nach oben

Erschienen in:

2023 | OriginalPaper | Buchkapitel

A Bicentric Study to Investigate the Impact of COVID-19 on Urological Patients

verfasst von : Emma Montella, Marta Rosaria Marino, Salvatore Bellopede, Sabrina Iodice, Massimo Majolo, Giuseppe Longo, Michele Sparano, Anna Borrelli, Maria Triassi

Erschienen in: Biomedical and Computational Biology

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

In December 2019, SARS-CoV-2 broke out, which raised great attention worldwide. In fact, it was essential to reorganize the management of economic, infrastructural and medical resources to deal with the inadequate preparation of medical practitioners for this emergency. It was evident that the global health, medical and scientific communities were not adequately prepared for this emergency, so during the pandemic. In this paper, data extracted from hospital discharge records of the Department of Urology of the A.O.R.N “Cardarelli” in Naples, Italy, were used. This work is an extension of a previous work, whose goal concerned how admission procedure in the Urology department of the “San Giovanni di Dio and Ruggi d’Aragona” hospital has been affected by COVID-19 pandemic. In this work we compare the results obtained for the patients of the University Hospital “San Giovanni di Dio and Ruggi d’Aragona” of Salerno and the patients of the A.O.R.N. “Antonio Cardarelli” of Naples (Italy). Data have been extracted from both hospitals discharge records of the Departments of Urology. Experimental analysis performed comparing pre-pandemic data with those collected during the epidemic showed an in-crease in the number of emergency hospitalizations and a decrease in planned pre-admission hospitalizations.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel EDWIN and NEDOCS Indices to Study Patient Flow in Emergency Department

Nächstes Kapitel Comparison Between Two Hospitals to Study the Impact of COVID-19 on Emergency Medicine Activities

WHO. Novel coronavirus – Thailand (ex-China). Geneva: World Health Organization (2020). https://www.who.int/csr/don/14-january2020-novel-coronavirus-thailand/en/. Accessed 23 Jan 23 2020

WHO. Novel Coronavirus – Japan (ex-China). Geneva: World Health Organization (2020). https://www.who.int/csr/don/16-january2020-novel-coronavirus-japan-ex-china/en/. Accessed 23 Jan 2020

China National Health Commission. Update on the novel coronavirus pneumonia outbreak. Beijing: China National Health Commission (2020). http://www.nhc.gov.cn/xcs/yqfkdt/202001/c5da49c4c5bf4bcfb320ec2036480627.shtml. Accessed 24 Jan 2020

WHO. Novel coronavirus – Republic of Korea (ex-China). Geneva: World Health Organization (2020). https://www.who.int/csr/don/21-january-2020-novel-coronavirus-republic-of-korea-ex-china/en/. Accessed 24 Jan 2020

US Centers for Disease Control and Prevention. First travel-related case of 2019 novel coronavirus detected in United States. Atlanta, GA: US Centers for Disease Control and Prevention (2020). https://www.cdc.gov/media/releases/2020/p0121-novel-coronavirus-travel-case.html. Accessed 24 Jan 2020

SAIF, L.J.: Coronaviruses : what can they teach us about the severe acute respiratory syndrome? Rev. Sci. Tech. l’OIE, 23(2), 643–660 (2004). https://doi.org/10.20506/rst.23.2.1513

Zumla, A., Chan, J.F.W., Azhar, E.I., Hui, D.S.C., Yuen, K.-Y.: Coronaviruses — drug discovery and therapeutic options. Nat. Rev. Drug Discov. 15(5), 327–347 (2016). https://doi.org/10.1038/nrd.2015.37CrossRefPubMedPubMedCentral

Konca, C., et al.: The first infant death associated with human coronavirus NL63 infection. Pediatr. Infect. Dis. J. 36(2), 231–233 (2017). https://doi.org/10.1097/INF.0000000000001390CrossRefPubMed

Mayer, K., et al.: Fatal outcome of human coronavirus NL63 infection despite successful viral elimination by IFN-alpha in a patient with newly diagnosed ALL. Eur. J. Haematol. 97(2), 208–210 (2016). https://doi.org/10.1111/ejh.12744CrossRefPubMedPubMedCentral

10.

