Visual Analogue Scale for the Evaluation of Olfactory and Gustatory Dysfunction of COVID-19 Patients in Northwestern Greece.

Background The visual analogue scale (VAS) has been used as a diagnostic tool for the evaluation of the severity of olfactory and gustatory dysfunction (OGD) caused by SARS-CoV2 infection. The main objective of the present study was the evaluation of OGD with VAS in COVID-19-positive patients in Northwestern Greece and its possible association with the patients' self-reported symptoms of olfactory and gustatory dysfunction. Methods The presence of olfactory and gustatory symptoms and their severity were assessed by questionnaire along with the use of specific odorants and tastant ingredients, in three time periods: prior to COVID-19, during COVID-19 (initial diagnosis) and post-COVID-19 disease (at four weeks from disease onset). Three hundred COVID-19-positive patients (home-quarantined and hospitalized) tested with RT-PCR test in the University Hospital of Ioannina Greece were included in this study. Statistical analysis was performed on SPSS Statistics 26.0 (IBM Corp., Armonk, NY) Results Out of a total of 300 patients, 146 and 190 patients had mild hyposmia and hypogeusia respectively, followed by patients with severe hyposmia or hypogeusia (118 and 88 respectively), at the time of COVID-19 onset (initial diagnosis). An increase in the number of patients with recovery of symptoms was observed during the follow-up period, during which only eight patients had non-resolving severe symptoms (six patients with hyposmia and two with hypogeusia). On further analysis, a statistically significant association was found between the severity of symptoms (assessed by VAS score) and the self-reported symptoms of sensory dysfunction by the patients. There was a significant association between the groups of patients with mild hyposmia and patients that reported no loss of smell; between the patients with moderate hyposmia and the patients who reported "loss of smell"; and between the patients with severe hyposmia and the group of patients who reported a loss of smell, at the COVID-19 onset period. Similarly, patients with mild hyposmia were associated with those that reported a loss of smell at the same time. The severity of hyposmia was also associated with the reported symptom of "loss of taste" at the time of COVID-19 diagnosis. Similar findings were observed regarding the severity of hypogeusia and the reported symptom of "loss of taste" among the groups of patients. Finally, the severity of hypogeusia was associated with smell loss at the time of initial diagnosis of the infection. Conclusion Similar to the literature data, our findings indicate that hyposmia and hypogeusia are common symptoms of COVID-19 disease with varying severity. In our study, most of the patients exerted a complete recovery of these OGD symptoms. In addition, we found an association between olfactory dysfunction and self-reported sensory of taste as well as gustatory dysfunction and sensory of smell. Finally, we found that the VAS score was a reliable diagnostic tool in the estimation of OGD in this cohort of patients. However, our results need to be confirmed by larger-scale trials.

Point of care transthoracic echocardiography for the prediction of post - spinal anesthesia hypotension in elderly patients with cardiac diseases and left ventricular dysfunction : Inferior vena cava and post-spinal anesthesia hypotension in elderly patients.

In elderly patients with cardiac diseases, changes in cardiovascular physiology diminish cardiovascular reserve and predispose to hemodynamic instability after spinal anesthesia; hence, such patients could be at risk of postoperative complications. Additionally, transthoracic echocardiography (TTE) is used in clinical practice to evaluate cardiovascular hemodynamics. Therefore, we hypothesized that echocardiographic measurements could display significant diagnostic power in the prediction of post - spinal anesthesia hypotension in elderly patients with cardiac diseases and reduced left ventricular ejection fraction (LV-EF). Therefore, sixty-one elderly orthopedic-trauma patients were recruited. Prior to spinal anesthesia a TTE examination was performed. The LV-EF, the stroke volume index (SVI), the peripheral vascular resistance (PVR), the LV filling pressures (E/Em ratio), the right ventricular function [tricuspid annular plane systolic excursion (TAPSE), tricuspid annular systolic velocity (TASV) and fractional area change (FAC)], as well as inferior vena cava (IVC) measurements, such as IVCCI (collapsibility index of the IVC) and dIVCmax (maximum diameter of IVC)-to-IVCCI ratio were assessed. Twenty-six out of sixty-one patients manifested hypotension. Preoperative dIVCmax-to-IVCCI ratio demonstrated the greatest performance amongst echocardiographic indices in predicting post - spinal anesthesia hypotension. The dIVCmax-to-IVCCI ratio < 48 had significantly higher diagnostic power than IVCCI > 0.28, FAC > 42, E/Em ratio < 9 and SVI < 32 (receiver operator characteristic curve analysis). The gray zone for the dIVCmax-to-IVCCI ratio (40-49) showed the lowest number of inconclusive measurements among echocardiographic variables. The preoperative dIVCmax-to-IVCCI ratio could be a reliable echocardiographic index to predict post - spinal anesthesia hypotension in elderly patients with left ventricular dysfunction.

Predicting the need for mechanical ventilation and mortality in hospitalized COVID-19 patients who received heparin.

