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1.
European Stroke Journal ; 7(1 SUPPL):349-350, 2022.
Article in English | EMBASE | ID: covidwho-1928076

ABSTRACT

Background and aims: There is a higher incidence of cerebrovascular disease (CVD) in patients with SARS-CoV-2 infection. We aim to describe a national series of CVD in patients with confirmed SARS-CoV-2 infection. Methods: Fourteen Brazilian Stroke Centers registered clinical, neuroimaging and laboratory findings from April to November 2020. Results: We included 344 patients in the final analysis. Age ranged from 20-95 (median 57[57, 75] years). Cerebral ischemia (CI) occurred in 83.7%(n=288), intraparenchymal hemorrhage (IPH) 6.7%(n=23), central venous thrombosis (CVT) 5.2%(n=18) and subarachnoid hemorrhage (SAH) 4.4% (n=15). CVD was the first symptom of SARS-CoV-2 in 37.8% of cases - among those with SAH, 60% had no systemic symptoms. CI cases had higher values of Dimer-D compared to others. Involvement of at least two arterial territories occurred in 13.8%. Among IPH patients, 25% were under anticoagulation with heparin. Patients with SAH had a spontaneous etiology in 35.7%. Dimer-D levels at admission were associated with worse outcomes (mRS3-6) (OR1.14, 95%CI1.008-1.29, p=0.03), in an adjusted analysis. The time of onset of neurological symptoms (TONS) since SARS-CoV-2 infection was indirectly related to neurological severity at admission (-0.17, p=0.04,). In-hospital treatment with corticosteroids was associated with in-hospital encephalopathy (OR2.5,95%CI 1.01-6.16,p=0.04). Poor outcome (mRS3-5) occurred in 54.1% of cases. Conclusions: Patients with CVD and SARS-CoV-2 are at higher risk of unfavorable outcomes. The TONS since infection is related to neurologic severity;and serum Dimer-D levels may be useful for prognostication. The higher prevalence of non-aneurysmal SAH cases suggests pathophysiological mechanisms other than a hypercoagulable state.

2.
Hematology, Transfusion and Cell Therapy ; 43:S543-S544, 2021.
Article in English | EMBASE | ID: covidwho-1859764

ABSTRACT

Introduction: The variation in human blood serum metabolites resulting from an infection can assist in understanding mechanisms of pathogen action and body response and improve diagnosis. Aim: To map serum signatures of hospitalized symptomatic patients, positive or negative to SARS-CoV-2. Methods: Patients (n = 64) admitted to Anhembi Field Municipal Hospital, a hospital set up for initial care to patients with moderate symptoms, were analyzed being discriminated in positive (n = 32) or negative patients. Age and gender were matched to ensure homogeneity in the basal metabolic rates. Three Nuclear Magnetic Resonance (NMR) data set were recorded on Bruker AVANCE III 600 MHz spectrometer for serum samples analyzed in MetaboAnalyst 5.0 software platform. Results and discussion: The mean age of groups was 54.92 ±12.41 and 54.30 ±12.15, for positive and negative patients, divided in 16 female and 16 male. The ethnicity was 56.2% vs 46.8% caucasian, 34.3% mixed race in both groups, and 9.3% 12.5% vs black in positive and negative groups, respectively. BMI was 24 ±6.93 vs 33.5 ±7.85 in comparison to positive and negative patients, respectively. In both groups 50% of patients presented alveolar infiltrate. Although the groups were not paired by comorbidities, they were homogeneous ensuring that the metabolic variation is due to COVID-19 as similar percentage of patients with arterial hypertension, diabetes and dyslipidemia. Clinical symptoms were also remarkably similar between the groups in relation to: fever, dry cough, dyspnea and myalgia. The Partial Least Squares - Discriminant Analysis (PLS-DA) performed onto noesy1d data discriminated positively from negative patients. Also, it covered lower variance. Combining NMR techniques, it was possible to depict the main metabolites that distinguished the COVID-19 signatures. Alanine, glucose, cholesterol, and glutamine were increased, and lactate decreased in COVID-19. Conclusion: These results suggest NMR as an excellent tool to differentiate hospitalized patients with moderate symptoms as COVID-19 positive or negative. The Ethics Research Committee of the University of Campinas approved all of the experimental procedures, and all individuals signed the informed consent form.

3.
Hematology, Transfusion and Cell Therapy ; 43:S242-S243, 2021.
Article in English | EMBASE | ID: covidwho-1859617

ABSTRACT

Introduction: The main factors associated with disease severity in Covid-19 are age, sex, body weight, hypertension, and diabetes. Biomarkers of hemostatic activation have been shown to be independent predictors of disease severity in different populations. Aim: To evaluate whether biomarkers of hemostatic activation were associated with clinical outcomes in patients admitted to a field hospital set up to provide initial care to patients in the early symptomatic phase of Covid-19. Methods: Data and samples were obtained from June to September 2020. Laboratory evaluation included complete blood counts, PT, aPTT, fibrinogen, D-dimer, factor VIII activity, Von Willebrand Factor (VWF) (activity and antigen), C reactive protein (CRP) and P-selectin (ELISA). Patients were segregated by outcome, with clinical worsening defined as need for ICU, mechanical ventilation, pulmonary embolism, deep vein thrombosis or death. Results and discussion: In total 209 were enrolled in the study, of which 24 presented clinical deterioration (11.5%). In both groups there was more male patients. In the group of clinical worsening the mean age was 58.1 and improvement was 53.6 years old. Concerning smoking, 3.2% of patients that improved smoke. Regarding pulmonar infiltrate, it was verified in 50% in the group that worsening versus 41% in clinical improvement. No differences could be observed between patient subgroups regarding the presence of fever (63.2% vs. 62.5%), dry cough (75.1% vs. 87.5%) and dyspnea (65.9% vs. 54.2%) at admission. As main comorbidities, the groups presented chronic obstructive pulmonary disease (2.2% vs 8.3%), asthma (3.2% vs 4.2%), chronic heart failure (1.1% vs 8.3%), arterial hypertension (46% vs 41.7%) and diabetes (28.1% vs 33.3%) in comparing improved with clinical deterioration patients. In general, it was verified a significant decrease in platelet number (p = 0.0426), and an increase in the parameters of aPTT (0.0084), CRP (p = 0.0450), vWF antigen (p = 0.0022) and ristocetin cofactor (p = 0.0032). Conclusion: Our results demonstrate that hemostasis activation is associated with clinical deterioration even at the early phases of Covid-19. The Ethics Research Committee of the University of Campinas approved all of the experimental procedures, and all individuals signed the informed consent form.

