scholarly journals A Nomogram for Predicting Acute Respiratory Failure After Cervical Traumatic Spinal Cord Injury Based on Admission Clinical Findings

2021 ◽  
Author(s):  
Yongfan Xie ◽  
Yongyi Wang ◽  
Yong Zhou ◽  
Mingxing Liu ◽  
Shengli Li ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Operating Characteristic ◽  
Predictive Accuracy ◽  
Characteristic Curve ◽  
Traumatic Spinal Cord Injury ◽  
Concordance Index ◽  
Platelet To Lymphocyte Ratio ◽  
Training Cohort ◽  
Cord Injury ◽  
Operating Characteristic Curve

Abstract Objectives Acute respiratory failure (ARF) is a common medical complication in patients with cervical traumatic spinal cord injury (TSCI). To identify independent predictors for ARF onset in patients who underwent cervical TSCI without premorbid respiratory diseases and to apply appropriate medical supports based on accurate prediction, a nomogram relating admission clinical information was developed for predicting ARF during acute care period. Methods We retrospectively reviewed clinical profiles of patients who suffered cervical TSCI and were emergently admitted to Qingdao Municipal Hospital from 2014 to 2020 as the training cohort. Univariate analysis was performed using admission clinical variables to estimate associated factors and a nomogram for predicting ARF occurrence was generated based on the independent predictors from multivariate logistic regression analysis. This nomogram was assessed by concordance index for discrimination and calibration curve with internal-validated bootstrap strategy. Receiver operating characteristic curve was conducted to compare the predictive accuracy between the nomogram and the traditional gold standard, which combines neuroimaging and neurological measurements by using area under the receiver operating characteristic curve (AUC). An additional 56-patient cohort from another medical center was retrospectively reviewed as the test cohort for external validation of the nomogram. Results 162 patients were eligible for this study and were included in the training cohort, among which 25 individuals developed ARF and were recorded to endure more complications. Despite the aggressive treatments and prolonged intensive care unit cares, 14 patients insulted with ARF died. Injury level, American Spinal Injury Association Impairment Scale (AIS) grade, admission hemoglobin (Hb), platelet to lymphocyte ratio, and neutrophil percentage to albumin ratio (NPAR) were independently associated with ARF onset. The concordance index of the nomogram incorporating these predictors was 0.933 in the training cohort and 0.955 in the test cohort, although both calibrations were good. The AUC of the nomogram was equal to concordance index, which presented better predictive accuracy compared with previous measurements using neuroimaging and AIS grade (AUC 0.933 versus 0.821, Delong’s test p < 0.001). Similar significant results were also found in the test cohort (AUC 0.955 versus 0.765, Delong’s test p = 0.034). In addition, this nomogram was translated to a Web-based calculator that could generate individual probability for ARF in a visualized form. Conclusions The nomogram incorporating the injury level, AIS grade, admission Hb, platelet to lymphocyte ratio, and NPAR is a promising model to predict ARF in patients with cervical TSCI who are absent from previous respiratory dysfunction. This nomogram can be offered to clinicians to stratify patients, strengthen evidence-based decision-making, and apply appropriate individualized treatment in the field of acute clinical care.

scholarly journals Clinical Characteristics and Prognostic Nomogram in Patients With Pineoblastoma

2020 ◽  
Author(s):  
YaJun JING ◽  
WenShuai DENG ◽  
YunXia JIANG ◽  
MingXia BI ◽  
MingChao FAN ◽  
...  
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Treatment Options ◽  
Concordance Index ◽  
Cox Regression Analysis ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Abstract Background: Pineoblastoma (PB) is an infrequent entity of the central nervous system. The data about clinical outcomes of PB is exceedingly limited due to its rarity. Notably, the optimal treatment approaches and prognostic factors on PB is still unclear. Thus the aims of this study are to identify prognosis-associated factors and develop a predictive nomogram of PB.Method: Data of 243 patients with PB (≤29 years), collected by the Surveillance, Epidemiology, and End Results database, were randomly carved up the primary (n=172) and validation cohort (n=71) two groups. A prognostic nomogram was developed based on primary cohorts and optimized via the Akaike Information Criterion. Calibration curves were applied to show the results of validation (internal, external, and cross-validation). Additionally, its predictive performance was evaluated by the concordance index and receiver operating characteristic curve. Finally, decision curve analyses were employed to assess its clinical utility. Results: Age, year of diagnosis, treatment, tumor size, and tumor extension were identified as independent predictors of PB based on multivariate Cox regression analysis. The model presented an excellent discriminating ability (concordance index of the nomogram: 0.805; 95% confidence interval: 0.78–0.83; area under the receiver operating characteristic curve with a range from 0.7 to 0.9). The calibration plots (probability of survival) is consistent with the results predicted by the nomogram. The results of the decision curve analysis showed that the nomogram has potential clinical applicability.Conclusion: The nomogram can be used to assess prognosis and determine appropriate treatment options.

