A non-lab nomogram of survival prediction in home hospice care patients with gastrointestinal cancer

Wang, Muqing; Jing, Xubin; Cao, Wei; Zeng, Yicheng; Wu, Chaofen; Weilong, Zeng; Chen, Wenxia; Hu, Xi; Zhou, Yanna; Cai, Xianbin

doi:10.1186/s12904-020-00690-2

Cited by 4 publications

(3 citation statements)

References 40 publications

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“…The prognosis demonstrated in the current study, of elderly patients hospitalized for acute illness in internal medicine wards and fed with NGT, was similar to that reported among patients with terminal cancer. 21 , 22 The poor prognosis of our patients may prompt questions regarding the initiation of NGT feeding. Possibly, some of our patients could have been better managed by assisted hand feeding or other palliative treatment.…”

Section: Discussionmentioning

confidence: 97%

Factors Associated with In-Hospital Mortality in Elderly Internal Medicine Patients with Nasogastric Tube Feeding

Plotnikov,

Sharif,

Buturlin

et al. 2023

CIA

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Purpose To evaluate demographic, clinical, and laboratory variables, and their associations with in-hospital mortality, among elderly internal medicine patients with nasogastric tube (NGT) feeding. Patients and Methods Demographic, clinical, and laboratory data were collected retrospectively for 129 patients aged ≥80 years who initiated NGT feeding during their hospitalization in internal medicine wards. The data were compared between survivors and non-survivors. Multivariate logistic regressions were performed to identify the variables most significantly associated with in-hospital mortality. Results The in-hospital mortality rate was 60.5%. Compared to survivors, non-survivors more often presented with pressure sores ( P =0.005) and lymphopenia ( P <0.001), were more often treated with invasive mechanical ventilation ( P <0.001), and less often underwent geriatric assessment ( P <0.001). Non-survivors demonstrated higher mean levels of C-reactive protein, and lower mean values of serum cholesterol, triglycerides, total protein, and albumin ( P <0.001 for all comparisons). On multivariate analysis, the following variables were most significantly associated with in-hospital mortality in the entire cohort: the presence of pressure sores (odds ratio [OR], 4.34; 95% confidence interval [CI], 1.68–11.48; P =0.003) and lymphopenia (OR, 4.09; 95% CI, 1.51–11.08; P =0.006), and serum cholesterol (OR, 0.98; 95% CI, 0.96–0.99; P =0.003). Conclusion Among elderly acutely ill patients who initiated NGT feeding during hospitalization, in-hospital mortality was extremely high. The factors most strongly associated with in-hospital mortality were the presence of pressure sores and lymphopenia, and lower serum cholesterol levels. These findings may provide useful prognostic information for decision-making regarding initiation of NGT feeding in elderly hospitalized patients.

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Section: Discussionmentioning

confidence: 97%

Factors Associated with In-Hospital Mortality in Elderly Internal Medicine Patients with Nasogastric Tube Feeding

Plotnikov,

Sharif,

Buturlin

et al. 2023

CIA

View full text Add to dashboard Cite

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“…Plyta et al (2020) explored the relationship between nutritional status and quality of life of hospitalized cancer patients with intestinal failure and need parenteral nutrition and found that KPS, which is impaired by muscle strength, was the main component of QoL damage in patients. In addition, Wang et al (2020) found that physical status can improve survival predictions in patients with advanced gastrointestinal cancer. Therefore, healthcare providers and caregivers are encouraged to pay attention to the level of self‐care ability of patients, which can not only help to evaluate the overall functional status of patients but also reflect the quality of life of patients.…”

Section: Discussionmentioning

confidence: 99%

Contribution of non‐socioeconomic factors to healthy quality of life in socioeconomically deprived patients with advanced gastrointestinal cancer: Measuring attributable fraction

