Good Discriminative Capacity Research Articles

Development of Machine Learning Algorithms to Predict Patient Dissatisfaction After Primary Total Knee Arthroplasty

BackgroundPostoperative dissatisfaction after primary total knee arthroplasty (TKA) that requires additional care or readmission may impose a significant financial burden to healthcare systems. The purpose of the current study is to develop machine learning algorithms to predict dissatisfaction after TKA. MethodsA retrospective review of consecutive TKA patients between 2014 and 2016 from 1 large academic and 2 community hospitals was performed. Preoperative variables considered for prediction included demographics, medical history, flexion contracture, knee flexion, and outcome scores (patient-reported health state, Knee Society Score [KSS], and KSS-Function [KSS-F]). Recursive feature elimination was used to select features that optimized algorithm performance. Five supervised machine learning algorithms were developed by training with 10-fold cross-validation 3 times. These algorithms were subsequently applied to an independent testing set of patients and assessed by discrimination, calibration, Brier score, and decision curve analysis. ResultsOf 430 patients, a total of 40 (9.0%) were dissatisfied with their outcome after primary TKA at a minimum of 2 years postoperatively. The random forest algorithm achieved the best performance in the independent testing set not used for algorithm development (c-statistic: 0.77, calibration intercept: 0.087, calibration slope: 0.74, Brier score: 0.082). The most important factors for predicting dissatisfaction were age, number of medical comorbidities, presence of one or more drug allergies, preoperative patient-reported health state score, and preoperative KSS. ConclusionThe current study developed machine learning algorithms based on partially modifiable risk factors for predicting dissatisfaction after TKA. This model demonstrates good discriminative capacity for identifying those at greatest risk for dissatisfaction and may allow for preoperative health optimization.

Disability and perceived stress in primary care patients with major depression.

Major depressive disorder (MDD) is highly prevalent in the Spanish primary care (PC) setting and the leading cause of disability in Spain. The aim of this study was to evaluate several key psychometric properties of the Sheehan Disability Scale (SDS) in patients with or without MDD and varying degrees of symptom severity using the Patient Health Questionnaire-9 (PHQ-9). A total of 1,704 PC patients participating in the PsicAP clinical trial completed the SDS and PHQ-9. We evaluated the factor structure, measurement invariance across gender, internal consistency, and the discriminative and predictive validity. Confirmatory factor analyses revealed a unifactorial model of the SDS containing 4 items (SDS-4) with the best model fit (CFI: .99; GFI: .99; TLI: 96; RMSEA: .10). This model contained the three life domain items (work, family, and social life) plus perceived stress (PS) with significant loadings. The internal consistency of the SDS-4 was acceptable in patients with or without MDD, regardless of symptom severity. The SDS-4 also showed good discriminative capacity and acceptable predictive validity in all subsamples. These findings support the use of the SDS-4 to assess depression-related disability in patients at Spanish primary care centres.

Predicting Post-Cesarean Surgical Site Infections: A Secondary Analysis of the Consortium on Safe Labor [27P

INTRODUCTION: Surgical site infections (SSI) have been estimated to complicate 2–18% of cesarean deliveries (CD). We sought to establish prediction models for post-CD SSIs, using the Consortium on Safe Labor (CSL), a study involving 12 institutes in all the nine districts in the American College of Obstetricians and Gynecologists (ACOG). METHODS: All the CDs in CSL were included. The primary outcomes were endometritis and wound infections. Covariates were selected from clinical and demographic variables that might alter post-CD SSI risks, using backward stepwise selection. Multi-level modeling was used to account for data arising from the same patients. Model discrimination was assessed by area under a receiver-operator characteristic curve (C-statistics), while model calibration was assessed by comparing the predicted vs empirical probabilities. The study was approved by the Institutional Review Board. RESULTS: In CSL, 208,695 women delivered 228,438 pregnancies between July 2002 and July 2008. There were 65,979 CDs (28.9%), all of which were included in this study. The overall incidences of post-CD endometritis (n=490) and wound infections (n=547) were 0.74% and 0.83%, respectively. The C-statistics for the endometritis and wound infection models were 0.89 and 0.80, respectively, demonstrating good discrimination capacity. The endometritis model demonstrated good calibration, mainly when the estimated risks were low (<2%). The wound infection model was less accurate. CONCLUSION: Methodological challenges remain in predicting relatively rare yet morbid events, such as post-CD SSIs. However, statistical modeling based on national data, such as CSL, and the Birth Registry led by ACOG, may provide opportunities to better predict and prevent post-CD SSIs.

