Excellent Discriminative Power Research Articles

Multi-level region-of-interest CNNs for end to end speech recognition

Efficient and robust automatic speech recognition (ASR) systems are in high demand in the present scenario. Mostly ASR systems are generally fed with cepstral features like mel-frequency cepstral coefficients and perceptual linear prediction. However, some attempts are also made in speech recognition to shift on simple features like critical band energies or spectrogram using deep learning models. These approaches always claim that they have the ability to train directly with the raw signal. Such systems highly depend on the excellent discriminative power of ConvNet layers to separate two phonemes having nearly similar accents but they do not offer high recognition rate. The main reason for limited recognition rate is stride based pooling methods that performs sharp reduction in output dimensionality i.e. at least 75%. To improve the performance, region-based convolutional neural networks (R-CNNs) and Fast R-CNN were proposed but their performances did not meet the expected level. Therefore, a new pooling technique, multilevel region of interest (RoI) pooling is proposed which pools the multilevel information from multiple ConvNet layers. The newly proposed architecture is named as multilevel RoI convolutional neural network (MR-CNN). It is designed by simply placing RoI pooling layers after up to four coarsest layers. It improves extracted features using additional information from the multilevel ConvNet layers. Its performance is evaluated on TIMIT and Wall Street Journal (WSJ) datasets for phoneme recognition. Phoneme error-rate offered by this model on raw speech is 16.4% and 17.1% on TIMIT and WSJ datasets respectively which is slightly better than spectral features.

Psoriatic arthritis screening by the dermatologist: development and first validation of the 'PURE-4 scale'.

Dermatologists are recommended to ask psoriasis patients about musculoskeletal complaints to allow early detection and treatment of psoriatic arthritis (PsA). Screening tools have been developed to help identify patients warranting further rheumatologic assessment, but evidence suggests room for improvement in their diagnostic value and ease of use for outpatient practice. To develop and internally validate a brief tool for dermatologists to screen patients to refer to a rheumatologist for PsA diagnosis. After the literature review, 23 items were selected, covering pain at various locations and inflammatory signs of PsA. The validation study was conducted in medically diagnosed psoriasis patients consecutively recruited between 2012 and 2014 (Saint Joseph Hospital, Paris, France). Patients were enrolled by a dermatologist who helped to complete the questionnaire. Diagnosis of PsA was established by a rheumatologist based on CASPAR criteria. Multivariate logistic regression models were performed to build the scale, assessing discrimination through sensitivity, specificity and area under the ROC curve (AUC). Final model was internally validated using bootstrapping techniques. One hundred and sixty-eight patients were recruited, of whom nine were excluded for known PsA and 21 did not attend the rheumatologist consultation. Of 137 included patients (median age 43 years, 59.6% men), 21 (15.3%) had a PsA diagnosis. Final regression model retained four independent items, including evocative signs of dactylitis, inflammatory heel pain, bilateral buttock pain and peripheral joint pain with swelling in patients aged <50. A total score (the PURE-4) was computed (0-4 points) that demonstrated excellent discriminative power (AUC = 87.6%; Sensitivity = 85.7% and Specificity = 83.6% at the threshold of ≥1/4 points), with no evidence for over-optimism in bootstrapped internal validation. These findings demonstrate the good diagnostic properties of a new screening scale using only four easy-to-collect items. If confirmed in other populations, it may prove useful in outpatient dermatology clinics for triage of psoriasis patients requiring further assessment by the rheumatologist.

Predictors of respiratory failure in patients with Guillain-Barré syndrome: a systematic review and meta-analysis.

