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Acute infection with human immunodeficiency virus (HIV) is often accompanied by a flu-like illness, and early identification and treatment may help control the infection and prevent transmission. We enrolled patients who presented to an urban urgent care center with any symptoms of a viral illness and any recent potential risk for HIV infection, and we tested them for acute HIV infection using enzyme-linked immunosorbent and RNA assays. Of 499 patients enrolled over a 1-year period, acute HIV infection was diagnosed in 5 (1.0%; 95% confidence interval [CI], 0.1%-1.9%), and chronic HIV infection was diagnosed in 6 (1.2%; 95% CI, 0.2%-2.2%). There were no false-positive results of the RNA assay. No signs or symptoms reliably distinguished patients with acute HIV infection from those who were HIV uninfected. Given the importance of this diagnosis, testing for acute HIV infection using RNA and antibody assays should be offered to all patients in similar settings with viral symptoms and any risk factors for HIV infection.

To the Editor: Recently, the trade name for omeprazole was changed from Losec to Prilosec after several physicians noted incidents in which prescriptions written for Losec were instead dispensed with Lasix. 1 2 3 We report a similar confusion between a popular new antibiotic, the fluoroquinolone norfloxacin, and a muscle relaxant, orphenadrine. Although the trade name for norfloxacin is Noroxin, it is frequently abbreviated as \"norflox,\" which can lead to confusion with orphenadrine, the trade name for which is Norflex. We have noted two cases of such confusion. In one case, a 60-year-old woman with end-stage liver disease was prescribed norfloxacin as . . .

The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W/sq. m, comprised of 1.81 (±0.09) W/sq. m from CO2, 1.08 (± 0.21) W/sq. m from other well-mixed greenhouse gases, −1.01 (± 0.23) W/sq. m from aerosols and −0.09 (±0.13) W/sq. m from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W/sq. m. The majority of the remaining 0.21 W/sq. m is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W/sq. m, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming.

Errors in the simulation of clouds in general circulation models (GCMs) remain a long-standing issue in climate projections, as discussed in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. This highlights the need for developing new analysis techniques to improve our knowledge of the physical processes at the root of these errors. The Cloud Feedback Model Intercomparison Project (CFMIP) pursues this objective, and under that framework the CFMIP Observation Simulator Package (COSP) has been developed. COSP is a flexible software tool that enables the simulation of several satellite-borne active and passive sensor observations from model variables. The flexibility of COSP and a common interface for all sensors facilitates its use in any type of numerical model, from high-resolution cloud-resolving models to the coarser-resolution GCMs assessed by the IPCC, and the scales in between used in weather forecast and regional models. The diversity of model parameterization techniques makes the comparison between model and observations difficult, as some parameterized variables (e.g., cloud fraction) do not have the same meaning in all models. The approach followed in COSP permits models to be evaluated against observations and compared against each other in a more consistent manner. This permits a more detailed diagnosis of the physical processes that govern the behavior of clouds and precipitation in numerical models. The World Climate Research Programme (WCRP) Working Group on Coupled Modelling has recommended the use of COSP in a subset of climate experiments that will be assessed by the next IPCC report. In this article we describe COSP, present some results from its application to numerical models, and discuss future work that will expand its capabilities.

A new radiation package, “McRad,” has become operational with cycle 32R2 of the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). McRad includes an improved description of the land surface albedo from Moderate Resolution Imaging Spectroradiometer (MODIS) observations, the Monte Carlo independent column approximation treatment of the radiative transfer in clouds, and the Rapid Radiative Transfer Model shortwave scheme. The impact of McRad on year-long simulations at TL159L91 and higher-resolution 10-day forecasts is then documented. McRad is shown to benefit the representation of most parameters over both shorter and longer time scales, relative to the previous operational version of the radiative transfer schemes. At all resolutions, McRad improves the representation of the cloud–radiation interactions, particularly in the tropical regions, with improved temperature and wind objective scores through a reduction of some systematic errors in the position of tropical convection as a result of a change in the overall distribution of diabatic heating over the vertical plane, inducing a geographical redistribution of the centers of convection. Although smaller, the improvement is also seen in the rmse of geopotential in the Northern and Southern Hemispheres and over Europe. Given the importance of cloudiness in modulating the radiative fluxes, the sensitivity of the model to cloud overlap assumption (COA) is also addressed, with emphasis on the flexibility that is inherent to this new RT approach when dealing with COA. The sensitivity of the forecasts to the space interpolation that is required to efficiently address the high computational cost of the RT parameterization is also revisited. A reduction of the radiation grid for the Ensemble Prediction System is shown to be of little impact on the scores while reducing the computational cost of the radiation computations. McRad is also shown to decrease the cold bias in ocean surface temperature in climate integrations with a coupled ocean system.

