An retrospective study on the effects of deep learning model-based optimization emergency nursing on treatment compliance and curative effect of patients with acute left heart failure

被引:0
作者
Dai, Qian [1 ]
Huang, Jing [1 ]
Huang, Hui [1 ]
Song, Lin [1 ]
机构
[1] Xuzhou Med Univ, Affiliated Hosp, Xuzhou 221000, Jiangsu, Peoples R China
来源
BMC EMERGENCY MEDICINE | 2024年 / 24卷 / 01期
关键词
Deep learning model; Emergency nursing; Treatment compliance; Acute left heart failure; ASSOCIATION; CARE;
D O I
10.1186/s12873-024-01156-x
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
BackgroundBased on explainable DenseNet model, the therapeutic effects of optimization nursing on patients with acute left heart failure (ALHF) and its application values were discussed.MethodIn this study, 96 patients with ALHF in the emergency department of the Affiliated Hospital of Xuzhou Medical University were selected. According to different nursing methods, they were divided into conventional group and optimization group. Activity of daily living (ADL) scale was used to evaluate ADL of patients 6 months after discharge. Self-rating anxiety scale (SAS) and self-rating depression scale (SDS) were employed to assess patients' psychological state. 45 min improvement rate, 60 min show efficiency, rescue success rate, and transfer rate were used to assess the effect of first aid. Likert 5-level scoring method was adopted to evaluate nursing satisfaction.ResultsThe optimization group showed shorter durations for first aid, hospitalization, electrocardiography, vein channel establishment, and blood collection compared to the conventional group. However, their SBP, DBP, and HR were inferior. On the other hand, LVEF and FS were significantly better in the optimization group. After nursing intervention, SAS and SDS scores were lower in the optimization group. Additionally, the optimization group had higher 45-minute improvement rates, 60-minute show efficiency, rescue success, and transfer rates. They also performed better in 6-minute walking distance and ADL scores 6 months post-discharge. The optimization group had better compliance, total effective rates, and satisfaction than the conventional group.ConclusionIt was demonstrated that explainable DenseNet model had application values in the diagnosis of ALHF. Optimization emergency method could effectively shorten the duration of first aid, relieve anxiety, and other adverse emotions, and improve rescue success rate and short-term efficacy. Nursing intervention has a positive impact on the total effective efficiency and patient satisfaction.
引用
收藏
页数:15
相关论文
共 32 条
  • [1] The Surprise Question Can Be Used to Identify Heart Failure Patients in the Emergency Department Who Would Benefit From Palliative Care
    Aaronson, Emily L.
    George, Naomi
    Ouchi, Kei
    Zheng, Hui
    Bowman, Jason
    Monette, Derek
    Jacobsen, Juliet
    Jackson, Vicki
    [J]. JOURNAL OF PAIN AND SYMPTOM MANAGEMENT, 2019, 57 (05) : 944 - 951
  • [2] Prevalence, Related Factors and Association of Left Bundle Branch Block With Prognosis in Patients With Acute Heart Failure: a Simultaneous Analysis in 3 Independent Cohorts
    Aguilo, Oriol
    Carles Trullas, Joan
    Wussler, Desiree
    Llorens, Pere
    Conde-Martel, Alicia
    Lopez-Ayala, Pedro
    Jacob, Javier
    Roca-Villanueva, Bernardino
    Gil, Victor
    Belkin, Maria
    Angel Satue-Bartolome, Jose
    Mueller, Christian
    Miro, Oscar
    [J]. JOURNAL OF CARDIAC FAILURE, 2022, 28 (07) : 1104 - 1115
  • [3] Aslanova Rena, 2022, J Hypertens, V40, pe72, DOI 10.1097/01.hjh.0000835904.53948.69
  • [4] Enhancing Palliative Care for Patients With Advanced Heart Failure Through Simple Prognostication Tools: A Comparison of the Surprise Question, the Number of Previous Heart Failure Hospitalizations, and the Seattle Heart Failure Model for Predicting 1-Year Survival
    Blum, Moritz
    Gelfman, Laura P.
    McKendrick, Karen
    Pinney, Sean P.
    Goldstein, Nathan E.
    [J]. FRONTIERS IN CARDIOVASCULAR MEDICINE, 2022, 9
  • [5] Acute Left Atrial Response to Different Eccentric Resistance Exercise Loads in Patients with Heart Failure with Middle Range Ejection Fraction: A Pilot Study
    Caminiti, Giuseppe
    Perrone, Marco Alfonso
    Iellamo, Ferdinando
    D'Antoni, Valentino
    Catena, Matteo
    Franchini, Alessio
    Volterrani, Maurizio
    [J]. JOURNAL OF PERSONALIZED MEDICINE, 2022, 12 (05):
  • [6] Cardiac Phase Detection in Echocardiograms With Densely Gated Recurrent Neural Networks and Global Extrema Loss
    Dezaki, Fatemeh Taheri
    Liao, Zhibin
    Luong, Christina
    Girgis, Hany
    Dhungel, Neeraj
    Abdi, Amir H.
    Behnami, Delaram
    Gin, Ken
    Rohling, Robert
    Abolmaesumi, Purang
    Tsang, Teresa
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 2019, 38 (08) : 1821 - 1832
  • [7] Hospitalization for acute heart failure: the in-hospital care pathway predicts one-year readmission
    Duflos, Claire
    Troude, Penelope
    Strainchamps, David
    Segouin, Christophe
    Logeart, Damien
    Mercier, Gregoire
    [J]. SCIENTIFIC REPORTS, 2020, 10 (01)
  • [8] Role of transthoracic echocardiogram in acute heart failure
    Fitzsimons, Sarah
    Doughty, Robert N.
    [J]. REVIEWS IN CARDIOVASCULAR MEDICINE, 2021, 22 (03) : 741 - 754
  • [9] Hamana Tomoyo, 2022, J Cardiol Cases, V25, P188, DOI 10.1016/j.jccase.2021.09.005
  • [10] RETRACTED: The Clinical Effect of High-Flow Oxygen Therapy through the Nose on Patients with Acute Left Heart Failure and Hypoxemia (Retracted Article)
    Hao, Xinlei
    Zhao, Shuoran
    Cheng, Jiajia
    Yang, Lihua
    Jiang, Haiming
    Qu, Fuzheng
    [J]. JOURNAL OF HEALTHCARE ENGINEERING, 2022, 2022