To systematically review the literature regarding the ability of clinical features to predict respiratory failure in patients with Guillain-Barré syndrome (GBS). We searched the PubMed and Ovid MEDLINE databases with the search terms "guillain barre syndrome" OR "acute inflammatory demyelinating polyneuropathy" OR "acute motor axonal neuropathy" OR "acute motor sensory axonal neuropathy" AND "respiratory failure" OR "mechanical ventilation". We excluded articles that did not report the results of original research (eg, review articles, letters), were case reports or series (ten or fewer patients), were not available in English, reported research in paediatric populations (16 years of age or younger), or were interventional studies. Article quality was assessed with the Newcastle-Ottawa quality assessment scale. Thirty-four relevant studies were identified. Short time from symptom onset to hospital admission (less than 7 days), bulbar (odds ratio [OR], 9.0; 95% CI, 3.94-20.6; P < 0.001) or neck weakness (OR, 6.36; 95% CI, 2.32-17.5; P < 0.001), and severe muscle weakness at hospital admission were associated with increased risk of intubation. Facial weakness (OR, 3.74; 95% CI, 2.05-6.81; P < 0.001) and autonomic instability (OR, 6.40; 95% CI, 2.83-14.5; P < 0.001) were significantly more frequent in patients requiring intubation in our meta-analyses; however, the differences were not statistically significant in individual multivariable analysis studies. Four predictive models have been developed to assess the risk of respiratory failure for patients with GBS, each with good to excellent discriminative power (area under the receiver operating characteristic curve, 0.79-0.96). Early identification of GBS patients at risk of respiratory failure could reduce the rates of adverse outcomes associated with delayed intubation. Algorithms that predict a patient's risk of subsequent respiratory failure at hospital admission appear more reliable than individual clinical variables.

Urinary exosomal viral microRNA as a marker of BK virus nephropathy in kidney transplant recipients.

ObjectiveBkv-miR-B1-5p, one of the microRNAs encoded by BK virus, was recently reported to be elevated in the blood among the patients with BK virus nephropathy (BKVN). Urinary exosome was suggested to be a possible source of biomarker for kidney diseases, but it was unknown whether it could contain viral microRNA as well as human microRNAs. The aim of this study was to evaluate whether urinary exosomal BK viral microRNA were expressed during replication and could be used to diagnose BKVN in kidney transplant recipients.Materials and methodsIn a cross-sectional multicenter study, we collected and analyzed 458 graft biopsies from 385 kidney transplant recipients. Urine samples were collected at the time of graft biopsy, and microRNAs in urinary exosome were measured once. For 13 patients with BKVN and 67 age, sex-matched kidney transplant recipients, we measured BK viral microRNA B1-5p, 3p and human microRNA-16 in urinary exosomal fraction and compared the diagnostic value with BK viral load in plasma and urine.ResultsPathology proven BKVN was diagnosed in 13 patients (2.8%). High levels of bkv-miR-B1-5p and bkv-miR-B1-3p were shown in all patients with BKVN. Meanwhile, plasma BK viral load assay (cut-off value of ≥ 4.0 log10 copies/mL) showed false negative in 3 cases and urinary BK viral load assay (cut-off value of ≥ 7.0 log10 copies/mL) showed false negative in 1 case among these 13 patients. The receiver operator characteristics curve analysis for bkv-miR-B1-5p and bkv-miR-B1-5p/miR-16 showed excellent discriminative power for the diagnosis of BKVN, with area under the curve values of 0.989 and 0.985, respectively.ConclusionsThis study suggests that urinary exosomal bkv-miR-B1-5p and bkv-miR-B1-5p/miR-16 could be surrogate markers for the diagnosis of BKVN.

GATA transcription factors in testicular adrenal rest tumours.

Testicular adrenal rest tumours (TARTs) are benign adrenal-like testicular tumours that frequently occur in male patients with congenital adrenal hyperplasia. Recently, GATA transcription factors have been linked to the development of TARTs in mice. The aim of our study was to determine GATA expression in human TARTs and other steroidogenic tissues. We determined GATA expression in TARTs (n = 16), Leydig cell tumours (LCTs; n = 7), adrenal (foetal (n = 6) + adult (n = 10)) and testis (foetal (n = 13) + adult (n = 8)). We found testis-like GATA4, and adrenal-like GATA3 and GATA6 gene expressions by qPCR in human TARTs, indicating mixed testicular and adrenal characteristics of TARTs. Currently, no marker is available to discriminate TARTs from LCTs, leading to misdiagnosis and incorrect treatment. GATA3 and GATA6 mRNAs exhibited excellent discriminative power (area under the curve of 0.908 and 0.816, respectively), while immunohistochemistry did not. GATA genes contain several CREB-binding sites and incubation with 0.1 mM dibutyryl cAMP for 4 h stimulated GATA3, GATA4 and GATA6 expressions in a human foetal testis cell line (hs181.tes). Incubation of adrenocortical cells (H295RA) with ACTH, however, did not induce GATA expression in vitro. Although ACTH did not dysregulate GATA expression in the only human ACTH-sensitive in vitro model available, our results do suggest that aberrant expression of GATA transcription factors in human TARTs might be involved in TART formation.

