Poor nutritional status and frailty associated with acute kidney injury after cardiac surgery: A retrospective observational study

The Five-Item Modified Frailty Index Predicts Adverse Surgical Outcomes in Patients Undergoing Mastectomy

BACKGROUND

The 5-item modified Frailty Index (mFI-5) is a clinical tool to predict adverse outcomes in surgical patients by assessing five comorbidities: diabetes, hypertension, congestive heart failure, chronic obstructive pulmonary disease, and dependent functional status. It helps to evaluate postoperative complication risks, recovery time, and overall survival, particularly in frail patients undergoing oncological and gynecological surgeries.

METHODS

This retrospective cohort study analyzed American College of Surgeons, National Surgical Quality Improvement Program data from adult female patients undergoing mastectomy procedures without reconstruction between 2017 and 2022. Patients were selected based on Current-Procedural-Terminology codes, excluding incomplete or non-breast-related cases. Preoperative, perioperative, and 30-day postoperative data were analyzed using logistic and linear regression models, with the mFI-5 cutoff set at 2.

RESULTS

Between 2017 and 2022, 860 patients underwent mastectomies at Yale Healthcare Network; 19% (n = 163) had mFI score ≥2. High-risk patients (mFI ≥2) were significantly older (66.32 ± 10.83 years) and had a higher body mass index (33.69 ± 7.73, both p < 0.001). Surgical complications occurred in 11.98% of patients, with a higher rate in the high-risk group (22.7% vs. 9.5%, p < 0.001). Adjusted multivariate logistic regression showed an increased risk of complications in frail patients (aOR 2.66; [1.60-4.43], p < 0.001). Although slight reductions in hospital stay and surgery duration were observed for high-risk patients, these differences were not significant. Sensitivity analysis confirmed higher odds of complications, including acute kidney failure (odds ratio [OR] 9.01) and pneumonia (OR 4.10).

CONCLUSIONS

The mFI-5 is a robust tool for predicting surgical complications in patients undergoing mastectomy, particularly those with multiple comorbidities.

The Five-Item Modified Frailty Index (mFI-5) Predicts Adverse Short-term Outcomes in Patients Undergoing Mastectomy: A Propensity Score-Matched Analysis of 252,054 Cases

BACKGROUND

Frailty has emerged as a critical predictor of postoperative outcomes, particularly in older surgical patients. However, its role in mastectomy patients remains underexplored. This study evaluates the utility of the 5-item Modified Frailty Index (mFI-5) in predicting 30-day postoperative complications in mastectomy patients, aiming to improve risk stratification and inform clinical decision-making.

METHODS

A retrospective analysis using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was conducted from 2008 to 2022. Patients were categorized into high-risk (mFI-5 ≥ 2) and low-risk (mFI-5 < 2) groups. Propensity score matching (PSM) was applied to create balanced cohorts and multivariate logistic regression was used to evaluate associations between frailty and postoperative outcomes.

RESULTS

Of the 252,054 adult female patients who underwent mastectomy, 1.2 % were identified as high-risk frail. High-risk patients were older (70 ± 9.9 vs. 60 ± 14 years, P < .001) and had a higher BMI (35 ± 9.1 vs. 29 ± 7.1 kg/m², P < .001) compared to low-risk patients. After PSM, high-risk patients had significantly higher odds of any complication (OR: 2.05, 95 % CI: 1.70-2.47, P < .001), surgical complications (OR: 1.70, 95 % CI: 1.38-2.10, P < .001), and medical complications (OR: 3.81, 95 % CI: 2.64-5.50, P < .001). Key complications included infections, bleeding requiring transfusion, and unplanned readmissions.

CONCLUSION

The mFI-5 effectively identifies mastectomy patients at higher risk of postoperative complications, including medical complications and unplanned reoperation or readmission, underscoring its value in preoperative risk stratification. Incorporating frailty assessments into clinical practice could enhance surgical decision-making, optimize resource allocation, and improve patient outcomes.

Association between frailty and acute kidney injury after cardiac surgery: unraveling the moderation effect of body fat through an international, retrospective, multicohort study

BACKGROUND

Acute kidney injury (AKI) is a common and serious complication after cardiac surgery that significantly affects patient outcomes. Given the limited treatment options available, identifying modifiable risk factors is critical. Frailty and obesity, two heterogeneous physiological states, have significant implications for identifying and preventing AKI. Our study investigated the interplay among frailty, body composition, and AKI risk after cardiac surgery to inform patient management strategies.

