Transcultural Adaptation and Validation of the Fonseca Anamnestic Index in a Spanish Population with Temporomandibular Disorders.

Abstract Background. The Fonseca Anamnestic Index (FAI) offers a simple method to screen temporomandibular disorders (TMD). This study aimed to validate the standard version of the FAI in a Spanish population and to analyze the clinimetric properties of the Spanish version of the FAI in patients with TMD.Methods. The sample consisted of 179 subjects aged over 18 years, of which 119 were diagnosed with TMD and 60 were healthy controls. Construct validity (exploratory factor analysis), internal consistency, test-retest reliability, and concurrent validity were analyzed. To discriminate between patients with and without TMD, Receiver Operating Characteristic (ROC) curve analysis was performed.Results. The Spanish version of the FAI showed construct validity formed by three factors. Cronbach’s alpha was 0.820, indicating good internal consistency. The reliability of the items measured with the weighted kappa coefficient was between 0.588 and 0.899, varying between moderate to almost perfect. The intraclass correlation coefficient (ICC) of the total score was 0.938, indicating excellent reliability. The standard error of measurement (SEM) was 6.42, with a minimum detectable change (MDC) of 12.59 points. The concurrent validity showed a significant correlation with headache, neck pain, vertigo and the Mental Component Summary (SF-12 MCS) of the SF-12. However, the relationship with the Physical Component Summary (SF-12 PCS) was not significant. The ROC curve analysis showed a good accuracy of the FAI in differentiating between healthy and TMD patients with an area under the curve (AUC) = 0.869, corresponding to a cut-off point for the FAI of >35 points, with a sensitivity = 83.19% and a specificity = 78.33%.Conclusions. The Spanish version of the FAI is a valid and reliable instrument for diagnosing people with TMD, with appropriate general clinimetric properties. Discrimination between patients with and without TMD is excellent.

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The Stigma of Suicide Scale

Crisis ◽

10.1027/0227-5910/a000156 ◽

2013 ◽

Vol 34 (1) ◽

pp. 13-21 ◽

Cited By ~ 82

Author(s):

Philip J. Batterham ◽

Alison L. Calear ◽

Helen Christensen

Keyword(s):

Construct Validity ◽

Psychometric Properties ◽

Factor Structure ◽

Internal Consistency ◽

Concurrent Validity ◽

Online Survey ◽

National University ◽

Stigmatizing Attitudes ◽

High Internal Consistency ◽

At Home

Background: There are presently no validated scales to adequately measure the stigma of suicide in the community. The Stigma of Suicide Scale (SOSS) is a new scale containing 58 descriptors of a “typical” person who completes suicide. Aims: To validate the SOSS as a tool for assessing stigma toward suicide, to examine the scale’s factor structure, and to assess correlates of stigmatizing attitudes. Method: In March 2010, 676 staff and students at the Australian National University completed the scale in an online survey. The construct validity of the SOSS was assessed by comparing its factors with factors extracted from the Suicide Opinion Questionnaire (SOQ). Results: Three factors were identified: stigma, isolation/depression, and glorification/normalization. Each factor had high internal consistency and strong concurrent validity with the Suicide Opinion Questionnaire. More than 25% of respondents agreed that people who suicided were “weak,” “reckless,” or “selfish.” Respondents who were female, who had a psychology degree, or who spoke only English at home were less stigmatizing. A 16-item version of the scale also demonstrated robust psychometric properties. Conclusions: The SOSS is the first attitudes scale designed to directly measure the stigma of suicide in the community. Results suggest that psychoeducation may successfully reduce stigma.

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Acute heart failure: predicting early in-hospital outcomes

European Journal of Preventive Cardiology ◽

10.1093/eurjpc/zwab061.019 ◽

2021 ◽

Vol 28 (Supplement_1) ◽

Author(s):

M Santos ◽

S Paula ◽

I Almeida ◽

H Santos ◽

H Miranda ◽

...