Reliability of Hindfoot Alignment Using Weightbearing CT Semi Automatic Software

Category: Ankle, Hindfoot, Imaging Introduction/Purpose: Hindfoot Alignment (HA) on 2D radiographs presents anatomical and operator-related bias. In this study, weightbearing CT (WBCT) was used to measure HA using a semi-automatic software which gives HA as a value of Foot Ankle Offset (FAO) after selecting four landmarks (weight bearing points of first and fifth Metatarsals, Calcaneus and center of the ankle joint). We assessed the intra and interobserver reproducibility and the distribution of FAO values in a series of datasets from clinically normal, varus and valgus cases. We hypothesized that reproducibility would be excellent. Furthermore, FAO in normals should have a Gaussian distribution and be significantly different to the varus and valgus groups. Methods: In this level 3, retrospective comparative study, WBCT (PedCAT ®, CurveBeam LLC, Warrington, PA, USA) datasets were obtained from an existing database. The 135 feet were assessed by a senior foot and ankle surgeon as normal, varus or valgus (57, 38 and 40 respectively). Two surgeon investigators (one senior and one trainee) independently analyzed each case using a semi-automatic HA measurement tool (TALAS ™, CurveBeam LLC, Warrington, PA, USA). A third, independent investigator conducted the statistical analysis using Stata® Software. Results: The overall intraoberver and interobserver reliability were 0.99 ± 0.002 and 0.97 ± 0.02 respectively. In normal cases, mean value for FAO was 2.38% ± 2.96, whereas in varus and valgus cases mean was -11.67% ± 6.90 and 11.47% ± 5.79, respectively (p&lt;0.001). The normal population had a Gaussian distribution with a Kolmogorov-Smirnov test &gt; 0.8 Conclusion: This study reports excellent reliability and discriminative power of a semi-automatic 3D measurement tool for Hindfoot Alignment in WBCT.

A single-tube flow cytometric procedure for enhancing the diagnosis and prognostic classification of patients with myelodysplastic syndromes.

We created a simple and effective flow cytometry scoring system (FCSS) for suspected Myelodysplastic syndromes (MDS) samples and evaluated its diagnostic and prognostic potential. Besides evaluating the four parameters suggested by Ogata, we investigated erythroid precursors and mast cells. We evaluated the six-parameter FCSS in a four-color setting (test cohort: 51 patients; 25 controls), then we implemented it into an eight-color setting and tested it on a validation cohort of patients with MDS (n=31). When we compared MDS cases to non-MDS samples in the test cohort, we detected significant differences regarding not only the four major parameters but also two additional ones, namely CD71 rCV% of erythroid precursors (P=.004) and mast cell percentage (MC%) (P=.001). The utilization of the modified six-parameter FCSS provided high sensitivity and specificity both in the four color (84% and 80%, respectively) and in the eight color (81% and 100%, respectively) setting, with an excellent discriminative power between MDS and non-MDS samples. Furthermore, we found significant difference in event-free survival between the risk groups based on the modified six-parameter FCSS (P=.001). We evaluated and validated a single-tube flow cytometric procedure for a simple six-parameter FCSS which has not only high diagnostic but also prognostic power.

Learning spherical hashing based binary codes for face recognition

Local feature descriptor has been widely used in computer vision field due to their excellent discriminative power and strong robustness. However, the forms of such local descriptors are predefined in the hand-crafted way, which requires strong domain knowledge to design them. In this paper, we propose a simple and efficient Spherical Hashing based Binary Codes (SHBC) feature learning method to learn a discriminative and robust binary face descriptor in the data-driven way. Firstly, we extract patch-wise pixel difference vectors (PDVs) by computing the difference between center patch and its neighboring patches. Then, inspired by the fact that hypersphere provide much stronger power in defining a tighter closed region in the original data space than hyperplane, we learn a hypersphere-based hashing function to map these PDVs into low-dimensional binary codes by an efficient iterative optimization process, which achieves both balanced bits partitioning of data points and independence between hashing functions. In order to better capture the semantic information of the dataset, our SHBC also can be used with supervised data embedding method, such as Canonical Correlation Analysis (CCA), namely Supervised-SHBC (S-SHBC). Lastly, we cluster and pool these learned binary codes into a histogram-based feature that describes the co-occurrence of binary codes. And we consider the histogram-based feature as our final feature representation for each face image. We investigate the performance of our SHBC and S-SHBC on FERET, CAS-PEAL-R1, LFW and PaSC databases. Extensive experimental results demonstrate that our SHBC descriptor outperforms other state-of-the-art face descriptors.