MATERIAL AND METHODS

This retrospective cohort study included three international cohorts. Primary analysis was conducted on adult patients who underwent cardiac surgery between 2014 and 2019 at Wuhan Union Hospital, China. We tested the generalizability of our findings with data from two independent international cohorts, the Medical Information Mart for Intensive Care IV (MIMIC-IV) and the eICU Collaborative Research Database. Frailty was assessed using a clinical lab-based frailty index (FI-LAB), while total body fat percentage (BF%) was calculated based on a formula accounting for BMI, sex, and age. Logistic regression models were used to analyze the associations between frailty, body fat, and AKI, adjusting for pertinent covariates.

RESULTS

A total of 8785 patients across three international cohorts were included in the study. In the primary analysis of 3569 patients from Wuhan Union Hospital, moderate and severe frailty were associated with an increased AKI risk after cardiac surgery. Moreover, a nonlinear relationship was observed between BF% and AKI risk. When stratified by the degree of frailty, lower body fat correlated with a decreased incidence of AKI. Extended analyses using the MIMIC-IV and eICU cohorts ( n =3951 and n =1265, respectively) validated these findings and demonstrated that a lower total BF% was associated with decreased AKI incidence. Moderation analysis revealed that the effect of frailty on AKI risk was moderated by the BF%. Sensitivity analyses demonstrated results consistent with the main analyses.

CONCLUSION

Higher degrees of frailty were associated with an elevated risk of AKI following cardiac surgery, and total BF% moderated this relationship. This research underscores the significance of integrating frailty and body fat assessments into routine cardiovascular care to identify high-risk patients for AKI and implement personalized interventions to improve patient outcomes.

Which frailty score in cardiac surgery patients?

Background

Frailty assessment for risk prediction is suggested in elderly patients undergoing cardiac surgery. We aimed to compare five different frailty tests.

Methods

Relation of Edmonton Frailty Score (EFS), Fried Frailty Phenotype (FFP), FRAIL (Fatigue, Resistance, Ambulation, Illness, and Loss of weight), Katz and hand grip strength (HGS) tests to each other, postoperative outcomes and mortality rates were evaluated prospectively in 140 consecutive patients aged ≥65 years.

Results

The median follow-up period was 880.5 (range, 0 to 1,237) days with higher EFS and FFP scores in non-survivors (p<0.05). Patients with any complication had higher EFS (p=0.002), FFP (p=0.004) and FRAIL (p=0,006) scores. Compared to non-frail patients, frail patients' NYHA capacity, EuroSCORE II and STS mortality risks were higher; hemoglobin values and HGS were lower with EFS, FFP, and FRAIL tests. Frail patients' hospitalization periods with EFS (p=0.003) and intensive care unit stay with FFP (p=0.029) were longer. No mortality was observed in non-frail patients according to the FFP test. The Kaplan-Meier (KM) log-rank survival curves showed significant differences in favor of non-frail subgroups according to EFS, FFP and HGS tests (p<0.05). Relative risks for mortality in frail and pre-frail patients were between 0.9 and 4. The FFP was the most sensitive test (area under curve=0.721). There was discordance rather than concordance among five different tests (Kappa <0.411).

Conclusion

For patients aged ≥65 years undergoing heart surgery the FFP can be used safely to determine non-frail patients. Although the EFS seems to be promising to identify frail patients, further large-scale studies using various tests are needed to predict an optimal cut-off value for this patient population.

Association of the geriatric nutritional risk index with poor outcomes in patients with coronary revascularization: a cohort study

Background

Poor nutritional status may affect outcomes after coronary revascularization, but the association between nutritional status and outcomes in patients undergoing coronary revascularization has not been fully evaluated. This study was based on the MIMIC-IV database to analyze the impact of baseline nutritional status on poor outcomes in patients with coronary revascularization.

Methods

Patients with coronary revascularization were screened from the MIMIC-IV database. A geriatric nutritional risk index (GNRI) was calculated and used to divide patients into 4 groups: no malnutrition (Q4: ≥96.79), mild malnutrition (Q3: 90.85-96.78), moderate malnutrition (Q2: 86.37-90.84), and severe malnutrition (Q1: 86.37). The primary outcome measure was 28-day mortality, and the secondary outcome measures were AKI and length of hospital stay. Cox proportional hazards model, Kaplan-Meier survival analysis, restricted cubic spline (RCS), and multiple linear regression model were used for statistical analysis, respectively, to ensure the robustness of study results.

Results

A total of 1,168 patients with coronary revascularization were included. The GNRI demonstrated a significant association with 28-day mortality in patients undergoing coronary revascularization. As a continuous variable, the GNRI exhibited a notable inverse correlation with mortality across unadjusted, partially adjusted, and fully adjusted Cox regression models [hazard ratios (HRs): 0.93, 0.94, 0.96, respectively; all P < 0.001]. When considered as a categorical variable, a low GNRI (first quartile, Q1) was significantly associated with elevated mortality risks (HRs: 2.64, 2.30, 1.82 in the unadjusted, partially adjusted, and fully adjusted models, respectively; all P < 0.05). Subgroup analysis revealed a more pronounced association in patients under 65 years of age (P for interaction = 0.014). Furthermore, reduced GNRI levels were also associated with an increased incidence of AKI and extended hospital lengths of stay.

