Zitieren

Bohn M, Lippi G, Horvath A, et al. Molecular, serological, and biochemical diagnosis and monitoring of COVID-19: IFCC taskforce evaluation of the latest evidence. Clin Chem and Lab Med (CCLM). 2020;58(7):1037–1052. BohnM LippiG HorvathA Molecular, serological, and biochemical diagnosis and monitoring of COVID-19: IFCC taskforce evaluation of the latest evidence Clin Chem and Lab Med (CCLM) 2020 58 7 1037 1052 Search in Google Scholar

U.S. Food and Drug Administration. Policy for coronavirus disease-2019 tests during the public health emergency (revised). https://www.fda.gov/regulatory-information/search-fda-guidance-documents. Accessed: 6 May 2023. U.S. Food and Drug Administration Policy for coronavirus disease-2019 tests during the public health emergency (revised) https://www.fda.gov/regulatory-information/search-fda-guidance-documents. Accessed: 6 May 2023. Search in Google Scholar

World Health Organization WHO coronavirus 2019 (COVID-19) pandemic. (2021). Accessed: 24/06/2023: https://www.who.int/emergencies/diseases/novel-coronavirus-2019. World Health Organization WHO coronavirus 2019 (COVID-19) pandemic 2021 Accessed: 24/06/2023: https://www.who.int/emergencies/diseases/novel-coronavirus-2019. Search in Google Scholar

Peng Y, Xu B, Sun B, Han G, Zhou YH. Importance of timely management of patients in reducing fatality rate of coronavirus disease 2019. J Infect Public Health. 2020;13:890–2. PengY XuB SunB HanG ZhouYH Importance of timely management of patients in reducing fatality rate of coronavirus disease 2019 J Infect Public Health 2020 13 890 2 Search in Google Scholar

Siow WT, Liew MF, Shrestha BR, Muchtar F, See KC. Managing COVID-19 in resource-limited settings: critical care considerations. Crit Care. 2020;24(1):167–9. SiowWT LiewMF ShresthaBR MuchtarF SeeKC Managing COVID-19 in resource-limited settings: critical care considerations Crit Care 2020 24 1 167 9 Search in Google Scholar

Barbas CSV, Mazza BF. Is It Possible to Predict Respiratory Evolution in COVID-19 Patients? Respiration. 2022;101(7):621–623. BarbasCSV MazzaBF Is It Possible to Predict Respiratory Evolution in COVID-19 Patients? Respiration 2022 101 7 621 623 Search in Google Scholar

Wynants L, Van Calster B, Collins GS, et al. Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal. BMJ. 2020; 369:m1328. WynantsL Van CalsterB CollinsGS Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal BMJ 2020 369 m1328 Search in Google Scholar

Aziz AB, Raqib R, Khan WA, Rahman M, Haque R, Alam M, Zaman K, Ross AG. Integrated control of COVID-19 in resource-poor countries. Int J Infect Dis. 2020;101:98–101. AzizAB RaqibR KhanWA RahmanM HaqueR AlamM ZamanK RossAG Integrated control of COVID-19 in resource-poor countries Int J Infect Dis 2020 101 98 101 Search in Google Scholar

Zhang K, Jiang X, Madadi M, Chen L, Savitz S, Shams S, DB Net. A novel deep learning framework for mechanical ventilation prediction using electronic health records. In Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, Gainesville, FL, USA, 1–4 August 2021. ZhangK JiangX MadadiM ChenL SavitzS ShamsS DB Net A novel deep learning framework for mechanical ventilation prediction using electronic health records In Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics Gainesville, FL, USA 1–4 August 2021 Search in Google Scholar

Pitamberwale A, Mahmood T, Ansari A, et al. Biochemical Parameters as Prognostic Markers in Severely Ill COVID-19 Patients. Cureus. 2022;14(8): e28594. PitamberwaleA MahmoodT AnsariA Biochemical Parameters as Prognostic Markers in Severely Ill COVID-19 Patients Cureus 2022 14 8 e28594 Search in Google Scholar

Bendavid I, Statlender L, Shvartser L, Teppler S, Azullay R, Sapir R, Singer P. A novel machine learning model to predict respiratory failure and invasive mechanical ventilation in critically ill patients suffering from COVID-19. Sci Rep. 2022 Jun 22;12(1):10573. BendavidI StatlenderL ShvartserL TepplerS AzullayR SapirR SingerP A novel machine learning model to predict respiratory failure and invasive mechanical ventilation in critically ill patients suffering from COVID-19 Sci Rep 2022 Jun 22 12 1 10573 Search in Google Scholar

