Postoperative surveillance in cranial and spinal tumor neurosurgery: when is this warranted?

OBJECTIVE: The outbreak of COVID-19 and the sudden increase in the number of patients requiring mechanical ventilation significantly affected the management of neurooncological patients. Hospitals were forced to reallocate already scarce human resources to maximize intensive care unit (ICU) capacities, resulting in a significant postponement of elective procedures for patients with brain and spinal tumors, who traditionally require elective postoperative surveillance on ICU or intermediate care wards. This study aimed to characterize those patients in whom postoperative monitoring is required by analyzing early postoperative complications and associated risk factors. METHODS: All patients included in the analysis experienced benign or malignant cerebral or intradural tumors and underwent surgery between September 2017 and May 2019 at University Hospital Münster, Germany. Patient data were generated from a semiautomatic, prospectively designed database. The occurrence of adverse events within 24 hours and 30 days postoperatively-including unplanned reoperation, postoperative hemorrhage, CSF leakage, and pulmonary embolism-was chosen as the primary outcome measure. Furthermore, reasons and risk factors that led to a prolonged stay on the ICU were investigated. By performing multivariable logistic regression modeling, a risk score for early postoperative adverse events was calculated by assigning points based on beta coefficients. RESULTS: Eight hundred eleven patients were included in the study. Eleven patients (1.4%) had an early adverse event within 24 hours, which was either an unplanned reoperation (0.9%, n = 7) or a pulmonary embolism (0.5%, n = 4) within 24 hours. To predict the incidence of early postoperative complications, a score was developed including the number of secondary diagnoses, BMI, and incision closure time, termed the SOS score. According to this score, 0.3% of the patients were at low risk, 2.5% at intermediate risk, and 12% at high risk (p < 0.001). CONCLUSIONS: Postoperative surveillance in cranial and spinal tumor neurosurgery might only be required in a distinct patient collective. In this study, the authors present a new score allowing efficient prediction of the likelihood of early adverse events in patients undergoing neurooncological procedures, thus helping to stratify the necessity for ICU or intermediate care unit beds. Nevertheless, validation of the score in a multicenter prospective setting is needed.

Can Currently Suggested Quality Indicators Be Transferred to Meningioma Surgery?-A Single-Center Pilot Study.

BACKGROUND: Risk stratification based on standardized quality measures has become crucial in neurosurgery. Contemporary quality indicators have often been developed for a wide range of neurosurgical procedures collectively. The accuracy of tumor-inherent characteristics of patients diagnosed with meningioma remains questionable. The objective of this study was the analysis of currently applied quality indicators in meningioma surgery and the identification of potential new measures. METHODS: Data of 133 patients who were operated on due to intracranial meningiomas were subjected to a retrospective analysis. The primary outcomes of interest were classical quality indicators such as the 30-day readmission, 30-day reoperation, 30-day mortality, 30-day nosocomial infection, and the 30-day surgical site infection rate. Uni- and multivariate analyses were performed. The occurrence of a new postoperative neurologic deficit was analyzed as a potential new quality indicator. RESULTS: The overall unplanned readmission rate was 3.8%; 13 patients were reoperated within 30 days (9.8%). The 30-day nosocomial infection and surgical site infection rates were 6.8 and 1.5%, respectively. A postoperative new neurologic deficit or neurologic deterioration as a currently assessed quality feature was observed in 12 patients (9.2%). The edema volume on preoperative scans proved to have a significant impact on the occurrence of a new postoperative neurologic deficit (p = 0.023). CONCLUSIONS: Classical quality indicators in neurosurgery have proved to correlate with considerable deterioration of the patient's health in meningioma surgery and thus should be taken into consideration for application in meningioma patients. The occurrence of a new postoperative neurologic deficit is common and procedure specific. Thus, this should be elucidated for application as a complementary quality indicator in meningioma surgery.

Classical and disease-specific quality indicators in glioma surgery-Development of a quality checklist to improve treatment quality in glioma patients.