4.
Actas Esp Psiquiatr ; 50(1):63-64, 2022.
Article in English | PubMed | ID: covidwho-1661267

ABSTRACT

The COVID-19 pandemic has already infected more than 182 million people and killed more than 4 million all over the globe. In addition to its direct health effects, lockdowns and other draconian public health measures, along with an expected economic crisis of unprecedent magnitude, unpre- dictable social effects are being generated.

5.
European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology ; 53:S592-S593, 2021.
Article in English | EuropePMC | ID: covidwho-1602243
6.
European Neuropsychopharmacology ; 53:S592-S593, 2021.
Article in English | EMBASE | ID: covidwho-1595781

ABSTRACT

Introduction: Evidence demonstrates that 25-33% of hospitalized patients with COVID-19 develop delirium [1,2], with rates up to 65% in critically ill patients [3]. Several potential reasons, including the use of deep sedation and invasive mechanical ventilation (IMV), as well as the restrictions to limit infection transmission, such as prohibition of family visits and minimal contact with health staff were identified [4]. Although factors and outcomes associated with delirium are well documented, limited data are available regarding severe COVID-19 patients. Aims: This study aims to estimate the rates of delirium in critically ill COVID-19 patients and to analyze factors that may be associated with its development, as well as to examine long-term outcomes. Methods: From March to May 2020 (in COVID-19 first wave), all adult patients (≥18y.o.) admitted due to COVID-19, in the Intensive Care Medicine Department (ICMD) of a University Hospital (CHUSJ), in Porto, Portugal, were assessed, unless they had a ICMD length of stay (LoS) ≤24h, terminal illness or major sensory loss or inability to communicate at the time of follow-up. Participants were evaluated during a scheduled telephone follow-up appointment with a comprehensive protocol, including: Six-item Cognitive Impairment Test (6CIT) (cognitive impairment);Patient Health Questionnaire (PHQ-9) (symptoms of depression);General Anxiety Disorder (GAD-7) (symptoms of anxiety);and EuroQol five-dimension five-level questionnaire (EQ-5D-5L) (health-related quality of life-HRQoL), which includes EQ-Visual Analogue Scale (EQ-VAS) (global health status patient perception). Data on acute illness severity, sedative/analgesic drugs use, respiratory support and major complications (including delirium, nosocomial infections and difficulty weaning from mechanical ventilation) during ICMD stay, were obtained from hospital electronic records review. Patients with and without delirium were compared, using Mann-Whitney test for continuous variables, and Chi-square or Fisher tests for paired categorical variables (significance level of 0.05). This study is part of an ongoing larger multidisciplinary research project (MAPA-Mental Health in Critically ill patients with COVID-19). Results: The sample included 59 patients (median age=65 years;66.1% male). Delirium was registered in almost half of the sample (49.2%). Patients with delirium were significantly older (median=72 vs. 62;p=0.010) and presented more nosocomial infections (82.8% vs 53.3%;p=0.032) particularly ventilator-associated pneumonia (75.9% vs. 33.3%;p=0.003). Also, they were significantly more likely to be deeply sedated (89.7% vs 60%;p=0.021), more often required IMV (89.7% vs 60%;p=0.021). Moreover, those with delirium stayed longer in the hospital (median=67 vs 37 days;p=0.014). Concerning HRQoL, assessed at follow-up appointment, patients who have developed delirium reported more problems in self-care (48.3% vs 10%;p=0.003) and in everyday activities (79.3% vs 53.3%;p=0.035) after hospital discharge. Nevertheless, no statistically significant differences were found for cognitive impairment, symptoms of anxiety and depression. Conclusions: Delirium was common in this critically ill COVID-19 sample, namely in older patients, who have been deeply sedated, invasively ventilated or had major ICU complications. It was associated with longer hospital stay and worse HRQoL. Recognizing potential associated factors will allow the identification of high-risk patients that should be targeted for early screening with preventive interventions to minimize the adverse outcomes associated to delirium in critical COVID-19 patients. No conflict of interest

