인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Although previous studies have suggested that albumin-corrected anion gap (ACAG) may be a predictor of mortality in critically ill patients in intensive care unit (ICU), its utility in the context of asthma has not been definitively established. In this study, baseline data, albumin concentration, anion gap (AG) and 30-d mortality data were retrieved from the Medical Information Mart for Intensive Care IV database (MIMIC-IV) for patients with asthma in the intensive care unit. Receiver operating characteristic (ROC) curves were constructed to analyze the predictive ability of ACAG and AG. The risk of 30-day mortality among patients with ACAG and asthma was analyzed using a restricted cubic spline (RCS) plot. Decision curve analysis (DCA) was used to evaluate the clinical usefulness of ACAG as a prognostic factor for 30-day mortality. Subsequently, subgroup analysis was conducted to explore potential variations in the relationship between ACAG and 30-day mortality based on factors such as sex, age, whether the asthma was acute, and other co-morbidities. Our study reveals that ACAG is a significant independent predictor of 30-day mortality in asthmatic patients receiving intensive care. The area under the AUC curve for ACAG was found to be 0.703, which is higher than that of AG, indicating that ACAG has a better predictive ability for 30-day mortality in this population. Furthermore, higher levels of ACAG were found to be associated with increased risk of 30-day mortality in asthmatic patients. In addition, decision curve analysis (DCA) demonstrated that the net benefit of ACAG was greater than that of AG. These findings suggest that ACAG may be a valuable prognostic factor for predicting 30-day mortality in asthmatic patients in the ICU. Our study provides evidence that ACAG is associated with an increased risk of 30-d mortality and has better predictive value in patients with combined asthma who are admitted to the ICU than AG.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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