Keyword(s):

Heart Failure ◽

Logistic Regression ◽

Acute Heart Failure ◽

Roc Curve ◽

Real Life ◽

Study Data ◽

Curve Analysis ◽

Older Age ◽

Invasive Ventilation ◽

Roc Curve Analysis

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Patients (P) with acute heart failure (AHF) are a heterogeneous population. Risk stratification at admission may help predict in-hospital complications and needs. The Get With The Guidelines Heart Failure score (GWTG-HF) predicts in-hospital mortality (M) of P admitted with AHF. ACTION ICU score is validated to estimate the risk of complications requiring ICU care in non-ST elevation acute coronary syndromes. Objective To validate ACTION-ICU score in AHF and to compare ACTION-ICU to GWTG-HF as predictors of in-hospital M (IHM), early M [1-month mortality (1mM)] and 1-month readmission (1mRA), using real-life data. Methods Based on a single-center retrospective study, data collected from P admitted in the Cardiology department with AHF between 2010 and 2017. P without data on previous cardiovascular history or uncompleted clinical data were excluded. Statistical analysis used chi-square, non-parametric tests, logistic regression analysis and ROC curve analysis. Results Among the 300 P admitted with AHF included, mean age was 67.4 ± 12.6 years old and 72.7% were male. Systolic blood pressure (SBP) was 131.2 ± 37.0mmHg, glomerular filtration rate (GFR) was 57.1 ± 23.5ml/min. 35.3% were admitted in Killip-Kimball class (KKC) 4. ACTION-ICU score was 10.4 ± 2.3 and GWTG-HF was 41.7 ± 9.6. Inotropes’ usage was necessary in 32.7% of the P, 11.3% of the P needed non-invasive ventilation (NIV), 8% needed invasive ventilation (IV). IHM rate was 5% and 1mM was 8%. 6.3% of the P were readmitted 1 month after discharge. Older age (p < 0.001), lower SBP (p = 0,035) and need of inotropes (p < 0.001) were predictors of IHM in our population. As expected, patients presenting in KKC 4 had higher IHM (OR 8.13, p < 0.001). Older age (OR 1.06, p = 0.002, CI 1.02-1.10), lower SBP (OR 1.01, p = 0.05, CI 1.00-1.02) and lower left ventricle ejection fraction (LVEF) (OR 1.06, p < 0.001, CI 1.03-1.09) were predictors of need of NIV. None of the variables were predictive of IV. LVEF (OR 0.924, p < 0.001, CI 0.899-0.949), lower SBP (OR 0.80, p < 0.001, CI 0.971-0.988), higher urea (OR 1.01, p < 0.001, CI 1.005-1.018) and lower sodium (OR 0.92, p = 0.002, CI 0.873-0.971) were predictors of inotropes’ usage. Logistic regression showed that GWTG-HF predicted IHM (OR 1.12, p < 0.001, CI 1.05-1.19), 1mM (OR 1.10, p = 1.10, CI 1.04-1.16) and inotropes’s usage (OR 1.06, p < 0.001, CI 1.03-1.10), however it was not predictive of 1mRA, need of IV or NIV. Similarly, ACTION-ICU predicted IHM (OR 1.51, p = 0.02, CI 1.158-1.977), 1mM (OR 1.45, p = 0.002, CI 1.15-1.81) and inotropes’ usage (OR 1.22, p = 0.002, CI 1.08-1.39), but not 1mRA, the need of IV or NIV. ROC curve analysis revealed that GWTG-HF score performed better than ACTION-ICU regarding IHM (AUC 0.774, CI 0.46-0-90 vs AUC 0.731, CI 0.59-0.88) and 1mM (AUC 0.727, CI 0.60-0.85 vs AUC 0.707, CI 0.58-0.84). Conclusion In our population, both scores were able to predict IHM, 1mM and inotropes’s usage.

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Presepsin values and prognostic nutritional index predict mortality in intensive care unit patients with sepsis: a pilot study

BMC Research Notes ◽

10.1186/s13104-021-05659-9 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Yuichiro Shimoyama ◽

Osamu Umegaki ◽

Noriko Kadono ◽

Toshiaki Minami

Keyword(s):

Multivariate Analysis ◽

Roc Curve ◽

Operating Characteristic ◽

Prognostic Nutritional Index ◽

Early Mortality ◽

Curve Analysis ◽

Rank Test ◽

Roc Curve Analysis ◽

Log Rank Test ◽

Nutritional Index

Abstract Objective Sepsis is a major cause of mortality for critically ill patients. This study aimed to determine whether presepsin values can predict mortality in patients with sepsis. Results Receiver operating characteristic (ROC) curve analysis, Log-rank test, and multivariate analysis identified presepsin values and Prognostic Nutritional Index as predictors of mortality in sepsis patients. Presepsin value on Day 1 was a predictor of early mortality, i.e., death within 7 days of ICU admission; ROC curve analysis revealed an AUC of 0.84, sensitivity of 89%, and specificity of 77%; and multivariate analysis showed an OR of 1.0007, with a 95%CI of 1.0001–1.0013 (p = 0.0320).