7.
Nguyen, T.; Qureshi, M.; Martins, S.; Yamagami, H.; Qiu, Z.; Mansour, O.; Czlonkowska, A.; Abdalkader, M.; Sathya, A.; de Sousa, D. A.; Demeestere, J.; Mikulik, R.; Vanacker, P.; Siegler, J.; Korv, J.; Biller, J.; Liang, C.; Sangha, N.; Zha, A.; Czap, A.; Holmstedt, C.; Turan, T.; Grant, C.; Ntaios, G.; Malhotra, K.; Tayal, A.; Loochtan, A.; Mistry, E.; Alexandrov, A.; Huang, D.; Yaghi, S.; Raz, E.; Sheth, S.; Frankel, M.; Lamou, E. G. B.; Aref, H.; Elbassiouny, A.; Hassan, F.; Mustafa, W.; Menecie, T.; Shokri, H.; Roushdy, T.; Sarfo, F. S.; Alabi, T.; Arabambi, B.; Nwazor, E.; Sunmonu, T. A.; Wahab, K. W.; Mohammed, H. H.; Adebayo, P. B.; Riahi, A.; Ben Sassi, S.; Gwaunza, L.; Rahman, A.; Ai, Z. B.; Bai, F. H.; Duan, Z. H.; Hao, Y. G.; Huang, W. G.; Li, G. W.; Li, W.; Liu, G. Z.; Luo, J.; Shang, X. J.; Sui, Y.; Tian, L.; Wen, H. B.; Wu, B.; Yan, Y. Y.; Yuan, Z. Z.; Zhang, H.; Zhang, J.; Zhao, W. L.; Zi, W. J.; Leung, T. K.; Sahakyan, D.; Chugh, C.; Huded, V.; Menon, B.; Pandian, J.; Sylaja, P. N.; Usman, F. S.; Farhoudi, M.; Sadeghi-Hokmabadi, E.; Reznik, A.; Sivan-Hoffman, R.; Horev, A.; Ohara, N.; Sakai, N.; Watanabe, D.; Yamamoto, R.; Doijiri, R.; Tokuda, N.; Yamada, T.; Terasaki, T.; Yazawa, Y.; Uwatoko, T.; Dembo, T.; Shimizu, H.; Sugiura, Y.; Miyashita, F.; Fukuda, H.; Miyake, K.; Shimbo, J.; Sugimura, Y.; Yagita, Y.; Takenobu, Y.; Matsumaru, Y.; Yamada, S.; Kono, R.; Kanamaru, T.; Yamazaki, H.; Sakaguchi, M.; Todo, K.; Yamamoto, N.; Sonodda, K.; Yoshida, T.; Hashimoto, H.; Nakahara, I.; Faizullina, K.; Kamenova, S.; Kondybayeva, A.; Zhanuzakov, M.; Baek, J. H.; Hwang, Y.; Lee, S. B.; Moon, J.; Park, H.; Seo, J. H.; Seo, K. D.; Young, C. J.; Ahdab, R.; Aziz, Z. A.; Zaidi, W. A. W.; Bin Basri, H.; Chung, L. W.; Husin, M.; Ibrahim, A. B.; Ibrahim, K. A.; Looi, I.; Tan, W. Y.; Yahya, Wnnw, Groppa, S.; Leahu, P.; Al Hashmi, A.; Imam, Y. Z.; Akhtar, N.; Oliver, C.; Kandyba, D.; Alhazzani, A.; Al-Jehani, H.; Tham, C. H.; Mamauag, M. J.; Narayanaswamy, R.; Chen, C. H.; Tang, S. C.; Churojana, A.; Aykac, O.; Ozdemir, A. O.; Hussain, S. I.; John, S.; Vu, H. L.; Tran, A. D.; Nguyen, H. H.; Thong, P. N.; Nguyen, T.; Nguyen, T.; Gattringer, T.; Enzinger, C.; Killer-Oberpfalzer, M.; Bellante, F.; De Blauwe, S.; Van Hooren, G.; De Raedt, S.; Dusart, A.; Ligot, N.; Rutgers, M.; Yperzeele, L.; Alexiev, F.; Sakelarova, T.; Bedekovic, M. R.; Budincevic, H.; Cindric, I.; Hucika, Z.; Ozretic, D.; Saric, M. S.; Pfeifer, F.; Karpowicz, I.; Cernik, D.; Sramek, M.; Skoda, M.; Hlavacova, H.; Klecka, L.; Koutny, M.; Vaclavik, D.; Skoda, O.; Fiksa, J.; Hanelova, K.; Nevsimalova, M.; Rezek, R.; Prochazka, P.; Krejstova, G.; Neumann, J.; Vachova, M.; Brzezanski, H.; Hlinovsky, D.; Tenora, D.; Jura, R.; Jurak, L.; Novak, J.; Novak, A.; Topinka, Z.; Fibrich, P.; Sobolova, H.; Volny, O.; Christensen, H. K.; Drenck, N.; Iversen, H.; Simonsen, C.; Truelsen, T.; Wienecke, T.; Vibo, R.; Gross-Paju, K.; Toomsoo, T.; Antsov, K.; Caparros, F.; Cordonnier, C.; Dan, M.; Faucheux, J. M.; Mechtouff, L.; Eker, O.; Lesaine, E.; Ondze, B.; Pico, F.; Pop, R.; Rouanet, F.; Gubeladze, T.; Khinikadze, M.; Lobjanidze, N.; Tsiskaridze, A.; Nagel, S.; Ringleb, P. A.; Rosenkranz, M.; Schmidt, H.; Sedghi, A.; Siepmann, T.; Szabo, K.; Thomalla, G.; Palaiodimou, L.; Sagris, D.; Kargiotis, O.; Kaliaev, A.; Liebeskind, D.; Hassan, A.; Ranta, A.; Devlin, T.; Zaidat, O.; Castonguay, A.; Jovin, T.; Tsivgoulis, G.; Malik, A.; Ma, A.; Campbell, B.; Kleinig, T.; Wu, T.; Gongora, F.; Lavados, P.; Olavarria, V.; Lereis, V. P.; Corredor, A.; Barbosa, D. M.; Bayona, H.; Barrientos, J. D.; Patino, M.; Thijs, V.; Pirson, A.; Kristoffersen, E. S.; Patrik, M.; Fischer, U.; Bernava, G.; Renieri, L.; Strambo, D.; Ayo-Martin, O.; Montaner, J.; Karlinski, M.; Cruz-Culebras, A.; Luchowski, P.; Krastev, G.; Arenillas, J.; Gralla, J.; Mangiafico, S.; Blasco, J.; Fonseca, L.; Silva, M. L.; Kwan, J.; Banerjee, S.; Sangalli, D.; Frisullo, G.; Yavagal, D.; Uyttenboogaart, M.; Bandini, F.; Adami, A.; de Lecina, M. A.; Arribas, M. A. T.; Ferreira, P.; Cruz, V. T.; Nunes, A. P.; Marto, J. P.; Rodrigues, M.; Melo, T.; Saposnik, G.; Scott, C. A.; Shuaib, A.; Khosravani, H.; Fields, T.; Shoamanesh, A.; Catanese, L.; Mackey, A.; Hill, M.; Etherton, M.; Rost, N.; Lutsep, H.; Lee, V.; Mehta, B.; Pikula, A.; Simmons, M.; Macdougall, L.; Silver, B.; Khandelwal, P.; Morris, J.; Novakovic-White, R.; Ramakrishnan, P.; Shah, R.; Altschul, D.; Almufti, F.; Amaya, P.; Ordonez, C. E. R.; Lara, O.; Kadota, L. R.; Rivera, L. I. P.; Novarro, N.; Escobar, L. D.; Melgarejo, D.; Cardozo, A.; Blanco, A.; Zelaya, J. A.; Luraschi, A.; Gonzalez, V. H. N.; Almeida, J.; Conforto, A.; Almeida, M. S.; Silva, L. D.; Cuervo, D. L. M.; Zetola, V. F.; Martins, R. T.; Valler, L.; Giacomini, L. V.; Cardoso, F. B.; Sahathevan, R.; Hair, C.; Hankey, G.; Salazar, D.; Lima, F. O.; Mont'Alverne, F.; Moises, D.; Iman, B.; Magalhaes, P.; Longo, A.; Rebello, L.; Falup-Pecurariu, C.; Mazya, M.; Wisniewska, A.; Fryze, W.; Kazmierski, R.; Wisniewska, M.; Horoch, E.; Sienkiewicz-Jarosz, H.; Fudala, M.; Rogoziewicz, M.; Brola, W.; Sobolewski, P.; Kaczorowski, R.; Stepien, A.; Klivenyi, P.; Szapary, L.; van den Wijngaard, I.; Demchuk, A.; Abraham, M.; Alvarado-Ortiz, T.; Kaushal, R.; Ortega-Gutierrez, S.; Farooqui, M.; Bach, I.; Badruddin, A.; Barazangi, N.; Nguyen, C.; Brereton, C.; Choi, J. H.; Dharmadhikari, S.; Desai, K.; Doss, V.; Edgell, R.; Linares, G.; Frei, D.; Chaturvedi, S.; Gandhi, D.; Chaudhry, S.; Choe, H.; Grigoryan, M.; Gupta, R.; Helenius, J.; Voetsch, B.; Khwaja, A.; Khoury, N.; Kim, B. S.; Kleindorfer, D.; McDermott, M.; Koyfman, F.; Leung, L.; Linfante, I.; Male, S.; Masoud, H.; Min, J. Y.; Mittal, M.; Multani, S.; Nahab, F.; Nalleballe, K.; Rahangdale, R.; Rafael, J.; Rothstein, A.; Ruland, S.; Sharma, M.; Singh, A.; Starosciak, A.; Strasser, S.; Szeder, V.; Teleb, M.; Tsai, J.; Mohammaden, M.; Pineda-Franks, C.; Asyraf, W.; Nguyen, T. Q.; Tarkanyi, G.; Horev, A.; Haussen, D.; Balaguera, O.; Vasquez, A. R.; Nogueira, R..
Neurology ; 96(15):42, 2021.
Article in English | Web of Science | ID: covidwho-1576349
8.
International Conference in Information Technology and Education, ICITED 2021 ; 256:861-869, 2022.
Article in English | Scopus | ID: covidwho-1565334