scholarly journals Cerebellar Arteriovenous Malformations

Neurosurgery ◽  
2012 ◽  
Vol 71 (6) ◽  
pp. 1111-1124 ◽  
Author(s):  
◽  
Ana Rodríguez-Hernández ◽  
Helen Kim ◽  
Tony Pourmohamad ◽  
William L. Young ◽  
...  
Keyword(s):  
Arteriovenous Malformations ◽  
Operating Characteristic ◽  
Predictive Accuracy ◽  
Characteristic Curve ◽  
Venous Drainage ◽  
Martin Grade ◽  
Operating Characteristic Curve ◽  
Cerebral Avms ◽  
Cerebellar Anatomy ◽  
Better Than

ABSTRACT BACKGROUND: Anatomic diversity among cerebellar arteriovenous malformations (AVMs) calls for a classification that is intuitive and surgically informative. Selection tools like the Spetzler-Martin grading system are designed to work best with cerebral AVMs but have shortcomings with cerebellar AVMs. OBJECTIVE: To define subtypes of cerebellar AVMs that clarify anatomy and surgical management, to determine results according to subtypes, and to compare predictive accuracies of the Spetzler-Martin and supplementary systems. METHODS: From a consecutive surgical series of 500 patients, 60 had cerebellar AVMs, 39 had brainstem AVMs and were excluded, and 401 had cerebral AVMs. RESULTS: Cerebellar AVM subtypes were as follows: 18 vermian, 13 suboccipital, 12 tentorial, 12 petrosal, and 5 tonsillar. Patients with tonsillar and tentorial AVMs fared best. Cerebellar AVMs presented with hemorrhage more than cerebral AVMs (P &lt; .001). Cerebellar AVMs were more likely to drain deep (P = .04) and less likely to be eloquent (P &lt; .001). The predictive accuracy of the supplementary grade was better than that of the Spetzler-Martin grade with cerebellar AVMs (areas under the receiver-operating characteristic curve, 0.74 and 0.59, respectively). The predictive accuracy of the supplementary system was consistent for cerebral and cerebellar AVMs, whereas that of the Spetzler-Martin system was greater with cerebral AVMs. CONCLUSION: Patients with cerebellar AVMs present with hemorrhage more often than patients with cerebral AVMs, justifying an aggressive treatment posture. The supplementary system is better than the Spetzler-Martin system at predicting outcomes after cerebellar AVM resection. Key components of the Spetzler-Martin system such as venous drainage and eloquence are distorted by cerebellar anatomy in ways that components of the supplementary system are not.

scholarly journals CANPT Score: A Tool to Predict Severe COVID-19 on Admission

2021 ◽  
Vol 8 ◽  
Author(s):  
Yuanyuan Chen ◽  
Xiaolin Zhou ◽  
Huadong Yan ◽  
Huihong Huang ◽  
Shengjun Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Operating Characteristic ◽  
Total Bilirubin ◽  
Predictive Accuracy ◽  
Characteristic Curve ◽  
Severe Disease ◽  
Multivariate Logistic Regression ◽  
Independent Risk Factors ◽  
Operating Characteristic Curve ◽  
Cr Creatine

Background and Aims: Patients with critical coronavirus disease 2019 (COVID-19) have a mortality rate higher than 50%. The purpose of this study was to establish a model for the prediction of the risk of severe disease and/or death in patients with COVID-19 on admission.Materials and Methods: Patients diagnosed with COVID-19 in four hospitals in China from January 22, 2020 to April 15, 2020 were retrospectively enrolled. The demographic, laboratory, and clinical data of the patients with COVID-19 were collected. The independent risk factors related to the severity of and death due to COVID-19 were identified with a multivariate logistic regression; a nomogram and prediction model were established. The area under the receiver operating characteristic curve (AUROC) and predictive accuracy were used to evaluate the model's effectiveness.Results: In total, 582 patients with COVID-19, including 116 patients with severe disease, were enrolled. Their comorbidities, body temperature, neutrophil-to-lymphocyte ratio (NLR), platelet (PLT) count, and levels of total bilirubin (Tbil), creatinine (Cr), creatine kinase (CK), and albumin (Alb) were independent risk factors for severe disease. A nomogram was generated based on these eight variables with a predictive accuracy of 85.9% and an AUROC of 0.858 (95% CI, 0.823–0.893). Based on the nomogram, the CANPT score was established with cut-off values of 12 and 16. The percentages of patients with severe disease in the groups with CANPT scores &lt;12, ≥12, and &lt;16, and ≥16 were 4.15, 27.43, and 69.64%, respectively. Seventeen patients died. NLR, Cr, CK, and Alb were independent risk factors for mortality, and the CAN score was established to predict mortality. With a cut-off value of 15, the predictive accuracy was 97.4%, and the AUROC was 0.903 (95% CI 0.832, 0.974).Conclusions: The CANPT and CAN scores can predict the risk of severe disease and mortality in COVID-19 patients on admission.