BACKGROUND: There is a pressing demand for more accurate, disease-specific quality measures in the field of neurosurgery. Aiming at most adequately measuring and reflecting the quality of glioma therapy, we developed a novel quality indicator bundle in form of a checklist for all patients that are treated operatively for glioma. METHODS: On the basis of possible glioma-specific quality indicators retrieved from the literature and quality guidelines, a multidisciplinary team developed a checklist containing 13 patient-need-specific outcome measures. Subsequently, the checklist was prospectively applied to a total of 78 patients compared with a control group consisting of 322 patients. A score was generated based on the maximum of quality measures achieved. RESULTS: Significant improvements in quality after prospectively introducing the checklist were achieved for supplemental physical and occupational therapy during inpatient stay (89.4% vs 100%, P = .002), consultation of a social worker during inpatient stay (64% vs 92.3%, P < .001), psycho-oncological screening (14.3% vs 70.5%, P < .001), psycho-oncological consultation (31.1% vs 82.1%, P < .001), and consultation of the palliative care team (20% vs 40%, P = .031). Overall, after introduction of the checklist one-third (n = 23) of patients reached best-practice measures in all categories, and over half of the patients (n = 44) achieved above 90% with respect to the outcome measures. CONCLUSIONS: Aiming at ensuring comprehensive, consistent, and timely care of glioma patients, the implementation of the checklist for routine use in glioma surgery represents an efficient, easily reproducible, and powerful tool for significant improvements.

Applicability of contemporary quality indicators in vestibular surgery-do they accurately measure tumor inherent postoperative complications of vestibular schwannomas?

BACKGROUND: Due to rising costs in health care delivery, reimbursement decisions have progressively been based on quality measures. Such quality indicators have been developed for neurosurgical procedures, collectively. We aimed to evaluate their applicability in patients that underwent surgery for vestibular schwannoma and to identify potential new disease-specific quality indicators. METHODS: One hundred and three patients operated due to vestibular schwannoma were subject to analysis. The primary outcomes of interest were 30-day and 90-day reoperation, readmission, mortality, nosocomial infection and surgical site infection (SSI) rates, postoperative cerebral spinal fluid (CSF) leak, facial, and hearing function. The secondary aim was the identification of prognostic factors for the mentioned primary outcomes. RESULTS: Thirty-day (90-days) outcomes in terms of reoperation were 10.7% (14.6%), readmission 9.7% (13.6%), mortality 1% (1%), nosocomial infection 5.8%, and SSI 1% (1%). A 30- versus 90-day outcome in terms of CSF leak were 6.8% vs. 10.7%, new facial nerve palsy 16.5% vs. 6.1%. Hearing impairment from serviceable to non-serviceable hearing was 6.8% at both 30- and 90-day outcome. The degree of tumor extension has a significant impact on reoperation (p < 0.001), infection (p = 0.015), postoperative hemorrhage (p < 0.001), and postoperative hearing loss (p = 0.026). CONCLUSIONS: Our data demonstrate the importance of entity-specific quality measurements being applied even after 30 days. We identified the occurrence of a CSF leak within 90 days postoperatively, new persistent facial nerve palsy still present 90 days postoperatively, and persisting postoperative hearing impairment to non-serviceable hearing as potential new quality measurement variables for patients undergoing surgery for vestibular schwannoma.

Computational augmentation of neoplastic endometrial glands in digital pathology displays.

The pathologic diagnosis of neoplasia requires localization and classification of lesional tissue, a process that depends on the recognition of an abnormal spatial distribution of neoplastic elements relative to admixed normal background tissue. In endometrial intraepithelial neoplasia (EIN), a pre-cancer usually managed by hysterectomy, a clonally mutated proliferation of cytologically altered glands ('neoplastic-EIN') aggregates in clusters that also contain background non-neoplastic glands ('background-NL'). Here, we used image analysis to classify individual glands within endometrial tissue fragments as neoplastic-EIN or background-NL, and we used the distribution of predictions to localize foci diagnostic of EIN. Nuclear coordinates were automatically assigned and were used as vertices to generate Delaunay triangulations for each gland. Graph statistical variables were used to develop random forest algorithms to classify glands as neoplastic-EIN or background-NL. Individual glands in an independent validation set were scored by a 'ground truth' biomarker (PAX2 immunohistochemistry). We found that exclusion of small glands led to improvement in classification accuracy. Using an inclusion threshold of 200 nuclei per gland, our final model classification accuracy was 77.5% in the validation set, with a positive predictive value of 0.81. We leveraged this high positive predictive value in a point cloud overlay display to assist end-user identification of EIN foci. This study demonstrates that graph theory approaches applied to small-scale anatomic elements in the endometrium allow biologic classification by machine learning, and that spatial superimposition over large-scale tissue expanses can have practical diagnostic utility. We expect this augmented diagnostic approach to be generalizable to commonly encountered problems in other organ systems. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Development and validation of prediction scores for nosocomial infections, reoperations, and adverse events in the daily clinical setting of neurosurgical patients with cerebral and spinal tumors.