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Soluble cytotoxic T-lymphocyte–associated antigen 4 (sCTLA-4) as a potential biomarker for diagnosis and evaluation of the prognosis in Glioma

BMC Immunology ◽

10.1186/s12865-021-00422-y ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Jiajia Liu ◽

Xiaoyi Tian ◽

Yan Wang ◽

Xixiong Kang ◽

Wenqi Song

Keyword(s):

T Lymphocyte ◽

Roc Curve ◽

Cytotoxic T Lymphocyte ◽

Tumor Grade ◽

Curve Analysis ◽

Enzyme Linked Immunosorbent Assay ◽

Low Grade ◽

High Grade ◽

Healthy Individuals ◽

Roc Curve Analysis

Abstract Background The cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) is widely considered as a pivotal immune checkpoint molecule to suppress antitumor immunity. However, the significance of soluble CTLA-4 (sCTLA-4) remains unclear in the patients with brain glioma. Here we aimed to investigate the significance of serum sCTLA-4 levels as a noninvasive biomarker for diagnosis and evaluation of the prognosis in glioma patients. Methods In this study, the levels of sCTLA-4 in serum from 50 patients diagnosed with different grade gliomas including preoperative and postoperative, and 50 healthy individuals were measured by an enzyme-linked immunosorbent assay (ELISA). And then ROC curve analysis and survival analyses were performed to explore the clinical significance of sCTLA-4. Results Serum sCTLA-4 levels were significantly increased in patients with glioma compared to that of healthy individuals, and which was also positively correlated with the tumor grade. ROC curve analysis showed that the best cutoff value for sCTLA-4 for glioma is 112.1 pg/ml, as well as the sensitivity and specificity with 82.0 and 78.0%, respectively, and a cut-off value of 220.43 pg/ml was best distinguished in patients between low-grade glioma group and high-grade glioma group with sensitivity 73.1% and specificity 79.2%. Survival analysis revealed that the patients with high sCTLA-4 levels (> 189.64 pg/ml) had shorter progression-free survival (PFS) compared to those with low sCTLA-4 levels (≤189.64 pg/ml). In the univariate analysis, elder, high-grade tumor, high sCTLA-4 levels and high Ki-67 index were significantly associated with shorter PFS. In the multivariate analysis, sCTLA-4 levels and tumor grade remained an independent prognostic factor. Conclusion These findings indicated that serum sCTLA-4 levels play a critical role in the pathogenesis and development of glioma, which might become a valuable predictive biomarker for supplementary diagnosis and evaluation of the progress and prognosis in glioma.

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Predictive CT features for the diagnosis of primary pulmonary mucoepidermoid carcinoma: comparison with squamous cell carcinomas and adenocarcinomas

Cancer Imaging ◽

10.1186/s40644-020-00375-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Xiaohua Ban ◽

Xinping Shen ◽

Huijun Hu ◽

Rong Zhang ◽

Chuanmiao Xie ◽

...

Keyword(s):

Logistic Regression ◽

Roc Curve ◽

Multinomial Logistic Regression ◽

Univariate Analysis ◽

Ct Imaging ◽

Squamous Cell Carcinomas ◽

Curve Analysis ◽

Imaging Features ◽

Roc Curve Analysis ◽

Ct Features

Abstract Background To determine the predictive CT imaging features for diagnosis in patients with primary pulmonary mucoepidermoid carcinomas (PMECs). Materials and methods CT imaging features of 37 patients with primary PMECs, 76 with squamous cell carcinomas (SCCs) and 78 with adenocarcinomas were retrospectively reviewed. The difference of CT features among the PMECs, SCCs and adenocarcinomas was analyzed using univariate analysis, followed by multinomial logistic regression and receiver operating characteristic (ROC) curve analysis. Results CT imaging features including tumor size, location, margin, shape, necrosis and degree of enhancement were significant different among the PMECs, SCCs and adenocarcinomas, as determined by univariate analysis (P < 0.05). Only lesion location, shape, margin and degree of enhancement remained independent factors in multinomial logistic regression analysis. ROC curve analysis showed that the area under curve of the obtained multinomial logistic regression model was 0.805 (95%CI: 0.704–0.906). Conclusion The prediction model derived from location, margin, shape and degree of enhancement can be used for preoperative diagnosis of PMECs.