Gupta M, Agrawal N, Sharma SK, Ansari AK, Mahmood T, Singh L: Study of utility of basic arterial blood gas parameters and lactate as prognostic markers in patients with severe dengue. Cureus. 2022;14:e24682. GuptaM AgrawalN SharmaSK AnsariAK MahmoodT SinghL Study of utility of basic arterial blood gas parameters and lactate as prognostic markers in patients with severe dengue Cureus 2022 14 e24682 Search in Google Scholar

Booth A, Reed AB, Ponzo S, Yassaee A, Aral M, Plans D, Labrique A, Mohan D. Population risk factors for severe disease and mortality in COVID-19: A global systematic review and meta-analysis. PLoS One. 2021 Mar 4;16(3):e0247461. BoothA ReedAB PonzoS YassaeeA AralM PlansD LabriqueA MohanD Population risk factors for severe disease and mortality in COVID-19: A global systematic review and meta-analysis PLoS One 2021 Mar 4 16 3 e0247461 Search in Google Scholar

Somers VK, Kara T, Xie J. Progressive Hypoxia: A Pivotal Pathophysiologic Mechanism of COVID-19 Pneumonia. Mayo Clin Proc. 2020 Nov;95(11):2339–2342. SomersVK KaraT XieJ Progressive Hypoxia: A Pivotal Pathophysiologic Mechanism of COVID-19 Pneumonia Mayo Clin Proc 2020 Nov 95 11 2339 2342 Search in Google Scholar

Ferro A, Kotecha S, Auzinger G, Yeung E, Fan K. Systematic review and meta-analysis of tracheostomy outcomes in COVID-19 patients. Br J Oral Maxillofac Surg. 2021 Nov;59(9):1013–1023. FerroA KotechaS AuzingerG YeungE FanK Systematic review and meta-analysis of tracheostomy outcomes in COVID-19 patients Br J Oral Maxillofac Surg 2021 Nov 59 9 1013 1023 Search in Google Scholar

Mat Nor MB, Md Ralib A: Procalcitonin clearance for early prediction of survival in critically ill patients with severe sepsis. Crit Care Res Pract. 2014;2014:819034. Mat NorMB Md RalibA Procalcitonin clearance for early prediction of survival in critically ill patients with severe sepsis Crit Care Res Pract 2014 2014 819034 Search in Google Scholar

Ahmed S, Jafri L, Hoodbhoy Z, Siddiqui I. Prognostic Value of Serum Procalcitonin in COVID-19 Patients: A Systematic Review. Indian J Crit Care Med. 2021 Jan;25(1):77–84 AhmedS JafriL HoodbhoyZ SiddiquiI Prognostic Value of Serum Procalcitonin in COVID-19 Patients: A Systematic Review Indian J Crit Care Med 2021 Jan 25 1 77 84 Search in Google Scholar

Twe CW, Khoo DKY, Law KB, et al. The role of procalcitonin in predicting risk of mechanical ventilation and mortality among moderate to severe COVID-19 patients. BMC Infect Dis. 2022 Apr 15;22(1):378. TweCW KhooDKY LawKB The role of procalcitonin in predicting risk of mechanical ventilation and mortality among moderate to severe COVID-19 patients BMC Infect Dis 2022 Apr 15 22 1 378 Search in Google Scholar

Xiang HX, Fei J, Xiang Y, et al.: Renal dysfunction and prognosis of COVID-19 patients: a hospital-based retrospective cohort study. BMC Infect Dis. 2021, 21:158. XiangHX FeiJ XiangY Renal dysfunction and prognosis of COVID-19 patients: a hospital-based retrospective cohort study BMC Infect Dis 2021 21 158 Search in Google Scholar

Tzoulis P, Waung JA, Bagkeris E, et al.. Dysnatremia is a Predictor for Morbidity and Mortality in Hospitalized Patients with COVID-19. J Clin Endocrinol Metab. 2021 May 13;106(6):1637–1648. TzoulisP WaungJA BagkerisE Dysnatremia is a Predictor for Morbidity and Mortality in Hospitalized Patients with COVID-19 J Clin Endocrinol Metab 2021 May 13 106 6 1637 1648 Search in Google Scholar

Tzoulis P, Grossman AB, Baldeweg SE, Bouloux P, Kaltsas G. MANAGEMENT OF ENDOCRINE DISEASE: Dysnatraemia in COVID-19: prevalence, prognostic impact, pathophysiology, and management. Eur J Endocrinol. 2021 Sep 6;185(4):R103–R111. TzoulisP GrossmanAB BaldewegSE BoulouxP KaltsasG MANAGEMENT OF ENDOCRINE DISEASE: Dysnatraemia in COVID-19: prevalence, prognostic impact, pathophysiology, and management Eur J Endocrinol 2021 Sep 6 185 4 R103 R111 Search in Google Scholar

