Comparison of the frailty index and frailty phenotype and their associations with postoperative delirium incidence and severity

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Stacie Deiner MS MD, LeRoy Garth Professor and Vice Chair for Research, Department of Anesthesiology, Dartmouth University Medical School, Hanover, NH

Studies show that preoperative frailty is associated with up to six times the odds of postoperative delirium, depending on which frailty measurement tool is used.1,2 There are two distinct paradigms of frailty measurement, Frailty Index and the Frailty Phenotype. The former is based on a multidimensional accumulation of unspecified deficits and the latter focuses on a distinct phenotype characterized by five specific physical performance measures. Some of the reported variability in the association between frailty and delirium may be explained by whether the frailty measure includes cognitive function; the best established and strongest predictor of delirium.3

Implementation of preoperative cognitive screening has been limited, requires staff training, and is a sensitive topic for patients.4,5 Frailty screening could be an easier and more acceptable alternative strategy for delirium risk stratification. However, with respect to postoperative delirium, it is unclear whether frailty adds value beyond standard preoperative risk stratification variables (such as comorbidity) and presurgical cognitive status.6,7 Therefore, we sought to determine whether one frailty screening method was more strongly associated with postoperative delirium than the other. Our hypothesis was that the Frailty Phenotype would be more strongly associated with delirium since it includes performance measures.

Study Design

This was a retrospective cohort study of the Successful Aging after Elective Surgery (SAGES) I study (n=560).8 Participants were at least 70 years of age, spoke English, and were scheduled for elective surgery at one of two Harvard affiliated hospitals in Boston, MA. All patients were hospitalized for two days or longer. Patients were excluded if they had a history of alcohol abuse, schizophrenia, legal blindness, uncorrected significant hearing impairment, current delirium or dementia, or terminal illness diagnoses. Only patients who completed preoperative Frailty Index and Frailty Phenotype evaluations were included (n=505).

The primary outcome was postoperative delirium incidence and severity. Delirium was assessed once daily utilizing the Confusion Assessment Method (CAM), administration of a brief cognitive assessment, delirium symptom probes from the Delirium Symptom Interview, and supplemented by information provided by family members and nursing staff.9,10 The medical record was also reviewed in detail for documentation of delirium and its related symptoms, and each instance was adjudicated by a validated chart review method.11,12 Delirium was defined as present if the CAM or chart criteria was positive on one or more days during the patient’s hospitalization post-surgery.12 Delirium feature severity was measured using the CAM-Severity (CAM-S) long form and reported as the sum of the daily delirium feature severity scores across all postoperative hospital days (sum CAM-S ).13

Results

On average, patients were 76.7 years old (standard deviation 5.22), 58.8% women. For the Frailty Index, the incidence of delirium was 14% in robust, 17% in prefrail, and 31% in frail patients (p<.001). For the Frailty Phenotype, delirium incidence was 13% in robust, 21% in prefrail, and 27% in frail patients (p=.016). Frailty Index, but not Phenotype, was independently associated with delirium after adjustment for comorbidities (relative risk [RR] 2.13, 95% confidence interval [CI] 1.23-3.70; RR 1.61, 95% CI 0.77-3.37, respectively). Both frailty measures were associated with the sum CAM-S delirium severity measure. After further adjustment for preoperative cognition using the Modified Mini-Mental Status score, the Frailty Index, but not the Frailty Phenotype, was associated with delirium incidence; neither the Index nor the Phenotype was associated with delirium severity.

Conclusions and Future Directions

Frail patients, as identified by either the Frailty Index or Phenotype, had twice the risk of developing postoperative delirium compared to robust patients. However, the Frailty Index was more strongly associated with delirium incidence than the Frailty Phenotype, and the Index remained significantly associated with delirium after adjustment for preoperative cognition, the strongest and most consistent risk factor for postoperative delirium.

A likely reason for this finding is that the Index includes more factors than the Phenotype, and likely better captures the multiple predisposing factors contributing to delirium risk. We conclude that measuring frailty status provides valuable information for older adults undergoing major surgery. The Frailty Index, which can be automatically populated by the electronic health record and requires no performance testing, might be more acceptable for both patients and clinicians.14

It is also notable that only 1/3 of patients classified as frail developed delirium. More studies are needed to understand which older adults classified as frail before major surgery are truly at risk for poor surgical outcomes and a persistence or worsening of their frailty status compared to other “frail” older adults who may do well with the surgery, improve functionally, and become less frail.

References

  1. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. The journals of gerontology Series A, Biological sciences and medical sciences. 2001;56(3). doi:10.1093/GERONA/56.3.M146
  2. Rockwood K, Mitnitski A. Frailty in relation to the accumulation of deficits. Journals of Gerontology – Series A Biological Sciences and Medical Sciences. 2007;62(7):722-727. doi:10.1093/gerona/62.7.722
  3. Marcantonio ER. Delirium in Hospitalized Older Adults. New England Journal of Medicine. 2017;377(15):1456-1466. doi:10.1056/NEJMcp1605501
  4. Deiner S, Fleisher L, Leung JM, Peden C, Miller T, Newman M. Adherence to recommended practices for perioperative anesthesia care for older adults among US anesthesiologists: results from the ASA Committee on Geriatric Anesthesia-Perioperative Brain Health Initiative ASA member survey. Perioperative Medicine. 2020;9:6. doi: 10.1186/s13741-020-0136-9
  5. Sherman JB, Chatterjee A, Urman RD, et al. Implementation of Routine Cognitive Screening in the Preoperative Assessment Clinic. A&A practice. 2019;12(4):125-127. doi:10.1213/XAA.0000000000000891
  6. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383. doi: 10.1016/0021-9681(87)90171-8
  7. Culley DJ, Flaherty D, Fahey MC, et al. Poor Performance on a Preoperative Cognitive Screening Test Predicts Postoperative Complications in Older Orthopedic Surgical Patients. Anesthesiology. 2017;127(5):765-774. doi:10.1097/ALN.0000000000001859
  8. Deiner SG, Marcantonio ER, Trivedi S, et al. Comparison of the frailty index and frailty phenotype and their associations with postoperative delirium incidence and severity. Journal of the American Geriatrics Society. Published online 2023;n/a(n/a). doi:10.1111/jgs.18677
  9. Schmitt EM, Marcantonio ER, Alsop DC, et al. Novel Risk Markers and Long-Term Outcomes of Delirium: The Successful Aging after Elective Surgery (SAGES) Study Design and Methods. Journal of the American Medical Directors Association. 2012;13(9). doi:10.1016/j.jamda.2012.08.004
  10. Inouye SK, van Dyck CH, Alessi CA, Balkin S, Siegal AP, Horwitz RI. Clarifying confusion: the confusion assessment method. A new method for detection of delirium. Annals of Internal Medicine. 1990;113(12):941-948. doi: 10.7326/0003-4819-113-12-941
  11. Inouye SK, Leo-Summers L, Zhang Y, Bogardus ST, Leslie DL, Agostini JV. A chart-based method for identification of delirium: Validation compared with interviewer ratings using the confusion assessment method. Journal of the American Geriatrics Society. 2005;53(2):312-318. doi:10.1111/j.1532-5415.2005.53120.x
  12. Saczynski JS, Kosar CM, Xu G, et al. A tale of two methods: Chart and interview methods for identifying delirium. Journal of the American Geriatrics Society. 2014;62(3):518-524. doi:10.1111/jgs.12684
  13. Inouye SK, Kosar CM, Tommet D, et al. The CAM-S: development and validation of a new scoring system for delirium severity in 2 cohorts. Annals of internal medicine. 2014;160(8):526-533. doi:10.7326/M13-1927
  14. Callahan KE, Clark CJ, Edwards AF, et al. Automated Frailty Screening At-Scale for Pre-Operative Risk Stratification Using the Electronic Frailty Index. J Am Geriatr Soc. 2021;69(5):1357-1362. doi:10.1111/jgs.17027

Suggested Citation

Deiner, Stacie. Comparison of the frailty index and frailty phenotype and their associations with postoperative delirium incidence and severity; April, 2024, Available at: https://deliriumnetwork.org/comparison-of-the-frailty-index-and-frailty-phenotype-and-their-associations-with-postoperative-delirium-incidence-and-severity/ (accessed today’s date)

Posted in Delirium Research.

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