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Objective: The therapeutic effect of deep brain stimulation (DBS) surgery mainly depends on the accuracy of electrode placement and the reduction in brain shift. Among the standard procedures, cerebrospinal fluid (CSF) loss or pneumocephalus caused by dura incision (DI) is thought to be the main reason for brain shift and inaccuracy of electrode placement. In the current study, we described a modified dura puncture (DP) procedure to reduce brain shift and compare it with the general procedure of DBS surgery in terms of electrode placement accuracy. Materials and Methods: We retrospectively analyzed a series of 132 patients who underwent DBS surgery in Wuhan Union Hospital from December 2015 to April 2021. According to the different surgery procedures, patients were classified into two cohorts: the DI group (DI cohort) had 49 patients who receive the general procedure, and the DP group (DP cohort) had 83 patients who receive the modified procedure. Postoperative pneumocephalus volume (PPV) and CSF loss volume, electrode fusion error (EFE), and trajectory number were calculated. Meanwhile, intraoperative electrophysiological signal length (IESL), electrode implantation duration, and other parameters were analyzed. Results: In the current study, we introduced an improved electrode implantation procedure for DBS surgery named the DP procedure. Compared with the general DI cohort (n = 49), the modified DP cohort (n = 83) had a shorter electrode implantation duration (p < 0.0001), smaller PPV, lower CSF leakage volume (p < 0.0001), and smaller EFE (p < 0.0001). There was no significant difference in IESL (p > 0.05) or adverse events (perioperative cerebral haematoma, skin erosion, epilepsy, p > 0.05) between the two cohorts. Conclusion: The DP procedure is a modified procedure that can reduce brain shift and ensure implantation accuracy during DBS surgery without adverse events.
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BACKGROUND: Lupus nephritis (LN) is classified by renal biopsy into proliferative and nonproliferative forms, with distinct prognoses, but renal biopsy is not available for every LN patient. The present study aimed to establish an alternate tool by building a predictive model to evaluate the probability of proliferative LN. METHODS: In this retrospective cohort with biopsy-proven LN, 382 patients in development cohort, 193 in internal validation cohort, and 164 newly diagnosed patients in external validation cohort were selected. Logistic regression model was established, and the concordance statistics (C-statistics), Akaike information criterion (AIC), integrated discrimination improvement, Hosmer-Lemeshow test, and net reclassification improvement were calculated to evaluate the performance and validation of models. RESULTS: The prevalence of proliferative LN was 77.7% in the whole cohort. A model, including age, gender, systolic blood pressure, hemoglobin, proteinuria, hematuria, and serum C3, performed well on good-of-fit and discrimination in the development chohort to predict the risk of proliferative LN (291 for AIC and 0.84 for C-statistics). In the internal and external validation cohorts, this model showed good capability for discrimination and calibration (0.84 and 0.82 for C-statistics, and 0.99 and 0.75 for P values, respectively). CONCLUSION: This study developed and validated a model including demographic and clinical indices to evaluate the probability of presenting proliferative LN to guide therapeutic decisions and outcomes.