Validation of the French Index for the Prediction of Waitlist Mortality in a New Cohort of Candidates

We derived and validated from the cohort of patients registered on the national registry CRISTAL, between January 2010 and December 2014, the Candidate Risk Score (CRS), predicting waitlist mortality. The CRS, converted into the Cardiac Risk Index (CRI), ranging from 0 to 40, includes 4 variables, venoarterial extracorporeal membrane oxygenator (VA-ECMO) use, plasma concentrations of natriuretic peptides (NP), glomerular filtration rate (GFR) and total serum bilirubin level. This study aimed to validate the CRI within the cohort of candidates listed on the CRISTAL registry between January 2018 and March 2019. All patients, aged 16 years or older, registered on the national registry CRISTAL, for heart transplantation, between January 2018 and March 2019, without score exception, (N=617) were included. The main outcome was 3-month waitlist mortality or delisting for worsening medical condition. Survival curves were estimated using Kaplan Meier method. Three-month survival curves stratified by CRI category were compared with the log rank test. The CRI calibration was assessed by calculating the correlation between the observed and predicted 3-month mortality by CRI decile. The slope of the calibration straight line was calculated. The CRI showed a good discriminative capacity with 3-month survival ranging from 34.8% [17.7%-52.6%] and 63.4% [43.0%-78.2%] in the highest (35-40) and second highest (30-34) CRI categories to 97.7% [93.1%-99.3%] and 93.4% [84.7%-97.2%] in the lowest (0-14) and second lowest (15-20) CRI categories(Figure). The correlation between predicted and observed 3-month waitlist mortality was excellent (r=0.90) and the slope of the calibration straight line was 0.93. This study validates the use of the CRI as a predictor of waitlist mortality in adult candidates. Currently the CRI is the cornerstone of the French heart allocation system.

Decision Tree Analysis for Prostate Cancer Prediction in Patients with Serum PSA 10 ng/ml or Less

Abstract Serum prostate-specific antigen (PSA) testing increases the number of persons who undergo prostate biopsy. However, the best possible strategy for selecting patients for prostate biopsy has not yet been defined. The aim of this study was to develop a classification and regression tree (CART) decision model that can be used to predict significant prostate cancer (PCa) in the course of prostate biopsy for patients with serum PSA levels of 10 ng/ml or less. The following clinicopathological characteristics of patients who had undergone ultrasound-guided transrectal prostate biopsy were collected: age, PSA, digital rectal examination, volume of the prostate, and PSA density (PSAD). CART analysis was carried out by using all predictors. Different aspects of the predictive performances of the prediction model were assessed. In this retrospective study, significant PCa values were detected in 26 (26.8%) of a total of 97 patients. The CART model had three branching levels based on PSAD as the most decisive variable and age. The model sensitivity was 73.1%, the specificity was 80.3% and the accuracy was 78.3%. Our model showed an area under the receiver operating characteristic curve of 82.6%. The model was well calibrated. In conclusion, CART analysis determined that PSAD was the key parameter for the identification of patients with a minimal risk for positive biopsies. The model showed a good discrimination capacity that surpassed individual predictors. However, before recommending its use in clinical practice, an evaluation of a larger and more complete database is necessary for the prediction of significant PCa.

Elevation of serum ferritin levels for predicting a poor outcome in hospitalized patients with influenza infection

ObjectivesThere is increasing evidence that ferritin is a key marker of macrophage activation, but its potential role in influenza infection remains unexplored. Our aim was to assess whether hyperferritinaemia (ferritin ≥500 ng/mL) could be a marker of poor prognosis in hospitalized patients with confirmed influenza A infection. MethodsWe prospectively recruited all hospitalized adult patients who tested positive for the influenza A rRT-PCR assay performed on respiratory samples in two consecutive influenza periods (2016–17 and 2017–18). Poor outcome was defined as the presence of at least one of the following: respiratory failure, admission to the intensive care unit, or in-hospital mortality. ResultsAmong 494 patients, 68 (14%) developed poor outcomes; 112 patients (23%) had hyperferritinaemia (39/68, 57% in the poor-outcome group versus 73/426, 17% in the remaining patients, p < 0.0001). Median serum ferritin levels were significantly higher in the subgroup of patients with poor outcomes (609 ng/mL, range 231–967 versus 217 ng/mL, range 140–394, p < 0.0001). In multivariate analysis, hyperferritinaemia was associated with a five-fold increase in the odds ratio of developing poor outcome. After adjusting for classic influenza risk factors, ferritin remained as a significant predictive factor in all exploratory models. Ferritin levels had a good discriminative capacity with an area under the ROC curve of 0.72 (95% confidence interval (CI) 0.65–0.8, p < 0.001) and an overall diagnostic accuracy for predicting poor outcome of 79.3% (95%CI 75.4–82.7%). ConclusionsSerum ferritin may discriminate a subgroup of patients with influenza infection who have a higher risk of developing a poor outcome.