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Mortality risk prediction in lupus patients complicated with invasive infection in the emergency department: LUPHAS score

Therapeutic Advances in Musculoskeletal Disease ◽

10.1177/1759720x19885559 ◽

2019 ◽

Vol 11 ◽

pp. 1759720X1988555 ◽

Cited By ~ 1

Author(s):

Wanlong Wu ◽

Jun Ma ◽

Yuhong Zhou ◽

Chao Tang ◽

Feng Zhao ◽

...

Keyword(s):

Emergency Department ◽

Prediction Model ◽

Risk Score ◽

Roc Curve ◽

Curve Analysis ◽

Multivariable Logistic Regression Analysis ◽

Invasive Infection ◽

Roc Curve Analysis ◽

All Cause Mortality ◽

Qsofa Score

Background: Infection remains a major cause of morbidity and mortality in patients with systemic lupus erythematosus (SLE). This study aimed to establish a clinical prediction model for the 3-month all-cause mortality of invasive infection events in patients with SLE in the emergency department. Methods: SLE patients complicated with invasive infection admitted into the emergency department were included in this study. Patient’s demographic, clinical, and laboratory characteristics on admission were retrospectively collected as baseline data and compared between the deceased and the survivors. Independent predictors were identified by multivariable logistic regression analysis. A prediction model for all-cause mortality was established and evaluated by receiver operating characteristic (ROC) curve analysis. Results: A total of 130 eligible patients were collected with a cumulative 38.5% 3-month mortality. Lymphocyte count <800/ul, urea >7.6mmol/l, maximum prednisone dose in the past ⩾60 mg/d, quick Sequential Organ Failure Assessment (qSOFA) score, and age at baseline were independent predictors for all-cause mortality (LUPHAS). In contrast, a history of hydroxychloroquine use was protective. In a combined, odds ratio-weighted LUPHAS scoring system (score 3–22), patients were categorized to three groups: low-risk (score 3–9), medium-risk (score 10–15), and high-risk (score 16–22), with mortalities of 4.9% (2/41), 45.9% (28/61), and 78.3% (18/23) respectively. ROC curve analysis indicated that a LUPHAS score could effectively predict all-cause mortality [area under the curve (AUC) = 0.86, CI 95% 0.79–0.92]. In addition, LUPHAS score performed better than the qSOFA score alone (AUC = 0.69, CI 95% 0.59–0.78), or CURB-65 score (AUC = 0.69, CI 95% 0.59–0.80) in the subgroup of lung infections ( n = 108). Conclusions: Based on a large emergency cohort of lupus patients complicated with invasive infection, the LUPHAS score was established to predict the short-term all-cause mortality, which could be a promising applicable tool for risk stratification in clinical practice.

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Right choice of a method for determination of cut-off values: A statistical tool for a diagnostic test

Asian Journal of Medical Sciences ◽

10.3126/ajms.v5i3.9296 ◽

2014 ◽

Vol 5 (3) ◽

pp. 30-34 ◽

Cited By ~ 19

Author(s):

Balkishan Sharma ◽

Ravikant Jain

Keyword(s):

Logistic Regression ◽

Discriminant Analysis ◽

Diagnostic Test ◽

Roc Curve ◽

Traditional Method ◽

Statistical Technique ◽

Curve Analysis ◽

Operating Characteristics ◽

Roc Curve Analysis

Objective: The clinical diagnostic tests are generally used to identify the presence of a disease. The cutoff value of a diagnostic test should be chosen to maximize the advantage that accrues from testing a population of human and others. When a diagnostic test is to be used in a clinical condition, there may be an opportunity to improve the test by changing the cutoff value. To enhance the accuracy of diagnosis is to develop new tests by using a proper statistical technique with optimum sensitivity and specificity. Method: Mean±2SD method, Logistic Regression Analysis, Receivers Operating Characteristics (ROC) curve analysis and Discriminant Analysis (DA) have been discussed with their respective applications. Results: The study highlighted some important methods to determine the cutoff points for a diagnostic test. The traditional method is to identify the cut-off values is Mean±2SD method. Logistic Regression Analysis, Receivers Operating Characteristics (ROC) curve analysis and Discriminant Analysis (DA) have been proved to be beneficial statistical tools for determination of cut-off points.Conclusion: There may be an opportunity to improve the test by changing the cut-off value with the help of a correctly identified statistical technique in a clinical condition when a diagnostic test is to be used. The traditional method is to identify the cut-off values is Mean ± 2SD method. It was evidenced in certain conditions that logistic regression is found to be a good predictor and the validity of the same can be confirmed by identifying the area under the ROC curve. Abbreviations: ROC-Receiver operating characteristics and DA-Discriminant Analysis. Asian Journal of Medical Science, Volume-5(3) 2014: 30-34 http://dx.doi.org/10.3126/ajms.v5i3.9296