ABSTRACT

In 2020, the world was plagued by the COVID-19 pandemic, given this circumstance;new ways of acting were implemented to stop the transmission of the virus. Non-essential services were transferred to work-from-home and educational institutions, with all their human structure, needed to operate in emergency and remotely. The graduate course and the necessary guidelines suddenly started to be carried out virtually employing communication and information technologies (ICT). Therefore, the objective of this paper was to report a work experience that involved three post-doctoral students and one doctoral student from a Brazilian graduate program in Education, in exchange in Portugal, during the 2020 Research Stay year. For that, forms were sent via Google Forms to the participants to collect their perceptions about the teaching and learning practice while using ICT, in an emergency remote way. Afterward, the data collected was organized in spreadsheets and qualitative analysis of the data was carried out with Content Analysis techniques. The results show that many tools were already used frequently and, during the pandemic, the free time to invest in other academic activities increased. The authors concluded that the physical distance and the use of technologies made it possible to reduce distances and increase social interaction for the efficient teaching-learning process in times of crisis. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

9.
International Psychogeriatrics ; 33:98-99, 2021.
Article in English | Web of Science | ID: covidwho-1548478
10.
European Journal of Public Health ; 31, 2021.
Article in English | ProQuest Central | ID: covidwho-1514519

ABSTRACT

Background Worldwide there is an overwhelming amount of information about COVID-19 circulating online, also named infodemic. Misinformation (the unintentional) and disinformation (the intentional) spreading of false information have proven to be very dangerous to public health. Hence, more than ever, people need skills for searching, evaluating and integrating information related to health in daily life, i.e., health literacy. Until now, little is known about the digital health literacy of university students and their information-seeking behaviour. Hence, this study aimed to analyse the associations between university students' digital health literacy and online information queries during the beginning of the COVID-19 pandemic (and infodemic) in Portugal. Methods A cross-sectional study of 3.084 Portuguese university students (75.7% females), with an average age of 24.2 (SD = 7.5), was conducted using an online survey. We used sociodemographic data (sex, age, subjective social status) and the digital health literacy questionnaire adapted to the specific COVID-19 context. Online information queries included the topics related to SARS-CoV-2 and COVID-19 searched by students. Logistic regression models were performed. Results Online information queries (e.g., individual measures to protect against infection, current spread of the virus, current situation assessments and recommendations) were associated with an increased odds of achieving sufficient digital health literacy. Conclusions Online information queries related to epidemiological and public health topics are significantly associated with digital health literacy in times of COVID-19. Further studies are needed, including programs that improve digital health literacy among university students and increase the availability of high-quality content information.