An,

Nie,

Huang

et al. 2023

Journal of Advanced Nursing

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BackgroundThe quality of life of patients with advanced gastrointestinal cancer is seriously impaired, and socioeconomic deprivation often has a serious impact on their quality of life. However, little is known about the relative contribution of non‐socioeconomic factors to the quality of life of patients with advanced gastrointestinal cancer with socioeconomic deprivation.AimThis study aims to investigate the situation and predictors of quality of life of patients with socioeconomic deprivation and evaluate the independent effects of some non‐socioeconomic factors.DesignA retrospective study based on cross‐sectional design.MethodsData were obtained from 1075 patients with advanced gastrointestinal cancer who received family palliative treatment in the hospice ward of Zhongnan Hospital of Wuhan University from March 2010 to October 2020, including demographic and clinical questionnaires, Karnofsky Performance Status scale and Cancer Pain and Quality of Life Questionnaire of Chinese Cancer Patients.ResultsThe quality of life of patients with advanced gastrointestinal cancer with socioeconomic deprivation is impaired and is affected by gait, self‐care ability, abdominal distension, nutritional status, weight loss, constipation and posture. Improvement in six of these factors—gait, self‐care ability, abdominal distension, nutritional status, weight loss and posture—has an independent positive impact on the development of a healthy quality of life for patients.ConclusionsGait, self‐care ability, abdominal distension, nutritional status, weight loss and posture are important determinants of healthy quality of life in patients with advanced gastrointestinal cancer with socioeconomic deprivation, and early identification and strength management of these non‐socioeconomic factors may neutralize the negative impact of socioeconomic factors on the quality of life.Implications for PracticeThis study provides new ideas and intervention entry points for global nurses in practice innovations to improve the quality of life of socioeconomically deprived patients with advanced gastrointestinal cancer. It enables them to focus on the effectiveness of non‐socioeconomic factors in the development and implementation of targeted care plans for patients with advanced gastrointestinal cancer experiencing socioeconomic deprivation globally.Reporting MethodThis study was reported in strict compliance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline.Patient or Public ContributionNo patient or public contribution.

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“…Digital health technology has been widely adopted in end-of-life care for various purposes, such as education, telemedicine, and prognosis prediction using electronic health records [24][25][26][27][28][29][30][31]. Although wearable devices have also been demonstrated to help monitor and predict physical conditions [32][33][34][35][36][37][38][39][40], there have been only a few studies on the use of wearable devices in end-of-life care.…”

Section: The Application Of Wearable Devices and Artificial Intellige...mentioning

confidence: 99%

Evaluating the Potential of Machine Learning and Wearable Devices in End-of-Life Care in Predicting 7-Day Death Events Among Patients With Terminal Cancer: Cohort Study

Liu,

Shih,

Huang

et al. 2023

J Med Internet Res

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Background An accurate prediction of mortality in end-of-life care is crucial but presents challenges. Existing prognostic tools demonstrate moderate performance in predicting survival across various time frames, primarily in in-hospital settings and single-time evaluations. However, these tools may fail to capture the individualized and diverse trajectories of patients. Limited evidence exists regarding the use of artificial intelligence (AI) and wearable devices, specifically among patients with cancer at the end of life. Objective This study aimed to investigate the potential of using wearable devices and AI to predict death events among patients with cancer at the end of life. Our hypothesis was that continuous monitoring through smartwatches can offer valuable insights into the progression of patients at the end of life and enable the prediction of changes in their condition, which could ultimately enhance personalized care, particularly in outpatient or home care settings. Methods This prospective study was conducted at the National Taiwan University Hospital. Patients diagnosed with cancer and receiving end-of-life care were invited to enroll in wards, outpatient clinics, and home-based care settings. Each participant was given a smartwatch to collect physiological data, including steps taken, heart rate, sleep time, and blood oxygen saturation. Clinical assessments were conducted weekly. The participants were followed until the end of life or up to 52 weeks. With these input features, we evaluated the prediction performance of several machine learning–based classifiers and a deep neural network in 7-day death events. We used area under the receiver operating characteristic curve (AUROC), F1-score, accuracy, and specificity as evaluation metrics. A Shapley additive explanations value analysis was performed to further explore the models with good performance. Results From September 2021 to August 2022, overall, 1657 data points were collected from 40 patients with a median survival time of 34 days, with the detection of 28 death events. Among the proposed models, extreme gradient boost (XGBoost) yielded the best result, with an AUROC of 96%, F1-score of 78.5%, accuracy of 93%, and specificity of 97% on the testing set. The Shapley additive explanations value analysis identified the average heart rate as the most important feature. Other important features included steps taken, appetite, urination status, and clinical care phase. Conclusions We demonstrated the successful prediction of patient deaths within the next 7 days using a combination of wearable devices and AI. Our findings highlight the potential of integrating AI and wearable technology into clinical end-of-life care, offering valuable insights and supporting clinical decision-making for personalized patient care. It is important to acknowledge that our study was conducted in a relatively small cohort; thus, further research is needed to validate our approach and assess its impact on clinical care. Trial Registration ClinicalTrials.gov NCT05054907; https://classic.clinicaltrials.gov/ct2/show/NCT05054907

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A non-lab nomogram of survival prediction in home hospice care patients with gastrointestinal cancer

Cited by 4 publications

References 40 publications

Factors Associated with In-Hospital Mortality in Elderly Internal Medicine Patients with Nasogastric Tube Feeding

Factors Associated with In-Hospital Mortality in Elderly Internal Medicine Patients with Nasogastric Tube Feeding

Contribution of non‐socioeconomic factors to healthy quality of life in socioeconomically deprived patients with advanced gastrointestinal cancer: Measuring attributable fraction

Evaluating the Potential of Machine Learning and Wearable Devices in End-of-Life Care in Predicting 7-Day Death Events Among Patients With Terminal Cancer: Cohort Study

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