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Introduction: The appraisal of disease severity and prediction of adverse outcomes using risk stratification tools at early disease stages is crucial to diminish mortality from coronavirus disease 2019 (COVID-19). While lung ultrasound (LUS) as an imaging technique for the diagnosis of lung diseases has recently gained a leading position, data demonstrating that it can predict adverse outcomes related to COVID-19 is scarce. The main aim of this study is therefore to assess the clinical significance of bedside LUS in COVID-19 patients who presented to the emergency department (ED). Methods: Patients with a confirmed diagnosis of SARS-CoV-2 pneumonia admitted to the ED of our hospital between March 2021 and May 2021 and who underwent a 12-zone LUS and a lung computed tomography scan were included prospectively. Logistic regression and Cox proportional hazard models were used to predict adverse events, which was our primary outcome. The secondary outcome was to discover the association of LUS score and computed tomography severity score (CT-SS) with the composite endpoints. Results: We assessed 234 patients [median age 59.0 (46.8-68.0) years; 59.4% M), including 38 (16.2%) in-hospital deaths for any cause related to COVID-19. Higher LUS score and CT-SS was found to be associated with ICU admission, intubation, and mortality. The LUS score predicted mortality risk within each stratum of NEWS. Pairwise analysis demonstrated that after adjusting a base prediction model with LUS score, significantly higher accuracy was observed in predicting both ICU admission (DBA −0.067, P = .011) and in-hospital mortality (DBA −0.086, P = .017). Conclusion: Lung ultrasound can be a practical prediction tool during the course of COVID-19 and can quantify pulmonary involvement in ED settings. It is a powerful predictor of ICU admission, intubation, and mortality and can be used as an alternative for chest computed tomography while monitoring COVID-19-related adverse outcomes.

BACKGROUND: Prognostic prediction and estimation of severity at early stages of acute pancreatitis (AP) are crucial to reduce the complication rates and mortality. The objective of the present study is to evaluate the predicting ability of different clinical and radiological scores in AP. METHODS: We retrospectively collected demographic and clinical data from 159 patients diagnosed with AP admitted to Canakkale Onsekiz Mart University Hospital between January 2017 and December 2019. Bedside index for severity AP (BISAP), and acute physiology and chronic health evaluation II (APACHE II) score at admission, Ranson and modified Glasgow Prognostic Score (mGPS) score at 48 h after admission were calculated. Modified computed tomography severity index (CTSI) was also calculated for each patient. Area under the curve (AUC) was calculated for each scoring system for predicting severe AP, pancreatic necrosis, length of hospital stay, and mortality by determining optimal cutoff points from the (ROC) curves. RESULTS: mGPS and APACHE II had the highest AUC (0.929 and 0.823, respectively) to predict severe AP on admission with the best specificity and sensitivity. In predicting mortality BISAP (with a sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) of 75.0%, 70.9%, 98.2%, and 12.0%, respectively, [AUC: 0.793]) and APACHE II (with a sensitivity, specificity, NPV and PPV of 87.5%, 86.1%, 99.2%, and 25.0%, respectively, [AUC: 0.840]). CONCLUSION: mGPS can be a valuable tool in predicting the patients more likely to develop severe AP and maybe somewhat better than BISAP score, APACHE II Ranson score, and mCTSI.

ÖzPurpose: In most countries, there is an ever-increasing admission rate of the elderly population into emergency departments (EDs). In particular, these elderly patients differ from younger patients because they have multiple comorbidities that affect the functionality and quality of life. The goal of this study is to reveal whether the Charlson comorbidity index (CCI) foresee the short-and long-term prognosis of the super-elderly patient population. Materials and Methods: The study was a descriptive, retrospective analysis of emergency department (ED) admissions by patients over 85 years of age and admitted to the Canakkale Onsekiz Mart University (COMU) Hospital between 2013 and 2018. The demographic data of the patients were analyzed according to CCI. Coxregression analyses were conducted to determine whether the variables affected mortality. Results: A total of 1142 patients aged 85 and older (507 men, 635 women) with a mean age of 86.96±2.49 were included in the study. According to the multivariable Cox regression analysis male gender, CCI ≥6 and ICU admission were significantly associated with increased mortality rates Conclusion: The CCI predicts short and long-term prognosis in acutely ill, hospitalized super-elderly patients. The CCI could be used to select super-elderly patients at admission as an indicator of improvement at hospital discharge. Amaç: Çoğu ülkede, yaşlı nüfusun acil servislere (AS'ler) giderek artan bir başvuru oranı vardır. Özellikle bu yaşlı hastalar, fonksiyonel ve yaşam kalitesini etkileyen birden fazla komorbiditeye sahip oldukları için genç hastalardan farklıdır. Bu çalışmanın amacı, Charlson komorbidite indeksinin (CCI) çok yaşlı hasta popülasyonunun kısa ve uzun vadeli prognozunu tahmin edip etmediğini belirlemektir. Gereç ve Yöntem: Çalışma, 2013 ve 2018 yılları arasında Çanakkale Onsekiz Mart Üniversitesi (ÇOMÜ) Hastanesine başvuran 85 yaş ve üstü hastaların acil servis (AS) ziyaretlerinin tanımlayıcı, retrospektif bir analiziydi. Hastaların demografik verileri CCI'ye göre analiz edildi. Değişkenlerin mortaliteyi etkileyip etkilemediğini belirlemek için Cox-regresyon analizleri yapıldı. Bulgular: Yaş ortalaması 86,96±2,49 olan 85 yaş ve üzeri (507 erkek, 635 kadın) toplam 1142 hasta çalışmaya dahil edildi. Çok değişkenli Cox regresyon analizine göre erkek cinsiyet, CCI ≥6 ve yoğun bakım ünitesine yatış, artan mortalite oranları ile anlamlı şekilde ilişkiliydi. Sonuç: CCI akut hasta olarak hastaneye yatırılan çok yaşlı hastalarda kısa ve uzun dönem prognozu tahmin eder. CCI, hastaneden taburculukta iyileşmenin bir göstergesi olarak, kabulde, çok yaşlı hastaların seçilmesinde kullanılabilir.

Introduction: As the mortality rate in coronavirus disease 2019 patients older than 65 years is considerable, evaluation of in-hospital mortality is crucial. This study aimed to evaluate in-hospital mortality in COVID-19 patients older than 65 years using the National Early Warning Score (NEWS), Quick Sequential Organ Failure Assessment (q-SOFA), Charlson Comorbidity Index (CCI), and Elixhauser Comorbidity Index (ECI).Methods: This retrospective study included data from 480 patients with confirmed COVID-19 and age over 65 years who were evaluated in a university emergency department in Turkey. Data from eligible but deceased COVID-19 patients was also included. NEWS, q-SOFA, CCI, and ECI scores were retrospectively calculated. All clinical data was accessed from the information management system of the hospital, retrieved, and analyzed.Results: In-hospital mortality was seen in 169 patients (169/480). Low oxygen saturation, high C-reactive protein (CRP) and urea levels, and high q-SOFA and ECI scores helped us identify mortality in high-risk patients. A statistically significant difference was found in mortality estimation between q-SOFA and ECI (p <0.001), respectively. Conclusion: Q-SOFA and ECI can be used both easily and practically in the early diagnosis of in-hospital mortality in COVID-19 positive patients over 65 years of age admitted to the emergency department. Low oxygen saturation, high CRP and urea levels, and high q-SOFA and ECI scores are helpful in identifying high-risk patients.