11.
Research and Practice in Thrombosis and Haemostasis ; 5(SUPPL 2), 2021.
Article in English | EMBASE | ID: covidwho-1509064

ABSTRACT

Background : The early prediction of Covid-19 progression could improve patient's treatment. It is important to develop mathematical models to perform this task using simple blood tests. Aims : To obtain a neural network (ANN) to predict the progression (death vs discharge and intubation vs discharge) of Covid-19 in patients with confirmed diagnosis. Methods : The patients included in this work were diagnosed with Covid-19 by RT-PCR. All data were collected from hospitalized patients admitted to Anhembi Field Municipal Hospital (São Paulo-Brazil), a hospital set up for initial care to patients with moderate symptoms during the pandemic, between June/2020 and October/2020. Blood was collected at the patient's admission. The inputs considered were: sex, age, ethinicity, body mass index, tabagism, ex-tabagism, alveolar infiltrate, arterial hypertension, diabetes, heart rate, respiration rate, body temperature, oxygen saturation, D-dimer, activated partial thromboplastin time, prothrombin time, levels of: hemoglobin, platelet, leukocytes, lymphocytes, monocytes, neutrophils, lactate dehydrogenase, C-reactive protein, and creatinine. Two ANNs were proposed, as shown at Table 1. The best ANN was defined by a 5-fold cross-validation scheme. Finally, a test step was performed to verify the ANN performance. ANNs with one and two hidden layers were tested. The number of neurons ranged from 5 to 35. Results : The main results are shown at Table 2. The best models were obtained with different ANN's structures, which show the influence of the different outcome. The models presented high ACC, AUC, PPV, NPV, and TNR. The ANN 2 presented better performance than ANN 1. We believe that this may be due the data homogeneity that rises from the inclusion criteria adopted in the study. Conclusions : The results showed that the ANNs could be used to predict the progression of Covid-19 based on simple blood tests. The models could be used in the future after an external validation with high number of patients.

12.
Research and Practice in Thrombosis and Haemostasis ; 5(SUPPL 2), 2021.
Article in English | EMBASE | ID: covidwho-1509063

ABSTRACT

Background : Fast and accurate diagnosis of COVID-19 is important to prevent dissemination and disease progression. Artificial Intelligence is known as a universal fitting tool and can be used on the formulation of predictive models for the disease's diagnosis. Aims : Obtain a neural network (ANN) to diagnose patients as positive or negative COVID-19 based on patient data and blood tests. Methods : Data from 678 patients with moderate symptoms from the Anhembi Field Municipal Hospital (São Paulo-Brazil), followed between June/2020 and October/2020 were used. Covid-19 by RTPCR was confirmed in 460 patients. The inputs considered were: sex, age, ethinicity, body mass index, tabagism, ex-tabagism, alveolar infiltrate, arterial hypertension, diabetes, heart rate, respiration rate, body temperature, oxygen saturation, D-dimer, activated partial thromboplastin time, prothrombin time, levels of: hemoglobin, platelet, leukocytes, lymphocytes, monocytes, neutrophils, lactate dehydrogenase, C-reactive protein, and creatinine. Blood was collected at the patient's admission. The ANNs had 25 inputs and the output was the Covid-19 diagnosis. The best ANN was defined by a 5-fold cross-validation scheme. Then, a test step was performed to assess the model's performance. ANNs with one and two hidden layers were proposed. The number of neurons ranged from 5 to 35. Results : The best result was obtained with an ANN containing 25 and 30 neurons in the first and second hidden layers, respectively. All the statistical parameters found for the best model are shown at Table 1. The model presented accuracy of 83.3 %, high capacity for the prediction of true positives (PPV = 0.917 and LR+ = 5.188), and moderate probability to indicate false negatives (LR-= 0.202). Conclusions : The results showed that the ANNs are promising to diagnose Covid-19 based on clinical parameters and blood tests. After future refinements and proper validation, this model could be used to diagnose Covid-19 on daily basis.

13.
Research and Practice in Thrombosis and Haemostasis ; 5(SUPPL 2), 2021.
Article in English | EMBASE | ID: covidwho-1509062

ABSTRACT

Background : The variation in human blood serum metabolites resulting from an infection can improve diagnosis. Aims : To map serum signatures of hospitalized symptomatic patients, positive or negative to SARS-CoV-2. Methods : Patients ( n = 64) admitted to Anhembi Field Municipal Hospital, a hospital set up for initial care to patients with moderate symptoms, were analyzed being discriminated in positive ( n = 32) or negative. Age and gender were matched to ensure homogeneity in the basal metabolic rates. Three Nuclear Magnetic Resonance (NMR) data set were recorded on Bruker AVANCE III spectrometer for serum samples analyzed in MetaboAnalyst 5.0 software platform. Results : The results for positive and negative patients were: mean age 54.92 ± 12.41 and 54.30 ± 12.15, and 50% female in each group. The ethnicity was 56.2% vs . 46.8% caucasian, 34.3% mixed race in both groups, and 9.3% vs . 12.5% black in positive and negative groups, respectively. BMI was 24 ± 6.93 vs . 33.5 ± 7.85 in comparison to positive and negative patients, respectively. In both groups 50% of patients presented alveolar infiltrate. Although the groups were not paired by comorbidities, they were homogeneous ensuring that the metabolic variation is due to COVID-19. Clinical symptoms were also remarkably similar between the groups (Table 1). The Partial Least Squares -Discriminant Analysis (PLS-DA) performed onto noesy1d data discriminated positively from negative patients (Figure 1.A). Also, it covered lower variance (Figure 1.B). Combining NMR techniques, it was possible to depict the main metabolites that distinguished the COVID-19 signatures. Alanine, glucose, cholesterol, and glutamine were increased, and lactate decreased (Figure 1.C.) in COVID-19. Conclusions : These results suggest NMR as an excellent tool to differentiate hospitalized patients with moderate symptoms as COVID-19 positive or negative.

