Comprehensive Geriatric Assessment of Older and Oldest-Old Patients in the Perioperative Period. Russian Gerontology Research and Clinical Centre Experience
Bibliographic record
Abstract
With the aging population, the significance of preoperative diagnostics and optimizing the treatment of surgical patients with frailty syndrome is gaining momentum. For such patients a comprehensive geriatric assessment (CGA) is carried out to clarify the severity of frailty and the individual characteristics of the geriatric status [1]. The results of this assessment are used to stratify the risk in the postoperative period and to determine targeted interventions for the correction of geriatric syndromes [2]. The introduction of new geriatric technologies during hip and knee replacement in weakened older patients needs scientific justification and confirmation of effectiveness. Objective: to test the method of complex geriatric management of older and oldest-old patients before and after surgical interventions in the provision of planned inpatient orthopedic care (knee and hip arthroplasty). Materials and methods: the study involved two groups of older and oldest-old patients with frailty: 50 patients, average age 69.2 ± 6.0 years [60 to 87 years] with gonarthrosis and 50 patients, average age 67.6 ± 5.5 years [60 to 81 years] with coxarthrosis. At the prehospital stage, patients were diagnosed with frailty, in accordance with the clinical recommendations of «Senile asthenia» [3]. Upon admission to surgical treatment, a CGA was performed, including indicators of basic (Barthel Activities of daily living Index, Barthel scale [4]) and instrumental activity (The Instrumental Activities of Daily Living Scale, IADL scale [5]), nutrition assessment (Mini Nutritional assessment, MNA scale [6]), cognitive functions (The Montreal Cognitive Assessment, MOCA test [7]), depression (Geriatric Depression Scale, GDS-15 scale [8]), as well as quality of life (A Visual Analogue Scale, EQ-VAS scale [9]), multimorbidity and polypragmasia. An individual plan of perioperative management was drawn up. Results. A comparative analysis demonstrated statistically significant improvements in functional status (based on the Barthel scale), cognitive status (based on the MOCA test), nutritional status (based on the MNA scale) and quality of life (based on the EQ-VAS scale) 12 months after surgical intervention in groups of patients after knee and hip replacement. In the group of patients after hip replacement, there was also an improvement in the quality of life of patients 12 months after surgery. The assessment and dynamics of indicators in functional and cognitive status within the control group were not carried out, which makes it difficult to compare the results. However, there was a reduction in hospital stay for patients using geriatric approaches compared with previously used surgical care in the control group. Conclusion: the management of patients with frailty in the perioperative period with the use of CGA allows for preventive measures aimed at maintaining functional, psycho-emotional status. Individual characteristics of the state of psychoemotional and functional status in older and oldest-old patients may not be considered during the traditional preoperative risk stratification and increase the risks of adverse outcomes of surgical treatment, duration of hospital staying and repeated hospitalizations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".