Neurosurgery 93:186–197, 2023
Transforaminal lumbar interbody fusion (TLIF) and posterolateral fusion (PLF) alone are two operations performed to treat degenerative lumbar spondylolisthesis. To date, it is unclear which operation leads to better outcomes.
OBJECTIVE: To compare TLIF vs PLF alone regarding long-term reoperation rates, complications, and patient-reported outcome measures (PROMs) in patients with degenerative grade 1 spondylolisthesis.
METHODS: A retrospective cohort study using prospectively collected data between October 2010 and May 2021 was undertaken. Inclusion criteria were patients aged 18 years or older with grade 1 degenerative spondylolisthesis undergoing elective, single-level, open posterior lumbar decompression and instrumented fusion with ≥1-year follow-up. The primary exposure was presence of TLIF vs PLF without interbody fusion. The primary outcome was reoperation. Secondary outcomes included complications, readmission, discharge disposition, return to work, and PROMs at 3 and 12 months postoperatively, including Numeric Rating Scale-Back/Leg and Oswestry Disability Index. Minimum clinically important difference of PROMs was set at 30% improvement from baseline.
RESULTS: Of 546 patients, 373 (68.3%) underwent TLIF and 173 underwent (31.7%) PLF. Median follow-up was 6.1 years (IQR = 3.6-9.0), with 339 (62.1%) >5-year follow-up. Multivariable logistic regression showed that patients undergoing TLIF had a lower odds of reoperation compared with PLF alone (odds ratio = 0.23, 95% CI = 0.54-0.99, P = .048). Among patients with >5-year follow-up, the same trend was seen (odds ratio = 0.15, 95% CI = 0.03-0.95, P = .045). No differences were observed in 90-day complications (P = .487) and readmission rates (P = .230) or minimum clinically important difference PROMs.
CONCLUSION: In a retrospective cohort study from a prospectively maintained registry, patients with grade 1 degenerative spondylolisthesis undergoing TLIF had signiﬁcantly lower long-term reoperation rates than those undergoing PLF.
J Neurosurg 139:94–105, 2023
Brainstem cavernous malformations (BSCMs) represent a unique subgroup of cavernous malformations with more hemorrhagic presentation and technical challenges. This study aimed to provide individualized assessment of the rehemorrhage clustering risk of BSCMs after the first symptomatic hemorrhage and to identify patients at higher risk of neurological deterioration after new hemorrhage, which would help in clinical decision-making.
METHODS A total of 123 consecutive BSCM patients with symptomatic hemorrhage were identified between 2015 and 2022, with untreated follow-up > 12 months or subsequent hemorrhage during the untreated follow-up. Nomograms were proposed to individualize the assessment of subsequent hemorrhage risk and neurological status (determined by the modified Rankin Scale [mRS] score) after future hemorrhage. The least absolute shrinkage and selector operation (LASSO) regression was used for feature screening. The calibration curve and concordance index (C-index) were used to assess the internal calibration and discrimination performance of the nomograms. Cross-validation was further performed to validate the accuracy of the nomograms.
RESULTS Prior hemorrhage times (adjusted OR [aOR] 6.78 per ictus increase) and Zabramski type I or V (OR 11.04) were associated with rehemorrhage within 1 year. A lower mRS score after previous hemorrhage (aOR 0.38 for a shift to a higher mRS score), Zabramski type I or V (OR 3.41), medulla or midbrain location (aOR 2.77), and multiple cerebral cavernous malformations (aOR 11.76) were associated with worsened neurological status at subsequent hemorrhage. The nomograms showed good accuracy and discrimination, with a C-index of 0.80 for predicting subsequent hemorrhage within 1 year and 0.71 for predicting neurological status after subsequent hemorrhage, which were maintained in cross-validation.
CONCLUSIONS An individualized approach to risk and severity assessment of BSCM rehemorrhage was feasible with clinical and imaging features.
J Neurosurg 137:675–684, 2022
The probable stability of the lesion is critical in guiding treatment decisions in unruptured intracranial aneurysms (IAs). The authors aimed to develop multidimensional predictive models for the stability of unruptured IAs.
METHODS Patients with unruptured IAs in the anterior circulation were prospectively enrolled and regularly followed up. Clinical data were collected, IA morphological features were assessed, and adjacent hemodynamic features were quantified with patient-specific computational fluid dynamics modeling. Based on multivariate logistic regression analyses, nomograms incorporating these factors were developed in a primary cohort (patients enrolled between January 2017 and February 2018) to predict aneurysm rupture or growth within 2 years. The predictive accuracies of the nomograms were compared with the population, hypertension, age, size, earlier rupture, and site (PHASES) and earlier subarachnoid hemorrhage, location, age, population, size, and shape (ELAPSS) scores and validated in the validation cohort (patients enrolled between March and October 2018).
RESULTS Among 231 patients with 272 unruptured IAs in the primary cohort, hypertension, aneurysm location, irregular shape, size ratio, normalized wall shear stress average, and relative resident time were independently related to the 2-year stability of unruptured IAs. The nomogram including clinical, morphological, and hemodynamic features (C+M+H nomogram) had the highest predictive accuracy (c-statistic 0.94), followed by the nomogram including clinical and morphological features (C+M nomogram; c-statistic 0.89), PHASES score (c-statistic 0.68), and ELAPSS score (c-statistic 0.58). Similarly, the C+M+H nomogram had the highest predictive accuracy (c-statistic 0.94) in the validation cohort (85 patients with 97 unruptured IAs).
CONCLUSIONS Hemodynamics have predictive values for 2-year stability of unruptured IAs treated conservatively. Multidimensional nomograms have significantly higher predictive accuracies than conventional risk prediction scores.