scholarly journals A Supplementary Grading Scale for Selecting Patients With Brain Arteriovenous Malformations for Surgery

Neurosurgery ◽  
2010 ◽  
Vol 66 (4) ◽  
pp. 702-713 ◽  
Author(s):  
Michael T. Lawton ◽  
Helen Kim ◽  
Charles E. McCulloch ◽  
Bahar Mikhak ◽  
William L. Young
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Patient Selection ◽  
Arteriovenous Malformations ◽  
Operating Characteristic ◽  
Predictive Accuracy ◽  
Characteristic Curve ◽  
Grading System ◽  
Modified Rankin Scale ◽  
Grading Scale ◽  
Operating Characteristic Curve

Abstract BACKGROUND Patient age, hemorrhagic presentation, nidal diffuseness, and deep perforating artery supply are important factors when selecting patients with brain arteriovenous malformations (AVMs) for surgery. OBJECTIVE We hypothesized that these factors outside of the Spetzler-Martin grading system could be combined into a simple, supplementary grading system that would accurately predict neurologic outcome and refine patient selection. METHODS A consecutive, single-surgeon series of 300 patients with AVMs treated microsurgically was analyzed in terms of change between preoperative and final postoperative modified Rankin Scale scores. Three different multivariable logistic models (full, Spetzler-Martin, and supplementary models) were constructed to test the association of combined predictor variables with the change in modified Rankin Scale score. A simplified supplementary grading system was developed from the data with points assigned according to each variable and added together for a supplementary AVM grade. RESULTS Predictive accuracy was highest for the full multivariable model (receiver operating characteristic curve area, 0.78), followed by the supplementary model (0.73), and least for the Spetzler-Martin model (0.66). Predictive accuracy of the simplified supplementary grade was significantly better than that of the Spetzler-Martin grade (P = .042), with receiver operating characteristic curve areas of 0.73 and 0.65, respectively. CONCLUSION This new AVM grading system supplements rather than replaces the well-established Spetzler-Martin grading system and is a better predictor of neurologic outcomes after AVM surgery. The supplementary grading scale has high predictive accuracy on its own and stratifies surgical risk more evenly. The supplementary grading system is easily applicable at the bedside, where it is intended to improve preoperative risk prediction and patient selection for surgery.

Defining the optimal PSA range for the maximal predictive efficacy of PSA density to detect prostate cancer on biopsy: Results from a multi-institutional and prospective contemporary cohort.

2016 ◽  
Vol 34 (2_suppl) ◽  
pp. 70-70
Author(s):  
Samarpit Rai ◽  
Nicola Pavan ◽  
Nachiketh Soodana-Prakash ◽  
Bruno Nahar ◽  
Yan Dong ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Prostate Biopsy ◽  
Operating Characteristic ◽  
Predictive Accuracy ◽  
Characteristic Curve ◽  
Psa Density ◽  
Detect Prostate Cancer ◽  
Operating Characteristic Curve ◽  
The Difference ◽  
Negative Prostate Biopsy

