Activated prothrombin complex concentrate to treat bleeding events in acquired hemophilia A: BAHAS study.

OBJECTIVE: Activated prothrombin complex concentrate (aPCC) is a bypassing agent indicated to treat bleeds in patients with acquired hemophilia A (AHA). Nevertheless, its efficacy and safety in the real-world setting have not often been addressed. METHODS: We report the experience of Spanish reference centers for coagulation disorders and from acquired hemophilia Spanish Registry (AHASR) from August 2012 to February 2021. Follow-up period of 30 days after aPCC withdrawal. RESULTS: Thirty patients with a median age of 70 years old, suffering from 51 bleeds treated with aPCC were finally evaluated. As first-line treatment, aPCC stopped bleeding in 13 of 14 (92.9%) cases. aPCC as the second line after recombinant factor VIIa failure, stopped bleeding in all cases. In 17 patients, aPCC was used far from initial bleed control as prophylaxis of rebleeding with 94% effectiveness. No thromboembolic episodes were communicated. One patient developed hypofibrinogenemia, which did not prevent aPCC from halting bleeding. No other serious adverse events possibly or probably associated with aPCC were reported. CONCLUSIONS: This data support aPCC as hemostatic treatment in AHA with high effectiveness and excellent safety profile in acute bleeds and as extended use to prevent rebleedings, even in aging people with high cardiovascular risk.

Metastatic Versus Osteoporotic Vertebral Fractures on MRI: A Blinded, Multicenter, and Multispecialty Observer Agreement Evaluation.

BACKGROUND: MRI is assumed to be valid for distinguishing metastatic vertebral fractures (MVFs) from osteoporotic vertebral fractures (OVFs). This study assessed (1) concordance between the image-based diagnosis of MVF versus OVF and the reference (biopsy or follow-up of >6 months), (2) interobserver and intraobserver agreement on key imaging findings and the diagnosis of MVF versus OVF, and (3) whether disclosing a patient's history of cancer leads to variations in diagnosis, concordance, or agreement. PATIENTS AND METHODS: This retrospective cohort study included clinical data and imaging from 203 patients with confirmed MVF or OVF provided to 25 clinicians (neurosurgeons, radiologists, orthopedic surgeons, and radiation oncologists). From January 2018 through October 2018, the clinicians interpreted images in conditions as close as possible to routine practice. Each specialist assessed data twice, with a minimum 6-week interval, blinded to assessments made by other clinicians and to their own previous assessments. The kappa statistic was used to assess interobserver and intraobserver agreement on key imaging findings, diagnosis (MVF vs OVF), and concordance with the reference. Subgroup analyses were based on clinicians' specialty, years of experience, and complexity of the hospital where they worked. RESULTS: For diagnosis of MVF versus OVF, interobserver agreement was fair, whereas intraobserver agreement was substantial. Only the latter improved to almost perfect when a patient's history of cancer was disclosed. Interobserver agreement for key imaging findings was fair or moderate, whereas intraobserver agreement on key imaging findings was moderate or substantial. Concordance between the diagnosis of MVF versus OVF and the reference was moderate. Results were similar regardless of clinicians' specialty, experience, and hospital category. CONCLUSIONS: When MRI is used to distinguish MVF versus OVF, interobserver agreement and concordance with the reference were moderate. These results cast doubt on the reliability of basing such a diagnosis on MRI in routine practice.

Morphological MRI-based features provide pretreatment survival prediction in glioblastoma.

OBJECTIVES: We wished to determine whether tumor morphology descriptors obtained from pretreatment magnetic resonance images and clinical variables could predict survival for glioblastoma patients. METHODS: A cohort of 404 glioblastoma patients (311 discoveries and 93 validations) was used in the study. Pretreatment volumetric postcontrast T1-weighted magnetic resonance images were segmented to obtain the relevant morphological measures. Kaplan-Meier, Cox proportional hazards, correlations, and Harrell's concordance indexes (c-indexes) were used for the statistical analysis. RESULTS: A linear prognostic model based on the outstanding variables (age, contrast-enhanced (CE) rim width, and surface regularity) identified a group of patients with significantly better survival (p < 0.001, HR = 2.57) with high accuracy (discovery c-index = 0.74; validation c-index = 0.77). A similar model applied to totally resected patients was also able to predict survival (p < 0.001, HR = 3.43) with high predictive value (discovery c-index = 0.81; validation c-index = 0.92). Biopsied patients with better survival were well identified (p < 0.001, HR = 7.25) by a model including age and CE volume (c-index = 0.87). CONCLUSIONS: Simple linear models based on small sets of meaningful MRI-based pretreatment morphological features and age predicted survival of glioblastoma patients to a high degree of accuracy. The partition of the population using the extent of resection improved the prognostic value of those measures. KEY POINTS: • A combination of two MRI-based morphological features (CE rim width and surface regularity) and patients' age outperformed previous prognosis scores for glioblastoma. • Prognosis models for homogeneous surgical procedure groups led to even more accurate survival prediction based on Kaplan-Meier analysis and concordance indexes.