14.
Research and Practice in Thrombosis and Haemostasis ; 5(SUPPL 2), 2021.
Article in English | EMBASE | ID: covidwho-1509022

ABSTRACT

Background : The main factors associated with disease severity in COVID-19 are age, sex, body weight, hypertension, and diabetes. Biomarkers of hemostatic activation have been shown to be independent predictors of disease severity in different populations of inpatients. Aims : To evaluate whether biomarkers of hemostatic activation were associated with clinical outcomes in patients admitted to a field hospital, set up to provide initial care to patients in the early symptomatic phase of COVID-19. Methods : Data and samples were obtained from June to September 2020. Laboratory evaluation included complete blood counts, PT, aPTT, fibrinogen, D-dimer, factor VIII activity, Von Willebrand Factor (VWF) (activity and antigen), C reactive protein (CRP) and Pselectin (ELISA). Patients were segregated by outcome, with clinical deterioration defined as need for ICU, mechanical ventilation, pulmonary embolism, deep vein thrombosis or death. Results : In total 209 were enrolled in the study, of which 24 presented clinical deterioration (11.5%). Clinical data are described in Table 1. No differences could be observed between patient subgroups regarding the presence of fever (63.2% vs . 62.5%), dry cough (75.1% vs . 87.5%) and dyspnea (65.9% vs . 54.2%) at admission. As main comorbidities, the groups presented chronic obstructive pulmonary disease (2.2% vs 8.3%), asthma (3.2% vs 4.2%), chronic heart failure (1.1% vs 8.3%), arterial hypertension (46% vs 41.7%) and diabetes (28.1% vs 33.3%) in comparing improved with clinical deterioration patients. Laboratory markers of hemostatic activation are shown in Table 2. In general, it was verified a significant decrease in platelet number, and an increase in the parameters of aPTT, CRP, vWF antigen and ristocetin cofactor. Conclusions : Our results demonstrate that hemostasis activation is associated with clinical deterioration even at the early phases of COVID-19.

15.
Surgery, Gastroenterology and Oncology ; 26(3):172-176, 2021.
Article in English | Scopus | ID: covidwho-1503026

ABSTRACT

Background: The COVID-19 pandemic created an enormous burden on global health systems by decreasing health care access and delaying care. Acute appendicitis (AA) is one of the most common surgical emergencies worldwide. Our goal was to determine if patients treated for AA during the pandemic period had more morbidity. Methods: A retrospective study was conducted including patients with AA, from a two-months period in 2020 and a control group from a homologous period in 2019. These groups were compared regarding demographics, surgical findings, surgical and postoperative complications. Results: 68 patients were diagnosed with AA (34 - 2020 and 34 - 2019). In 2020, 2 patients were conservatively treated and 32 underwent surgical appendectomy (2 open surgery - OS and 30 laparoscopic surgery - LPS). In 2019, 1 patient had OS and 33 had LPS. No prior demographic and discharge times were observed. An increase in time until surgery and in number of complications was observed. Conclusion: There were no differences in the total number of AA, however the increased time until surgery can be attributed to the time spent waiting for SARS-CoV test results. The similar discharge time but increased number of complications could be explained by delayed presentation to the emergencies room. © 2021 Celsius Publishing House. All rights reserved.

