently close that air mass sources during this storm were almost identical, but the inland site was exposed to terrestrial sources of warm INPs while the coastal site was not. Warm INPs were more numerous in precipitation at the inland site by an order of magnitude. Using FLEXPART (FLEXible PARTicle dispersion model) dispersion modeling and radar-derived cloud vertical structure, we detected influence from terrestrial INP sources at the inland site but did not find clear evidence of marine warm INPs at either site. We episodically detected warm INPs from long-range-transported sources at both sites. By extending the FLEXPART modeling using a meteorological reanalysis, we demonstrate that long-range-transported warm INPs were observed only when the upper tropospheric jet provided transport to cloud tops. Using radar-derived hydrometeor classifications, we demonstrate that hydrometeors over the terrestrially influenced inland site were more likely to be in the ice phase for cloud temperatures between 0 and −10 ∘C. We thus conclude that terrestrial and long-range-transported aerosol were important sources of warm INPs during this atmospheric river. Meteorological details such as transport mechanism and cloud structure were important in determining (i) warm INP source and injection temperature and (ii) ultimately the impact of warm INPs on mixed-phase cloud properties.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2019
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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  • 9
    In: Journal of Hydrometeorology, American Meteorological Society, Vol. 21, No. 2 ( 2020-02), p. 355-375
    Abstract: We examine thermodynamic and kinematic structures of terrain trapped airflows (TTAs) during an atmospheric river (AR) event impacting Northern California 10–11 March 2016 using Alpha Jet Atmospheric eXperiment (AJAX) aircraft data, in situ observations, and Weather and Research Forecasting (WRF) Model simulations. TTAs are identified by locally intensified low-level winds flowing parallel to the coastal ranges and having maxima over the near-coastal waters. Multiple mechanisms can produce TTAs, including terrain blocking and gap flows. The changes in winds can significantly alter the distribution, timing, and intensity of precipitation. We show here how different mechanisms producing TTAs evolve during this event and influence local precipitation variations. Three different periods are identified from the time-varying wind fields. During period 1 (P1), a TTA develops during synoptic-scale onshore flow that backs to southerly flow near the coast. This TTA occurs when the Froude number (Fr) is less than 1, suggesting low-level terrain blocking is the primary mechanism. During period 2 (P2), a Petaluma offshore gap flow develops, with flows turning parallel to the coast offshore and with Fr 〉 1. Periods P1 and P2 are associated with slightly more coastal than mountain precipitation. In period 3 (P3), the gap flow initiated during P2 merges with a pre-cold-frontal low-level jet (LLJ) and enhanced precipitation shifts to higher mountain regions. Dynamical mixing also becomes more important as the TTA becomes confluent with the approaching LLJ. The different mechanisms producing TTAs and their effects on precipitation pose challenges to observational and modeling systems needed to improve forecasts and early warnings of AR events.
    Type of Medium: Online Resource
    ISSN: 1525-755X , 1525-7541
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2020
    detail.hit.zdb_id: 2042176-X
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  • 10
    In: Journal of Hydrometeorology, American Meteorological Society, Vol. 21, No. 4 ( 2020-04), p. 751-771
    Abstract: The partitioning of rain and snow during atmospheric river (AR) storms is a critical factor in flood forecasting, water resources planning, and reservoir operations. Forecasts of atmospheric rain–snow levels from December 2016 to March 2017, a period of active AR landfalls, are evaluated using 19 profiling radars in California. Three forecast model products are assessed: a global forecast model downscaled to 3-km grid spacing, 4-km river forecast center operational forecasts, and 50-km global ensemble reforecasts. Model forecasts of the rain–snow level are compared with observations of rain–snow melting-level brightband heights. Models produce mean bias magnitudes of less than 200 m across a range of forecast lead times. Error magnitudes increase with lead time and are similar between models, averaging 342 m for lead times of 24 h or less and growing to 700–800 m for lead times of greater than 144 h. Observed extremes in the rain–snow level are underestimated, particularly for warmer events, and the magnitude of errors increases with rain–snow level. Storms with high rain–snow levels are correlated with larger observed precipitation rates in Sierra Nevada watersheds. Flood risk increases with rain–snow levels, not only because a greater fraction of the watershed receives rain, but also because warmer storms carry greater water vapor and thus can produce heavier precipitation. The uncertainty of flood forecasts grows nonlinearly with the rain–snow level for these reasons as well. High rain–snow level ARs are a major flood hazard in California and are projected to be more prevalent with climate warming.
    Type of Medium: Online Resource
    ISSN: 1525-755X , 1525-7541
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2020
    detail.hit.zdb_id: 2042176-X
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