Abstract P3-07-04: A dedicated nomogram to predict nodal pathological complete response in node-positive breast cancer patients undergoing neoadjuvant chemotherapy

Abstract Background and rationale In breast cancer patients with nodal metastases at presentation, neoadjuvant chemotherapy (NAC) may downstage axillary disease. Until a few years ago, axillary lymph node dissection (ALND) has been the standard of care for node positive disease, irrespective of nodal status after completion of NAC. However, nodal pathologic complete response (pCR) is well documented in about 40-70% of women presenting with cN+ status at baseline. In this subset of patiens, ALND is therefore unnecessary. Sentinel lymph node (SLN) biopsy is accepted as a staging procedure for clinically node negative patients at baseline. Recent trials have assessed the feasibility of SLN biopsy also for patients who had clinical conversion of nodal status from cN+ to ycN0, if at least three SLNs are retrieved. However, a higher false-negative rate is the major point of controversy about adoption of SLN biopsy in these patients. A preoperative predictive model, able to assess the likelihood of axillary pCR after NAC, could help to select those patients who might be suitable candidates for SLN surgery. This approach could provide reliable nodal staging information, avoiding unjustified ALNDs and associated morbidities. Methods A retrospective review of all node-positive breast cancer patients treated by NAC between November 2000 and April 2019 at the Breast Unit of IRCCS Maugeri Hospital was performed. Patients were considered as cN+ in case of palpable axillary lymph nodes and/or suspicious lymphadenopathy on ultrasound and/or biopsy-proven nodal metastasis. After NAC completion, all patients have been treated by ALND. Baseline pre-NAC and post-NAC variables were collected and analyzed in a multivariate analysis to find predictors of axillary pCR. Identified predictors were included to develop a dedicated nomogram. Results A total of 371 clinically node-positive patients were identified. Axillary pCR (ypN0 status) was achieved in 142 patients (38%). In multivariate analysis, post-NAC clinical N stage (ycN0 vs ycN+, OR 4.61, 95%CI 2.73-7.78, p&amp;lt;0.0001), biomolecular subtype (for triple-negative breast cancer: OR 4.36, 95%CI 1.45-13.15, p=0.009; for ER+/HER2+: OR 3.68, 95%CI 1.86-7.3, p=0.0002; for ER-/HER2+: OR 3.03, 95%CI 1.06-8.62, p=0.038)-) and clinical complete response on the breast assessed on ultrasound (OR 2.26, 95%CI 1.11-4.59, p=0.024) resulted to be the strongest indipendent predictors of axillary pCR. Based on statistical findings and clinically relevant factors, a nomogram for prediction of pCR after NAC was developed and included the above-mentioned variables and Ki67, grading and pre-NAC clinical T stage. The developed model demonstrated a good discrimination capacity (AUC: 0.77). Conclusions The developed nomogram could help to identify, among patiens cN+ at time of diagnosis, those more likely to achieve nodal pCR after completing NAC. In clinical practice, this tool could contribute to select suitable cadidates for SLN biopsy, preventing them from unnecessary ALND. Citation Format: Fabio Corsi, Valentina Forlini, Daniela Bossi, Sara Albasini, Marta Truffi, Luca Sorrentino. A dedicated nomogram to predict nodal pathological complete response in node-positive breast cancer patients undergoing neoadjuvant chemotherapy [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-07-04.

