✓ The smooth-muscle relaxant action of adenosine 5′-triphosphate (ATP)-sensitive potassium (KATP) channels in cerebral arteries of large diameter has been confirmed in a number of in vitro studies, but there is still debate about the presence of KATP channels in small cerebral arteries. In the present study, the authors compare the effects of cromakalim and bimakalim, two putative KATP channel activators, in different parts of the feline isolated middle cerebral artery (MCA) designated proximal, intermediate, and distal. The latter corresponds to those small pial arteries that are usually studied in vivo. In ring segments precontracted with 10−5 M of uridine-5-triphosphate (UTP), both cromakalim and bimakalim induced concentration-related relaxation, with bimakalim being more potent than cromakalim, and no significant differences noted among segments obtained from the different regions of the MCA. In vessels precontracted by adding 30 mM KCl the potency of cromakalim and bimakalim was reduced compared with that obtained after UTP precontraction. In the presence of 10−6 M glibenclamide, an antagonist of KATP channel activators, the concentration—effect curve to bimakalim was shifted to the right in the proximal and distal MCA, indicating a similar route of action for bimakalim and cromakalim in these arteries. The present study therefore indicates the presence of KATP channels in isolated small cerebral arteries according to results obtained in vivo. Activators of KATP channels may prove helpful in the treatment of vasospasm, which may occur in large and small cerebral arteries after subarachnoid hemorrhage.
Lothar Schilling, Andrew A. Parsons, and Michael Wahl
Jeff Ehresman, Zach Pennington, James Feghali, Andrew Schilling, Andrew Hersh, Bethany Hung, Daniel Lubelski, and Daniel M. Sciubba
More than 8000 patients are treated annually for vertebral column tumors, of whom roughly two-thirds will be discharged to an inpatient facility (nonroutine discharge). Nonroutine discharge is associated with increased care costs as well as delays in discharge and poorer patient outcomes. In this study, the authors sought to develop a prediction model of nonroutine discharge in the population of vertebral column tumor patients.
Patients treated for primary or metastatic vertebral column tumors at a single comprehensive cancer center were identified for inclusion. Data were gathered regarding surgical procedure, patient demographics, insurance status, and medical comorbidities. Frailty was assessed using the modified 5-item Frailty Index (mFI-5) and medical complexity was assessed using the modified Charlson Comorbidity Index (mCCI). Multivariable logistic regression was used to identify independent predictors of nonroutine discharge, and multivariable linear regression was used to identify predictors of prolonged length of stay (LOS). The discharge model was internally validated using 1000 bootstrapped samples.
The authors identified 350 patients (mean age 57.0 ± 13.6 years, 53.1% male, and 67.1% treated for metastatic vs primary disease). Significant predictors of prolonged LOS included higher mCCI score (β = 0.74; p = 0.026), higher serum absolute neutrophil count (β = 0.35; p = 0.001), lower hematocrit (β = −0.34; p = 0.001), use of a staged operation (β = 4.99; p < 0.001), occurrence of postoperative pulmonary embolism (β = 3.93; p = 0.004), and surgical site infection (β = 9.93; p < 0.001). Significant predictors of nonroutine discharge included emergency admission (OR 3.09; p = 0.001), higher mFI-5 score (OR 1.90; p = 0.001), lower serum albumin level (OR 0.43 per g/dL; p < 0.001), and operations with multiple stages (OR 4.10; p < 0.001). The resulting statistical model was deployed as a web-based calculator (https://jhuspine4.shinyapps.io/Nonroutine_Discharge_Tumor/).
The authors found that nonroutine discharge of patients with surgically treated vertebral column tumors was predicted by emergency admission, increased frailty, lower serum albumin level, and staged surgical procedures. The resulting web-based calculator tool may be useful clinically to aid in discharge planning for spinal oncology patients by preoperatively identifying patients likely to require placement in an inpatient facility postoperatively.