OBJECTIVE: Various quality indicators are currently under investigation, aiming at measuring the quality of care in neurosurgery; however, the discipline currently lacks practical scoring systems for accurately assessing risk. The aim of this study was to develop three accurate, easy-to-use risk scoring systems for nosocomial infections, reoperations, and adverse events for patients with cerebral and spinal tumors. METHODS: The authors developed a semiautomatic registry with administrative and clinical data and included all patients with spinal or cerebral tumors treated between September 2017 and May 2019. Patients were further divided into development and validation cohorts. Multivariable logistic regression models were used to develop risk scores by assigning points based on ß coefficients, and internal validation of the scores was performed. RESULTS: In total, 1000 patients were included. An unplanned 30-day reoperation was observed in 6.8% of patients. Nosocomial infections were documented in 7.4% of cases and any adverse event in 14.5%. The risk scores comprise variables such as emergency admission, nursing care level, ECOG performance status, and inflammatory markers on admission. Three scoring systems, NoInfECT for predicting the incidence of nosocomial infections (low risk, 1.8%; intermediate risk, 8.1%; and high risk, 26.0% [p < 0.001]), LEUCut for 30-day unplanned reoperations (low risk, 2.2%; intermediate risk, 6.8%; and high risk, 13.5% [p < 0.001]), and LINC for any adverse events (low risk, 7.6%; intermediate risk, 15.7%; and high risk, 49.5% [p < 0.001]), showed satisfactory discrimination between the different outcome groups in receiver operating characteristic curve analysis (AUC ≥ 0.7). CONCLUSIONS: The proposed risk scores allow efficient prediction of the likelihood of adverse events, to compare quality of care between different providers, and further provide guidance to surgeons on how to allocate preoperative care.

Establishing risk-adjusted quality indicators in surgery using administrative data-an example from neurosurgery.

BACKGROUND: The current draft of the German Hospital Structure Law requires remuneration to incorporate quality indicators. For neurosurgery, several quality indicators have been discussed, such as 30-day readmission, reoperation, or mortality rates; the rates of infections; or the length of stay. When comparing neurosurgical departments regarding these indicators, very heterogeneous patient spectrums complicate benchmarking due to the lack of risk adjustment. OBJECTIVE: In this study, we performed an analysis of quality indicators and possible risk adjustment, based only on administrative data. METHODS: All adult patients that were treated as inpatients for a brain or spinal tumour at our neurosurgical department between 2013 and 2017 were assessed for the abovementioned quality indicators. DRG-related data such as relative weight, PCCL (patient clinical complexity level), ICD-10 major diagnosis category, secondary diagnoses, age and sex were obtained. The age-adjusted Charlson Comorbidity Index (CCI) was calculated. Logistic regression analyses were performed in order to correlate quality indicators with administrative data. RESULTS: Overall, 2623 cases were enrolled into the study. Most patients were treated for glioma (n = 1055, 40.2%). The CCI did not correlate with the quality indicators, whereas PCCL showed a positive correlation with 30-day readmission and reoperation, SSI and nosocomial infection rates. CONCLUSION: All previously discussed quality indicators are easily derived from administrative data. Administrative data alone might not be sufficient for adequate risk adjustment as they do not reflect the endogenous risk of the patient and are influenced by certain complications during inpatient stay. Appropriate concepts for risk adjustment should be compiled on the basis of prospectively designed registry studies.