66 Simple bedside cardiovascular autonomic examinations for predicting chronotropic incompetence

Abstract Background Simple bedside cardiovascular autonomic reflex test (CARTs) are usually used to determine cardiovascular autonomic neuropathy (CAN). CAN may contribute to chronotropic incompetence (CI) which is the inability of the heart rate (HR) to rise in proportion to an increase in metabolic demand. Determination of CI is widely based on measurement of maximum HR during exercise testing. This study aimed to evaluate the role of CARTs to determine CI. Methods We included in 105 patients using a derivation and validation sampling ratio of 2:1. CARTs were performed for analyzing heart rate variation during three parasymphathetic standard tests (deep breathing, lying to standing, Valsava maneuver) and two sympathetic standard tests (systolic blood pressure from lying to standing and diastolic blood pressure during handgrip maneuver). Variables independently associated with CI in multivariable analysis in the derivation set were assigned points based on their respective odds ratios. Results CI group showed significantly lower values of among three parasympathetic standard tests (p &amp;lt; 0.05) but not significantly among two sympathetic standars tests. Valsava maneuver (OR 0.1, p &amp;lt; 0.001, 95%CI 0.001-0.004), deep breathing (OR 0.91, p = 0.025, 95% CI 0.836-0.988), and handgrip maneuver (OR 0.85, p = 0.01, 95% CI 0.744-0.961) were found to be an independent risk factor for CI from multivariate regression analysis. The accuracy of different CART parameters in the prediction of CI was described by the receiver operating curve (ROC) analysis. Regarding logistic regression model, we constructed formula of 15 - ([12 x Valsava maneuver] + [0.1 x deep breathing] + [0.2 x handgrip maneuver]) which will show negative and positive results indicating CI and non-CI, respectively. The resulting score showed good calibration and discriminatory capacity in the derivation (Hosmer-Lemeshow x² 10.051, p = 0.186, AUC = 0.878). The difference between AUCs in the derivation and validation sets was Δ = 0.122 (p = 0.174). Conclusion The decrease in heart rate variations during Valsava maneuver and deep breathing and in diastolic blood pressure during handgrip maneuver seems to be related to development of CI. Formula of CARTs score is a useful tool for predicting CI. Final score sheet based on formula Total score CI probability &amp;lt;-0.1 High probaility 0.2-0.6 Intermediate probability &amp;gt;0.6 Low probability

458 Clinical Utility of Contemporary Guideline-Based High-Risk Features in the Prediction of Cardiac Syncope

Recent European Society of Cardiology Syncope Guidelines highlights key high-risk clinical characteristics to facilitate risk stratification of patients presenting with syncope. We sought to validate the utility of these indices in the prediction of primary cardiac syncope. A retrospective cohort study was performed assessing consecutive patients presenting to the Emergency Department with the primary diagnosis of syncope over a 6-month period. High-risk features were defined as per 2018 ESC syncope guidelines. Among the 400 consecutive patients presenting with syncope, 30 (7.5%) had primary cardiac syncope. Patients with cardiac syncope were significantly older (83.3±10 vs 65.3±23, p=0.001) with a higher proportion of cardiovascular risk factors. After adjusting for variables significant on univariate analyses, high-risk category as per ESC guidelines was the strongest independent predictor for cardiac syncope (odds ratio 3.91; 95% CI 1.3-11.6, p=0.01). The final model demonstrated a c-statistic of 0.77 with appropriate calibration. Absence of high-risk features demonstrated excellent negative predictive value of 97.6% to exclude cardiac syncope. Contemporary syncope guidelines demonstrate good discriminative capacity for predicting cardiogenic syncope. This data supports the routine use of these guidelines for risk stratification in emergency departments.

Determination of serum free light chains as a marker of systemic lupus flare.

The aim of this study was to explore the usefulness of the determination of free light chains (FLC) in serum as a biomarker of flare in patients with systemic lupus erythematosus (SLE) and to analyze the differences in their discriminatory capacity with complement C3 and C4. This was a prospective cohort study. The definition of flare was based on the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) Flare Index. The discriminatory capacity of FLC and C3 and C4 levels was compared using receiver operating characteristic (ROC) curves and the area under the curve (AUC). Forty-six patients were enrolled. Patients with SLE flare showed significantly lower C3 (p = 0.025) and C4 levels (p = 0.028), as well as a higher concentration of lambda light chains (λ-LC) (p = 0.028) compared with the non-flare group. λ-LC, as opposed to kappa light chains and total light chains, demonstrated a discriminatory capacity for detecting the presence of SLE flare (AUC 0.781), with 100% sensitivity, 65% specificity, and 69.6% of patients correctly classified for a cutoff point of ≥ 19.5 mg/L. Complement C3 and C4 also showed a high discriminatory capacity for SLE flare (AUC 0.804 and 0.837, respectively). Comparing λ-LC, C3, and C4, the last one demonstrates better discriminatory capacity for SLE flare with the highest AUC (0.837; 95% CI 0.663-1.000). λ-LC have good discriminatory capacity for SLE flare and could be useful as a biomarker of SLE exacerbation.Key Points• The usefulness of free light chains as a biomarker could be compared with complement.• Lambda free light chains have good discriminatory capacity for SLE flare.• Free light chains are a promising marker of SLE activity.

