| Literature DB >> 31190770 |
Maisha M Khan1,2, Krista L Lanctôt1,2,3, Stephen E Fremes4, Harindra C Wijeysundera4, Sam Radhakrishnan4, Damien Gallagher3, Dov Gandell5, Megan C Brenkel1, Elias L Hazan1, Natalia G Docteur1, Nathan Herrmann1,3.
Abstract
Background: Current surgical risk assessment tools fall short of appreciating geriatric risk factors including cognitive deficits, depressive, and frailty symptoms that may worsen outcomes post-transcatheter aortic valve implantation (TAVI). This study hypothesized that a screening tool, SMARTIE, would improve detection of these risks pre-TAVI, and thus be predictive of postoperative delirium (POD) and 30-day mortality post-TAVI. Design: Prospective observational cohort study, using a historical cohort for comparison. Participants: A total of 234 patients (age: 82.2±6.7 years, 59.4% male) were included. Half were screened using SMARTIE.Entities:
Keywords: TAVI; cognition; depression; frailty
Mesh:
Year: 2019 PMID: 31190770 PMCID: PMC6512610 DOI: 10.2147/CIA.S201615
Source DB: PubMed Journal: Clin Interv Aging ISSN: 1176-9092 Impact factor: 4.458
Baseline characteristics and outcomes in patients before and after the SMARTIE screen was implemented
| Pre-SMARTIE (n=117) | SMARTIE (n=117) | |||
|---|---|---|---|---|
| Age, mean±SD | 81.2±7.4 | 83.3±5.7 | −2.45 | 0.015* |
| Gender (Male), n(%) | 68 (58.1) | 71 (60.7) | 0.16 | 0.69 |
| Screening outcomes | ||||
| Cognitive deficits, n(%) | 19 (16.2) | 42 (35.9) | 11.73 | 0.001* |
| Depressive symptoms, n(%) | 5 (4.3) | 18 (15.4) | 8.15 | 0.004* |
| Frailty symptoms, n(%) | 6 (5.1) | 17 (14.5) | 5.73 | 0.017* |
| TAVI characteristics | ||||
| General anesthesia, n(%) ǂ | 116 (99.1) | 27 (23.1) | 142.4 | <0.001* |
| TAVI urgency, n(%) ǂǂ | 21 (17.9) | 12 (10.3) | 2.86 | 0.09 |
| Procedural outcomes | ||||
| Postoperative delirium, n(%) | 16 (13.7) | 7 (6.0) | 3.91 | 0.048* |
| Stroke/transient ischemic attack, n(%) | 4 (3.4) | 7 (6.0) | 0.86 | 0.35 |
| Procedural complications, n(%) | 22 (18.8) | 24 (20.5) | 0.11 | 0.74 |
| Hospital length of stay, mean±SD | 11.5±23.7 | 5.4±6.4 | 2.67 | 0.008* |
| 30-day mortality, n(%) | 9 (7.7) | 4 (3.4) | 2.04 | 0.15 |
Notes: ǂGeneral anesthesia compared to the use of local anesthesia with conscious sedation. Urgent TAVI (including emergency and salvage surgery) compared the pre-planned procedure. *p significance: p<0.05.
Abbreviation: TAVI, transcatheter aortic valve implantation.
Predictors of postoperative delirium (POD)
| Standard error | Wald | Odds | 95% CI for Odds ratio | ||||
|---|---|---|---|---|---|---|---|
| Cognitive deficits | 2.13 | 0.54 | 15.51 | 1.00 | <0.01* | 8.44 | 2.92–24.38 |
| Depressive symptoms | −1.74 | 1.25 | 1.93 | 1.00 | 0.17 | 0.18 | 0.02–2.05 |
| Frailty symptoms | 1.47 | 0.76 | 3.73 | 1.00 | 0.05 | 4.35 | 0.98–19.31 |
| Age | 0.09 | 0.05 | 3.45 | 1.00 | 0.06 | 1.09 | 1.00–1.19 |
| General anesthesiaǂǂ | 2.91 | 0.83 | 12.39 | 1.00 | <0.01* | 18.37 | 3.63–92.89 |
| Constant | −12.61 | 4.09 | 9.50 | 1.00 | <0.01 | 0.00 |
Notes: ǂǂCompared to local anesthesia under conscious sedation. *p significance, p<0.05. Without SMARTIE: The model (χ2(5) =39.2, p<0.001) explained 33.3% (Nagelkerke R2) of the variance in predicting POD correctly classifying 91.1% of POD cases. The Hosmer & Lemeshow test of the goodness of fit suggested the model was a good fit to the data (p=0.91).
Predictors of 30-day mortality rate
| Standard error | Wald | Odds | 95% CI for Odds ratio | ||||
|---|---|---|---|---|---|---|---|
| Cognitive deficits | 1.40 | 0.63 | 4.91 | 1.00 | 0.03* | 4.06 | 1.18–14.04 |
| Depressive symptoms | −18.82 | 7,720.98 | 0.00 | 1.00 | 1.00 | 0.00 | 0.00 |
| Frailty symptoms | 1.35 | 0.78 | 2.96 | 1.00 | 0.09 | 3.84 | 0.83–17.76 |
| Age | 0.01 | 0.05 | 0.09 | 1.00 | 0.77 | 1.01 | 0.92–1.12 |
| General anesthesiaǂǂ | 1.19 | 0.72 | 2.73 | 1.00 | 0.10 | 3.30 | 0.80–13.57 |
| Constant | −5.43 | 4.14 | 1.72 | 1.00 | 0.19 | 0.00 |
Notes: ǂǂ Compared to local anesthesia under conscious sedation. *p significance, p<0.05. Without SMARTIE: The model (χ2(5) =13.3, p=0.02), explained 15.9% (Nagelkerke R2) of the variance in predicting mortality, correctly classifying 94.4% of cases. It was a good fit to the data (p=0.31) on the Hosmer & Lemeshow test of the goodness of fit.