Staartjes, Victor E.

BACKGROUND AND OBJECTIVES: Preventive treatment of unruptured intracranial aneurysms (UIAs) requires assessment of treatment risks vs expected benefit. Although established scores exist to estimate rupture and growth risk, currently, no externally validated tools exist to estimate the risks of microsurgical treatment of UIAs. Clinical prediction models based on machine learning enable generation of personalized risk estimates for each individual patient based on their specific patient and aneurysm characteristics. METHODS: Using data from 20 international centers from the prediction of adverse events after microsurgery for intracranial unruptured aneurysms study on patients treated microsurgically for UIAs, we developed and externally validated clinical prediction models for 3 outcomes measured at hospital discharge: poor neurological outcome (modified Rankin Score ≥3), new sensorimotor neurological deficits, and all-cause adverse events (Clavien-Dindo Grade ≥1). RESULTS: A total of 3705 patients were included. Data from 13 centers (2881, 78%) were used for model development. Fully trained models were evaluated on 824 patients (22%) from 7 additional centers. Average age was 56 ± 12 years, and 1049 (28%) were male. At discharge, poor neurological outcome was seen in 514 patients (14%). New sensorimotor deficits were observed in 534 patients (14%), and 894 patients (24%) experienced adverse events until discharge. At external validation, prediction of poor neurological outcome was achieved with good calibration and an area under the curve (AUC) = 0.70 (95% CI: 0.63-0.75). Similarly, new neurological deficits were predicted with good calibration and with an AUC = 0.69 (95% CI: 0.63-0.74). Prediction of all-cause adverse events only achieved an AUC = 0.59 (95% CI: 0.55-0.64) with fair calibration. The prediction model was integrated into a web application accessible at https://neurosurgery.shinyapps.io/PRAEMIUM/. CONCLUSION: The developed models for prediction of poor neurological outcome and new sensorimotor neurological deficits at discharge exhibit good calibration and fair discrimination based on a multinational external validation, indicating that the predicted probabilities correspond well to real-world risks and may thus be clinically useful in more objectively estimating the risk of microsurgical treatment.

OBJECTIVE Objective values on procedural risk are essential to facilitate informed consent and optimize clinical decision-making in patients with unruptured intracranial aneurysms (UIAs). While robust heuristics, such as the PHASES (population, hypertension, age, size of aneurysm, earlier subarachnoid hemorrhage, and site of aneurysm) score, are established for predicting rupture risk, contemporary and granular benchmarks for procedural safety remain scarce. The multinational Prediction of Adverse Events After Microsurgery for Intracranial Unruptured Aneurysms (PRAEMIUM) study aims to comprehensively characterize contemporary adverse event rates following microsurgical treatment at high-volume expert centers, stratified by aneurysm location, morphology, and complexity factors to better inform individual risk/benefit analyses. METHODS A cohort study among 20 participating expert centers from 9 countries was established. Patients treated microsurgically for UIAs were included. The authors describe the epidemiology of treated patients and UIAs and a comprehensive adverse event profile using 3 outcomes measured at hospital discharge: 1) poor neurological outcome (modified Rankin Scale score ≥ 3), 2) new sensorimotor neurological deficits, and 3) all-cause adverse events (Clavien-Dindo grade ≥ 1). Subgroup reports were given for aneurysm location, morphology, and complexity factors (prior aneurysm treatment, calcifications, complex angioanatomy involving critical branch vessels or perforators, and thrombosis). The authors purposely chose discharge as the time point to capture early postoperative risks and complications in patients with asymptomatic UIAs, for whom preserving neurological function is paramount. RESULTS The cohort included 3705 patients (mean age 56 [SD 12] years, 28% male). Overall, at discharge 13.9% of patients (95% CI 12.8%–15.0%) had poor neurological functional outcomes, 14.4% (95% CI 13.3%–15.5%) had new sensorimotor deficits, and 24.1% (95% CI 22.8%–25.5%) experienced all-cause adverse events. Poor neurological outcomes ranged from 8.5% (M1 aneurysms) to 37.4% (posterior circulation aneurysms), neurological deficits from 9.3% (distal anterior cerebral artery [ACA] aneurysms) to 34.2% (posterior circulation aneurysms), and all-cause adverse events from 21.2% (distal ACA aneurysms) to 31.3% (posterior circulation aneurysms). Dissecting and fusiform aneurysms showed notably high rates of poor neurological outcomes (22.0%–33.3%), new deficits (25.4%–26.7%), and adverse events (26.7%–37.0%). Complexity factors significantly influenced outcomes, with prior treatment (22.9%, 19.7%, and 30.1%), calcification (16.3%, 18.1%, and 30.5%), complex angioanatomy (13.1%, 15.9%, and 26.9%), and thrombosis (19.6%, 23.9%, and 39.6%) notably increasing the risks for poor neurological outcomes, deficits, and adverse events, respectively. CONCLUSIONS This large international cohort provides contemporary benchmarks for microsurgical treatment of UIAs, emphasizing variability in outcomes based on aneurysm location, morphology, and complexity. The presented granular and quotable adverse event rates support informed patient counseling and individualized risk/benefit assessments in comparable high-volume centers.