Conclusion

GNRI is associated with prognosis in patients with coronary revascularization. Patients with lower GNRI had higher 28-day mortality, greater risk of AKI, and longer hospital stays.

Prognostic value of preoperative nutritional status for postoperative moderate to severe acute kidney injury among older patients undergoing coronary artery bypass graft surgery: a retrospective study based on the MIMIC-IV database

OBJECTIVE

To investigate the association between preoperative nutritional scores and moderate-to-severe acute kidney injury (AKI) after coronary artery bypass graft (CABG) surgery and the predictive significance of nutritional indices for moderate to severe AKI.

METHODS

This study retrospectively included older patients underwent CABG surgery from the Medical Information Mart for Intensive Care (MIMIC) database. Nutritional scores were calculated by the Geriatric Nutritional Risk Index (GNRI) and the Prognostic Nutritional Index (PNI), respectively. Moderate-to-severe injury was determined by KDIGO criteria. Logistic regression, subgroup analysis, and restricted cubic splines were utilized to investigate the association. The predictive value was also assessed by the area under the curve (AUC), net reclassification index (NRI), and integrated discrimination improvement (IDI).

RESULTS

A total of 1,007 patients were retrospectively included, of which 100 (9.9%) and 380 (37.7%) had malnutrition calculated by GNRI and PNI scores. The incidence of moderate-to-severe AKI was 524 (52.0%). After adjustment for selected risk factors, worse nutritional scores were associated with a higher incidence of moderate-to-severe AKI (PGNRI<0.001; PPNI=0.001). Integrating these indices into different base models improves their performance, as manifested by significant improvements in AUCs and NRIs (p < 0.05).

CONCLUSION

Worse preoperative nutritional status was associated with an elevated risk of postoperative moderate-to-severe AKI. Integrating these indices into base models improve their predictive performance. These results highlight the importance of assessing nutritional status among older patients had CABG surgery.

Prognostic nutritional index as a predictive marker for acute kidney injury in adult critical illness population: a systematic review and diagnostic test accuracy meta-analysis

BACKGROUND

The prognostic nutritional index (PNI), integrating nutrition and inflammation markers, has been increasingly recognized as a prognostic predictor in diverse patient cohorts. Recently, its effectiveness as a predictive marker for acute kidney injury (AKI) in various clinical settings has gained attention. This study aims to assess the predictive accuracy of the PNI for AKI in critically ill populations through systematic review and meta-analysis.

METHODS

A systematic review was conducted using the databases MEDLINE, EMBASE, PubMed, and China National Knowledge Infrastructure up to August 2023. The included trials reported the PNI assessment in adult population with critical illness and its predictive capacity for AKI. Data on study characteristics, subgroup covariates, and diagnostic performance of PNI, including sensitivity, specificity, and event rates, were extracted. A diagnostic test accuracy meta-analysis was performed. Subgroup analyses and meta-regression were utilized to investigate the sources of heterogeneity. The GRADE framework evaluated the confidence in the meta-analysis's evidence.

RESULTS

The analysis encompassed 16 studies with 17 separate cohorts, totaling 21,239 patients. The pooled sensitivity and specificity of PNI for AKI prediction were 0.67 (95% CI 0.58-0.74) and 0.74 (95% CI 0.67-0.80), respectively. The pooled positive likelihood ratio was 2.49 (95% CI 1.99-3.11; low certainty), and the negative likelihood ratio was 0.46 (95% CI 0.37-0.56; low certainty). The pooled diagnostic odds ratio was 5.54 (95% CI 3.80-8.07), with an area under curve of summary receiver operating characteristics of 0.76. Subgroup analysis showed that PNI's sensitivity was higher in medical populations than in surgical populations (0.72 vs. 0.55; p < 0.05) and in studies excluding patients with chronic kidney disease (CKD) than in those including them (0.75 vs. 0.56; p < 0.01). Overall, diagnostic performance was superior in the non-chronic kidney disease group.

CONCLUSION

Our study demonstrated that PNI has practical accuracy for predicting the development of AKI in critically ill populations, with superior diagnostic performance observed in medical and non-CKD populations. However, the diagnostic efficacy of the PNI has significant heterogeneity with different cutoff value, indicating the need for further research.

