Background: To identify the incidence of, risk factors for, and outcomes associated with postoperative delirium (POD) in older adult patients who underwent noncardiac surgery. Methods: This prospective study recruited patients aged ≥ 60 years who were scheduled to undergo noncardiac surgery at Siriraj Hospital (Bangkok, Thailand). Functional and cognitive statuses were assessed preoperatively using Barthel Index (BI) and the modified Informant Questionnaire on Cognitive Decline in the Elderly, respectively. POD was diagnosed based on the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition criteria. Incidence of POD was reported. Univariate and multivariate analyses were used to identify risk factors for POD. Results: Of the 249 included patients, 29 (11.6%) developed POD. Most patients (61.3%) developed delirium on postoperative day 1. Univariate analysis showed age ≥ 75 years, BI score ≤ 70, pre-existing dementia, preoperative use of opioid or benzodiazepine, preoperative infection, and hematocrit < 30% to be significantly associated with POD. Multivariate logistic analysis revealed pre-existing dementia (adjusted risk ratio [RR]: 3.95, 95% confidence interval [CI]: 1.91-8.17; p < 0.001) and age ≥ 75 years (adjusted RR: 2.54, 95% CI: 1.11-5.80; p = 0.027) to be independent risk factors for POD. Median length of hospital stay was 10 (range: 3-36) days for patients with POD versus 6 (range: 2-76) days for those without delirium (p < 0.001). Conclusions: POD remains a common surgical complication, with an incidence of 11.6%. Patients with pre-existing dementia and age ≥ 75 years are the most vulnerable high-risk group. A multidisciplinary team consisting of anesthesiologists and geriatricians should implement perioperative care to prevent and manage POD.

Background Several methods are available for identifying frailty, but limited tools have been validated in Thai context. Our objective was to evaluate the validity and reliability of the Thai version of the Simple Frailty Questionnaire (T- FRAIL) compared to the Thai Frailty Index (TFI) and to explore modifications to improve its diagnostic properties. Methods The T-FRAIL was translated with permission using a standardized protocol, that included forward and back-translation. Content validity analysis was performed using input from 5 geriatricians. Test-retest reliability, concurrent validity, diagnostic properties, and options to increase the sensitivity of the questionnaire were explored. A cross-sectional study for evaluation validity and reliability was carried out among 3 hundred patients aged 60 or more undergoing elective surgery at a university hospital. Results The item content validity index (I-CVI) showed 1.0 for each questionnaire item. Test-retest reliability within a 7-day interval was done in 30 patients with a good intraclass correlation coefficient of 0.880. Compared with the TFI, the T-FRAIL yielded an excellent accuracy (area under the curve = 0.882). The identification of frailty using a score of 2 points or more provided the best Youden’s index at 63.1 with a sensitivity of 77.5% (95% CI 69.0–84.6) and a specificity of 85.6% (95% CI 79.6–90.3). A cutoff point of 1 out of 5 items for original T-FRAIL provided a sensitivity of 93.3% and a specificity of 61.1%. The modified T-FRAIL (T-FRAIL_M1), by reducing the “illnesses” criterion to 4 or more diseases, at a cutoff point at 1 had a sensitivity of 94.2% and a specificity of 57.8%. Another modified T-FRAIL (T-FRAIL_M2), by combining three components, at a cutoff point at 1 yielded a sensitivity of 85.8% and a specificity of 80.6%. Conclusion The T-FRAIL and its modification demonstrated satisfactory validity and reliability to identify frailty in elderly patients. The cutoff score of 1 point from 5 items from the original version of T-FRAIL and T-FRAIL_M1 provides a highly sensitive screening tool. T-FRAIL_M1 with a cutoff point of 2 and T-FRAIL_M2 yields reasonable sensitivity and specificity for practical use.

Aim To evaluate the diagnostic performance of the Confusion Assessment Method for the intensive care unit (CAM‐ICU) among postoperative older patients in non‐ICU settings. Methods The CAM‐ICU was used by trained staff to prospectively evaluate postoperative patients for delirium. The patients were aged ≥60 years, were in general wards and had no critical illnesses. The assessments occurred for 7 consecutive days after surgery. The results were compared with delirium diagnoses obtained by geriatricians using Diagnostic and Statistical Manual of Mental Disorders 5th edition criteria as the reference standard. Results The sensitivity of delirium detection for the CAM‐ICU was 31.6% (95% confidence interval [CI] 12.6–56.6), while the specificity was 97.6% (95% CI 94.9–99.1), positive predictive value was 50.0% (95% CI 26.3–73.7) and negative predictive value was 95.0% (95% CI 93.3–96.3). Feature 4 (disorganized thinking) yielded the highest sensitivity (60%; 95% CI 14.7–94.7), whereas feature 2 (inattention) had low sensitivity (36.8%; 95% CI 16.3–61.6). Further analyses to explore the highest sensitive criteria showed that if CAM‐ICU diagnoses were made by the presence of any two out of feature 1 (acute change or fluctuation of cognition), feature 3 (altered level of consciousness) or feature 4, the sensitivity increased substantially to 80.0% (95% CI 28.4–99.5), with a reasonably high specificity of 81.8% (95% CI 48.2–97.7). Conclusions Modification of the flow of delirium diagnosis using the CAM‐ICU appears to offer a better sensitivity for detecting delirium in non‐ICU settings. Furthermore, changing feature 2 to evaluate patients’ attention levels over a longer period of time might yield a better diagnostic performance. Geriatr Gerontol Int 2019; 19: 762–767.