Correction to: Morphological MRI-based features provide pretreatment survival prediction in glioblastoma.

The original version of this article, published on 15 October 2018, unfortunately contained a mistake. The following correction has therefore been made in the original: The name of Mariano Amo-Salas and the affiliation of Ismael Herruzo were presented incorrectly.

Tumor Surface Regularity at MR Imaging Predicts Survival and Response to Surgery in Patients with Glioblastoma.

Purpose To evaluate the prognostic and predictive value of surface-derived imaging biomarkers obtained from contrast material-enhanced volumetric T1-weighted pretreatment magnetic resonance (MR) imaging sequences in patients with glioblastoma multiforme. Materials and Methods A discovery cohort from five local institutions (165 patients; mean age, 62 years ± 12 [standard deviation]; 43% women and 57% men) and an independent validation cohort (51 patients; mean age, 60 years ± 12; 39% women and 61% men) from The Cancer Imaging Archive with volumetric T1-weighted pretreatment contrast-enhanced MR imaging sequences were included in the study. Clinical variables such as age, treatment, and survival were collected. After tumor segmentation and image processing, tumor surface regularity, measuring how much the tumor surface deviates from a sphere of the same volume, was obtained. Kaplan-Meier, Cox proportional hazards, correlations, and concordance indexes were used to compare variables and patient subgroups. Results Surface regularity was a powerful predictor of survival in the discovery (P = .005, hazard ratio [HR] = 1.61) and validation groups (P = .05, HR = 1.84). Multivariate analysis selected age and surface regularity as significant variables in a combined prognostic model (P < .001, HR = 3.05). The model achieved concordance indexes of 0.76 and 0.74 for the discovery and validation cohorts, respectively. Tumor surface regularity was a predictor of survival for patients who underwent complete resection (P = .01, HR = 1.90). Tumors with irregular surfaces did not benefit from total over subtotal resections (P = .57, HR = 1.17), but those with regular surfaces did (P = .004, HR = 2.07). Conclusion The surface regularity obtained from high-resolution contrast-enhanced pretreatment volumetric T1-weighted MR images is a predictor of survival in patients with glioblastoma. It may help in classifying patients for surgery.

Glioblastoma: does the pre-treatment geometry matter? A postcontrast T1 MRI-based study.

BACKGROUND: The potential of a tumour's volumetric measures obtained from pretreatment MRI sequences of glioblastoma (GBM) patients as predictors of clinical outcome has been controversial. Mathematical models of GBM growth have suggested a relation between a tumour's geometry and its aggressiveness. METHODS: A multicenter retrospective clinical study was designed to study volumetric and geometrical measures on pretreatment postcontrast T1 MRIs of 117 GBM patients. Clinical variables were collected, tumours segmented, and measures computed including: contrast enhancing (CE), necrotic, and total volumes; maximal tumour diameter; equivalent spherical CE width and several geometric measures of the CE "rim". The significance of the measures was studied using proportional hazards analysis and Kaplan-Meier curves. RESULTS: Kaplan-Meier and univariate Cox survival analysis showed that total volume [p = 0.034, Hazard ratio (HR) = 1.574], CE volume (p = 0.017, HR = 1.659), spherical rim width (p = 0.007, HR = 1.749), and geometric heterogeneity (p = 0.015, HR = 1.646) were significant parameters in terms of overall survival (OS). Multivariable Cox analysis for OS provided the later two parameters as age-adjusted predictors of OS (p = 0.043, HR = 1.536 and p = 0.032, HR = 1.570, respectively). CONCLUSION: Patients with tumours having small geometric heterogeneity and/or spherical rim widths had significantly better prognosis. These novel imaging biomarkers have a strong individual and combined prognostic value for GBM patients. KEY POINTS: • Three-dimensional segmentation on magnetic resonance images allows the study of geometric measures. • Patients with small width of contrast enhancing areas have better prognosis. • The irregularity of contrast enhancing areas predicts survival in glioblastoma patients.