Prognostic significance of preoperative nutritional status for postoperative acute kidney injury in older patients undergoing major abdominal surgery: a retrospective cohort study

BACKGROUND

The association between malnutrition and postoperative acute kidney injury (AKI) has not been well studied. In this study, the authors examined the association between preoperative nutritional status and postoperative AKI in older patients who underwent major abdominal surgery, as well as the predictive value of malnutrition for AKI.

MATERIALS AND METHODS

The authors retrospectively included patients aged 65 or older who underwent major elective abdominal surgery. The nutritional status of the patient was evaluated using three objective nutritional indices, such as the geriatric nutritional risk index (GNRI), the prognostic nutritional index (PNI), and the controlling nutritional status (CONUT). AKI was determined using the KDIGO criteria. The authors performed logistic regression analysis to investigate the association between preoperative nutritional status and postoperative AKI, as well as the predictive value of nutritional scores for postoperative AKI.

RESULTS

A total of 2775 patients were included in the study, of which 707 (25.5%), 291 (10.5%), and 517 (18.6%) had moderate to severe malnutrition according to GNRI, PNI, and CONUT calculations. After surgery, 144 (5.2%) patients developed AKI, 86.1% at stage 1, 11.1% at stage 2, and 2.8% at stage 3 as determined by KDIGO criteria. After adjustment for traditional risk factors, worse nutritional scores were associated with a higher AKI risk. In addition to traditional risk factors, these nutritional indices improved the predictive ability of AKI prediction models, as demonstrated by significant improvements in integrated discrimination and net reclassification.

CONCLUSIONS

Poor preoperative nutritional status, as assessed by GNRI, PNI, and CONUT scores, was associated with an increased risk of postoperative AKI. Incorporating these scores into AKI prediction models improved their performance. These findings emphasize the need for screening surgical patients for malnutrition risk. Further research is needed to determine whether preoperative malnutrition assessment and intervention can reduce postoperative AKI incidence.

Association of Malnutrition with Risk of Acute Kidney Injury: A Systematic Review and Meta-Analysis

Background

Acute kidney injury (AKI) is a complex clinical syndrome of hospitalization that may be affected by undernutrition and metabolic changes. The aim of this meta-analysis was to systematically assess the association between malnutrition and the risk of prevalent AKI.

Materials and Methods

We searched PubMed, Embase, Ovid MEDLINE, Web of Science, and Chinese databases (WANFANG, VIP, and CKI) from database inception until May 1, 2023, for studies evaluating the association of malnutrition with the risk of AKI. Summary odds ratios (ORs) were estimated using a random-effects model.

Results

We identified 17 observational studies, which included 273,315 individuals. Compared with patients with normal nutritional status, those with malnutrition had a 125% increased risk of prevalent AKI (pooled ORs, 2.25; 95% confidence interval, 1.80-2.82). Malnutrition was also significantly associated with prevalent AKI across all subgroups when subgroup analyses were performed on covariates such as region, study design, age, sample size, malnutrition assessment method, patient characteristics, covariate adjustment degree, and risk of bias. Meta-regression models demonstrated no significant differences in AKI risk between patients with malnutrition and without malnutrition.

Conclusions

Our results suggest that malnutrition may be a potential target for AKI prevention. However, well-designed studies with ethnically or geographically diverse populations are needed to evaluate strategies and interventions to prevent or slow the development and progression of AKI in malnourished individuals.

Association of Preoperative Prognostic Nutritional Index with Risk of Postoperative Acute Kidney Injury: A Meta-Analysis of Observational Studies

This meta-analysis aimed to assess the clinical association of the preoperative prognostic nutritional index (pre-PNI) with the risk of postoperative acute kidney injury. Four databases (e.g., Medline) were searched from inception to December 2022 to investigate the association between pre-PNI (i.e., low vs. high) and PO-PNI as well as the correlation between pre-PNI and other postoperative prognostic indices. Overall, 13 observational studies, including 9185 patients, were eligible for analysis. A low PNI was related to increased risks of PO-AKI [odd ratio (OR) = 1.65, p = 0.001, 3811 patients], postoperative infection (OR = 2.1, p < 0.00001, 2291 patients), and mortality (OR = 1.93, p < 0.0001, 2159 patients). Albeit statistically nonsignificant, a trend was noted, linking a low PNI to higher risks of postoperative bleeding (OR = 2.5, p = 0.12, 1157 patients) and stroke (OR = 1.62, p = 0.07, 2036 patients). Pooled results revealed a prolonged intensive care unit (ICU) stay in patients with low PNIs compared to those with high PNIs (MD: 0.98 days, p = 0.02, 2209 patients) without a difference in hospital stay between the two groups (MD: 1.58 days, p = 0.35, 2249 patients). This meta-analysis demonstrated an inverse correlation between PNI and the risks of PO-AKI, postoperative infection, and mortality, as well as the length of ICU stay, which warrants further investigations for verification.