Oosterhof, L., Christensen, C.B., Sengeløv, H.: Fatal lower respiratory tract disease with human corona virus NL63 in an adult haematopoietic cell transplant recipient. Bone Marrow Transplant. 45(6), 1115–1116 (2010). https://doi.org/10.1038/bmt.2009.292CrossRefPubMed

11.

van der Hoek, L.: Human coronaviruses: what do they cause? Antiviral Ther. 12(4_part_2), 651–658 (2007). https://doi.org/10.1177/135965350701200S01.1

12.

Du, L., Qiu, J.C., Wang, M.: Analysis on the characteristics of blood serum Ab-IgG detective result of severe acute respiratory syndrome patients in Guangzhou, China. Zhonghua Liu Xing Bing Xue Za Zhi 25(11), 925–928 (2004)PubMed

13.

Peiris, J.S.M., Yuen, K.Y., Osterhaus, A.D.M.E., Stöhr, K.: The severe acute respiratory syndrome. N. Engl. J. Med. 349(25), 2431–2441 (2003). https://doi.org/10.1056/NEJMra032498CrossRefPubMed

14.

Booth, T.F., et al.: Detection of airborne severe acute respiratory syndrome (SARS) coronavirus and environmental contamination in SARS outbreak units. J. Infect. Dis. 191(9), 1472–1477 (2005). https://doi.org/10.1086/429634CrossRefPubMed

15.

Peiris, J., et al.: Coronavirus as a possible cause of severe acute respiratory syndrome. Lancet 361(9366), 1319–1325 (2003). https://doi.org/10.1016/S0140-6736(03)13077-2CrossRefPubMedPubMedCentral

16.

Atalan, A.: Is the lockdown important to prevent the COVID-19 pandemic? Effects on psychology, environment and economy-perspective. Ann. Med. Surg. 56, 38–42 (2020). https://doi.org/10.1016/j.amsu.2020.06.010CrossRef

17.

World Health Organization. Coronavirus Disease 2019 (COVID-19) Situation Report—44 (2020). https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200304-sitrep-44-covid-19.pdf?sfvrsn=93937f92_6

18.

Cauchemez, S., et al.: Closure of schools during an influenza pandemic. Lancet. Infect. Dis. 9(8), 473–481 (2009). https://doi.org/10.1016/S1473-3099(09)70176-8CrossRefPubMedPubMedCentral

19.

UK Government, Department of Health and Social Care. Coronavirus action plan (2020)

20.

Horton, R.: Offline: COVID-19 and the NHS—a national scandal. Lancet 395(10229), 1022 (2020). https://doi.org/10.1016/S0140-6736(20)30727-3CrossRefPubMedPubMedCentral

21.

Grass, F., et al.: Impact of delay to surgery on survival in stage I-III colon cancer. Eur. J. Surg. Oncol. 46(3), 455–461 (2020). https://doi.org/10.1016/j.ejso.2019.11.513CrossRefPubMed

22.

Tabiri, S.: Elective surgery cancellations due to the COVID-19 pandemic: global predictive modelling to inform surgical recovery plans. (2020). Br. J. Surg. https://doi.org/10.1002/bjs.11746

23.

Revetria, R., et al.: Improving healthcare using cognitive computing based software: an application in emergency situation. In: International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems. Springer, Berlin (2012). https://doi.org/10.1007/978-3-642-31087-4_50

24.

Cesarelli, G., Montella, E., Scala, A., Raiola, E., Triassi, M., Improta, G.: DMAIC approach for the reduction of healthcare-associated infections in the neonatal intensive care unit of the university hospital of naples “federico ii”. In: European Medical and Biological Engineering Conference, pp. 414–423. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-64610-3_48

25.

Improta, G., et al.: Evaluation of medical training courses satisfaction: qualitative analysis and analytic hierarchy process. In: Jarm, T., Cvetkoska, A., Mahnič-Kalamiza, S., Miklavcic, D. (eds.) EMBEC 2020. IP, vol. 80, pp. 518–526. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-64610-3_59CrossRef

26.

Ponsiglione, A.M., Cosentino, C., Cesarelli, G., Amato, F., Romano, M.: A comprehensive review of techniques for processing and analyzing fetal heart rate signals. Sensors 21, 6136 (2021). https://doi.org/10.3390/s21186136CrossRefPubMedPubMedCentral

27.

Ponsiglione, A.M., Amato, F., Romano, M.: Multiparametric investigation of dynamics in fetal heart rate signals. Bioengineering 9, 8 (2022). https://doi.org/10.3390/bioengineering9010008CrossRef

28.

