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Early hypoxia prediction in diseased patients via wheezing sounds in respiration: a prospective cohort study.

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Frontiers in medicine 📖 저널 OA 100% 2021: 5/5 OA 2022: 14/14 OA 2023: 10/10 OA 2024: 14/14 OA 2025: 175/175 OA 2026: 119/119 OA 2021~2026 2025 Vol.12() p. 1649991
Retraction 확인
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PICO 자동 추출 (휴리스틱, conf 2/4)

유사 논문
P · Population 대상 환자/모집단
216 patients were recruited, and 171 (7.
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
This finding may facilitate early risk stratification and optimize oxygen resource allocation at the initial encounter, before laboratory or imaging examinations are available. Through voice-print analysis and artificial intelligence, future studies are warranted to further explore the predictive potential of breath sounds.

Huang CH, Fan CY, Chen CH, Sung CW, Chen CY, Lin SY, Tzeng JT, Lee CC, Sheed A, Chou EH, Huang EP

📝 환자 설명용 한 줄

[BACKGROUND] Early detection of hypoxia in the emergency room may reduce complications.

🔬 핵심 임상 통계 (초록에서 자동 추출 — 원문 검증 권장)
  • 95% CI 1.99-6.36
  • OR 3.56

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↓ .bib ↓ .ris
APA Huang CH, Fan CY, et al. (2025). Early hypoxia prediction in diseased patients via wheezing sounds in respiration: a prospective cohort study.. Frontiers in medicine, 12, 1649991. https://doi.org/10.3389/fmed.2025.1649991
MLA Huang CH, et al.. "Early hypoxia prediction in diseased patients via wheezing sounds in respiration: a prospective cohort study.." Frontiers in medicine, vol. 12, 2025, pp. 1649991.
PMID 41694682 ↗

Abstract

[BACKGROUND] Early detection of hypoxia in the emergency room may reduce complications. Breath sounds can be evaluated immediately. Our research endeavors to investigate the relationship between breath sounds and oxygen demand.

[METHODS] We recruited patients from the emergency department. Respiratory sounds in four locations were recorded with an electronic stethoscope and classified into normal, wheezing, or crackles. The primary outcome was increased oxygen demand (IOD) in the emergency room, and the secondary outcome was intensive care unit (ICU) admission. The prediction model was evaluated by logistic regression model.

[RESULTS] Overall, 2,216 patients were recruited, and 171 (7.7%) had IOD. Through multivariable logistic regression, independent predictive factors for IOD were age (odds ratio [OR]: 1.02, 95% confidence interval [CI]: 1.01-1.03), lung cancer (OR: 3.56, 95% CI: 1.99-6.36), triage respiratory rate (OR: 1.02, 95% CI: 1.00-1.04), triage oxygen saturation (OR: 0.95, 95% CI: 0.92-0.98), and wheezing (OR: 2.87, 95% CI: 1.31-6.29). The area under receiver operating characteristic curve (AUROC) for IOD was 0.791 (95% CI 0.756-0.8273. Age (OR: 1.02, 95% CI: 1.00-1.03), coronary artery disease (OR: 3.00, 95% CI: 1.82-4.95), chronic obstructive pulmonary disease (aOR = 2.53, 95% CI = 1.32-4.84) and triage oxygen saturation (aOR = 0.96, 95% CI = 0.93-0.99) were significantly associated with increased ICU admission.

[CONCLUSION] Wheezing, together with other bedside-available predictors, was independently associated with increased oxygen demand. This finding may facilitate early risk stratification and optimize oxygen resource allocation at the initial encounter, before laboratory or imaging examinations are available. Through voice-print analysis and artificial intelligence, future studies are warranted to further explore the predictive potential of breath sounds.

🏷️ 키워드 / MeSH 📖 같은 키워드 OA만

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