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Surfactant protein D: A useful biomarker for distinguishing COVID-19 pneumonia from COVID-19 pneumonia-like diseases.
Togashi, Yuki; Kono, Yuta; Okuma, Takashi; Shioiri, Nao; Mizushima, Reimi; Tanaka, Akane; Ishiwari, Mayuko; Toriyama, Kazutoshi; Kikuchi, Ryota; Takoi, Hiroyuki; Abe, Shinji.
  • Togashi Y; Department of Respiratory Medicine Tokyo Medical University Hospital Shinjuku-ku Tokyo Japan.
  • Kono Y; Department of Respiratory Medicine Tokyo Medical University Hospital Shinjuku-ku Tokyo Japan.
  • Okuma T; Department of Respiratory Medicine Tokyo Medical University Hospital Shinjuku-ku Tokyo Japan.
  • Shioiri N; Department of Respiratory Medicine Tokyo Medical University Hospital Shinjuku-ku Tokyo Japan.
  • Mizushima R; Department of Respiratory Medicine Tokyo Medical University Hospital Shinjuku-ku Tokyo Japan.
  • Tanaka A; Department of Respiratory Medicine Tokyo Medical University Hospital Shinjuku-ku Tokyo Japan.
  • Ishiwari M; Department of Respiratory Medicine Tokyo Medical University Hospital Shinjuku-ku Tokyo Japan.
  • Toriyama K; Department of Respiratory Medicine Tokyo Medical University Hospital Shinjuku-ku Tokyo Japan.
  • Kikuchi R; Department of Respiratory Medicine Tokyo Medical University Hospital Shinjuku-ku Tokyo Japan.
  • Takoi H; Department of Respiratory Medicine Tokyo Medical University Hospital Shinjuku-ku Tokyo Japan.
  • Abe S; Department of Respiratory Medicine Tokyo Medical University Hospital Shinjuku-ku Tokyo Japan.
Health Sci Rep ; 5(3): e622, 2022 May.
Article in English | MEDLINE | ID: covidwho-1802281
ABSTRACT

Introduction:

Computed tomography is useful for the diagnosis of coronavirus disease (COVID-19) pneumonia. However, many types of interstitial lung diseases and even bacterial pneumonia can show abnormal chest shadows that are indistinguishable from those observed in COVID-19 pneumonia. Thus, it is necessary to identify useful biomarkers that can efficiently distinguish COVID-19 pneumonia from COVID-19 pneumonia-like diseases. Herein, we investigated the usefulness of serum Krebs von den Lungen 6 (KL-6) and surfactant protein D (SP-D) for identifying patients with COVID-19 pneumonia among patients with abnormal chest shadows consistent with COVID-19 pneumonia.

Method:

This was a retrospective cohort study of consecutive patients who underwent evaluation of serum KL-6 and SP-D at a single center from February 2019 to December 2020. A total of 54 patients with COVID-19 pneumonia and 65 patients with COVID-19 pneumonia-like diseases were enrolled in this study from the source population. Serum KL-6 and SP-D levels in both groups were analyzed.

Result:

The serum levels of KL-6 and SP-D in patients with COVID-19 pneumonia were significantly lower than those in patients with COVID-19 pneumonia-like disease (median [interquartile range] 208.5 [157.5-368.5] U/ml vs. 430 [284.5-768.5] U/ml, p < 0.0001 and 24.7 [8.6-51.0] ng/ml vs. 141 [63.7-243.5] ng/ml, p < 0.0001, respectively). According to receiver operating characteristic (ROC) analysis, the areas under the ROC curves (95% confidence intervals) of serum KL-6 and SP-D levels for distinguishing COVID-19 pneumonia from COVID-19 pneumonia-like diseases were 0.761 (0.675-0.847) and 0.874 (0.812-0.936), respectively. The area under the ROC curve of serum SP-D was significantly larger than that of serum KL-6 (p = 0.0213), suggesting that serum SP-D can more efficiently distinguish COVID-19 pneumonia from COVID-19 pneumonia-like diseases.

Conclusion:

Serum SP-D is a promising biomarker for distinguishing COVID-19 pneumonia from COVID-19 pneumonia-like diseases. Serum SP-D can be useful for the management of patients with abnormal chest shadow mimicking COVID-19 pneumonia.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Language: English Journal: Health Sci Rep Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Language: English Journal: Health Sci Rep Year: 2022 Document Type: Article