James Feghali, Zach Pennington, Jeff Ehresman, Daniel Lubelski, Ethan Cottrill, A. Karim Ahmed, Andrew Schilling, and Daniel M. Sciubba
Symptomatic spinal metastasis occurs in around 10% of all cancer patients, 5%–10% of whom will require operative management. While postoperative survival has been extensively evaluated, postoperative health-related quality-of-life (HRQOL) outcomes have remained relatively understudied. Available tools that measure HRQOL are heterogeneous and may emphasize different aspects of HRQOL. The authors of this paper recommend the use of the EQ-5D and Spine Oncology Study Group Outcomes Questionnaire (SOSGOQ), given their extensive validation, to capture the QOL effects of systemic disease and spine metastases. Recent studies have identified preoperative QOL, baseline functional status, and neurological function as potential predictors of postoperative QOL outcomes, but heterogeneity across studies limits the ability to derive meaningful conclusions from the data. Future development of a valid and reliable prognostic model will likely require the application of a standardized protocol in the context of a multicenter study design.
Zach Pennington, Jeff Ehresman, Ethan Cottrill, Daniel Lubelski, Kurt Lehner, James Feghali, A. Karim Ahmed, Andrew Schilling, and Daniel M. Sciubba
Accurate prediction of patient survival is an essential component of the preoperative evaluation of patients with spinal metastases. Over the past quarter of a century, a number of predictors have been developed, although none have been accurate enough to be instituted as a staple of clinical practice. However, recently more comprehensive survival calculators have been published that make use of larger data sets and machine learning to predict postoperative survival among patients with spine metastases. Given the glut of calculators that have been published, the authors sought to perform a narrative review of the current literature, highlighting existing calculators along with the strengths and weaknesses of each. In doing so, they identify two “generations” of scoring systems—a first generation based on a priori factor weighting and a second generation comprising predictive tools that are developed using advanced statistical modeling and are focused on clinical deployment. In spite of recent advances, the authors found that most predictors have only a moderate ability to explain variation in patient survival. Second-generation models have a greater prognostic accuracy relative to first-generation scoring systems, but most still require external validation. Given this, it seems that there are two outstanding goals for these survival predictors, foremost being external validation of current calculators in multicenter prospective cohorts, as the majority have been developed from, and internally validated within, the same single-institution data sets. Lastly, current predictors should be modified to incorporate advances in targeted systemic therapy and radiotherapy, which have been heretofore largely ignored.
Jeff Ehresman, Zach Pennington, Aditya V. Karhade, Sakibul Huq, Ravi Medikonda, Andrew Schilling, James Feghali, Andrew Hersh, A. Karim Ahmed, Ethan Cottrill, Daniel Lubelski, Erick M. Westbroek, Joseph H. Schwab, and Daniel M. Sciubba
Incidental durotomy is a common complication of elective lumbar spine surgery seen in up to 11% of cases. Prior studies have suggested patient age and body habitus along with a history of prior surgery as being associated with an increased risk of dural tear. To date, no calculator has been developed for quantifying risk. Here, the authors’ aim was to identify independent predictors of incidental durotomy, present a novel predictive calculator, and externally validate a novel method to identify incidental durotomies using natural language processing (NLP).
The authors retrospectively reviewed all patients who underwent elective lumbar spine procedures at a tertiary academic hospital for degenerative pathologies between July 2016 and November 2018. Data were collected regarding surgical details, patient demographic information, and patient medical comorbidities. The primary outcome was incidental durotomy, which was identified both through manual extraction and the NLP algorithm. Multivariable logistic regression was used to identify independent predictors of incidental durotomy. Bootstrapping was then employed to estimate optimism in the model, which was corrected for; this model was converted to a calculator and deployed online.
Of the 1279 elective lumbar surgery patients included in this study, incidental durotomy occurred in 108 (8.4%). Risk factors for incidental durotomy on multivariable logistic regression were increased surgical duration, older age, revision versus index surgery, and case starts after 4 pm. This model had an area under curve (AUC) of 0.73 in predicting incidental durotomies. The previously established NLP method was used to identify cases of incidental durotomy, of which it demonstrated excellent discrimination (AUC 0.97).
Using multivariable analysis, the authors found that increased surgical duration, older patient age, cases started after 4 pm, and a history of prior spine surgery are all independent positive predictors of incidental durotomy in patients undergoing elective lumbar surgery. Additionally, the authors put forth the first version of a clinical calculator for durotomy risk that could be used prospectively by spine surgeons when counseling patients about their surgical risk. Lastly, the authors presented an external validation of an NLP algorithm used to identify incidental durotomies through the review of free-text operative notes. The authors believe that these tools can aid clinicians and researchers in their efforts to prevent this costly complication in spine surgery.