Learning iterative quantization binary codes for face recognition

Binary feature descriptors have been widely used in computer vision field due to their excellent discriminative power and strong robustness, and local binary patterns (LBP) and its variations have proven that they are effective face descriptors. However, the forms of such binary feature descriptors are predefined in the hand-crafted way, which requires strong domain knowledge to design them. In this paper, we propose a simple and efficient iterative quantization binary codes (IQBC) feature learning method to learn a discriminative binary face descriptor in the data-driven way. Firstly, similar to traditional LBP method, we extract patch-wise pixel difference vectors (PDVs) by computing and concatenating the difference between center patch and its neighboring patches. Then, inspired by multi-class spectral clustering and the orthogonal Procrustes problem, which both are widely used in image retrieval field, we learn an optimized rotation to minimize the quantization error of mapping data to the vertices of a zero-centered binary hypercube by using iterative quantization scheme. In other words, we learn a feature mapping to project these pixel difference vectors into low-dimensional binary vectors. And our IQBC can be used with unsupervised data embedding method such as principle component analysis (PCA) and supervised data embedding method such as canonical correlation analysis (CCA), namely IQBC-PCA and IQBC-CCA. Lastly, we cluster and pool these projected binary codes into a histogram-based feature that describes the co-occurrence of binary codes. And we consider the histogram-based feature as our final feature representation for each face image. We investigate the performance of our IQBC-PCA and IQBC-CCA on FERET, CAS-PEAL-R1, LFW and PaSC databases. Extensive experimental results demonstrate that our IQBC descriptor outperforms other state-of-the-art face descriptors.

Responsiveness of the 7-item Eustachian Tube Dysfunction Questionnaire.

Baro-challenge-induced Eustachian tube (ET) dysfunction is defined as the presence of aural discomfort, popping, or pain, which only arises in case of ambient pressure changes, without abnormalities on otoscopy or tympanometry. Our primary aim was to determine the discriminative power of the 7-item Eustachian Tube Dysfunction Questionnaire (ETDQ-7) in patients with baro-challenge-induced ET dysfunction in comparison with that in healthy controls. The secondary aim was to determine the responsiveness of ETDQ-7 in patients with baro-challenge-induced obstructive ET dysfunction who underwent balloon dilation tuboplasty (BDET). The accuracy of the diagnostic test was determined on the basis of the area under the curve in receiver-operating curve (ROC) analysis. Responsiveness to change of ETDQ-7 was assessed by exploring preoperative and postoperative ETDQ-7 scores using Cohen's kappa coefficient. Patients were asked whether their complaints improved, remained stable, or deteriorated after BDET. The findings of subjective evaluation were then compared with the difference in the ETDQ-7 score after BDET. In the baro-challenge-induced ET dysfunction group, the median preoperative total ETDQ-7 score was 26, decreasing to 16 after BDET. ROC analysis demonstrated excellent discriminative power for the baro-challenge-induced ET dysfunction group. Cohen's kappa coefficient was 0.633, indicating that there was substantial agreement between the ETDQ-7 values before and after BDET. ETDQ-7 can discriminate between patients with baro-challenge-induced ET dysfunction and healthy controls and can therefore be useful in its diagnosis. Furthermore the ETDQ-7 is responsive to change in patients with baro-challenge-induced ET dysfunction who have undergone BDET, although a larger sample size is required to confirm these preliminary findings.