OBJECTIVE The landscape of healthcare policies has undergone significant reforms, with a notable shift toward a patient-centered basis. This change has prioritized the use of metrics reflecting subjective patient-reported outcome measures (PROMs). However, these metrics are often limited, especially in terms of determining clinically relevant changes over time. The concept of the minimal clinically important difference (MCID) has been introduced to address this limitation. In this study, the authors aimed to assess the predictive capability of relative change and its corresponding threshold value, the minimal clinically important relative change (MCIRC), as an alternative to the absolute difference and MCID. METHODS Prospectively collected data from 2006 to 2021 were obtained from the Swedish Spine Registry (Swespine). PROMs included the numeric rating scale (NRS) neck and arm pain scores, the EQ-5D index and EQ visual analog scale (VAS), and the Neck Disability Index (NDI). Anchor-based methods were used to determine MCID and MCIRC. Absolute differences and relative changes were compared in terms of predictive power using the area under the receiver operating characteristic curve (AUC). RESULTS A total of 5323 patients were included. The chosen MCID values were −3 for NRS neck pain, −3 for NRS arm pain, 0.08 for EQ-5D index, 13 for EQ VAS, and −30 for NDI scores. The chosen MCIRC values were −40% for NRS neck pain, −50% for arm pain, 323% for EQ-5D index, 55% for EQ VAS, and −33% for NDI scores. Relative change was superior for NRS neck and arm pain scores and NDI, while absolute difference was superior for EQ-5D and EQ VAS scores. CONCLUSIONS Relative change and its corresponding MCIRC were found to be more appropriate as a surrogate of subjective satisfaction when studying the NRS and NDI scores, whereas absolute difference and MCID was more appropriate when addressing EQ-5D index and EQ VAS scores.

BACKGROUND AND OBJECTIVES: Healthcare policies have seen significant reforms, with a marked transition toward a patient-centered approach. This shift emphasizes the use of subjective patient-reported outcome measures as key metrics. However, these measures often face limitations, particularly in identifying clinically meaningful changes over time. To address this challenge, the concept of the minimal clinically important difference (MCID) was introduced. This study aims to evaluate the predictive effectiveness of relative change and its associated threshold, the minimal clinically important relative change (MCIRC), as a potential alternative to absolute differences and the MCID. METHODS: Data prospectively collected between 2006 and 2021 from the Swedish Spine Registry (Swespine) were analyzed. Patient-reported outcome measures included the Numeric Rating Scale (NRS) for neck and arm pain, the EQ5D index, EQ VAS, and the Neck Disability Index (NDI). Anchor-based methods were used to calculate the MCID and MCIRC. The predictive performance of absolute differences and relative changes was compared using the area under the receiver operating characteristic curve. RESULTS: 1756 patients were included. The selected MCID values were −3 for NRS neck pain intensity, −2 for arm pain intensity, 0.09 for the EQ5D index, 7 for EQ VAS, and −12 for NDI scores. For MCIRC, the chosen values were −47% for NRS neck pain intensity, −40% for arm pain intensity, 386% for the EQ5D index, 52% for EQ VAS, and −32% for NDI scores. On area under the ROC curve, relative change was superior for NRS neck and arm pain scores and NDI, while absolute difference was superior for EQ5D and EQ VAS scores. CONCLUSION: Relative change, along with its associated minimal clinically important value (MCIRC), proved to be a more suitable indicator of subjective satisfaction for NRS and NDI scores. By contrast, absolute differences and the MCID were better suited for evaluating the EQ5D index and EQ VAS scores.