Journals / Adnan Menderes Üniversitesi Sağlık Bilimleri Fakültesi Dergisi / 2023 / Cilt: 7 - Sayı: 1

Laboratory Tests to Distinguish COVID-19 Intensive Care Patients

Covid-19 Yoğun Bakım Hastalarını Ayırt Etmek İçin Kullanılabilecek Laboratuvar Testleri

Pages
208–216
Publication Date
2023-01-31
DOI
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AI Summary & Key Takeaways

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⚡ TL;DR(Too Long; Didn't Read)

Lymphopenia, increase in neutrophil level, N/L ratio, D-dimer, CRP and procalcitonin levels are remarkable in intensive care patients.

📌 3 Key Takeaways

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Objective & Hypothesis:Objective: The need for intensive care units has increased in the COVID-19 pandemic, and in this process, laboratory parameters are important.
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Key Findings & Data:We aimed to evaluate the admission symptoms retrospectively, comorbid diseases, mean age, and laboratory data of RT-PCR(+) 60 service and 26 intensive care COVID-19 patients, to reveal the clinical and laboratory characteristics of the patients and to define the parameters that will help us about the prognosis..Methods: We divided 86 COVID-19 RT-PCR (+) patients treated in our hospital into two groups as inpatients and intensive care patients.
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Conclusion & Impact:Lymphopenia, increase in neutrophil level, N/L ratio, D-dimer, CRP and procalcitonin levels are remarkable in intensive care patients.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:COVID-19 · Lenfopeni · D-dimer

Abstract

Objective: The need for intensive care units has increased in the COVID-19 pandemic, and in this process, laboratory parameters are important. We aimed to evaluate the admission symptoms retrospectively, comorbid diseases, mean age, and laboratory data of RT-PCR(+) 60 service and 26 intensive care COVID-19 patients, to reveal the clinical and laboratory characteristics of the patients and to define the parameters that will help us about the prognosis..Methods: We divided 86 COVID-19 RT-PCR (+) patients treated in our hospital into two groups as inpatients and intensive care patients. We compared symptom, comorbid disease and laboratory data in these patient groups and compared laboratory data statistically.Results: In our study, while the mean age of intensive care patients was 64, it was 58 in service patients. Comorbid diseases were found in 73% of intensive care patients and 51.6% in service patients. Hypertension (43%) and diabetes mellitus (22%) are the most common comorbid diseases in both groups. In addition, while neutrophil [(6.11(1.18-19.7) vs. 3.83(1.51-12.07) 109 /L, p=0.007], N/L ratio [5.74 (1.34-28.86) vs. 2.11 (0.64-9.14), p<0.001], D-dimer [ 482 (52-2522) vs. 249 (59-3561) µg/L, p=0.001], CRP [91.8 (0.49-331.7) vs. 14 (0-161) mg/L, p< 0.001], and procalcitonin [0.19 (0-6.94) vs. 0.04 (0-0.86) µg/L, p< 0.001] values were found to be significantly higher in intensive care patients, lymphocyte values [(1.12±0.54 ) vs. ( 1.81±0.90) 109 /L, p<0.001] were found to be significantly lower.Conclusion: COVID-19 is still affecting our world, and patients need intensive care. Lymphopenia, increase in neutrophil level, N/L ratio, D-dimer, CRP and procalcitonin levels are remarkable in intensive care patients.