P4619Comparison of the CRUSADE, ACUITY-HORIZONS, and ACTION bleeding risk scores for predicting in-hospital bleeding in acute myocardial infarction patients undergoing primary PCI

Abstract Background Considering clinical importance of bleeding complications in patients with acute myocardial infarction (AMI), bleeding risk stratification is a key part of the management of these patients. CRUSADE, ACTION and ACUITY-HORIZONS bleeding risk scores are available for predicting in-hospital major bleeding events in patients with acute myocardial infarction. Purpose We aimed to evaluate performance of the three above mentioned risk scores for predicting in-hospital bleeding events defined according to The Bleeding Academic Research Consortium (BARC) criteria. Methods From a prospective electronic registry of a high-volume catheterization laboratory in a period from January 2009 to December 2017, a total of 6505 consecutive patients with acute myocardial infarction who underwent pPCI were included in analysis. Calibration and discrimination of the three risk models were evaluated by the Hosmer-Lemeshow (H-L) goodness-of-fit test and C-statistic, respectively. Results Overall there were 372 (5.7%) bleeding events out of which 117 (1.8%) fulfilled stage BARC 3 or higher bleeding criteria. All three scores showed good model calibration as assessed by the H-Ls test and very good discriminative power for BARC 3 of higher bleeding events detection as assessed by C-statistics (Table 1 &amp; Figure 1): Bleeding events stage BARC 3 or higher were statistically highly related with higher in-hospital mortality (13.7% vs. 3.5%; p&lt;0.000). Table 1 Risk score H-L H-L p AUC 95% CI p CRUSADE 11.46 0.177 0.761 0.750–0.771 vs. ACUITY = ns vs. ACTION &lt;0.000 ACUITY-HORIZONS 10.47 0.236 0735 0.724–0.745 vs. ACTION = ns ACTION 5.74 0.677 0.701 0.698–0.712 Figure 1 Conclusions All three evaluated scores showed very good discriminative capacity for predicting BARC 3 or higher bleeding events in patients undergoing pPCI for AMI.

Identifying critically ill patients with low muscle mass: Agreement between bioelectrical impedance analysis and computed tomography

Low muscle mass and -quality on ICU admission, as assessed by muscle area and -density on CT-scanning at lumbar level 3 (L3), are associated with increased mortality. However, CT-scan analysis is not feasible for standard care. Bioelectrical impedance analysis (BIA) assesses body composition by incorporating the raw measurements resistance, reactance, and phase angle in equations. Our purpose was to compare BIA- and CT-derived muscle mass, to determine whether BIA identified the patients with low skeletal muscle area on CT-scan, and to determine the relation between raw BIA and raw CT measurements. This prospective observational study included adult intensive care patients with an abdominal CT-scan. CT-scans were analysed at L3 level for skeletal muscle area (cm2) and skeletal muscle density (Hounsfield Units). Muscle area was converted to muscle mass (kg) using the Shen equation (MMCT). BIA was performed within 72h of the CT-scan. BIA-derived muscle mass was calculated by three equations: Talluri (MMTalluri), Janssen (MMJanssen), and Kyle (MMKyle). To compare BIA- and CT-derived muscle mass correlations, bias, and limits of agreement were calculated. To test whether BIA identifies low skeletal muscle area on CT-scan, ROC-curves were constructed. Furthermore, raw BIA and CT measurements, were correlated and raw CT-measurements were compared between groups with normal and low phase angle. 110 patients were included. Mean age 59±17 years, mean APACHE II score 17 (11-25); 68% male. MMTalluri and MMJanssen were significantly higher (36.0±9.9kg and 31.5±7.8kg, respectively) and MMKyle significantly lower (25.2±5.6kg) than MMCT (29.2±6.7kg). For all BIA-derived muscle mass equations, a proportional bias was apparent with increasing disagreement at higher muscle mass. MMTalluri correlated strongest with CT-derived muscle mass (r=0.834, p<0.001) and had good discriminative capacity to identify patients with low skeletal muscle area on CT-scan (AUC: 0.919 for males; 0.912 for females). Of the raw measurements, phase angle and skeletal muscle density correlated best (r=0.701, p<0.001). CT-derived skeletal muscle area and -density were significantly lower in patients with low compared to normal phase angle. Although correlated, absolute values of BIA- and CT-derived muscle mass disagree, especially in the high muscle mass range. However, BIA and CT identified the same critically ill population with low skeletal muscle area on CT-scan. Furthermore, low phase angle corresponded to low skeletal muscle area and -density. ClinicalTrials.gov (NCT02555670).