Agreement in Metastatic Spinal Cord Compression.

BACKGROUND: Metastatic epidural spinal cord compression (ESCC) is a devastating medical emergency. The purpose of this study was to determine the reliability of the 6-point ESCC scoring system and the identification of the spinal level presenting ESCC. METHODS: Clinical data and imaging from 90 patients with biopsy-proven spinal metastases were provided to 83 specialists from 44 hospitals. The spinal levels presenting metastases and the ESCC scores for each case were calculated twice by each clinician, with a minimum of 6 weeks' interval. Clinicians were blinded to assessments made by other specialists and their own previous assessment. Fleiss kappa (κ) statistic was used to assess intraobserver and interobserver agreement. Subgroup analyses were performed according to clinicians' specialty (medical oncology, neurosurgery, radiology, orthopedic surgery, and radiation oncology), years of experience, and type of hospital. RESULTS: Intraobserver and interobserver agreement on the location of ESCC was substantial (κ>0.61). Intraobserver agreement on the ESCC score was "excellent" (κ=0.82), whereas interobserver agreement was substantial (κ=0.64). Overall agreement with the tumor board classification was substantial (κ=0.71). Results were similar across specialties, years of experience and hospital category. CONCLUSIONS: The ESCC score can help improve communication among clinicians involved in oncology care.

Disc degeneration and chronic low back pain: an association which becomes nonsignificant when endplate changes and disc contour are taken into account.

INTRODUCTION: The objective of this study was to assess the association between severe disc degeneration (DD) and low back pain (LBP). METHODS: A case-control study was conducted with 304 subjects, aged 35-50, recruited in routine clinical practice across six hospitals; 240 cases (chronic LBP patients with a median pain duration of 46 months) and 64 controls (asymptomatic subjects without any lifetime history of significant LBP). The following variables were assessed once, using previously validated methods: gender, age, body mass index (BMI), lifetime smoking exposure, degree of physical activity, severity of LBP, disability, and findings on magnetic resonance (MRI) (disc degeneration, Modic changes (MC), disc protrusion/hernia, annular tears, spinal stenosis, and spondylolisthesis). Radiologists who interpreted MRI were blinded to the subjects' characteristics. A multivariate logistic regression model assessed the association between severe DD and chronic LBP, adjusting for gender, age, BMI, physical activity, MC, disc protrusion/hernia, and spinal stenosis. RESULTS: Severe DD at ≥1 level was found in 46.9 % of the controls and 65.8 % of the cases. Crude odds ratio (95 % CI), for suffering chronic LBP when having severe DD, was 2.06 (1.05; 4.06). After adjusting for "MC" and "disc protrusion/hernia," it was 1.81 (0.81; 4.05). CONCLUSIONS: The association between severe DD and LBP ceases to be significant when adjusted for MC and disc protrusion/hernia. These results do not support that DD as a major cause of chronic LBP.

Volumetric analysis: Rethinking brain metastases response assessment.

Background: The Response Assessment in Neuro-Oncology for Brain Metastases (RANO-BM) criteria are the gold standard for assessing brain metastases (BMs) treatment response. However, they are limited by their reliance on 1D, despite the routine use of high-resolution T1-weighted MRI scans for BMs, which allows for 3D measurements. Our study aimed to investigate whether volumetric measurements could improve the response assessment in patients with BMs. Methods: We retrospectively evaluated a dataset comprising 783 BMs and analyzed the response of 185 of them from 132 patients who underwent stereotactic radiotherapy between 2007 and 2021 at 5 hospitals. We used T1-weighted MRIs to compute the volume of the lesions. For the volumetric criteria, progressive disease was defined as at least a 30% increase in volume, and partial response was characterized by a 20% volume reduction. Results: Our study showed that the proposed volumetric criteria outperformed the RANO-BM criteria in several aspects: (1) Evaluating every lesion, while RANO-BM failed to evaluate 9.2% of them. (2) Classifying response effectively in 140 lesions, compared to only 72 lesions classified by RANO-BM. (3) Identifying BM recurrences a median of 3.3 months earlier than RANO-BM criteria. Conclusions: Our study demonstrates the superiority of volumetric criteria in improving the response assessment of BMs compared to the RANO-BM criteria. Our proposed criteria allow for evaluation of every lesion, regardless of its size or shape, better classification, and enable earlier identification of progressive disease. Volumetric criteria provide a standardized, reliable, and objective tool for assessing treatment response.