Li W, Lin F, Dai M, Chen L, Han D, Cui Y, Pan P. Early predictors for mechanical ventilation in COVID-19 patients. Ther Adv Respir Dis. 2020 Jan–Dec;14:1753466620963017. LiW LinF DaiM ChenL HanD CuiY PanP Early predictors for mechanical ventilation in COVID-19 patients Ther Adv Respir Dis 2020 Jan–Dec 14 1753466620963017 Search in Google Scholar

Vidali S, Morosetti D, Cossu E, Luisi MLE, Pancani S, Semeraro V, Consales G. D-dimer as an indicator of prognosis in SARSCoV-2 infection: a systematic review. ERJ Open Res. 2020 Jul 13;6(2):00260–2020. VidaliS MorosettiD CossuE LuisiMLE PancaniS SemeraroV ConsalesG D-dimer as an indicator of prognosis in SARSCoV-2 infection: a systematic review ERJ Open Res 2020 Jul 13 6 2 00260 2020 Search in Google Scholar

Yao Y, Cao J, Wang Q, et al. D-dimer as a biomarker for disease severity and mortality in COVID-19 patients: a case control study. J Intensive Care. 2020 Jul 10;8:49. YaoY CaoJ WangQ D-dimer as a biomarker for disease severity and mortality in COVID-19 patients: a case control study J Intensive Care 2020 Jul 10 8 49 Search in Google Scholar

Varikasuvu SR, Varshney S, Dutt N, Munikumar M, Asfahan S, Kulkarni PP, Gupta P. D-dimer, disease severity, and deaths (3D-study) in patients with COVID-19: a systematic review and meta-analysis of 100 studies. Sci Rep. 2021;11(1):21888. VarikasuvuSR VarshneyS DuttN MunikumarM AsfahanS KulkarniPP GuptaP D-dimer, disease severity, and deaths (3D-study) in patients with COVID-19: a systematic review and meta-analysis of 100 studies Sci Rep 2021 11 1 21888 Search in Google Scholar

Kulkarni, AR, Athavale A.M, Sahni A, et al. Deep learning model to predict the need for mechanical ventilation using chest X ray images in hospitalised patients with COVID-19. BMJ Innov. 2021;7:261–270. KulkarniAR AthavaleA.M SahniA Deep learning model to predict the need for mechanical ventilation using chest X ray images in hospitalised patients with COVID-19 BMJ Innov 2021 7 261 270 Search in Google Scholar

Aljouie AF, Almazroa A, Bokhari Y, et al. Early Prediction of COVID-19 Ventilation Requirement and Mortality from Routinely Collected Baseline Chest Radiographs, Laboratory, and Clinical Data with Machine Learning. J. Multidiscip. Healthc. 2021;14:2017–2033. AljouieAF AlmazroaA BokhariY Early Prediction of COVID-19 Ventilation Requirement and Mortality from Routinely Collected Baseline Chest Radiographs, Laboratory, and Clinical Data with Machine Learning J. Multidiscip. Healthc. 2021 14 2017 2033 Search in Google Scholar

Mat Nor MB, Md Ralib A. Procalcitonin clearance for early prediction of survival in critically ill patients with severe sepsis. Crit Care Res Pract. 2014;2014:819034. Mat NorMB Md RalibA Procalcitonin clearance for early prediction of survival in critically ill patients with severe sepsis Crit Care Res Pract 2014 2014 819034 Search in Google Scholar

Burke H, Freeman A, O’Regan P, et al. Biomarker identification using dynamic time warping analysis: a longitudinal cohort study of patients with COVID-19 in a UK tertiary hospital. BMJ 2022 15;12(2):e050331. BurkeH FreemanA O’ReganP Biomarker identification using dynamic time warping analysis: a longitudinal cohort study of patients with COVID-19 in a UK tertiary hospital BMJ 2022 15 12 2 e050331 Search in Google Scholar

eISSN:
2393-1817
Sprache:
Englisch
Zeitrahmen der Veröffentlichung:
4 Hefte pro Jahr
Fachgebiete der Zeitschrift:
Medizin, Klinische Medizin, Allgemeinmedizin, Innere Medizin, andere, Chirurgie, Anästhesiologie, Intensivmedizin und Notfallmedizin