Applicability of the Zwolle risk score for safe early discharge after primary percutaneous coronary intervention in ST-segment elevation myocardial infarction

Introduction and AimThe optimal length of stay for patients with uncomplicated ST-segment elevation myocardial infarction (STEMI) treated with primary percutaneous coronary intervention (PPCI) is still undetermined. The Zwolle risk score (ZRS) is a simple tool designed to identify patients who can be safely discharged within 72 hours. The purpose of this study was to assess the applicability and performance of the ZRS in our population. MethodsWe studied 276 consecutive patients (mean age 62±14 years, 75% male, 20% Killip class >1) admitted over a two-year period for STEMI and treated with PPCI. ZRS, length of stay, 30-day mortality and readmission were obtained for all patients. Low risk was defined as ZRS ≤3. ResultsThe median ZRS was 3 (interquartile range [IQR] 1–4), with 171 patients (62%) being classified as low risk. Thirty-day mortality was 4.7% (13 patients). Compared to other patients, low-risk patients had shorter length of stay (median 5.0 [IQR 4–7] vs. 7.0 [5–13] days, p<0.001), and lower 30-day mortality (0 vs. 12.4%, p<0.001), yielding a negative predictive value of 100% (95% CI 97.0–100%) for the proposed cutoff. The ZRS showed excellent discriminative power (C-statistic: 0.937, 95% CI 0.906–0.968, p<0.001), and good calibration against the original cohort. ConclusionsThe ZRS appears to perform well in identifying low-risk STEMI patients who could be safely discharged within 72 hours of admission. Using the ZRS in our population could result in a more rational use of in-patient resources.

Applicability of the Zwolle risk score for safe early discharge after primary percutaneous coronary intervention in ST-segment elevation myocardial infarction

Introduction and AimThe optimal length of stay for patients with uncomplicated ST-segment elevation myocardial infarction (STEMI) treated with primary percutaneous coronary intervention (PPCI) is still undetermined. The Zwolle risk score (ZRS) is a simple tool designed to identify patients who can be safely discharged within 72 hours. The purpose of this study was to assess the applicability and performance of the ZRS in our population. MethodsWe studied 276 consecutive patients (mean age 62±14 years, 75% male, 20% Killip class >1) admitted over a two-year period for STEMI and treated with PPCI. ZRS, length of stay, 30-day mortality and readmission were obtained for all patients. Low risk was defined as ZRS ≤3. ResultsThe median ZRS was 3 (interquartile range [IQR] 1–4), with 171 patients (62%) being classified as low risk. Thirty-day mortality was 4.7% (13 patients). Compared to other patients, low-risk patients had shorter length of stay (median 5.0 [IQR 4–7] vs. 7.0 [5–13] days, p<0.001), and lower 30-day mortality (0 vs. 12.4%, p<0.001), yielding a negative predictive value of 100% (95% CI 97.0–100%) for the proposed cutoff. The ZRS showed excellent discriminative power (C-statistic: 0.937, 95% CI 0.906–0.968, p<0.001), and good calibration against the original cohort. ConclusionsThe ZRS appears to perform well in identifying low-risk STEMI patients who could be safely discharged within 72 hours of admission. Using the ZRS in our population could result in a more rational use of in-patient resources.

A new marker of sepsis post burn injury?*.

Accurate diagnosis of sepsis is difficult in patients post burn due to the large inflammatory response produced by the major insult. We aimed to estimate the values of serum N-terminal pro-B-type natriuretic peptide and procalcitonin and the changes in hemodynamic variables as markers of sepsis in critically ill burn patients. Prospective, observational study. A quaternary-level university-affiliated ICU. Fifty-four patients with burns to total body surface area of greater than or equal to 15%, intubated with no previous cardiovascular comorbidities, were enrolled. At admission, a FloTrac/Vigileo system was attached and daily blood samples taken from the arterial catheter. Infection surveillance was carried out daily with patients classified as septic/nonseptic according to American Burns Consensus criteria. N-terminal pro-B-type natriuretic peptide, procalcitonin, and waveform analysis of changes in stroke volume index and systemic vascular resistance index were measured within the first 24 hours after burn and daily thereafter for the length of the ICU stay or until their first episode of sepsis. Prevalences of stroke volume variation less than 12% (normovolemia) with hypotension (systolic blood pressure < 90 mm Hg) were recorded. Patients with sepsis differed significantly from "no sepsis" for N-terminal pro-B-type natriuretic peptide, systemic vascular resistance index, and stroke volume index on days 3-7. Procalcitonin did not differ between sepsis and "no sepsis" except for day 3. Area under the receiver operating characteristic curves showed excellent discriminative power for B-type natriuretic peptide (p = 0.001; 95% CI, 0.99-1.00), systemic vascular resistance index (p < 0.001; 95% CI, 0.97-0.99), and stroke volume index (p < 0.01; 95% CI, 0.96-0.99) in predicting sepsis but not for procalcitonin (not significant; 95% CI, 0.29-0.46). A chi-square crosstab found that there was no relationship between hypotension with normovolemia (stroke volume variation < 12%) and sepsis. Serum N-terminal pro-B-type natriuretic peptide levels and certain hemodynamic changes can be used as an early indicator of sepsis in patients with burn injury. Procalcitonin did not assist in the early diagnosis of sepsis.