Although several studies have utilized AI (artificial intelligence)-based solutions to enhance the decision making for mechanical ventilation, as well as, for mortality in COVID-19, the extraction of explainable predictors regarding heparin's effect in intensive care and mortality has been left unresolved. In the present study, we developed an explainable AI (XAI) workflow to shed light into predictors for admission in the intensive care unit (ICU), as well as, for mortality across those hospitalized COVID-19 patients who received heparin. AI empowered classifiers, such as, the hybrid Extreme gradient boosting (HXGBoost) with customized loss functions were trained on time-series curated clinical data to develop robust AI models. Shapley additive explanation analysis (SHAP) was conducted to determine the positive or negative impact of the predictors in the model's output. The HXGBoost predicted the risk for intensive care and mortality with 0.84 and 0.85 accuracy, respectively. SHAP analysis indicated that the low percentage of lymphocytes at day 7 along with increased FiO2 at days 1 and 5, low SatO2 at days 3 and 7 increase the probability for mortality and highlight the positive effect of heparin administration at the early days of hospitalization for reducing mortality.

Clinical Symptoms in Hospitalized and Self-Quarantined Patients with SARS-CoV-2 Infection in Northwestern Greece - Association with Olfactory and Gustatory Dysfunction.

Backround: We aimed to assess the relation of chemosensory dysfunction with the reported symptoms in two subgroups of patients in Northwestern Greece: the first one included patients with moderate to severe symptomatology who needed hospitalization and the second one, patients with mild symptoms who recovered at home. Methods:We used a questionnaire to select information about patient demographics, medical history and reported symptoms during infection. Three hundred COVID-19 positive patients who were identified via RT-PCR test in the University Hospital of Ioannina, Greece, were included in the present study, of which 150 recovered at home and the remaining 150 needed hospitalization. Statistical analysis was based on IBM-SPSS Statistics 26.0. Results:The majority of patients had fever during infection, while o minor percentage of those who needed hospitalization (12.67%) suffered from sore throat. There was a statistically significant difference between the loss of smell and clinical symptoms including fatigue, nose congestion, body aches and headache, and loss of taste and reported symptoms including fatigue, body aches, runny nose, headache and sore throat. Conclusion: Fever was the symptom with the highest percentage rate, while sore throat was the symptom with the lowest percentage rate. There are reported clinical symptoms related with olfactory and gustatory dysfunction during COVID-19 infection.

The Impact of Age and Gender and Their Association with Chemosensory Dysfunction, in Hospitalized and Self-Quarantine Patients with Covid-19 Infection, in Epirus, Greece.

Objective:Olfactory and gustatory dysfunction that relates with the infection from severe acute respiratory syndrome-related coronavirus (SARS-CoV-2) has already improved. The relation between chemosensory dysfunction and age and gender in covid-19 positive patients is the main objective of the present study. Methods:We used a questionnaire to select information about medical history, patient demographics and reported symptoms during infection. Three hundred covid-19 positive patients, who underwent a RT-PCR test in the University Hospital of Ioannina, Grecce, were included in this study; 150 of them recovered at home and the remaining 150 were admitted to hospital. Statistical analysis based on ÉBM-SPSS Statistics 26.0 was done. Results:The total sample included 300 patients, of which 106 females and 194 males. There was a statistically significant difference between the subgroup of patients aged 21-25, 61-65 and 71-75 with loss of smell, that of hospitalized patients aged 41-45 with loss of smell and the subgroup of those aged 31-35 and 71-75 with loss of taste. Conclusion:There is a significant association between chemosensory dysfunction and younger age groups. Olfactory and gustatory dysfunction appears more frequently in women than men. Male gender relates with disease severity.

ICU admission and mortality classifiers for COVID-19 patients based on subgroups of dynamically associated profiles across multiple timepoints.

The coronavirus disease 2019 (COVID-19) which is caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is consistently causing profound wounds in the global healthcare system due to its increased transmissibility. Currently, there is an urgent unmet need to identify the underlying dynamic associations among COVID-19 patients and distinguish patient subgroups with common clinical profiles towards the development of robust classifiers for ICU admission and mortality. To address this need, we propose a four step pipeline which: (i) enhances the quality of multiple timeseries clinical data through an automated data curation workflow, (ii) deploys Dynamic Bayesian Networks (DBNs) for the detection of features with increased connectivity based on dynamic association analysis across multiple points, (iii) utilizes Self Organizing Maps (SOMs) and trajectory analysis for the early identification of COVID-19 patients with common clinical profiles, and (iv) trains robust multiple additive regression trees (MART) for ICU admission and mortality classification based on the extracted homogeneous clusters, to identify risk factors and biomarkers for disease progression. The contribution of the extracted clusters and the dynamically associated clinical data improved the classification performance for ICU admission to sensitivity 0.83 and specificity 0.83, and for mortality to sensitivity 0.74 and specificity 0.76. Additional information was included to enhance the performance of the classifiers yielding an increase by 4% in sensitivity and specificity for mortality. According to the risk factor analysis, the number of lymphocytes, SatO2, PO2/FiO2, and O2 supply type were highlighted as risk factors for ICU admission and the percentage of neutrophils and lymphocytes, PO2/FiO2, LDH, and ALP for mortality, among others. To our knowledge, this is the first study that combines dynamic modeling with clustering analysis to identify homogeneous groups of COVID-19 patients towards the development of robust classifiers for ICU admission and mortality.