Persistent ischiorectal fistula secondary to rectal extrusion of posterior vaginal mesh: Case report.

INTRODUCTION AND HYPOTHESIS: Vaginal mesh has been used for years to try to improve the results of pelvic organ prolapse surgery, but current evidence does not confirm this improvement and instead describes serious and frequent adverse events. CLINICAL CASE: 64-year-old patient with rectal extrusion of posterior vaginal mesh placed 8 years earlier, and persistent left ischiorectal fistula refractory to surgery. She required 5 surgeries, carried out jointly between gynecology and general surgery, to solve, firstly, the bilateral perianal abscess secondary to extrusion of the posterior vaginal mesh into the rectum and then the persistent left ischiorectal fistula, despite the removal of the material prosthetic. Finally, the fistula was solved by injection of platelet-rich plasma. CONCLUSIONS: Vaginal mesh complications often need a multidisciplinary approach, and treatment may require multiple approaches and more than one surgical procedure. In the case of a persistent fistula refractory to surgery, after removing the mesh, non-invasive regenerative therapies that promote vascular growth and tissue regeneration could be considered such as platelet-rich plasma.

Growth dynamics of brain metastases differentiate radiation necrosis from recurrence.

Background: Radiation necrosis (RN) is a frequent adverse event after fractionated stereotactic radiotherapy (FSRT) or single-session stereotactic radiosurgery (SRS) treatment of brain metastases (BMs). It is difficult to distinguish RN from progressive disease (PD) due to their similarities in the magnetic resonance images. Previous theoretical studies have hypothesized that RN could have faster, although transient, growth dynamics after FSRT/SRS, but no study has proven that hypothesis using patient data. Thus, we hypothesized that lesion size time dynamics obtained from growth laws fitted with data from sequential volumetric measurements on magnetic resonance images may help in discriminating recurrent BMs from RN events. Methods: A total of 101 BMs from different institutions, growing after FSRT/SRS (60 PDs and 41 RNs) in 86 patients, displaying growth for at least 3 consecutive MRI follow-ups were selected for the study from a database of 1031 BMs. The 3 parameters of the Von Bertalanffy growth law were determined for each BM and used to discriminate statistically PDs from RNs. Results: Growth exponents in patients with RNs were found to be substantially larger than those of PD, due to the faster, although transient, dynamics of inflammatory processes. Statistically significant differences (P < .001) were found between both groups. The receiver operating characteristic curve (AUC = 0.76) supported the ability of the growth law exponent to classify the events. Conclusions: Growth law exponents obtained from sequential longitudinal magnetic resonance images after FSRT/SRS can be used as a complementary tool in the differential diagnosis between RN and PD.

Growth exponents reflect evolutionary processes and treatment response in brain metastases.

Tumor growth is the result of the interplay of complex biological processes in huge numbers of individual cells living in changing environments. Effective simple mathematical laws have been shown to describe tumor growth in vitro, or simple animal models with bounded-growth dynamics accurately. However, results for the growth of human cancers in patients are scarce. Our study mined a large dataset of 1133 brain metastases (BMs) with longitudinal imaging follow-up to find growth laws for untreated BMs and recurrent treated BMs. Untreated BMs showed high growth exponents, most likely related to the underlying evolutionary dynamics, with experimental tumors in mice resembling accurately the disease. Recurrent BMs growth exponents were smaller, most probably due to a reduction in tumor heterogeneity after treatment, which may limit the tumor evolutionary capabilities. In silico simulations using a stochastic discrete mesoscopic model with basic evolutionary dynamics led to results in line with the observed data.

A comprehensive dataset of annotated brain metastasis MR images with clinical and radiomic data.

