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- Magnusson, Carl, 1976, et al.
(författare)
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Prediction of a time-sensitive condition among patients with dizziness assessed by the emergency medical services
- 2021
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Ingår i: BMC Emergency Medicine. - : Springer Science and Business Media LLC. - 1471-227X .- 1471-227X. ; 21:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Dizziness is a relatively common symptom among patients who call for the emergency medical services (EMS).AIM: To identify factors of importance for the early identification of a time-sensitive condition behind the symptom of dizziness among patients assessed by the EMS.METHODS: All patients assessed by the EMS and triaged using Rapid Emergency Triage and Treatment (RETTS) for adults code 11 (=dizziness) in the 660,000 inhabitants in the Municipality of Gothenburg, Sweden, in 2016, were considered for inclusion. The patients were divided into two groups according to the final diagnosis (a time-sensitive condition, yes or no).RESULTS: There were 1536 patients who fulfilled the inclusion criteria, of which 96 (6.2%) had a time-sensitive condition. The majority of these had a stroke/transitory ischaemic attack (TIA). Eight predictors of a time-sensitive condition were identified. Three were associated with a reduced risk: 1) the dizziness was of a rotatory type, 2) the dizziness had a sudden onset and 3) increasing body temperature. Five were associated with an increased risk: 1) sudden onset of headache, 2) a history of head trauma, 3) symptoms of nausea or vomiting, 4) on treatment with anticoagulants and 5) increasing systolic blood pressure.CONCLUSION: Among 1536 patients who were triaged by the EMS for dizziness, 6.2% had a time-sensitive condition. On the arrival of the EMS, eight factors were associated with the risk of having a time-sensitive condition. All these factors were linked to the type of symptoms or to clinical findings on the arrival of the EMS or to the recent clinical history.
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- Martinsson, Johan, et al.
(författare)
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Carbonaceous aerosol source apportionment using the Aethalometer model - evaluation by radiocarbon and levoglucosan analysis at a rural background site in southern Sweden
- 2017
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Ingår i: Atmospheric Chemistry and Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 17:6, s. 4265-4281
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Tidskriftsartikel (refereegranskat)abstract
- With the present demand on fast and inexpensive aerosol source apportionment methods, the Aethalometer model was evaluated for a full seasonal cycle (June 2014June 2015) at a rural atmospheric measurement station in southern Sweden by using radiocarbon and levoglucosan measurements. By utilizing differences in absorption of UV and IR, the Aethalometer model apportions carbon mass into wood burning (WB) and fossil fuel combustion (FF) aerosol. In this study, a small modification in the model in conjunction with carbon measurements from thermal-optical analysis allowed apportioned non-light-absorbing biogenic aerosol to vary in time. The absorption differences between WB and FF can be quantified by the absorption angstrom ngstrom exponent (AAE). In this study AAE(WB) was set to 1.81 and AAE(FF) to 1.0. Our observations show that the AAE was elevated during winter (1.36 +/- 0.07) compared to summer (1.12 +/- 0.07). Quantified WB aerosol showed good agreement with levoglucosan concentrations, both in terms of correlation (R-2 = 0 : 70) and in comparison to reference emission inventories. WB aerosol showed strong seasonal variation with high concentrations during winter (0.65 mu gm(-3), 56% of total carbon) and low concentrations during summer (0.07 mu gm(-3), 6% of total carbon). FF aerosol showed less seasonal dependence; however, black carbon (BC) FF showed clear diurnal patterns corresponding to traffic rush hour peaks. The presumed non-light-absorbing biogenic carbonaceous aerosol concentration was high during summer (1.04 mu gm(-3), 72% of total carbon) and low during winter (0.13 mu gm(-3), 8% of total carbon). Aethalometer model results were further compared to radiocarbon and levoglucosan source apportionment results. The comparison showed good agreement for apportioned mass of WB and biogenic carbonaceous aerosol, but discrepancies were found for FF aerosol mass. The Aethalometer model overestimated FF aerosol mass by a factor of 1.3 compared to radiocarbon and levoglucosan source apportionment. A performed sensitivity analysis suggests that this discrepancy can be explained by interference of non-light-absorbing biogenic carbon during winter. In summary, the Aethalometer model offers a costeffective yet robust high-time-resolution source apportionment at rural background stations compared to a radiocarbon and levoglucosan alternative.
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