Simultaneous Craniotomies for Multiple Intracranial Aneurysm Clippings-One-Stage Surgery with Multiple Craniotomies

Application of zone classification in multiple intracranial aneurysmal subarachnoid hemorrhage treatment strategies

Background

The options of surgical approach and treatment stage are two challenging treatment strategy issues with multiple intracranial aneurysmal subarachnoid hemorrhage (MIA-SAH).

Methods

We retrospectively analyzed data from patients with MIA-SAH who underwent surgery in our center between January 1, 2014 and September 1, 2022. To define "zone classification", the cranial cavity was divided into four zones by the planes of cerebral falx and tentorium cerebelli. Aneurysms isolated to one zone were defined as zone classification I; those crossing two zones were defined as zone classification II; those crossing three zones were defined as zone classification III; and those crossing four zones were defined as zone classification IV. General and aneurysmal-related characteristics of patients with different zone classifications were collected and compared between two surgical approaches. Multivariate logistic regression analysis was used to identify factors independently associated with multistage treatment options.

Results

A total of 226 patients with 523 aneurysms were included. The proportion of patients undergoing endovascular treatment increased with higher zone classification (I: 85.4%; II: 94.0%; III: 100.0%; IV: 100.0%). The proportion of patients receiving one-stage treatment decreased with higher zone classification (I: 60.2%; II: 33.6%; III: 0.0%; IV: 0.0%). Compared with patients undergoing microsurgical clipping, more patients undergoing endovascular treatment had zone classification II-IV (56.9% vs. 31.8%, p = 0.025). Zone classification II-IV (odds ratio [OR] = 3.821, 95% confidence interval [CI]: 2.041-7.154, p < 0.001), endovascular treatment (OR = 8.756, 95% CI: 2.589-29.609, p < 0.001), and size of all unruptured aneurysms <3 mm (OR = 4.531, 95% CI: 2.315-8.871, p < 0.001) were each independently associated with multistage treatment.

Conclusions

Zone classification provides a new idea in MIA-SAH treatment strategies, especially regarding surgical approach and treatment stage options.

Cerebral Angiography under Artificial Intelligence Algorithm in the Design of Nursing Cooperation Plan for Intracranial Aneurysm Patients in Craniotomy Clipping

This research was to investigate the value of indocyanine green angiography (ICGA) based on maximum interclass variance (Otsu) method in the nursing plan of intracranial aneurysm clipping (ICAC) for intracranial aneurysm patients. An Otsu algorithm was selected to optimize the original images with the optimal threshold. In addition, the algorithm was applied to ICGA images of 86 patients with intracranial aneurysms, who were randomly divided into an experimental group (using ICGA + ICAC+ perioperative nursing) and a control group (ICAC + conventional nursing), to observe the clinical indicators, treatment, complications, nursing satisfaction, and quality of life of patients in two groups. The results showed that the mean square error (MSE), structural similarity (SSIM), and shape error (SE) were 3.71, 0.84, and 0.47, respectively. The length of hospital stay in the experimental group (19.9 ± 3.5 days) was significantly shorter than that in the control group (23.2 ± 3.0 days), the rate of excellent treatment was significantly higher than that in the control group, and the incidence of complications was lower. WHOQOL-BREF scores of the two groups after nursing intervention were higher than before, and the score in the experimental group was higher than the control group. In addition, the nursing satisfaction was also significantly higher in the experimental group, and the difference was statistically significant (P < 0.05). In conclusion, ICGA based on the Otsu method could effectively evaluate the cerebrovascular morphology during craniotomy and ICAP and improve the surgical efficacy. Combined with perioperative nursing intervention, it could greatly reduce the incidence of postoperative complications, improve the treatment effect and quality of life, and enhance the long-term prognosis.

Model-Based Computational Analysis on the Effectiveness of Enhanced Recovery after Surgery in the Operating Room with Nursing

Objective

In order to better understand the relative surgical process, this work used a model-based computational analysis on the effectiveness of enhanced recovery after surgery (ERAS) in the operating room with nursing.

Methods

A total of 360 surgical patients in the First Affiliated Hospital, Sun Yat-sen University, from the period June 2020 to March 2021, were randomly divided into two groups, namely, observation group and control group, with 180 cases in each group. Routine nursing was used in the control group, while ERAS was implemented in the observation group from the point of view of four aspects, namely, preoperative visit, intraoperative cooperation, postoperative return visit, and psychological intervention.

Results

Postoperative complications, average hospital stay, nursing satisfaction, and postoperative quality of life in the observation group were significantly better than those in the control group (all p &lt; 0.05).

Conclusion

The application of ERAS for surgical patients can enhance team awareness, optimize the process of cooperation, reduce surgical complications and improve nursing quality, and prognosis, and it is worth popularizing in the operating room.