Brain metastasis (BM) is one of the main complications of many cancers, and the most frequent malignancy of the central nervous system. Imaging studies of BMs are routinely used for diagnosis of disease, treatment planning and follow-up. Artificial Intelligence (AI) has great potential to provide automated tools to assist in the management of disease. However, AI methods require large datasets for training and validation, and to date there have been just one publicly available imaging dataset of 156 BMs. This paper publishes 637 high-resolution imaging studies of 75 patients harboring 260 BM lesions, and their respective clinical data. It also includes semi-automatic segmentations of 593 BMs, including pre- and post-treatment T1-weighted cases, and a set of morphological and radiomic features for the cases segmented. This data-sharing initiative is expected to enable research into and performance evaluation of automatic BM detection, lesion segmentation, disease status evaluation and treatment planning methods for BMs, as well as the development and validation of predictive and prognostic tools with clinical applicability.

Direct detection and quantification of methylation in nucleic acid sequences using high-resolution melting analysis.

High-resolution melting (HRM) analysis exploits the reduced thermal stability of DNA fragments that contain base mismatches to detect single nucleotide polymorphisms (SNPs). However, the capacity of HRM to reveal other features of DNA chemistry remains unexplored. DNA methylation plays a key role in regulating gene expression and is essential for normal development in many higher organisms. The presence of methylated bases perturbs the double-stranded DNA structure, although its effect on DNA thermal stability is largely unknown. Here, we reveal that methylated DNA has enhanced thermal stability and is sufficiently divergent from nonmethylated DNA to allow detection and quantification by HRM analysis. This approach reliably distinguishes between sequence-identical DNA differing only in the methylation of one base. The method also provides accurate discrimination between mixes of methylated and nonmethylated DNAs, allowing discrimination between DNA that is 1% and 0% methylated and also between 97.5% and 100% methylated. Thus, the method provides a new means of adjusting thermal optima for DNA hybridization and PCR-based techniques and to empirically measure the impact of DNA methylation marks on the thermostability of regulatory regions. In the longer term, it could enable the development of new techniques to quantify methylated DNA.

Structural abnormalities in the substantia nigra and neighbouring nuclei in Tourette's syndrome.

Although midbrain nuclei (substantia nigra, ventral tegmental area, and periaqueductal grey) are considered candidate loci of pathology in Tourette's syndrome (TS), few imaging studies have examined midbrain structure. The objective of this study was to evaluate the presence of subtle structural abnormalities in the midbrain of patients with TS. High-field magnetic resonance imaging (MRI) (1.5- and 3-T) was used in 23 patients with TS and in 20 age- and sex-matched normal control subjects. Tics symptoms were rated using the Yale Global Tic Severity Scale and comorbid neuropsychiatric disorders were evaluated with standardised psychiatric rating scales. MRI scans revealed subtle structural abnormalities consistent with expanded perivascular spaces (EPVS) in the substantia nigra (compacta and reticulata) and neighbouring nuclei in 6 (26%) patients with TS, but in none of the normal control subjects (P = 0.045). Stereotyped movements were more frequent (P = 0.017) amongst TS patients with midbrain EPVS than in TS patients with normal MRI. Parkinsonism, posttraumatic stress disorder and autistic spectrum disorders exclusively occurred in TS patients with midbrain EPVS. There were no significant between-group differences in other comorbid neuropsychiatric disorders and in tics. Although EPVS are generally viewed as incidental findings, our results suggest that when EPVS are located in the midbrain they may be symptomatic. These abnormalities would reduce the actual number of neurons in specific midbrain nuclei (e.g., substantia nigra) and disrupt their connectivity with limbic, associative, and motor circuits.

Efficacy of colonoscopy after an episode of acute diverticulitis and risk of colorectal cancer.