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Assessment of Biomarkers for Clinical Diagnosis of Papillary Thyroid Carcinoma with Distant Metastasis

The International Journal of Biological Markers ◽

10.1177/172460081002500106 ◽

2010 ◽

Vol 25 (1) ◽

pp. 38-45 ◽

Cited By ~ 20

Author(s):

Huasheng Liang ◽

Yuhua Zhong ◽

Zuojie Luo ◽

Yu Huang ◽

Huade Lin ◽

...

Keyword(s):

Growth Factor ◽

Papillary Thyroid Carcinoma ◽

Thyroid Carcinoma ◽

Clinical Diagnosis ◽

Distant Metastasis ◽

Roc Curve ◽

Curve Analysis ◽

Papillary Thyroid ◽

Roc Curve Analysis ◽

Thyroid Carcinomas

Early diagnosis and treatment of thyroid cancers are critical for better prognosis and better survival rates. The purpose of this study was to identify potential diagnostic markers for papillary thyroid carcinomas with distant metastasis. Fifty-eight papillary thyroid tumor specimens (27 papillary thyroid carcinomas with distant metastasis and 31 without metastasis) were examined, and protein expression of pituitary tumor-transforming gene (PTTG), E-cadherin, p27kip1, vascular endothelial growth factor (VEGF)-C, metalloproteinase (MMP) 2, MMP9, chemokine receptor CXCR4, and basic fibroblast growth factor (bFGF) in these tumors was assessed by immunohistochemistry. The clinicopathological variables with diagnostic significance were determined by multivariate analysis, and their diagnostic values were evaluated by ROC curve analysis. PTTG, VEGF-C, MMP2, MMP9, CXCR4, and bFGF were overexpressed in metastatic papillary thyroid carcinomas, whereas p27kip1 expression was elevated only in carcinomas lacking metastasis. Multiple-factor binary ordinal logistic regression analysis revealed that PTTG, VEGF-C, MMP2, and bFGF were independently related to biological metastatic behavior in thyroid tumors, suggesting their potential use as biomarkers. ROC curve analysis showed that among these four proteins, VEGF-C and bFGF were the best diagnostic biomarkers. A VEGF-C and bFGF cluster was the most useful factor for the differential diagnosis between metastatic and non-metastatic papillary thyroid cancers. Thus, the combined use of VEGF-C and bFGF as biomarkers may improve the diagnostic accuracy of papillary thyroid carcinoma and may be useful in multimodal screening programs for the clinical diagnosis of papillary thyroid carcinoma and early detection of papillary thyroid carcinoma with distant metastasis.

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The Rowland Universal Dementia Assessment Scale (RUDAS): a multicultural cognitive assessment scale

International Psychogeriatrics ◽

10.1017/s1041610204000043 ◽

2004 ◽

Vol 16 (1) ◽

pp. 13-31 ◽

Cited By ~ 158

Author(s):

Joella E. Storey ◽

Jeffrey T. J. Rowland ◽

David A. Conforti ◽

Hugh G. Dickson

Keyword(s):