Variations in the hospital standardized mortality ratios in Korea.

Objectives:The hospital standardized mortality ratio (HSMR) has been widely used because it allows for robust risk adjustment using administrative data and is important for improving the quality of patient care.Methods:All inpatients discharged from hospitals with more than 700 beds (66 hospitals) in 2008 were eligible for inclusion. Using the claims data, 29 most responsible diagnosis (MRDx), accounting for 80% of all inpatient deaths among these hospitals, were identified, and inpatients with those MRDx were selected. The final study population included 703 571 inpatients including 27 718 (3.9% of all inpatients) in-hospital deaths. Using logistic regression, risk-adjusted models for predicting in-hospital mortality were created for each MRDx. The HSMR of individual hospitals was calculated for each MRDx using the model coefficients. The models included age, gender, income level, urgency of admission, diagnosis codes, disease-specific risk factors, and comorbidities. The Elixhauser comorbidity index was used to adjust for comorbidities.Results:For 26 out of 29 MRDx, the c-statistics of these mortality prediction models were higher than 0.8 indicating excellent discriminative power. The HSMR greatly varied across hospitals and disease groups. The academic status of the hospital was the only factor significantly associated with the HSMR.Conclusions:We found a large variation in HSMR among hospitals; therefore, efforts to reduce these variations including continuous monitoring and regular disclosure of the HSMR are required.

Value of anatomic and physiologic scoring systems in outcome prediction of trauma patients

The goal of this study was to compare the prediction performance of two anatomic scales, the Injury Severity Scale (ISS) and the New Injury Severity Scale (NISS), with two physiologic scales, the Revised Trauma Scale (RTS) and the Simplified Acute Physiology Scale II (SAPS II), in trauma patients. Prospective study carried out over a 16-month period. Emergency department of a teaching hospital. Hospitalized victims of trauma up to 14 years of age. The primary endpoint was the survival status at hospital discharge; the secondary outcome was need for ICU admission. Model discrimination was evaluated by the area under the receiver-operating characteristic curve and model calibration was evaluated using the Hosmer-Lemeshow goodness-of-fit statistic. A total of 1136 patients, with an average age of 37.6 years, fulfilled the inclusion criteria. The mortality rate was 4.5%. The combined rate of hospital death and ICU admission was 17.3%. The ISS and the NISS showed excellent discriminative power for mortality prediction (AUC 0.94 and 0.93, respectively) and ICU admission decision (0.91 and 0.89, respectively), and a good calibration. The SAPS II and the RTS showed lower discriminative power. Combining ISS or NISS with SAPS II did not improve significantly the predictive performance of each scale alone. Both ISS and NISS showed better predictive severity performance compared with RTS and SAPS II in trauma patients. The combination of anatomic scales with physiologic ones did not improve the prediction performance of each scale considered alone.

Detection of Volatile Organic Compounds in Brucella abortus-Seropositive Bison

Brucellosis is of great public health and economic importance worldwide. Detection of brucellosis currently relies on serologic testing of an antibody response to Brucella infection, which suffers from cross-sensitivities to other antibody responses. Here we present a new method for identifying Brucella exposure that is based on profiling volatile organic compounds (VOCs) in exhaled breath. Breath samples from Brucella-seropositive bison and controls were chemically analyzed and demonstrated statistically significant differences in the concentration profiles of five VOCs. A point-of-care device incorporating an array of nanomaterial-based sensors could identify VOC patterns indicative of Brucella exposure with excellent discriminative power, using a statistical algorithm. We show that the patterns were not affected by the animals' environment and that the discriminative power of the approach was stable over time. The Brucella-indicative VOCs and collective patterns that were identified in this pilot study could lead to the development of a novel diagnostic screening test for quickly detecting infected animals chute-side, pen-side, or even remotely in populations of free-ranging ungulates. The promising preliminary results presented encourage subsequent larger scale trials in order to further evaluate the proposed method.