Kappa index as a biomarker for disease severity in multiple sclerosis

The importance of studying the cerebrospinal fluid (CSF) in Multiple Sclerosis (MS) is included in the last McDonald criteria (2018). The study of oligoclonal IgG bands (OCGB) assay is strongly recommended in some situations in which MS diagnosis is uncertain. New biomarkers are developed during the last years. Kappa free light chains (FLC) can predict conversion to MS in patients with Clinically Isolated Syndrome (CIS).The aim of this work is to validate the clinical usefulness of the kappa index, and to establish the actual state of knowledge for kappa index as a biomarker of conversion in CIS patients by a meta-analysis. Kappa index seems more relevant than the mere concentration of kappa FLC in CSF.In the validation study, 334 patients were included; in which 100 were CIS patients. Patients were divided in two groups according kappa index cut-off of 10.62: group 1 (kappa index>10.62); group 2 (kappa index<10.62). In group 1 more patients had positive OCGB, IgG index>0.56 and fulfilled magnetic resonance imaging (MRI) criteria. In contrast, in group 2, more patients showed negative OCGB, IgG index<0.56 and did not fulfilled MRI criteria. While 67.6% of patients from group 1 converted to MS, only 12.5% of patients from group 2 converted to MS. An HR of 6.02 was obtained in the Kaplan-Meier analysis.In the meta-analysis, 8 studies were finally included. The SROC curve revealed a high diagnostic performance for the kappa index as a MS diagnostic biomarker. Despite heterogeneity found between studies, the global OR revealed a good discriminatory capacity of kappa index.In conclusion, kappa index has a great clinical sensitivity and specificity as a support in MS diagnosis. High kappa index increase the probability of CIS to MS conversion. A correct sample processing in the preanalytical stage is key to obtain right results and to allow establishing comparison between laboratories.

The diagnostic and prognostic utility of risk factors defined by the AHA/ACCF on the evaluation of cardiac disease in liver transplantation candidates

BackgroundThe diagnostic and prognostic utility of risk factors proposed by the 2012 American Heart Association and American College of Cardiology Foundation (AHA/ACCF) Scientific Statement on the cardiac assessment of asymptomatic liver transplantation candidates have not been validated. We investigated whether the sum of risk factors proposed by the AHA/ACCF can identify liver transplant candidates at increased cardiac risk.MethodsIn a retrospective cohort of consecutive liver transplantation recipients, we calculated, for each subject, the pre-transplantation sum of AHA/ACCF risk factors (age > 60 years, prior cardiovascular disease, hypertension, dyslipidemia, diabetes mellitus, smoking, and left ventricular hypertrophy). The primary outcome was the presence of severe coronary artery disease (CAD), defined as ≥70% stenosis or ≥ 50% left main stenosis on pre-transplantation angiography. The secondary outcomes were the composite of cardiac death or myocardial infarction (MI) and the composite of cardiac death, MI, or coronary revascularization.ResultsAmong 220 liver transplant recipients, the sum of AHA/ACCF risk factors had good discriminatory capacity for severe CAD [area under the curve, 0.77; 95% confidence interval (CI), 0.62–0.92; P = 0.007]; having ≥3 risk factors provided 75% sensitivity and 77% specificity for severe CAD. During mean post-transplantation follow-up of 48 ± 31 months, having ≥3 risk factors was associated with increased risk of the secondary composite outcomes of cardiac death or MI [hazard ratio, 2.39; P = 0.044] and cardiac death, MI, or coronary revascularization [hazard ratio, 2.39; P = 0.044].ConclusionsIn patients undergoing cardiac assessment prior to liver transplantation, the sum of risk factors proposed by the AHA/ACCF provides significant diagnostic and prognostic utility. Having ≥3 AHA/ACCF risk factors is a reasonable threshold to prompt non-invasive stress testing in asymptomatic liver transplantation candidates.

Early improvement in HAMD-17 and HAMD-7 scores predict response and remission in depressed patients treated with fluoxetine or electroconvulsive therapy

