Patient-centred measurement of recovery from day-case surgery using wrist worn accelerometers: a pilot and feasibility study

Treatment effect analysis of the Frailty Care Bundle (FCB) in a cohort of patients in acute care settings

PURPOSE

The aim of this study is to explore the feasibility of using machine learning approaches to objectively differentiate the mobilization patterns, measured via accelerometer sensors, of patients pre- and post-intervention.

METHODS

The intervention tested the implementation of a Frailty Care Bundle to improve mobilization, nutrition and cognition in older orthopedic patients. The study recruited 120 participants, a sub-group analysis was undertaken on 113 patients with accelerometer data (57 pre-intervention and 56 post-intervention), the median age was 78 years and the majority were female. Physical activity data from an ankle-worn accelerometer (StepWatch 4) was collected for each patient during their hospital stay. These data contained daily aggregated gait variables. Data preprocessing included the standardization of step counts and feature computation. Subsequently, a binary classification model was trained. A systematic hyperparameter optimization approach was applied, and feature selection was performed. Two classifier models, logistic regression and Random Forest, were investigated and Shapley values were used to explain model predictions.

RESULTS

The Random Forest classifier demonstrated an average balanced accuracy of 82.3% (± 1.7%) during training and 74.7% (± 8.2%) for the test set. In comparison, the logistic regression classifier achieved a training accuracy of 79.7% (± 1.9%) and a test accuracy of 77.6% (± 5.5%). The logistic regression model demonstrated less overfitting compared to the Random Forest model and better performance on the hold-out test set. Stride length was consistently chosen as a key feature in all iterations for both models, along with features related to stride velocity, gait speed, and Lyapunov exponent, indicating their significance in the classification.

CONCLUSION

The best performing classifier was able to distinguish between patients pre- and post-intervention with greater than 75% accuracy. The intervention showed a correlation with higher gait speed and reduced stride length. However, the question of whether these alterations are part of an adaptive process that leads to improved outcomes over time remains.

Ambulatory anesthesia and discharge: an update around guidelines and trends

PURPOSE OF REVIEW

Provide an oversight of recent changes in same-day discharge (SDD) of patient following surgery/anesthesia.

RECENT FINDINGS

Enhanced recovery after surgery pathways in combination with less invasive surgical techniques have dramatically changed perioperative care. Preparing and optimizing patients preoperatively, minimizing surgical trauma, using fast-acting anesthetics as well as multimodal opioid-sparing analgesia regime and liberal prophylaxis against postoperative nausea and vomiting are basic cornerstones. The scope being to maintain physiology and minimize the impact on homeostasis and subsequently hasten and improve recovery.

SUMMARY

The increasing adoption of enhanced protocols, including the entire perioperative care bundle, in combination with increased use of minimally invasive surgical techniques have shortened hospital stay. More intermediate procedures are today transferred to ambulatory pathways; SDD or overnight stay only. The traditional scores for assessing discharge eligibility are however still valid. Stable vital signs, awake and oriented, able to ambulate with acceptable pain, and postoperative nausea and vomiting are always needed. Drinking and voiding must be acknowledged but mandatory. Escort and someone at home the first night following surgery are strongly recommended. Explicit information around postoperative care and how to contact healthcare in case of need, as well as a follow-up call day after surgery, are likewise of importance. Mobile apps and remote monitoring are techniques increasingly used to improve postoperative follow-up.