Özet

Amaç: COVID-19 pandemisinde yoğun bakım ihtiyacı artmıştır ve bu süreçte laboratuvar parametreleri önem kazanmıştır. RT-PCR(+) 60 servis ve 26 yoğun bakım COVID-19 hastasının başvuru semptomlarını, eşlik eden hastalıklarını, yaş ortalamasını ve laboratuvar verilerini retrospektif olarak değerlendirip, hastaların klinik ve laboratuvar özelliklerini ortaya koymayı prognoz hakkında bize yardımcı olacak parametreleri belirlemeyi amaçladık.Yöntem: RT-PCR (+) COVID-19 hastalarının verileri hastane ve laboratuvar bilgi sistemlerinden geriye dönük olarak toplandı. Hastanemizde tedavi gören toplam 86 COVID-19 hastası, yatan hastalar ve yoğun bakım hastaları olarak gruplandırıldı. Hastaneye başvuru semptomları, komorbid hastalıkları ve laboratuvar verileri istatistiksel olarak değerlendirildi. Bulgular: Çalışma popülasyonunun ortalama yaşları yoğun bakım ve servis hastalarında sırasıyla 64 ve 58 idi. Yoğun bakım hastalarının %73'ünde, servis hastalarının %51,6'sında komorbid hastalık saptandı. Her iki grupta da hipertansiyon (43%) ve diabetes mellitus (22%) en sık eşlik eden hastalıklardı. Yoğun bakım hastalarında nötrofil [(6.11(1.18-19.7) ile 3.83(1.51-12.07) 109 /L, p=0.007], nötrofil/lenfosit oranı [5.74 (1.34-28.86) ile 2.11 (0.64-9.14), p<0.001], D-dimer [ 482 (52-2522) ile 249 (59-3561) µg/L, p=0.001], CRP [91.8 (0.49-331.7) ile 14 (0-161) mg/L, p< 0.001] ve prokalsitonin [0.19 (0-6.94) ile 0.04 (0-0.86) µg/L, p< 0.001] değerleri anlamlı olarak daha yüksek, lenfosit [(1.12±0.54 ) ile ( 1.81±0.90) 109 /L, p<0.001] değerleri daha düşük olarak bulundu.Sonuç: COVID-19 virüsü insanları etkilemeye devam etmekte ve bazı hastalarda yoğun bakım ihtiyacı görülmektedir. Yoğun bakım hastalarında lenfopeni ve nötrofil, N/L oranı, D-dimer, CRP, prokalsitonin düzeylerindeki artış dikkat çekicidir.

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Cite This Article

DEMİR, L., ÇUHADAR, S., VAN, T. Ö., AKSUN, S. (2023). Laboratory Tests to Distinguish COVID-19 Intensive Care Patients. Adnan Menderes Üniversitesi Sağlık Bilimleri Fakültesi Dergisi, Cilt: 7 - Sayı: 1, 208–216. https://ajindex.com/articles/880450

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References (10)

  1. Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., et al. (2020). Early transmission dynamics in Wuhan, China, of novel coronavirus-ınfected pneumonia. The New England journal of medicine, 382(13), 1199–1207
  2. Hussain, Y. H,, Baderkhan, B., Hamid, M., Hamid, A. (2020). Mortalities and morbidities trends of COVID-19 infection, from explosiveness to aggressiveness, understanding gaps in system response and transmission chain events. Journal of Health Care and Research. 1. 22-27
  3. Prompetchara, E., Ketloy, C., & Palaga, T. (2020). Immune responses in COVID-19 and potential vaccines: Lessons learned from SARS and MERS epidemic. Asian Pacific journal of allergy and immunology, 38(1), 1–9
  4. Ochani, R., Asad, A., Yasmin, F., Shaikh, S., Khalid, H., Batra, S., et al. (2021). COVID-19 pandemic: from origins to outcomes. A comprehensive review of viral pathogenesis, clinical manifestations, diagnostic evaluation, and management. Le infezioni in medicina, 29(1), 20–36
  5. Wan, S., Yi, Q., Fan, S., Lv, J., Zhang, X., Guo, L.X., et al. (2020). Characteristics of lymphocyte subsets and cytokines in peripheral blood of 123 hospitalized patients with 2019 novel coronavirus pneumonia (NCP). medRxiv
  6. Karaca, B. (2020). Clinical findings of the COVID-19 in the adult group. J Biotechnol and Strategic Health Res. 4, 85-90 7. Zhang, Z. L., Hou, Y. L., Li, D. T., Li, F. Z. (2020). Laboratory findings of COVID-19: a systematic review and meta-analysis. Scandinavian journal of clinical and laboratory investigation, 80(6), 441–447
  7. Cheng, Z., Lu, Y., Cao, Q., Qin, L., Pan, Z., Yan, F., et al. (2020). Clinical features and chest CT manifestations of coronavirus disease 2019 (COVID-19) in a single-center study in Shanghai, China. AJR. American journal of roentgenology, 215(1), 121–126
  8. Xiong, Y., Sun, D., Liu, Y., Fan, Y., Zhao, L., Li, X., et al. (2020). Clinical and high-resolution CT features of the COVID-19 infection: Comparison of the initial and follow-up changes. Investigative radiology, 55(6), 332–339
  9. Huang, Y., Tu, M., Wang, S., Chen, S., Zhou, W., Chen, D., et al. (2020). Clinical characteristics of laboratory confirmed positive cases of SARS-CoV-2 infection in Wuhan, China: A retrospective single center analysis. Travel medicine and infectious disease, 36, 101606
  10. Chan, J. F., Yuan, S., Kok, K. H., To, K. K., Chu, H., Yang, J., et al. (2020). A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-pers