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Objective: Pituitary neuroendocrine tumours (PitNETs) are the second most common type of intracranial tumour. Several studies have explored the prognostic factors for PitNETs. However, prognostic factors for postoperative PitNET recurrence remain not fully understood. This study aimed to explore potential prognostic factors for PitNET recurrence, such as surrounding tissue invasion and the extent of surgical resection in patients with postoperative PitNETs., Methods: We included 106 patients who underwent PitNET surgery between 2013 and 2018, dividing them into two groups: those with recurrence and those without recurrence. Tumours were classified based on demographics, neuroradiological, and immunohistological characteristics. Univariate and multivariate analyses were used to determine factors predicting recurrence. Kaplan-Meier plots and log-rank tests were used to analyse each independent factor based on the cumulative 5-year recurrence rate., Results: During the 5-year follow-up period, 29.2% of the patients ( n  = 31) had disease recurrence. Univariate analysis showed that predictors of recurrence included cavernous and sphenoid sinus invasions, optic chiasm compression, larger tumour volume, giant adenoma >4 cm, and gross total resection (GTR). Multivariate analysis showed that lactotroph tumour type, sphenoid sinus invasion, and GTR were independent predictors. Kaplan-Meier analysis revealed significant differences in the 5-year recurrence rate among the three independent predictors, with significantly lower recurrence rate in patients with lactotroph tumours and GTR, and a significantly higher recurrence risk in patients with sphenoid sinus invasion., Conclusions: Lactotroph tumour type, sphenoid sinus invasion, and GTR are independent predictors of postoperative PitNET recurrence. This study provides insights into the factors affecting postoperative PitNET recurrence.

Background: The occurrence of postoperative complications within 30 days (PC1M) of a craniotomy for the removal of a primary malignant brain tumor has been associated with a poor prognosis. However, it is still unclear to early predict the occurrence of PC1M. This study aimed to identify the potential perioperative predictors of PC1M from its preoperative, intraoperative, and 24-h postoperative parameters., Methods: Patients who had undergone craniotomy for primary malignant brain tumor (World Health Organization grades III and IV) from January 2011 to December 2020 were enrolled from a databank of Kaohsiung Veterans General Hospital, Taiwan. The patients were classified into PC1M and nonPC1M groups. PC1M was defined according to the classification by Landriel et al. as any deviation from an uneventful 30-day postoperative course. In both groups, data regarding the baseline characteristics and perioperative parameters of the patients, including a new marker-kinetic estimated glomerular filtration rate, were collected. Logistic regression was used to analyze the predictability of the perioperative parameters., Results: The PC1M group included 41 of 95 patients. An American Society of Anesthesiologists score of > 2 (aOR, 3.17; 95% confidence interval [CI], 1.19-8.45; p = 0.021), longer anesthesia duration (aOR, 1.16; 95% CI, 0.69-0.88; p < 0.001), 24-h postoperative change in hematocrit by >  - 4.8% (aOR, 3.45; 95% CI, 1.22-9.73; p = 0.0019), and 24-h postoperative change in kinetic estimated glomerular filtration rate of < 0 mL/min (aOR, 3.99; 95% CI, 1.52-10.53; p = 0.005) were identified as independent risk factors for PC1M via stepwise logistic regression analysis. When stratified according to the age of ≥ 65 years (OR, 11.55; 95% CI, 1.30-102.79; p = 0.028), the reduction of kinetic estimated glomerular filtration rate was more robustly associated with a higher risk of PC1M., Conclusions: Four parameters were demonstrated to significantly influence the risk of PC1M in patients undergoing primary malignant brain tumor removal. Measuring and verifying these markers, especially kinetic estimated glomerular filtration rate, would help early recognition of PC1M risk in clinical care., (© 2023. BioMed Central Ltd., part of Springer Nature.)