BACKGROUND: Diverticular disease of the colon has a high global prevalence. The guidelines suggest performing a colonoscopy 4-6 weeks after the acute episode to exclude colorectal cancer (CRC). However, these recommendations are based on old studies, when computed tomography was not used to diagnose acute diverticulitis (AD). There are currently some studies showing that CRC incidence is low in uncomplicated AD (UAD). Therefore, we decided to perform this study to determine the CRC incidence after an AD episode and the diagnostic efficacy of colonoscopy in these patients. METHOD: This was a retrospective cohort study that included patients with AD between July 2016 and December 2017. RESULTS: One hundred seventy-four patients had AD. Of these, 46 patients were excluded and we analyzed 128 patients, 72 (56.3%) women and 56 (43.7%) men. Ninety (70.3%) had UAD and 38 (29.7%) complicated AD (CAD). The colonoscopy showed lesions in 18 (14.06%), 5 (3.9%) being CRC. The patients with CRC had shown CAD and were >70 years old (P=0.0001 and P=0.002 respectively). CONCLUSIONS: Routine colonoscopy in patients with UAD appears not have many benefits as a diagnostic tool. However, it has a higher efficacy if the patients have CAD and are >70 years old.

[Relevance of clinical and serum parameters on severe urinary sepsis after renal obstruction.] / Importancia de los parámetros clínicos y analíticos de la sepsis grave en la uropatía obstructiva.

INTRODUCTION: Urosepsis is an underdiagnosed entity with high morbidity and mortality and significant associated costs. The delay in diagnosis leads to an increased risk of multiorgan failure and death. Although its prognosis is better than that of other sepsis, the mortality rate is 20 - 40%. OBJECTIVE: Describe the obstructive uropathy cases (OU) that are complicated by severe sepsis (SS) and identify early biomarkers of SS. MATERIAL AND METHODS: Observational and prospective study of 65 patients with urgent high OU. All patients were evaluated at three different times (0, 24 and 48 hours). An SS predictor model has been constructed and a multivariate risk analysis has been carried out. RESULTS: 64.61% (n=42) developed SS (NSS: n=13). The only statistically significant variables in the 3 moments evaluated and that obtained a good area under the curve [AUROC (>0.70)] were the elevation of neutrophils, procalcitonin, and decrease of bicarbonate. At the time of patient admission, the variable that best predicted SS was the elevation of procalcitonin (AUROC:0.919). SS risk factors (p<0.005) were the history of cancer immunosuppression, and/or urinary tract surgeries, complete UO and high blood values of lactate, potassium and decrease of bicarbonate. The potassium-lactate combination on admission predicted SS with a probability function of 0.805. CONCLUSIONS: There is an analytical profile maintained over the time characteristic of SS that allows anearly identification of patients with OU subsidiary of been complicated with SS.

INTRODUCCIÓN: La Sepsis urinaria obstructiva (SUO) es una entidad infradiagnosticada con una elevada morbimortalidad e importantes costes asociados. El retraso en su diagnóstico condiciona un mayor riesgo de fracaso multiorgánico y fallecimiento. Aunque su pronóstico es mejor que el de otros focos de sepsis, su mortalidad es del 20 - 40%. OBJETIVO: Describir los cuadros de uropatía obstructiva (UO) que se complican con sepsis grave (SG) e identificarlos biomarcadores diagnósticos de SG en la UOde forma precoz.MATERIAL Y MÉTODOS: Estudio observacional y prospectivo de 72 pacientes con UO alta ingresados de manera urgente en el Servicio de Urología del Hospital Clínico Universitario de Valladolid. Todos los pacientes del estudio fueron evaluados en tres momentos diferentes (0, 24 y 48 horas). Se ha creado un modelo predictor de SG y se ha realizado un análisis multivariante de riesgo. RESULTADOS: El 64,61% de los pacientes (n=42) desarrolló SG (NSG: n=13). Las únicas variables estadísticamente significativas en los tres momentos evaluados y que obtenían una buena área bajo la curva [AUROC (>0,70)] fueron la elevación de neutrófilos y procalcitonina y la disminución de bicarbonato. En el momento del ingreso la variable que mejor predecía SG fue la elevación de procalcitonina (AUROC: 0,919). Los factores de riesgo de SG (p<0,05) fueron los antecedentes de cáncer, la inmunosupresión y/o cirugías de vías urinarias, la UO completa y los valores elevados en sangre de lactato y potasio y la disminución del bicarbonato en la gasometría venosa. La combinación potasio-lactato al ingreso predecía SG con una función de probabilidad de 0,805. CONCLUSIONES: Existe un perfil analítico, mantenido en el tiempo, característico de SG que permite la identificación precoz de los pacientes con UO subsidiarios de complicarse con SG.