Trunfio, T.A., et al.: Multiple regression model to analyze the total LOS for patients undergoing laparoscopic appendectomy. BMC Med. Inf. Decis. Making 22(1), 1–8 (2022)

29.

Scala, A., et al.: Regression models to study the total LOS related to valvuloplasty. Int. J. Environ. Res. Publ. Health 19(5), 3117 (2022)CrossRef

30.

Santini, S., et al.: Using fuzzy logic for improving clinical daily-care of β-thalassemia patients. In: Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference, pp. 1–6. IEEE (2017)

31.

Improta, G., Mazzella, V., Vecchione, D., Santini, S., Triassi, M.: Fuzzy logic–based clinical decision support system for the evaluation of renal function in post-transplant patients. J. Eval. Clin. Pract. 26(4), 1224–1234 (2020)CrossRefPubMed

32.

Improta, G., et al.: Analytic hierarchy process (AHP) in dynamic configuration as a tool for health technology assessment (HTA): the case of biosensing optoelectronics in oncology. Int. J. Inf. Technol. Decis. Making 18(05), 1533–1550 (2019)CrossRef

33.

Sperlí, G.: A cultural heritage framework using a deep learning based chatbot for supporting tourist journey. Expert Syst. Appl. 183, 115277 (2021). https://doi.org/10.1016/j.eswa.2021.115277CrossRef

34.

Sperlí, G.: A deep learning based chatbot for cultural heritage. In: Proceedings of the 35th Annual ACM Symposium on Applied Computing, pp. 935–937 (2020). https://doi.org/10.1145/3341105.3374129

35.

Han, Q., Molinaro, C., Picariello, A., Sperli, G., Subrahmanian, V.S., Xiong, Y.: Generating fake documents using probabilistic logic graphs. IEEE Trans. Dependable Secure Comput. (2021). https://doi.org/10.1109/TDSC.2021.3058994

36.

La Gatta, V., Moscato, V., Pennone, M., Postiglione, M., Sperlí, G.: Music recommendation via hypergraph embedding. IEEE Trans. Neural Netw. Learn. Syst. (2022). https://doi.org/10.1109/TNNLS.2022.3146968CrossRefPubMed

37.

Esposito, C., Moscato, V., Sperlí, G.: Trustworthiness Assessment of Users in Social Reviewing Systems. IEEE Trans. Syst. Man Cybern.: Syst. 52(1), 151–165 (2022). https://doi.org/10.1109/TSMC.2020.3049082CrossRef

38.

Ianni, M., Masciari, E., Sperlí, G.: A survey of big data dimensions vs social networks analysis. J. Intell. Inf. Syst. 57(1), 73–100 (2020). https://doi.org/10.1007/s10844-020-00629-2CrossRefPubMedPubMedCentral

39.

Improta, G., et al.: Management of the diabetic patient in the diagnostic care pathway. In: Jarm, T., Cvetkoska, A., Mahnič-Kalamiza, S., Miklavcic, D. (eds.) EMBEC 2020. IP, vol. 80, pp. 784–792. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-64610-3_88CrossRef

40.

Improta, G., Scala, A., Trunfio, T.A., Guizzi, G.: Application of Supply Chain Management at Drugs Flow in an Italian Hospital District. In: Journal of Physics Conference Series, vol. 1828, no. 1 (2021). https://doi.org/10.1088/1742-6596/1828/1/012081

41.

Loperto, I., Borrelli, A., Sparano, M., Triassi, M.: Hospital activities and CoViD-19: the case study of a Urology Department. Int. Symp. Biomed. Eng. Comput. Biol. 2021, 1–4 (2021). https://doi.org/10.1145/3502060.3503663CrossRef

42.

Hall, G.H., Round, A.P.: Logistic regression–explanation and use. J. Roy. Coll. Phys. London 28(3), 242–246 (1994)

Titel: A Bicentric Study to Investigate the Impact of COVID-19 on Urological Patients
verfasst von: Emma Montella
Marta Rosaria Marino
Salvatore Bellopede
Sabrina Iodice
Massimo Majolo
Giuseppe Longo
Michele Sparano
Anna Borrelli
Maria Triassi
Verlag: Springer International Publishing
Buch: Biomedical and Computational Biology
Print ISBN: 978-3-031-25190-0

Electronic ISBN: 978-3-031-25191-7

Copyright-Jahr: 2023
DOI: https://doi.org/10.1007/978-3-031-25191-7_30

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner