Table 1 Characteristics of the included studies
Author year | Country | Study design | Male (%) | Age (mean/SD) | Sample size | Type of IBD | Follow-up | Participants | Definition of frailty/frailty Criteria | Frailty assessment (cut-off) | Prevalence of frailty | Outcome | Quality score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Alexander 2020 [25] | USA | Retrospective cohort study | 42.89 | 53.35 ± 19.34 | 47,402 | CD and UC | 10 months | The Nationwide Readmissions Database (NRD) 2013 | The Hospital Frailty Risk Score ICD-9-CM | Medium frailty risk (score 5–15) and high frailty risk (score > 15) | 15,507 (32.71%) | Mortality, readmission, hospitalization, and IBD-related surgery | 9 |
Bharati Kochar 2021 [26] | USA | Retrospective cohort study | 46.91 | 34.37 ± 17.04 | 1210 | CD and UC | 1 year | An electronic health record (EHR)-based cohort of patients with CD or UC | A validated claims-based frailty index (CFI) | Normalized CFI frailty score ≥ 3 | 189 (15.6%) | NA | 7 |
Bharati Kochar 2020 [27] | USA | Prospective cohort study | 47 | 46.82 ± 21.58 | 11,036 | CD and UC | 8.61 ± 8.48 years | Used a previously well-described cohort of 11,001 patients with IBD | International Classification of Disease ICD-10 codes | The presence ≥ 1 ICD code | 675 (6%) | NA | 9 |
Bharati Kochar 2020 [28] | Boston | Retrospective cohort study | 3975 | CD and UC | A cohort study of 11,001 patients with IBD from Partners Healthcare system | Frailty Risk Score, a International Classification of Disease codes (ICD-9,10 codes) | Presence of at least one frailty related ICD-9 code in the 2 y prior to the first electronic prescription | NA | 9 | ||||
46 | 36.95 ± 18.58 | 1299 | 8.59 ± 7.47 years | Anti-TNF Study Population | 68 (5.23%) | ||||||||
48 | 39.58 ± 20.24 | 2676 | 8.94 ± 7.59 years | Immunomodulator (IMM) Study population | 212 (7.92%) | ||||||||
Adam S.Faye 2021 [33] | USA | Retrospective cohort study | 43.21 | all age | 1,405,529 | CD and UC | 30 days | Weighted Nationwide Readmission Database(NRD) | A validated ICD-9-CM codes | Patients with any of the aforementioned ICD-9-CM codes were considered frail | 152,974 (10.9%) | NA | 8 |
Siddharth Singh 2020 [34] | USA | Retrospective cohort study | 50.50 | 41.57 ± 15.37 | 5987 | CD and UC | 14.45 ± 13.32 years | An administrative claims database | The Hospital Frailty Risk Score (ICD-9-CM; ICD-10-CM) | Frailty risk score 5 or higher | 2350 (39.3%) | Serious and/or opportunistic infections† | 8 |
Joshua 2021 [35] | Baltimore | Retrospective cohort study | 46.76 | > 18 | 9023 | CD | 30 days | The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) | Simplified Frailty Index (SFI) score | A score of 0 is the least frail, whereas 5 is the most frail | 1610 (17.8%)‡ | NA | 8 |
Edwin telemi 2018 [53] | Arizona | Retrospective cohort study | 54.30 | 46 ± 19.30 | 943 | UC | 30 days | The National Surgical Quality and Improvement Program (NSQIP) cross-institutional database | Modified frailty index (MFI) | MFI > 0 | 305 (32.34%) | NA | 7 |
Bharati Kochar 2022 [54] | Sweden | Prospective cohort study | 48 | 71 ± 8 | 10,590 | CD and UC | 5 ± 3 years | Nationwide Patient Register (NPR) Database | The Hospital Frailty Risk Score (HFRS) | Low frailty risk(score 0–5) and high frailty risk (score > 5) | 1264(12%) | Mortality and hospitalization | 8 |