70 Background: PSA density (PSAD) is an important predictor of prostate cancer (PCa). We assessed whether the predictive accuracy of PSAD varied based on the range of PSA or whether the patient had a previous negative prostate biopsy (PB). Methods: We assessed a prospective cohort of men who were referred for a PB due to suspicion of PCa at 26 different sites across USA. The area under the receiver operating characteristic curve (AUC) was used to assess the added predictive accuracy of PSAD versus PSA across 3 different PSA ranges ( < 4, 4 – 10, > 10 ng/mL) and in men with or without a prior negative PB for the detection of any and significant (Gleason ≥ 7) PCa. Results: Of the 1,290 men, 585 (45%) and 284 (22%) had any and significant PCa, respectively. PSAD was significantly more predictive than PSA for detecting any PCa in the PSA ranges of 4 – 10 (AUC 0.70 vs 0.53, P < 0.00001) and > 10 (AUC 0.84 vs 0.65, P < 0.00001) ng/mL. Similarly, for significant PCa, PSAD was more predictive than PSA in the PSA ranges of 4 – 10 (AUC 0.72 vs 0.57, P < 0.00001) and > 10 (AUC 0.82 vs 0.68, P = 0.0001) ng/mL. Furthermore, PSAD was significantly more predictive than PSA in detecting PCa in men that had a prior negative PB (AUC 0.69 vs 0.56, P = 0.0001 for any PCa and AUC 0.81 vs 0.70, P = 0.0042 for significant PCa), and those that didn’t (AUC 0.72 vs 0.67, P = 0.0001 for any PCa and AUC 0.77 vs 0.73, P = 0.0026 for significant PCa). However the difference between the AUC of PSAD and PSA (ΔAUC) was a lot more pronounced in men that had a prior negative PB (ΔAUC = 0.13 for any PCa and ΔAUC = 0.11 for significant PCa) as opposed to those that didn’t (ΔAUC = 0.05 for any PCa and ΔAUC = 0.04 for significant PCa), suggesting that PSAD is a much better predictor than PSA alone in men who have undergone a previous PB. Conclusions: As PSA increases, the predictive accuracy of PSAD over PSA appears to improve for the detection of any PCa and significant PCa. Additionally, PSAD has a more pronounced predictive value over PSA in detecting any and significant PCa in men who have undergone a prior negativePB. We support the use of PSAD testing to avoid unnecessary biopsies in men who have elevated PSA secondary to an enlarged prostate.

scholarly journals Comparative Analysis of Anterior Segment Parameters in Normal and Keratoconus Eyes Generated by Scheimpflug Tomography

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Faik Orucoglu ◽  
Ebru Toker
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Sensitivity And Specificity ◽  
Operating Characteristic ◽  
Predictive Accuracy ◽  
Characteristic Curve ◽  
Anterior Segment ◽  
Area Under The Curve ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Purpose. To assess and compare the anterior and posterior corneal surface parameters, keratoconus indices, thickness profile data, and data from enhanced elevation maps of keratoconic and normal corneas with the Pentacam Scheimpflug corneal tomography and to determine the sensitivity and specificity of these parameters in discriminating keratoconus from normal eyes.Methods. The study included 656 keratoconus eyes and 515 healthy eyes with a mean age of30.95±9.25and32.90±14.78years, respectively. Forty parameters obtained from the Pentacam tomography were assessed by the receiver operating characteristic curve analysis for their efficiency.Results. Receiver operating characteristic curve analyses showed excellent predictive accuracy (area under the curve, ranging from 0.914 to 0.972) for 21 of the 40 parameters evaluated. Among all parameters indices of vertical asymmetry, keratoconus index, front elevation at thinnest location, back elevation at thinnest location, Ambrósio Relational Thickness (ARTmax), deviation of average pachymetric progression, deviation of ARTmax, and total deviation showed excellent (>90%) sensitivity and specificity in addition to excellent area under the receiver operating characteristic curve (AUROC).Conclusions. Parameters derived from the topometric and Belin-Ambrósio enhanced ectasia display maps very effectively discriminate keratoconus from normal corneas with excellent sensitivity and specificity.

Neurological Recovery in Traumatic Spinal Cord Injury Patient with Delayed Surgical Intervention

2018 ◽  
Vol 1 (2) ◽  
pp. 34
Author(s):  
Mochamad Targib Alatas
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Surgical Intervention ◽  
Case Series ◽  
Spinal Cord Injury Patient ◽  
Traumatic Spinal Cord Injury ◽  
Best Interest ◽  
Score Improvement ◽  
Cord Injury ◽  
Injury Patient

Early surgical treatment for traumatic spinal cord injury (SCI) patients has been proven to yield better improvement on neurological state, and widely practiced among surgeons in this field. However, it is not always affordable in every clinical setting. It is undeniable that surgery for chronic SCI has more challenges as the malunion of vertebral bones might have initiated, thus requires more complex operating techniques. In this case series, we report 7 patients with traumatic SCI whose surgical intervention is delayed due to several reasons. Initial motoric scores vary from 0 to 3, all have their interval periods supervised between outpatient clinic visits. On follow up they demonstrate significant neurological development defined by at least 2 grades motoric score improvement. Physical rehabilitation also began before surgery was conducted. These results should encourage surgeons to keep striving for the patient’s best interest, even when the injury has taken place weeks or even months before surgery is feasible because clinical improvement for these patients is not impossible. 

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