Datos genéticos poblacionales de 15 marcadores tipo «short tandem repeats» empleados en las pruebas de paternidad e identificación de individuos por genética forense en el área metropolitana de la región centro de México

IntroductionNowadays in Mexico the use of short tandem repeats has increased in Forensic practice for individual identification, due to its excellent discriminative power and its widespread use in laboratories around the world. ObjectiveThe aim of this research work was to delve into the knowledge of allelic frequencies from markers such as D8S1179, D21S11, D7S820, CSF1PO, D3S1358, TH01, D13S317, D16S539, D2S1338, D19S433, vWA, TPOX, D18S51, D5S818 and FGA in the metropolitan area in the central region of Mexico. Material and methodsA study about the allelic frequencies obtained from 300 healthy and unrelated individuals was developed. Data were analyzed statistically. Results and conclusionsThe combined power of discrimination was 0.999999999. All loci are in Hardy-Weinberg equilibrium, and show high discrimination for paternity analysis and forensic genetic applications. Results contribute to establishing a representative database of genome admixture in the region, and show the marked genetic heterogeneity that characterizes Latin American populations.

Acute renal failure in cirrhotic patients with severe sepsis: Value of urinary interleukin‐18

Acute renal failure (ARF) is a common complication of liver cirrhosis and severe sepsis. Differentiating functional renal failure from acute tubular necrosis (ATN) has been difficult in this clinical setting. It has been shown that urinary interleukin 18 (IL-18) can serve as a sensitive marker for ARF and ATN. This study was aimed to investigate the diagnostic and prognostic values of urinary IL-18 in ARF associated with liver cirrhosis and severe sepsis. We prospectively evaluated the relationship between urinary IL-18 and clinical outcomes in 168 consecutive cirrhotic patients with severe sepsis. One hundred and eight patients (64.3%) developed ARF at admission to the intensive care unit. ARF was associated with higher urinary IL-18 and impaired effective arterial volume. Renal failure was functional in 64 (59.2%), due to acute tubular necrosis (ATN) in 30 (27.7%), and mixed type in 14 (12.9%). Patients with ATN had significantly higher levels of urinary IL-18, rates of vasopressor dependency, and hospital mortality than those with functional renal failure. By using the areas under receiver operating characteristic (AUROC) curve, urinary IL-18 demonstrated an excellent discriminative power (AUROC 0.882) for diagnosing tubular injury in those with ARF. Meanwhile, hospital survivors had significantly lower urinary and serum IL-18 levels, compared to non-survivors. In multivariate analysis, urinary IL-18, international normalized ratio, and mean arterial pressure were independent factors to predict hospital mortality. Urinary IL-18 can serve as a diagnostic and prognostic marker in cirrhotic patients with severe sepsis.

ACHTUNG-Rule: a new and improved model for prognostic assessment in myocardial infarction

