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Abstract Introduction Fine-needle aspiration cytology (FNAC) is an effective tool in the diagnostic work-up of patients with thyroid nodules. The aim of our study was to assess the diagnostic sensitivity of FNAC in thyroid cancer (TC) in Sweden by correlating the findings of preoperative FNAC with those obtained through final histology of the surgical specimen. Methods A Swedish nationwide cohort of patients having surgery for TC (n = 2519) from the Scandinavian Quality Register for Thyroid, Parathyroid and Adrenal surgery between 2004 and 2013 was obtained. Data was validated through scrutinizing patient FNAC and histology reports. Results Among the 2519 cases operated with a final diagnosis of TC, the diagnosis was substantiated and validated through the histology report in 2332 cases (92.6%), included in the present study. Among these, 1679 patients (72%) were female and the median age at TC diagnosis was 52.3 years (range 18-94.6). In 353 cases (15.1%) FNAC was not performed at all; whereas in the remaining 1965 cases, the diagnostic sensitivity of FNAC was 81.6%. In lesions > 1 cm, FNAC diagnostic sensitivity reached 86.5%, whereas in lesions 1 cm, the diagnostic sensitivity of US-guided FNAC (n = 1504) was 86.9% as compared to 76.9% in clinically applied FNAC without US utilization (n = 118). Conclusions FNAC is performed in most patients operated for TC in Sweden (85%) and retains its value as a tool in TC diagnostic work-up with an overall sensitivity of 82%, reaching 87% in lesions > 1 cm, that harbor clinically relevant TC.

This study develops a reproducible method for estimating the cost-efficient flexibility potential of a local or regional energy system. Future scenarios that achieve ambitious climate targets and estimate the cost-efficient flexibility potential of demonstration sites were defined. Flexible potentials for energy system assessment are upscaled from the demonstration sites in Eskilstuna (Sweden) and Lower Austria (Austria). As heat pumps (HPs) and district heating (DH) are critical for future heat demand, these sites are representative types of DH networks in terms of size and integration with the electricity grid. In both regions a TIMES model is used for energy system optimization, while for upscaling, Eskilstuna uses the building-stock model ECCABS, whereas Lower Austria uses a mixed integer linear programming optimization model, and the BALMOREL power system model. According to the modeling, HPs will dominate Eskilstuna’s heating sector by 2040. In Lower Austria, DH becomes more prevalent, in combination with wood biomass and HPs. These findings are explained by the postulated technological-economic parameters, energy prices, and CO _2 prices. We conclude that future electricity prices will determine future heating systems: either a high share of centralized HPs (if electricity prices are low) or a high share of combined heat-and-power (if electricity prices are high). Large-scale energy storage and biomass can be essential solutions as may deliver increased cost-effectiveness, if available and under certain conditions.