Wildfire risk in temperate forests has become a nearly intractable problem that can be characterized as a socioecological “pathology”: that is, a set of complex and problematic interactions among social and ecological systems across multiple spatial and temporal scales. Assessments of wildfire risk could benefit from recognizing and accounting for these interactions in terms of socioecological systems, also known as coupled natural and human systems (CNHS). We characterize the primary social and ecological dimensions of the wildfire risk pathology, paying particular attention to the governance system around wildfire risk, and suggest strategies to mitigate the pathology through innovative planning approaches, analytical tools, and policies. We caution that even with a clear understanding of the problem and possible solutions, the system by which human actors govern fire‐prone forests may evolve incrementally in imperfect ways and can be expected to resist change even as we learn better ways to manage CNHS.

Our understanding of the interactions between clouds, circulation and climate is limited. Four central research questions — now tractable through advances in models, concepts and observations — are proposed to accelerate future progress. Fundamental puzzles of climate science remain unsolved because of our limited understanding of how clouds, circulation and climate interact. One example is our inability to provide robust assessments of future global and regional climate changes. However, ongoing advances in our capacity to observe, simulate and conceptualize the climate system now make it possible to fill gaps in our knowledge. We argue that progress can be accelerated by focusing research on a handful of important scientific questions that have become tractable as a result of recent advances. We propose four such questions below; they involve understanding the role of cloud feedbacks and convective organization in climate, and the factors that control the position, the strength and the variability of the tropical rain belts and the extratropical storm tracks.

Background:Osteoarthritis (OA) and rheumatoid arthritis (RA) are associated with a high prevalence of comorbid anxiety (ANX), depression (DEP) and fibromyalgia (FM), but these comorbidities are infrequently assessed in routine rheumatology care. A multidimensional health assessment questionnaire (MDHAQ), which is completed by more than 80% of patients in 5-10 minutes and available on a smart phone, includes 3 validated screening indices for ANX, DEP, and FM, as well as routine assessment of index data (RAPID3) to assess clinical status.Objectives:To analyze MDHAQ data in unselected OA or RA routine-care patients for the prevalence of positive screening according to MAS2 (MDHAQ anxiety screen), MDS2 (MDHAQ depression screen), and/or FAST3F (fibromyalgia assessment screening tool).Methods:A retrospective analysis of MDHAQ data in unselected OA or RA routine-care patients was conducted at one setting where an MDHAQ is completed by all patients with all diagnoses at all visits. MAS2, MDS2, and FAST3F indices within the MDHAQ agree more than 80% with reference HADS-D (hospital anxiety and depression scale), PHQ-9 (patient health questionnaire 9), and 2011 revised fibromyalgia criteria, respectively. RAPID3 consists of the 3 RA self-report patient’s self-report measures for physical function, pain, and patient global assessment. The prevalence of anxiety, depression, and fibromyalgia in patients who screened positive or negative for MAS2, MDS2, and/or FAST3F was analyzed and compared to mean 0-30 RAPID3 and 0-10 patient global assessment in each category.Results:In 361 OA and 488 RA patients, positive screening was seen in for ANX, DEP and/or FM in 40.4% and 36.3%, respectively (Table 1). Patients with all 3 comorbidities exhibited higher (worse) RAPID3 and PATGL scores than those with 1 or 2 comorbidities (Table 1). Among those with one comorbidity, highest (worst) RAPID3 and PATGL were seen for FM compared to DEP or ANX. Results were similar in both diagnoses and were not explained by age, gender or other possible confounding variables.Conclusion:FM, DEP and ANX rates were 40.4% in OA and 36.3% in RA, associated with poorer RAPID3 patient status. Feasible screening for FM, DEP and ANX on the MDHAQ in routine care may inform patient management.REFERENCES:NIL.Acknowledgements:NIL.Disclosure of Interests:None declared.