A 58-year-old woman experienced relapsing acute longitudinally extensive transverse myelitis that developed rapidly in 3 days after lumbar surgery. The patient had a history of systemic lupus erythematosus with acute transverse myelitis and had undergone plasmapheresis 16 years ago. New neurologic deficits including paraplegia of the lower limbs, sensory alterations, and bowel incontinence presented 3 days postoperatively. Magnetic resonance imaging revealed a long-segment hyperintense signal over the thoracic spine on T2-weighted imaging. Intravenous pulse therapy with high-dose corticosteroid was first used for 5 days but was ineffective. Plasmapheresis after pulse therapy resulted in improved neurologic deficit. The patient then underwent 6 months of rehabilitation therapy but was partially wheelchair bound. She no longer had bladder and bowel incontinence., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Hydrocephalus is a common complication of hemorrhagic stroke and has been reported to contribute to poor neurological outcomes. Herein, we aimed to investigate the validity of cerebrospinal fluid (CSF) data in predicting shunt-dependent hydrocephalus (SDHC) in patients with hemorrhagic stroke. PubMed, CENTRAL, and Embase databases were searched for relevant studies published through July 31, 2021. The 16 studies with 1505 patient included those in which CSF data predicted risk for SDHC and reports on CSF parameters in patients in whom SDHC or hydrocephalus that was not shunt-dependent developed following hemorrhagic stroke. We appraised the study quality using Newcastle-Ottawa Scale and conducted a meta-analysis of the pooled estimates of the CSF predictors. The meta-analysis revealed three significant CSF predictors for shunt dependency, i.e., higher protein levels (mean difference [MD] = 32.09 mg/dL, 95% confidence interval [CI] = 25.48-38.70, I 2 = 0%), higher levels of transforming growth factor β1 (TGF-β1; MD = 0.52 ng/mL, 95% CI = 0.42-0.62, I 2 = 0%), and higher ferritin levels (MD = 108.87 µg/dL, 95% CI = 56.68-161.16, I 2 = 36%). The red blood cell count, lactate level, and glucose level in CSF were not significant in predicting SDHC in patients with hemorrhagic stroke. Therefore, higher protein, TGF-β1, and ferritin levels in CSF are significant predictors for SDHC in patients with hemorrhagic stroke. Measuring these CSF parameters would help in the early recognition of SDHC risk in clinical care., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

A 30-year-old woman experienced nasal stuffiness followed by a progressive headache and reduced visual acuity for 3 weeks. She underwent an endoscopic endonasal transsphenoidal approach for pituitary spindle cell oncocytoma 13 months before the present admission. Magnetic resonance imaging revealed an intrasellar cystic lesion with a suprasellar extension. After endoscopic endonasal transsphenoidal approach for tumor removal, the histologic findings of inflammatory infiltration showed a pituitary abscess. Microscopy revealed mites and fungal hyphae. Cultures from the abscess showed Staphylococcus hyicus, Stenotrophomonas maltophilia, and Aspergillus sp. The patient received a 6-week antibiotic treatment, which completely resolved the clinical symptoms and cleared the magnetic resonance imaging findings., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Objective: This study aimed to create a prediction model with a radiographic score, serum, and cerebrospinal fluid (CSF) values for the occurrence of shunt-dependent hydrocephalus (SDHC) in patients with aneurysmal subarachnoid hemorrhage (aSAH) and to review and analyze literature related to the prediction of the development of SDHC., Methods: Sixty-three patients with aSAH who underwent external ventricular drain insertion were included and separated into 2 subgroups: non-SDHC and SDHC. Patient characteristics, computed tomography scoring system, and serum and CSF parameters were collected. Multivariate logistic regression was conducted to illustrate a nomogram for determining the predictors of SDHC. Furthermore, we sorted and summarized previous meta-analyses for predictors of SDHC., Results: The SDHC group had 42 cases. Stepwise logistic regression analysis revealed 3 independent predictive factors associated with a higher modified Graeb (mGraeb) score, lower level of estimated glomerular filtration rate group, and lower level of CSF glucose. The nomogram, based on these 3 factors, was presented with significant predictive performance (area under curve = 0.895) for SDHC development, compared with other scoring systems (AUC = 0.764-0.885). In addition, a forest plot was generated to present the 12 statistically significant predictors and odds ratio for correlations with the development of SDHC., Conclusions: First, the development of a nomogram with combined significant factors had a good performance in estimating the risk of SDHC in primary patient evaluation and assisted in clinical decision making. Second, a narrative review, presented with a forest plot, provided the current published data on predicting SDHC., (Copyright © 2021. Published by Elsevier Inc.)