BackgroundCompared to the 17-Item Hamilton Rating Scale for Depression (HAMD-17), the 7-Item Hamilton Rating Scale for Depression (HAMD-7) would be more practical for use in busy clinical settings. Herein, we aim to evaluate (1) whether the HAMD-7 is a reliable and valid measure that is sensitive to changes in depressive symptoms, and (2) whether early improvement of depressive symptoms, as measured by the HAMD-7, is capable of predicting response and remission in patients with major depressive disorder (MDD) during acute treatment with fluoxetine or electroconvulsive therapy (ECT). MethodsThis is a post-hoc analysis of two clinical trials in MDD. Internal consistency, validity, and sensitivity-to-change of the HAMD-17 and HAMD-7 were compared during acute treatment and at 3-month follow-up. Receiver operating characteristic analyses were used to evaluate the discriminative capacity of the HAMD-17 and HAMD-7. ResultsThe HAMD-7 is a reliable and valid measure that is sensitive to changes in depressive symptoms. Early improvement, as measured by either the HAMD-17 or HAMD-7, was capable of predicting response and remission to acute treatment with fluoxetine or ECT with good discriminative capacity. LimitationsThis is a post-hoc analysis of two open-label clinical trials with limited sample sizes. All patients were Taiwanese, which limits the generalizability of our results. ConclusionsHAMD-7 is a clinically useful measure that is capable of detecting early improvement of depressive symptoms. The HAMD-7 may have the potential to inform clinical assessment as part of measurement-based care.

Reply to the editor

The importance of studying the cerebrospinal fluid (CSF) in Multiple Sclerosis (MS) is included in the last McDonald criteria (2018). The study of oligoclonal IgG bands (OCGB) assay is strongly recommended in some situations in which MS diagnosis is uncertain. New biomarkers are developed during the last years. Kappa free light chains (FLC) can predict conversion to MS in patients with Clinically Isolated Syndrome (CIS).The aim of this work is to validate the clinical usefulness of the kappa index, and to establish the actual state of knowledge for kappa index as a biomarker of conversion in CIS patients by a meta-analysis. Kappa index seems more relevant than the mere concentration of kappa FLC in CSF.In the validation study, 334 patients were included; in which 100 were CIS patients. Patients were divided in two groups according kappa index cut-off of 10.62: group 1 (kappa index>10.62); group 2 (kappa index<10.62). In group 1 more patients had positive OCGB, IgG index>0.56 and fulfilled magnetic resonance imaging (MRI) criteria. In contrast, in group 2, more patients showed negative OCGB, IgG index<0.56 and did not fulfilled MRI criteria. While 67.6% of patients from group 1 converted to MS, only 12.5% of patients from group 2 converted to MS. An HR of 6.02 was obtained in the Kaplan-Meier analysis.In the meta-analysis, 8 studies were finally included. The SROC curve revealed a high diagnostic performance for the kappa index as a MS diagnostic biomarker. Despite heterogeneity found between studies, the global OR revealed a good discriminatory capacity of kappa index.In conclusion, kappa index has a great clinical sensitivity and specificity as a support in MS diagnosis. High kappa index increase the probability of CIS to MS conversion. A correct sample processing in the preanalytical stage is key to obtain right results and to allow establishing comparison between laboratories.

Spanish validation of the pathological buying screener in patients with eating disorder and gambling disorder.

Background and aimsPathological buying (PB) is a behavioral addiction that presents comorbidity with several psychiatric disorders. Despite the increase in the prevalence estimates of PB, relatively few PB instruments have been developed. Our aim was to assess the psychometric properties of the Spanish version of the pathological buying screener (PBS) and to explore the associations between PB, psychopathology, and personality traits.MethodsA total of 511 participants, including gambling disorder (GD) and eating disorder (ED) patients diagnosed according to DSM-5 criteria, as well as healthy controls (HCs), took part in the study.ResultsHigher PB prevalence was obtained in ED patients than in the other two study groups (ED 12.5% vs. 1.3% HC and 2.7% GD). Confirmatory factor analysis (CFA) verified the 13-item structure of the PBS, and indexes of convergent and discriminant capacity were estimated. CFA confirmed the structure in two factors (excessive buying behavior and loss of control) with excellent internal consistency (α = .92 and .86, respectively). Good convergent capacity was obtained with external psychopathology and personality measures (positive correlations with novelty seeking and negative associations with self-directedness and harm avoidance were found). Good discriminative capacity to differentiate between the study groups was obtained.Discussion and conclusionsThis study provides support for the reliability and validity of the Spanish adaptation of the PBS. Female sex, higher impulsivity, and higher psychopathology were associated with PB.

Genetically elevated circulating homocysteine concentrations increase the risk of diabetic kidney disease in Chinese diabetic patients.