Jeff Ehresman, Zach Pennington, Andrew Schilling, Ravi Medikonda, Sakibul Huq, Kevin R. Merkel, A. Karim Ahmed, Ethan Cottrill, Daniel Lubelski, Erick M. Westbroek, Salia Farrokh, Steven M. Frank, and Daniel M. Sciubba
Blood transfusions are given to approximately one-fifth of patients undergoing elective lumbar spine surgery, and previous studies have shown that transfusions are accompanied by increased complications and additional costs. One method for decreasing transfusions is administration of tranexamic acid (TXA). The authors sought to evaluate whether the cost of TXA is offset by the decrease in blood utilization in lumbar spine surgery patients.
The authors retrospectively reviewed patients who underwent elective lumbar or thoracolumbar surgery for degenerative conditions at a tertiary care center between 2016 and 2018. Patients who received intraoperative TXA (TXA patients) were matched with patients who did not receive TXA (non-TXA patients) by age, sex, BMI, ASA (American Society of Anesthesiologists) physical status class, and surgical invasiveness score. Primary endpoints were intraoperative blood loss, number of packed red blood cell (PRBC) units transfused, and total hemostasis costs, defined as the sum of TXA costs and blood transfusion costs throughout the hospital stay. A subanalysis was then performed by substratifying both cohorts into short-length (1–4 levels) and long-length (5–8 levels) spinal constructs.
Of the 1353 patients who met inclusion criteria, 68 TXA patients were matched to 68 non-TXA patients. Patients in the TXA group had significantly decreased mean intraoperative blood loss (1039 vs 1437 mL, p = 0.01). There were no differences between the patient groups in the total costs of blood transfusion and TXA (p = 0.5). When the 2 patient groups were substratified by length of construct, the long-length construct group showed a significant net cost savings of $328.69 per patient in the TXA group (p = 0.027). This result was attributable to the finding that patients undergoing long-length construct surgeries who were given TXA received a lower amount of PRBC units throughout their hospital stay (2.4 vs 4.0, p = 0.007).
TXA use was associated with decreased intraoperative blood loss and significant reductions in total hemostasis costs for patients undergoing surgery on more than 4 levels. Furthermore, the use of TXA in patients who received short constructs led to no additional net costs. With the increasing emphasis put on value-based care interventions, use of TXA may represent one mechanism for decreasing total care costs, particularly in the cases of larger spine constructs.
Jeff Ehresman, Andrew Schilling, Zach Pennington, Chengcheng Gui, Xuguang Chen, Daniel Lubelski, A. Karim Ahmed, Ethan Cottrill, Majid Khan, Kristin J. Redmond, and Daniel M. Sciubba
Vertebral compression fractures (VCFs) in patients with spinal metastasis can lead to destabilization and often carry a high risk profile. It is therefore important to have tools that enable providers to predict the occurrence of new VCFs. The most widely used tool for bone quality assessment, dual-energy x-ray absorptiometry (DXA), is not often available at a patient’s initial presentation and has limited sensitivity. While the Spinal Instability Neoplastic Score (SINS) has been associated with VCFs, it does not take patients’ baseline bone quality into consideration. To address this, the authors sought to develop an MRI-based scoring system to estimate trabecular vertebral bone quality (VBQ) and to assess this system’s ability to predict the occurrence of new VCFs in patients with spinal metastasis.
Cases of adult patients with a diagnosis of spinal metastasis, who had undergone stereotactic body radiation therapy (SBRT) to the spine or neurosurgical intervention at a single institution between 2012 and 2019, were retrospectively reviewed. The novel VBQ score was calculated for each patient by dividing the median signal intensity of the L1–4 vertebral bodies by the signal intensity of cerebrospinal fluid (CSF). Multivariable logistic regression analysis was used to identify associations of demographic, clinical, and radiological data with new VCFs.
Among the 105 patients included in this study, 56 patients received a diagnosis of a new VCF and 49 did not. On univariable analysis, the factors associated with new VCFs were smoking status, steroid use longer than 3 months, the SINS, and the novel scoring system—the VBQ score. On multivariable analysis, only the SINS and VBQ score were significant predictors of new VCFs and, when combined, had a predictive accuracy of 89%.
As a measure of bone quality, the novel VBQ score significantly predicted the occurrence of new VCFs in patients with spinal metastases independent of the SINS. This suggests that baseline bone quality is a crucial factor that requires assessment when evaluating these patients’ conditions and that the VBQ score is a novel and simple MRI-based measure to accomplish this.