Development of a prognostic model of COVID-19 severity: a population-based cohort study in Iceland.

BACKGROUND: The severity of SARS-CoV-2 infection varies from asymptomatic state to severe respiratory failure and the clinical course is difficult to predict. The aim of the study was to develop a prognostic model to predict the severity of COVID-19 in unvaccinated adults at the time of diagnosis. METHODS: All SARS-CoV-2-positive adults in Iceland were prospectively enrolled into a telehealth service at diagnosis. A multivariable proportional-odds logistic regression model was derived from information obtained during the enrollment interview of those diagnosed between February 27 and December 31, 2020 who met the inclusion criteria. Outcomes were defined on an ordinal scale: (1) no need for escalation of care during follow-up; (2) need for urgent care visit; (3) hospitalization; and (4) admission to intensive care unit (ICU) or death. Missing data were multiply imputed using chained equations and the model was internally validated using bootstrapping techniques. Decision curve analysis was performed. RESULTS: The prognostic model was derived from 4756 SARS-CoV-2-positive persons. In total, 375 (7.9%) only required urgent care visits, 188 (4.0%) were hospitalized and 50 (1.1%) were either admitted to ICU or died due to complications of COVID-19. The model included age, sex, body mass index (BMI), current smoking, underlying conditions, and symptoms and clinical severity score at enrollment. On internal validation, the optimism-corrected Nagelkerke's R2 was 23.4% (95%CI, 22.7-24.2), the C-statistic was 0.793 (95%CI, 0.789-0.797) and the calibration slope was 0.97 (95%CI, 0.96-0.98). Outcome-specific indices were for urgent care visit or worse (calibration intercept -0.04 [95%CI, -0.06 to -0.02], Emax 0.014 [95%CI, 0.008-0.020]), hospitalization or worse (calibration intercept -0.06 [95%CI, -0.12 to -0.03], Emax 0.018 [95%CI, 0.010-0.027]), and ICU admission or death (calibration intercept -0.10 [95%CI, -0.15 to -0.04] and Emax 0.027 [95%CI, 0.013-0.041]). CONCLUSION: Our prognostic model can accurately predict the later need for urgent outpatient evaluation, hospitalization, and ICU admission and death among unvaccinated SARS-CoV-2-positive adults in the general population at the time of diagnosis, using information obtained by telephone interview.

[Obesity isn't always obesity: Cushing's disease - case report]. / Offita er ekki alltaf offita: Cushing-sjúkdómur, sjúkratilfelli

Woman in her thirties presented to the emergency room with a two-week history of worsening headache and diplopia. For eight years she had suffered from progressive weight gain, diabetes and hypertension that didn't improve with lifestyle modification. A lumbar puncture demonstrated increased intracranial pressure and MRI a pituitary adenoma. Physical examination was consistent with Cushing's syndrome and endocrine workup confirmed Cushing's disease. Treatment was complex, including unsuccessful pituitary surgery and gamma knife radiosurgery, and eventually bilateral adrenalectomy with subsequent development of Nelsons syndrome. This case illustrates the diagnostic delay that many patients with CD suffer from.

[First case of COVID-19 treated with tocilizumab in Iceland]. / Fyrsta meðferð með tocilizumab við COVID-19 hérlendis - sjúkratilfelli

A gentleman in his early fifties became ill with flu-like symptoms after vacationing abroad and was diagnosed with COVID-19 after returning to Iceland. A few days later he was admitted to the University Hospital, Landspitali, due to worsening respiratory symptoms and severe fatigue. A computed tomography scan of lthe lungs showed diffuse bilateral consolidations and ground glass changes. He developed respiratory failure and was transferred to the intensive care unit where he received further treatment, including tocilizumab (IL-6 receptor inhibitor). He subsequently showed clinical improvement and did not require endotracheal intubation.

Corrigendum to "A Clinical Decision Support System for the Diagnosis, Fracture Risks and Treatment of Osteoporosis".

[This corrects the article DOI: 10.1155/2015/189769.].

A clinical decision support system for the diagnosis, fracture risks and treatment of osteoporosis.

Expanding medical knowledge increases the potential risk of medical errors in clinical practice. We present, OPAD, a clinical decision support system in the field of the medical care of osteoporosis. We utilize clinical information from international guidelines and experts in the field of osteoporosis. Physicians are provided with user interface to insert standard patient data, from which OPAD provides instant diagnostic comments, 10-year risk of fragility fracture, treatment options for the given case, and when to offer a follow-up DXA-evaluation. Thus, the medical decision making is standardized according to the best expert knowledge at any given time. OPAD was evaluated in a set of 308 randomly selected individuals. OPAD's ten-year fracture risk computation is nearly identical to FRAX (r = 0.988). In 58% of cases OPAD recommended DXA evaluation at the present time. Following a DXA measurement in all individuals, 71% of those that were recommended to have DXA at the present time received recommendation for further investigation or specific treatment by the OPAD. In only 5.9% of individuals in which DXA was not recommended, the result of the BMD measurement changed the recommendations given by OPAD.