Functional outcome and frailty in colorectal surgery patients

Elabbas, Elhassan; Sharma, Anita; Thu, Khin; Tan, Azriel; Alim, Melissa; Zhang, Yan

doi:10.1111/ans.18602

Cited by 2 publications

(3 citation statements)

References 27 publications

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“…This endeavor holds significant value in averting frailty onset and enhancing patient quality of life. Notably, the occurrence of early postoperative frailty in elderly colorectal cancer patients was notably high at 78.4%, surpassing the findings of ELABBAS et al study (50%) ( 15 ) and falling below the previous research group investigation (92.2%) ( 4 ). The higher incidence of frailty in this study may be attributed to the inclusion of elderly patients over 65 years old, as age is a significant risk factor for frailty.…”

Section: Discussioncontrasting

confidence: 60%

“…Subsequently, a questionnaire was developed to evaluate early frailty risk factors post-enterostomy in the elderly population. These factors include gender ( 4 ), age ( 13 ) education ( 4 ), marital status ( 14 ), acute and chronic diseases ( 15 ), self-perceived health status ( 14 ) monthly income ( 4 ), stoma complications (such as fecal skin dermatitis, stoma bleeding, injury, allergic dermatitis, necrosis, and mucosal separation) ( 16 ), receipt of chemoradiotherapy ( 17 ), stoma acceptance ( 16 ), sleep quality ( 18 ), social support ( 4 ), anxiety ( 14 ), preoperative frailty ( 19 ), and cancer stage ( 16 ). The recovery process post-enterostomy was divided into three stages: early surgery, recovery period, and post-discharge recovery.…”

Section: Methodsmentioning

confidence: 99%

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Comparative study of the risk prediction model of early postoperative frailty in elderly enterostomy patients based on machine learning methods

Ya-juan,

Fang-hui,

Yi-wei

et al. 2024

Front. Med.

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ObjectiveBased on machine learning method, four types of early postoperative frailty risk prediction model of enterostomy patients were constructed to compare the performance of each model and provide the basis for preventing early postoperative frailty of elderly patients with enterostomy.MethodsThe prospective convenience sampling method was conducted and 362 early postoperative enterostomy patients were selected in three hospitals from July 2020 to November 2023 in Shanghai, four different prediction models of Support Vector Machine (SVM), Bayes, XG Boost, and Logistic regression were used and compared the test effects of the four models (MCC, F1, AUC, and Brier index) to judge the classification performance of the four models in the data of this study.ResultsA total of 21 variables were included in this study, and the predictors mainly covered demographic information, stoma-related information, quality of life, anxiety and depression, and frailty. The validated models on the test set are XGBoost, Logistic regression, SVM prediction model, and Bayes on the MCC and F1 scores; on the AUC, XGBoost, Logistic regression, Bayes, and SVM prediction model; on the Brier scores, Bayes, Logistic regression, and XGBoost.ConclusionXGBoost based on machine learning method is better than SVM prediction model, Logistic regression model and Bayes in sensitivity and accuracy. Quality of life in the early postoperative period can help guide clinical patients to identify patients at high risk of frailty and reduce the incidence of early postoperative frailty in elderly patients with enterostomy.

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Section: Discussioncontrasting

confidence: 60%

Section: Methodsmentioning

confidence: 99%

Comparative study of the risk prediction model of early postoperative frailty in elderly enterostomy patients based on machine learning methods

Ya-juan,

Fang-hui,

Yi-wei

et al. 2024

Front. Med.

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“…As the elderly population burgeons, the necessity for colorectal cancer (CRC) surgery among this cohort becomes pronounced. Each patient in this context confronts intricate functional challenges compounded by an array of complex co-morbidities 15 , 16 , thereby necessitating resource-intensive preoperative assessment clinics and reviews to facilitate the final decision to operate. With these considerations in mind, we posit that a streamlined frailty index tool could potentially serve as a valuable aid within the preliminary assessment stage, thereby contributing to the arrangement of postoperative care strategies tailored to propel octogenarians toward the restoration of functional baselines, particularly for those expected to experience sustained survival following CRC resection surgery.…”

Section: Introductionmentioning

confidence: 99%

Relationship between the m-FI 11 score and 2-year survival in octogenarians undergoing colorectal cancer resection

Ari,

Iqbal,

Crane

et al. 2023

Annals of Medicine &Amp; Surgery

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Introduction: The modified Frailty Index (m-FI) offers a simple scoring tool, predicting short-term outcomes in elderly colorectal cancer (CRC) patients. However, links between m-FI scores and 2-year postoperative mortality in octogenarian CRC resection patients remain underexplored. A streamlined frailty index can aid in preoperative assessments to identify elderly patients who are likely to live longer after curative resection surgery to then tailor postoperative care. Our study aims to assess the association between m-FI scores and 2-year postoperative mortality in elderly CRC surgery patients. Methods: A retrospective analysis was conducted on a cohort of consecutive patients aged older than or equal to 80 years who underwent colorectal cancer resection at a tertiary referral centre between 2010 and 2017. The m-FI-11 scores less than or equal to two denoted the non-frail category, whereas m-FI scores equal to or exceeding 3 were categorised as frail. The primary outcome measure was defined as 2-year all-cause mortality. Results: A total of 337 patients were studied. The 2-year overall survival rate was 83% with an overall median survival time of 84 months (95% CI: 74–94 months). Patients with m-FI scores less than or equal to 2 had a 2-year survival rate of 85% and a median survival time of 94 months (95% CI: 84–104 months). Conversely, patients with m-FI scores greater than or equal to 3 had a 2-year survival rate of 72% and a median survival time of 69 months (95% CI: 59–79 months). An m-FI score greater than or equal to 3 showed a hazard ratio of 1.73 (95% CI: 0.92–3.26, P=0.092) for 2-year mortality compared to an m-FI score less than or equal to 2. Conclusion: Higher m-FI scores significantly correlate with an increased 2-year mortality risk among octogenarian CRC resection patients. This highlights the potential of the m-FI as a preoperative tool for identifying patients likely to survive longer post-surgery. Its integration aids in tailored postoperative care strategies, ensuring efficient recovery to functional baselines in this cohort.

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Functional outcome and frailty in colorectal surgery patients

Cited by 2 publications

References 27 publications

Comparative study of the risk prediction model of early postoperative frailty in elderly enterostomy patients based on machine learning methods

Comparative study of the risk prediction model of early postoperative frailty in elderly enterostomy patients based on machine learning methods

Relationship between the m-FI 11 score and 2-year survival in octogenarians undergoing colorectal cancer resection

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