Roc Curve ◽

Predictive Accuracy ◽

Geriatric Medicine ◽

Community Dwelling ◽

Assessment Scale ◽

Elderly Persons ◽

Roc Curve Analysis ◽

Simple Method ◽

Cognitive Domains ◽

Cut Point

Objective: To develop and validate a simple method for detecting dementia that is valid across cultures, portable and easily administered by primary health care clinicians.Design: Culture and Health Advisory Groups were used in Stage 1 to develop culturally fair cognitive items. In Stage 2, clinical testing of 42 items was conducted in a multicultural sample of consecutive new referrals to the geriatric medicine outpatient clinic at Liverpool Hospital, Sydney, Australia (n=166). In Stage 3, the predictive accuracy of items was assessed in a random sample of community-dwelling elderly persons stratified by language background and cognitive diagnosis and matched for sex and age (n=90).Measurements: A research psychologist administered all cognitive items, using interpreters when needed. Each patient was comprehensively assessed by one of three geriatricians, who ordered relevant investigations, and implemented a standardized assessment of cognitive domains. The geriatricians also collected demographic information, and administered other functional and cognitive measures. DSM-IV criteria were used to assign cognitive diagnoses. Item validity and weights were assessed using frequency and logistic regression analyses. Receiver-operating characteristic (ROC) curve analysis was used to determine overall predictive accuracy of the RUDAS and the best cut-point for detecting cognitive impairment.Results: The 6-item RUDAS assesses multiple cognitive domains including memory, praxis, language, judgement, drawing and body orientation. It appears not to be affected by gender, years of education, differential performance factors and preferred language. The area under the ROC curve for the RUDAS was 0.94 (95% CI 0.87–0.98). At a cut-point of 23 (maximum score of 30), sensitivity and specificity were 89% and 98%, respectively. Inter-rater (0.99) and test-retest (0.98) reliabilities were very high.Conclusions: The 6-item RUDAS is portable and tests multiple cognitive domains. It is easily interpreted to other languages, and appears to be culturally fair. However, further validation is needed in other settings, and in longitudinal studies to determine its sensitivity to change in cognitive function over time.

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58 Relationship Between Early Laboratory Measures and Neurological Injury in Neonates Undergoing Therapeutic Hypothermia

Paediatrics & Child Health ◽

10.1093/pch/pxab061.045 ◽

2021 ◽

Vol 26 (Supplement_1) ◽

pp. e39-e41

Author(s):

Lilian Kebaya ◽

Mong Tieng Ee ◽

Michael Miller ◽

Soume Bhattacharya

Keyword(s):

Therapeutic Hypothermia ◽

Roc Curve ◽

Base Excess ◽

Curve Analysis ◽

Neurological Injury ◽

Acid Base ◽

Roc Curve Analysis ◽

Baseline Characteristics ◽

Laboratory Measures

Abstract Primary Subject area Neonatal-Perinatal Medicine Background Hypoxic-ischemic encephalopathy (HIE) is a major contributor to morbidity and mortality. Therapeutic hypothermia (TH) is the standard of care for neonates with moderate to severe HIE. Brain magnetic resonance imaging (MRI) is the imaging modality of choice for confirmation of HIE, assessment of injury severity, and prognostication. Reliable, inexpensive and widely available laboratory measures for early identification of risk for neurological injury can play a critical role in the optimal management of neonatal HIE, especially in the resource-limited setting. Our study examined whether derangements in early routine laboratory measures (acid-base, haematological, metabolic) were worse in neonates with MRI findings of neurological injury. Objectives Primary objective: To evaluate the role of early laboratory measures in predicting neurological injury as detected by MRI at 72 hours. Secondary objective: To evaluate the role of early laboratory measures in predicting survival to NICU discharge in patients with HIE. Design/Methods This single-centre, retrospective cohort study included neonates ≥ 35 weeks gestation with moderate to severe HIE, who had undergone therapeutic hypothermia. Based on findings of brain MRI completed within 72 hours of life, our cohort was divided into 2 groups: neonates with, and without, evidence of neurological injury consistent with HIE. Baseline characteristics, as well as laboratory measures, were compared between groups, and a receiver operating characteristic (ROC) curve analysis was conducted to determine the cut-off for prediction of neurological injury based on the highest sensitivity and specificity values. Results 104 neonates were analyzed. Baseline characteristics (Table 1) were similar between both groups, except for cord venous pH and base excess (BE), which were significantly lower in the abnormal MRI group (p = 0.02). In bivariate analysis, pH (at 1 h of age, p = 0.027), BE (at 1 h, p = 0.001, and 6 h of age, p = 0.004), ionized calcium (at 6 h of age, p = 0.02), and platelets (at 1 h of age, p = 0.004) were significantly different in neonates with abnormal MRI. In ROC curve analysis, BE at 1 h of life was the best predictor of abnormal MRI (AUC = 0.71, p = 0.002), with a cut-off value of ≤ -14.95, sensitivity of 67% and specificity of 66% (Figure 1). Conclusion Among neonates with HIE undergoing TH, early laboratory measures such as acid-base status, ionized calcium, and platelet count were worse in neonates with abnormal MRI, in comparison to neonates with normal MRI. Base excess at 1 h of life is a good predictor of abnormal MRI. Future prospective studies to validate these findings are needed

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