Diabetic kidney disease (DKD) is a devastating and frequent complication of diabetes mellitus. Here, we first adopted methylenetetrahytrofolate reductase (MTHFR) gene C677T polymorphism as an instrument to infer the possible causal relevance between circulating homocysteine and DKD risk in a Chinese population and next attempted to build a risk prediction model for DKD. This is a hospital‐based case‐control association study. Total 1107 study participants were diagnosed with type 2 diabetes mellitus, including 547 patients with newly diagnosed and histologically confirmed DKD. MTHFR gene C677T polymorphism was determined using the TaqMan method. Carriers of 677TT genotype (14.55 μmol/L) had significantly higher homocysteine concentrations than carriers of 677CT genotype (12.88 μmol/L) (P < 0.001). Carriers of 677TT genotype had a 1.57‐fold increased risk of DKD (odds ratio: 1.57, 95% CI: 1.21‐2.05, P = 0.001) relative to carriers of 677CT genotype after adjusting for confounders. Mendelian randomization analysis revealed that the odds ratio for DKD relative to diabetes mellitus per 5 μmol/L increment of circulating homocysteine concentrations was 3.86 (95% confidence interval: 1.21‐2.05, P < 0.001). In the Logistic regression analysis, hypertension, homocysteine and triglyceride were significantly associated with an increased risk of DKD and they constituted a risk prediction model with good test performance and discriminatory capacity. Taken together, our findings provide evidence that elevated circulating homocysteine concentrations were causally associated with an increased risk of DKD in Chinese diabetic patients.

The Swedish version of the pelvic girdle questionnaire, cross-cultural adaptation and validation

Purpose: The aims of this study were to translate and culturally adapt The Pelvic Girdle Questionnaire to Swedish, and to evaluate the construct and discriminative validity.Materials and methods: A translation and cultural adaptation process was performed according to international guidelines. Pilot tests were conducted among 16 women during pregnancy and post-partum. Analysis of the construct and discriminative validity of the Swedish version of the Pelvic Girdle Questionnaire was performed in a sample of 177 pregnant women suffering from pain in the lumbo-pelvic area. Participants completed the Pelvic Girdle Questionnaire along with Oswestry Disability Index, numeric rating scales for pain intensity and for pelvic girdle pain concerns.Results: The Swedish version of the Pelvic Girdle Questionnaire showed high internal consistency with Cronbach’s alphas between 0.82 and 0.96, good convergent validity with high correlations with the Oswestry Disability Index and the pain intensity numeric rating scale, whereas moderate correlation was shown between the concerns numeric rating scale and the other instruments as hypothesized. Receiver operating characteristic curves showed good discriminatory capacity for women in need of treatment.Conclusions: The Swedish version of the Pelvic Girdle Questionnaire has patient acceptability. It has good construct and discriminative validity for measurements of consequences of pregnancy-related pelvic girdle pain among Swedish speaking women.IMPLICATIONS FOR REHABILITATIONPregnancy-related pelvic girdle pain may be disabling and long-lasting, however treatable when identified.The Pelvic Girdle Questionnaire is the only condition-specific, reliability tested and validated questionnaire for pelvic girdle pain.The Swedish version of the Pelvic Girdle Questionnaire has patient acceptability, good construct validity for pelvic girdle pain among Swedish speaking women, and shows good discriminative capacity for women in need of treatment.

Assessing borderline personality disorder based on the Hierarchical Taxonomy of Psychopathology (HiTOP): Dimensional Clinical Personality Inventory 2 – BPD

Aim of the studyThe aim of this study was to develop a specific version of the Dimensional Clinical Personality Inventory 2 (IDCP-2), a self-reported measure developed in Brazil to pathological personality traits assessment, focused on the assessment of traits related to BPD in accordance to the HiTOP model.Subject or material and methods. In step 1 we developed new factors to cover all the BPD traits according to HiTOP. In step 2, data were collected from 207 adults from the community (N = 207; Mage = 35.9). Participants completed the developed measure (IDCP Borderline Personality Disorder Scale; IDCP-BPD), and factors from IDCP-2, PID-5, FFBI, and FFHI.ResultsExploratory structural equation modeling (E-SEM) suggested a 3-solution for the grouping of the fifteen factors of the IDCP-BPD. Factors and total score reliability was good. Correlations between IDCP-BPD factors and external measures were coherent, corroborating expectations. The bootstrap two-sample t test comparing healthy and pathological group suggested good discrimination capacity of the IDCP-BPD factors, mainly Fragility and Impotency feelings factors.DiscussionFavorable evidences were find for the use of IDCP-BPD to BPD traits measurement. New factors composing this measure seems to extend the coverage of the IDCP-2 factors in measuring BPD symptoms. Correlations suggest that the factors composing IDCP-BPD measure the traits considered as relevant according to HiTOP.ConclusionsDiscriminant capacity of the factors also indicate the use of the measure, although future studies must to replicate the verifications in samples composed by BPD patients.