BackgroundNon-articular comorbidities, including anxiety (ANX), depression (DEP) and fibromyalgia (FM), are common in patients with rheumatic diseases. Their presence may impact measures of disease activity and responses to treatment. The burden of ANX, DEP and FM has been described in many reports concerning patients with rheumatoid arthritis (RA), but far less information is available concerning these comorbidities in patients with osteoarthritis (OA). It is feasible to screen for these comorbidities in all patients seen in routine care using a multidimensional health assessment questionnaire (MDHAQ)[1,2], completed by patients in 5-10 minutes before seeing the rheumatologist, which includes screening indices for ANX, DEP, and FM.ObjectivesTo analyze the prevalence of positive screening for ANX, DEP, and/or FM in patients with OA compared to RA in routine care at an academic rheumatology center.MethodsAll patients seen for routine rheumatology care are asked to complete an MDHAQ, which includes 0-3 physical function and ANX and DEP scales in the patient friendly HAQ format, three 0-10 visual numeric scales (VNS) for pain, fatigue and global status, self-report 0-54 RADAI painful joint count, 60-symptom checklist review of systems (ROS) including ANX and DEP, medical history queries, and 4 indices: RAPID3 (routine assessment of patient index data to assess patient status in all diseases studied), MDHAQ ANX screen (MAS2), MDHAQ DEP screen (MDS2)[1], and fibromyalgia assessment screening tool (FAST4)[2]. MAS2 and MDS2 are positive for ANX or DEP if 0-3 ANX or DEP response is ≥2 OR positive ANX or DEP on the symptom checklist. FAST4 is positive if 3/4: pain VNS ≥6/10, fatigue VNS ≥6/10, self-report painful joint count ≥16/54, and/or symptom checklist ≥16/60. Patients were classified as OA or RA according to primary ICD 10 diagnosis. An MDHAQ database was used to compute retrospectively medians and interquartile ranges (IQR).ResultsThe study included 366 OA and 488 RA patients seen between 2013 and 2022. Patients were mostly female and OA patients were slightly older (Table 1). RAPID3 was similar in RA and OA patients. Positive screening for ANX was seen in 28.4% of OA and 21.9% of RA patients (p= 0.04, Table 1), for DEP in 21.6% of OA and 18% of RA patients (p>0.05), and for FM in 20.4% of OA and 20% of RA patients (p>0.05).ConclusionPositive ANX, DEP, and FM screening is seen in > 20% of routine care patients with primary diagnoses of OA or RA, at similar levels in OA and RA. Although definitive diagnosis requires a physician, MAS2, MDS2, and FAST4 agree more than 80% with reference standards which are highly associated with positive diagnoses. The results underscore a need for rheumatologists to aware of these comorbidities, easily screened for using an MDHAQ.References[1]Arthritis Care Res, 73: 120-129, 2021[2]ACR Open Rheumatology, 1: 516-525, 2019Table 1.Positive anxiety, depression and fibromyalgia screening in routine care OA and RA patientsRheumatoid ArthritisOsteoarthritisp-value*N488366RAPID3 median (IQR)13.3(13.2)14.0(10.1)0.48MAS screening for anxiety n (%)107(21.9%)104(28.4%)0.04MDS screening for anxiety n(%)88(18.0%)79(21.6%)0.23FAST4 ≥3 screening for fibromyalgia n(%)98(20%)75(20.4%)0.95*Chi square test for comparison of proportions, Mood’s median test for comparison of RAPID3Acknowledgements.Acknowledgements:NIL.Disclosure of InterestsNone Declared.