Introduction: The functional decline seen in frail patients is associated with significant morbidity and mortality. The modified frailty index 5 (mFI-5) score is an accepted risk predictor score in surgery. Hypoalbuminemia has been correlated with poor postoperative outcomes.There exists, however, a gap in the literature regarding the combined assessment of frailty and hypoalbuminemia and the predictive power of this combined assessment. This retrospective cohort study aimed to investigate the association of preoperative albumin and frailty, as assessed with the mFI-5 score, and its ability to predict surgical outcomes.
Methods: We queried the ACS-NSQIP database (2008-2021) to identify all surgical patients. Perioperative data, including demographics and preoperative laboratory values, including albumin, were collected. The predictive power of the mFI-5 and hypoalbuminemia (Alb) independently and in combination (mFI-5+Alb), was assessed using multivariable linear and logistic regression models 30-day outcomes were assessed including mortality, length of hospital stay, reoperation, medical and surgical complications, and discharge destination.
Results: A total of 9 782 973 patients were identified, of whom 4 927 520 (50.4%) were nonfrail (mFI=0), 3 266 636 had a frailty score of 1 (33.4%), 1 373 968 a score of 2 (14.0%), 188 821 a score of 3 (1.9%), and 26 006 a score greater or equal to 4 (0.3%). Albumin levels were available for 4 570 473 patients (46.7%), of whom 848 315 (18.6%) had hypoalbuminemia. The combined assessment (mFI-5+Alb) was found to be a more accurate risk predictor than each factor independently for all outcomes. A weak negative correlation between serum albumin levels and mFI scores was established (Spearman R : -0.2; <0.0001).
Conclusions: Combined assessment of frailty and albumin was the strongest risk predictor. Therefore, for patients undergoing surgery, we recommend consideration of both serum albumin and frailty in order to optimally determine perioperative planning, including multidisciplinary care mobilization and prehabilitation and posthabilitation.
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http://dx.doi.org/10.1097/JS9.0000000000002025 | DOI Listing |
Background: Coronary heart disease (CHD) and depression frequently co-occur, significantly impacting patient outcomes. However, comprehensive health status assessment tools for this complex population are lacking. This study aimed to develop and validate an explainable machine learning model to evaluate overall health status in patients with comorbid CHD and depression.
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January 2025
Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
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Adv Skin Wound Care
January 2025
Li-li Ma, MSc, RN, is PhD Candidate, Medical College, Tongji University, Shanghai, China Department of Nursing, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China. Ya-juan Zhang, MSc, RN, is Head Nurse, Department of Nursing, Shanghai Sixth People's Hospital, School of Medicine, Jiao Tong University, Shanghai. Hui-ren Zhuang, MSc, RN, is Department Head Nursing, Department of Nursing, Shanghai East Hospital, School of Medicine, Tongji University. Hui Jiang, PhD, RN, is Nursing Director, Department of Nursing, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University.
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J Head Trauma Rehabil
January 2025
Author Affiliations: Program Executive Office, Defense Healthcare Management Systems, Arlington, Virginia (Ms Wal and Dr Caban); National Center for Collaborative Healthcare Innovation (NCCHI), VA Palo Alto Health Care System, Palo Alto, California (Mr Hoover); Department of Health Law, Policy and Management, Boston University School of Public Health, Boston, Massachusetts (Dr Adams); Veterans Health Administration Rocky Mountain Mental Illness Research Education and Clinical Center, Aurora, Colorado (Drs Adams and Forster); Department of Physical Medicine & Rehabilitation, University of Colorado, Anschutz Medical Campus, Aurora, Colorado (Dr Forster); and Uniformed Services University of the Health Sciences, Graduate School of Nursing, Bethesda, Maryland (Dr Engler).
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Asian Pac J Cancer Prev
January 2025
Department of Physics, Faculty of Sciences, Arak University, Arak, Iran.
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