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Nguyen, T.; Qureshi, M.; Martins, S.; Yamagami, H.; Qiu, Z.; Mansour, O.; Czlonkowska, A.; Abdalkader, M.; Sathya, A.; Sousa, D. A.; Demeester, J.; Mikulik, R.; Vanacker, P.; Siegler, J.; Korv, J.; Biller, J.; Liang, C.; Sangha, N.; Zha, A.; Czap, A.; Holmstedt, C.; Turan, T.; Grant, C.; Ntaios, G.; Malhotra, K.; Tayal, A.; Loochtan, A.; Mistry, E.; Alexandrov, A.; Huang, D.; Yaghi, S.; Raz, E.; Sheth, S.; Frankel, M.; Lamou, E. G. B.; Aref, H.; Elbassiouny, A.; Hassan, F.; Mustafa, W.; Menecie, T.; Shokri, H.; Roushdy, T.; Sarfo, F. S.; Alabi, T.; Arabambi, B.; Nwazor, E.; Sunmonu, T. A.; Wahab, K. W.; Mohammed, H. H.; Adebayo, P. B.; Riahi, A.; Sassi, S. B.; Gwaunza, L.; Rahman, A.; Ai, Z.; Bai, F.; Duan, Z.; Hao, Y.; Huang, W.; Li, G.; Li, W.; Liu, G.; Luo, J.; Shang, X.; Sui, Y.; Tian, L.; Wen, H.; Wu, B.; Yan, Y.; Yuan, Z.; Zhang, H.; Zhang, J.; Zhao, W.; Zi, W.; Leung, T. K.; Sahakyan, D.; Chugh, C.; Huded, V.; Menon, B.; Pandian, J.; Sylaja, P. N.; Usman, F. S.; Farhoudi, M.; Sadeghi-Hokmabadi, E.; Reznik, A.; Sivan-Hoffman, R.; Horev, A.; Ohara, N.; Sakai, N.; Watanabe, D.; Yamamoto, R.; Doijiri, R.; Kuda, N.; Yamada, T.; Terasaki, T.; Yazawa, Y.; Uwatoko, T.; Dembo, T.; Shimizu, H.; Sugiura, Y.; Miyashita, F.; Fukuda, H.; Miyake, K.; Shimbo, J.; Sugimura, Y.; Yagita, Y.; Takenobu, Y.; Matsumaru, Y.; Yamada, S.; Kono, R.; Kanamaru, T.; Yamazaki, H.; Sakaguchi, M.; Todo, K.; Yamamoto, N.; Sonodda, K.; Yoshida, T.; Hashimoto, H.; Nakahara, I.; Faizullina, K.; Kamenova, S.; Kondybayev, A.; Zhanuzakov, M.; Baek, J. H.; Hwang, Y.; Lee, S. B.; Moon, J.; Park, H.; Seo, J. H.; Seo, K. D.; Young, C. J.; Ahdab, R.; Aziz, Z. A.; Zaidi, W. A. W.; Basr, H. B.; Chung, L. W.; Husin, M.; Ibrahim, A. B.; Ibrahim, K. A.; Looi, I.; Tan, W. Y.; Yahya, W. N. W.; Groppa, S.; Leahu, P.; Hashmi, A. A.; Imam, Y. Z.; Akhtar, N.; Oliver, C.; Kandyba, D.; Alhazzani, A.; Al-Jehani, H.; Tham, C. H.; Mamauag, M. J.; Narayanaswamy, R.; Chen, C. H.; Tang, S. C.; Churojana, A.; Aykaç, O.; Özdemir, A.; Hussain, S. I.; John, S.; Vu, H. L.; Tran, A. D.; Nguyen, H. H.; Thong, P. N.; Nguyen, T.; Nguyen, T.; Gattringer, T.; Enzinger, C.; Killer-Oberpfalzer, M.; Bellante, F.; Deblauwe, S.; Hooren, G. V.; Raedt, S. D.; Dusart, A.; Ligot, N.; Rutgers, M.; Yperzeele, L.; Alexiev, F.; Sakelarova, T.; Bedekovic, M.; Budincevic, H.; Cindric, I.; Hucika, Z.; Ozretic, D.; Saric, M. S.; Pfeifer, F.; Karpowicz, I.; Cernik, D.; Sramek, M.; Skoda, M.; Hlavacova, H.; Klecka, L.; Koutny, M.; Skoda, O.; Fiksa, J.; Hanelova, K.; Nevsimalova, M.; Rezek, R.; Prochazka, P.; Krejstova, G.; Neumann, J.; Vachova, M.; Brzezanski, H.; Hlinovsky, D.; Tenora, D.; Jura, R.; Jurak, L.; Novak, J.; Novak, A.; Topinka, Z.; Fibrich, P.; Sobolova, H.; Volny, O.; Christensen, H. K.; Drenck, N.; Iversen, H.; Simonsen, C.; Truelsen, T.; Wienecke, T.; Vibo, R.; Gross-Paju, K.; Toomsoo, T.; Antsov, K.; Caparros, F.; Cordonnier, C.; Dan, M.; Faucheux, J. M.; Mechtouff, L.; Eker, O.; Lesaine, E.; Pico, F.; Pop, R.; Rouanet, F.; Gubeladze, T.; Khinikadze, M.; Lobjanidze, N.; Tsiskaridze, A.; Nagel, S.; Arthurringleb, P.; Rosenkranz, M.; Schmidt, H.; Sedghi, A.; Siepmann, T.; Szabo, K.; Thomalla, G.; Palaiodimou, L.; Sagris, D.; Kargiotis, O.; Kaliaev, A.; Liebeskind, D.; Hassan, A.; Ranta, A.; Devlin, T.; Zaidat, O.; Castonguay, A.; Jovin, T.; Tsivgoulis, G.; Malik, A.; Ma, A.; Campbel, B.; Kleinig, T.; Wu, T.; Gongora, F.; Lavados, P.; Olavarria, V.; Lereis, V. P.; Corredor, A.; Barbosa, D. M.; Bayona, H.; Barrientos, J. D.; Patino, M.; Thijs, V.; Pirson, A.; Kristoffersen, E. S.; Patrik, M.; Fischer, U.; Bernava, G.; Renieri, L.; Strambo, D.; Ayo-Martin, O.; Montaner, J.; Karlinski, M.; Cruz-Culebras, A.; Luchowski, P.; Krastev, G.; Arenillas, J.; Gralla, J.; Mangiafico, S.; Blasco, J.; Fonseca, L.; Silva, M. L.; Kwan, J.; Banerjee, S.; Sangalli, D.; Frisullo, G.; Yavagal, D.; Uyttenboogaart, M.; Bandini, F.; Adami, A.; Lecina, M. A. D.; Arribas, M. A. T.; Ferreira, P.; Cruz, V. T.; Nunes, A. P.; Marto, J. P.; Rodrigues, M.; Melo, T.; Saposnik, G.; Scott, C. A.; Shuaib, A.; Khosravani, H.; Fields, T.; Shoamanesh, A.; Catanese, L.; MacKey, A.; Hill, M.; Etherton, M.; Rost, N.; Lutsep, H.; Lee, V.; Mehta, B.; Pikula, A.; Simmons, M.; MacDougall, L.; Silver, B.; Khandelwal, P.; Morris, J.; Novakovic-White, R.; Shah, R.; Altschul, D.; Almufti, F.; Amaya, P.; Ordonez, C. E. R.; Lara, O.; Kadota, L. R.; Rivera, L. I.; Novarro, N.; Escobar, L. D.; Melgarejo, D.; Cardozo, A.; Blanco, A.; Zelaya, J. A.; Luraschi, A.; Gonzalez, V. H.; Almeida, J.; Conforto, A.; Almeida, M. S.; Silva, L. D. D.; Cuervo, D. L. M.; Zetola, V. F.; Martins, R. T.; Valler, L.; Giacomini, L. V.; Buchdidcardoso, F.; Sahathevan, R.; Hair, C.; Hankey, G.; Salazar, D.; Lima, F. O.; Mont'alverne, F.; Iman, D. M. B.; Longo, A.; Rebello, L.; Falup-Pecurariu, C.; Mazya, M.; Wisniewska, A.; Fryze, W.; Kazmierski, R.; Wisniewska, M.; Horoch, E.; Sienkiewicz-Jarosz, H.; Fudala, M.; Goziewicz, M.; Brola, W.; Sobolewski, P.; Kaczorowski, R.; Stepien, A.; Klivenyi, P.; Szapary, L.; Wijngaard, I. V. D.; Demchuk, A.; Abraham, M.; Alvarado-Ortiz, T.; Kaushal, R.; Ortega-Gutierrez, S.; Farooqui, M.; Bach, I.; Badruddin, A.; Barazangi, N.; Nguyen, C.; Brereton, C.; Choi, J. H.; Dharmadhikari, S.; Desai, K.; Doss, V.; Edgell, R.; Linares, G.; Frei, D.; Chaturvedi, S.; Gandhi, D.; Chaudhry, S.; Choe, H.; Grigoryan, M.; Gupta, R.; Helenius, J.; Voetsch, B.; Khwaja, A.; Khoury, N.; Kim, B. S.; Kleindorfer, D.; McDermott, M.; Koyfman, F.; Leung, L.; Linfante, I.; Male, S.; Masoud, H.; Min, J.; Mittal, M.; Multani, S.; Nahab, F.; Nalleballe, K.; Rahangdale, R.; Rafael, J.; Rothstein, A.; Ruland, S.; Sharma, M.; Singh, A.; Starosciak, A.; Strasser, S.; Szeder, V.; Teleb, M.; Tsai, J.; Mohammaden, M.; Pineda-Franks, C.; Asyraf, W.; Nguyen, T. Q.; Tarkanyi, A.; Haussen, D.; Balaguera, O.; Rodriguezvasquez, A.; Nogueira, R..
Neurology ; 96(15 SUPPL 1), 2021.
Article in English | EMBASE | ID: covidwho-1407898