THROMBOLYSIS IN MYOCARDIAL INFARCTION (TIMI), PLATELET GLYCOPROTEIN IIB/IIIA IN UNSTABLE ANGINA: Receptor Suppression Using Integrilin (PURSUIT) and Global Registry of Acute Coronary Events (GRACE) scores have been developed for risk stratification in myocardial infarction (MI). The latter is the most validated score, yet active research is ongoing for improving prognostication in MI. Derivation and validation of a new model for intrahospital, post-discharge and combined/total all-cause mortality prediction - ACHTUNG-Rule - and comparison with the GRACE algorithm. 1091 patients admitted for MI (age 68.4 ± 13.5, 63.2% males, 41.8% acute MI with ST-segment elevation (STEMI)) and followed for 19.7 ± 6.4 months were assigned to a derivation sample. 400 patients admitted at a later date at our institution (age 68.3 ± 13.4, 62.7% males, 38.8% STEMI) and followed for a period of 7.2 ± 4.0 months were assigned to a validation sample. Three versions of the ACHTUNG-Rule were developed for the prediction of intrahospital, post-discharge and combined (intrahospital plus post-discharge) all-cause mortality prediction. All models were evaluated for their predictive performance using the area under the receiver operating characteristic (ROC) curve, calibration through the Hosmer-Lemeshow test and predictive utility within each individual patient through the Brier score. Comparison through ROC curve analysis and measures of risk reclassification - net reclassification improvement index (NRI) or Integrated Discrimination Improvement (IDI) - was performed between the ACHTUNG versions for intrahospital, post-discharge and combined mortality prediction and the equivalent GRACE score versions for intrahospital (GRACE-IH), post-discharge (GRACE-6PD) and post-admission 6-month mortality (GRACE-6). Assessment of calibration and overall performance of the ACHTUNG-Rule demonstrated a good fit (p value for the Hosmer-Lemeshow goodness-of-fit test of 0.258, 0.101 and 0.550 for ACHTUNG-IH, ACHTUNG-T and ACHTUNG-R, respectively) and high discriminatory power in the validation cohort for all the primary endpoints (intrahospital mortality: AUC ACHTUNG-IH 0.886 ± 0.035 vs. AUC GRACE-IH 0.906 ± 0.026; post-discharge mortality: AUC ACHTUNG-R 0.827 ± 0.036 vs. AUC GRACE-6PD 0.811 ± 0.034; combined/total mortality: AUC ACHTUNG-T 0.831 ± 0.028 vs. AUC GRACE-6 0.815 ± 0.033). Furthermore, all versions of the ACHTUNG-Rule accurately reclassified a significant number of patients in different, more appropriate, risk categories (NRI ACHTUNG-IH 17.1%, p (2-sided) = 0.0021; NRI ACHTUNG-R 22.0%, p = 0.0002; NRI ACHTUNG-T 18.6%, p = 0.0012). The prognostic performance of the ACHTUNG-Rule was similar in both derivation and validation samples. All versions of the ACHTUNG-Rule have shown excellent discriminative power and good calibration for predicting intrahospital, post-discharge and combined in-hospital plus post-discharge mortality. The ACHTUNG version for intrahospital mortality prediction was not inferior to its equivalent GRACE model, and ACHTUNG versions for post-discharge and combined/total mortality demonstrated apparent superiority. External validation in wider, independent, preferably multicentre, registries is warranted before its potential clinical implementation.

Improved Parameterization of the Transcranial Doppler Signal

The great potential of transcranial Doppler (TCD) as a tool for neuromonitoring is limited by the current parameterization of the signal. This article proposes a set of new parameters that more accurately represents the shape of the waveform and eliminates a number of confounding factors. This set of parameters was tested in 227 patients with ipsilateral carotid artery stenosis and compared with 31 normal subjects recruited at our laboratory. From the TCD waveform, we calculated on a beat-to-beat basis the maximal change in flow velocity at stroke onset (acceleration or acc), the maximal flow velocity during the first 100 ms of systole (sys1) and the maximal flow velocity in the remaining part of systole (sys2). All data were normalized relative to the mean diastolic flow velocity over an interval ranging from 520 till 600 ms after stroke onset (dias@560). For the group with carotid stenosis compared with the normal controls the average ± SD for acc (20.2 ± 9.5 vs. 20.2 ± 6.7; p = 0.98) and sys1 (1.82 ± 0.38 vs. 1.77 ± 0.56; p = 0.35) did not differ significantly. The average ±SD for sys2 (1.94 ± 0.33 vs. 1.50 ± 0.12; p < 0.001), however, was significantly higher in the group with carotid stenosis than in the group of normal subjects. The difference between sys1 and sys2 (“sys1–sys2”) was lower in the patient group than in controls (−0.12 ± 0.16 vs. 0.27 ± 0.22; p < 0.001). For the acc, there was a significantly higher variance in the group with stenosis than without (p < 0.001). Of the old parameters, the beat-to-beat mean (37.0 ± 13.1 vs. 41.3 ± 15.9; p = 0.17) and the pulsatility index (PI; 1.00 ± 0.26 vs. 0.91 ± 0.23; p = 0.06) were not significantly different between groups. Graphed together the acc and “sys1–sys2” parameters allowed a clear demarcation of both groups whereas in a graph of the old parameters mean and PI both groups overlapped considerably. In conclusion, the proposed set of new parameters not only has theoretical and practical benefits but also has excellent discriminative power in a group of carotid patients compared with normal controls.