ABSTRACT

Objective: The objectives of this study were to measure the global impact of the pandemic on the volumes for intravenous thrombolysis (IVT), IVT transfers, and stroke hospitalizations over 4 months at the height of the pandemic (March 1 to June 30, 2020) compared with two control 4-month periods. Background: The COVID-19 pandemic led to widespread repercussions on the delivery of health care worldwide. Design/Methods: We conducted a cross-sectional, observational, retrospective study across 6 continents, 70 countries, and 457 stroke centers. Diagnoses were identified by ICD-10 codes and/or classifications in stroke center databases. Results: There were 91,373 stroke admissions in the 4 months immediately before compared to 80,894 admissions during the pandemic months, representing an 11.5% (95%CI,-11.7 to-11.3, p<0.0001) decline. There were 13,334 IVT therapies in the 4 months preceding compared to 11,570 procedures during the pandemic, representing a 13.2% (95%CI,-13.8 to-12.7, p<0.0001) drop. Interfacility IVT transfers decreased from 1,337 to 1,178, or an 11.9% decrease (95%CI,-13.7 to-10.3, p=0.001). There were greater declines in primary compared to comprehensive stroke centers (CSC) for stroke hospitalizations (-17.3% vs-10.3%, p<0.0001) and IVT (-15.5% vs-12.6%, p=0.0001). Recovery of stroke hospitalization volume (9.5%, 95%CI 9.2-9.8, p<0.0001) was noted over the two later (May, June) versus the two earlier (March, April) months of the pandemic, with greater recovery in hospitals with lower COVID-19 hospitalization volume, high volume stroke center, and CSC. There was a 1.48% stroke rate across 119,967 COVID-19 hospitalizations. SARS-CoV-2 infection was noted in 3.3% (1,722/52,026) of all stroke admissions. Conclusions: The COVID-19 pandemic was associated with a global decline in the volume of stroke hospitalizations, IVT, and interfacility IVT transfers. Primary stroke centers and centers with higher COVID19 inpatient volumes experienced steeper declines. Recovery of stroke hospitalization was noted in the later pandemic months, with greater recovery in hospitals with lower COVID-19 hospitalizations, high volume stroke centers, and CSCs.

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European Psychiatry ; 64(S1):S258, 2021.
Article in English | ProQuest Central | ID: covidwho-1357148

ABSTRACT

IntroductionSurvivors of critical illness stay frequently experience long-term mental health morbidity, suggesting that many critically ill patients with COVID-19 may also show a high prevalence of psychiatric conditions.ObjectivesTo describe depression in COVID-19 survivors 4-months post-hospital discharge and to examine its association with health-related quality of life (HRQoL).MethodsThis pilot study involved COVID-19 adult patients admitted in Intensive Care Medicine Service (ICMS) of a University Hospital. Exclusion criteria were: ICMS length of stay (LoS)≤24h, terminal illness, major sensory loss and inability to communicate at the time of assessment. All participants were evaluated at ICMS scheduled telephone follow-up appointment, with Patient Health Questionnaire (PHQ-9) (depression) and EQ-5D-5L (HRQoL). Critical-illness severity was assessed with APACHE-II and SAPS-II.ResultsTwenty patients were included with a median age of 62(range: 24-77) y.o., the majority male (75%) and married (70%). Median (range) APACHE-II and SAPS-II was 17 (5-34) and 32.5 (7-77), respectively, and LoS was 18 (4-58) days. Overall, 25% patients presented depression symptoms and most reported problems on EQ-5D-5L domains of pain/discomfort (65%), anxiety/depression (55%) and mobility (50%). Depression scores were higher in patients with problems in EQ-5D-5L domains of usual activities (median 4 vs 1.5;p=0.046), pain/discomfort (median 0 vs 4;p=0.004) and anxiety/depression (median 4 vs 0;p<0.001).ConclusionsThese preliminary findings show that depression is frequent in COVID-19 survivors and it is associated with worse HRQoL. This pilot study highlights the importance of psychological assessment and treatment of COVID-19 survivors, in order to minimize its negative impact on HRQoL, optimizing their recovery.

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