Acute imaging does not improve ASTRAL score's accuracy despite having a prognostic value.

BACKGROUND: The ASTRAL score was recently shown to reliably predict three-month functional outcome in patients with acute ischemic stroke. AIM: The study aims to investigate whether information from multimodal imaging increases ASTRAL score's accuracy. METHODS: All patients registered in the ASTRAL registry until March 2011 were included. In multivariate logistic-regression analyses, we added covariates derived from parenchymal, vascular, and perfusion imaging to the 6-parameter model of the ASTRAL score. If a specific imaging covariate remained an independent predictor of three-month modified Rankin score > 2, the area-under-the-curve (AUC) of this new model was calculated and compared with ASTRAL score's AUC. We also performed similar logistic regression analyses in arbitrarily chosen patient subgroups. RESULTS: When added to the ASTRAL score, the following covariates on admission computed tomography/magnetic resonance imaging-based multimodal imaging were not significant predictors of outcome: any stroke-related acute lesion, any nonstroke-related lesions, chronic/subacute stroke, leukoaraiosis, significant arterial pathology in ischemic territory on computed tomography angiography/magnetic resonance angiography/Doppler, significant intracranial arterial pathology in ischemic territory, and focal hypoperfusion on perfusion-computed tomography. The Alberta Stroke Program Early CT score on plain imaging and any significant extracranial arterial pathology on computed tomography angiography/magnetic resonance angiography/Doppler were independent predictors of outcome (odds ratio: 0·93, 95% CI: 0·87-0·99 and odds ratio: 1·49, 95% CI: 1·08-2·05, respectively) but did not increase ASTRAL score's AUC (0·849 vs. 0·850, and 0·8563 vs. 0·8564, respectively). In exploratory analyses in subgroups of different prognosis, age or stroke severity, no covariate was found to increase ASTRAL score's AUC, either. CONCLUSIONS: The addition of information derived from multimodal imaging does not increase ASTRAL score's accuracy to predict functional outcome despite having an independent prognostic value. More selected radiological parameters applied in specific subgroups of stroke patients may add prognostic value of multimodal imaging.

Influence of deep sternal wound infection on long-term survival after cardiac surgery.

BACKGROUND: This study aimed to investigate the influence of deep sternal wound infection on long-term survival following cardiac surgery. MATERIAL AND METHODS: In our institutional database we retrospectively evaluated medical records of 4732 adult patients who received open-heart surgery from January 1995 through December 2005. The predictive factors for DSWI were determined using logistic regression analysis. Then, each patient with deep sternal wound infection (DSWI) was matched with 2 controls without DSWI, according to the risk factors identified previously. After checking balance resulting from matching, short-term mortality was compared between groups using a paired test, and long-term survival was compared using Kaplan-Meier analysis and a Cox proportional hazard model. RESULTS: Overall, 4732 records were analyzed. The mean age of the investigated population was 69.3±12.8 years. DSWI occurred in 74 (1.56%) patients. Significant independent predictive factors for deep sternal infections were active smoking (OR 2.19, CI95 1.35-3.53, p=0.001), obesity (OR 1.96, CI95 1.20-3.21, p=0.007), and insulin-dependent diabetes mellitus (OR 2.09, CI95 1.05-10.06, p=0.016). Mean follow-up in the matched set was 125 months, IQR 99-162. After matching, in-hospital mortality was higher in the DSWI group (8.1% vs. 2.7% p=0.03), but DSWI was not an independent predictor of long-term survival (adjusted HR 1.5, CI95 0.7-3.2, p=0.33). CONCLUSIONS: The results presented in this report clearly show that post-sternotomy deep wound infection does not influence long-term survival in an adult general cardio-surgical patient population.

Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

Land use improves spatial predictions of mountain plant abundance but not presence-absence

Question Does a land-use variable improve spatial predictions of plant species presence-absence and abundance models at the regional scale in a mountain landscape? Location Western Swiss Alps. Methods Presence-absence generalized linear models (GLM) and abundance ordinal logistic regression models (LRM) were fitted to data on 78 mountain plant species, with topo-climatic and/or land-use variables available at a 25-m resolution. The additional contribution of land use when added to topo-climatic models was evaluated by: (1) assessing the changes in model fit and (2) predictive power, (3) partitioning the deviance respectively explained by the topo-climatic variables and the land-use variable through variation partitioning, and (5) comparing spatial projections. Results Land use significantly improved the fit of presence-absence models but not their predictive power. In contrast, land use significantly improved both the fit and predictive power of abundance models. Variation partitioning also showed that the individual contribution of land use to the deviance explained by presence-absence models was, on average, weak for both GLM and LRM (3.7% and 4.5%, respectively), but changes in spatial projections could nevertheless be important for some species. Conclusions In this mountain area and at our regional scale, land use is important for predicting abundance, but not presence-absence. The importance of adding land-use information depends on the species considered. Even without a marked effect on model fit and predictive performance, adding land use can affect spatial projections of both presence-absence and abundance models.

Recanalization and Collaterals Predict Outcome in Proximal MCA Occlusion, but neither Penumbra nor Core of Stroke

Data on new predictors of outcome include penumbra core or collaterals.Objective: To test the predictive value of recanalization, collaterals, penumbra and core of ischemia for functional outcome in a large group of patients with MCA occlusion. Method: Consecutive events included prospectively in the Acute Stroke Registry and Analysis of Lausanne from April 2002 to April 2009 with an acute stroke due to proximal MCA occlusion (M1) were considered for analysis. Acute CTA were reviewed to grade the collaterals (dichotomized in poor __50% or good _50% compared to the normal side) and localization of M1 occlusion (proximal or mid-distal). Acute CTP were reviewed and reconstructed to determine penumbra, core and stroke index (penumbra/penumbra_core) of brain ischemia. Good outcome was defined by mRS 0-2 at 3 months.Results: Among 242 events (115 male, mean NIHSS 18.1, SD 5.8, mean age 66, SD 15), 42% were treated with intravenous thrombolysis, and 3% with intraarterial thrombolysis. Collateral status was rated as poor in 53% of events and proximal M1 occlusion was present in 64%. Recanalization determined at 24 hours with CTA was complete in 26% events and partial/absent in 54%.CTP was available for 212 events. Mean penumbra was 88.6 cm3 (median 84.4, SD 53.8), mean core was 54.1 cm3 (median 46.2, SD 45.7) and stroke index was 64% (median 68%, SD 25%). Good outcome was observed in 87 events (36%) and was associated in multivariate logistic regression with thrombolysis (p_0.02, OR_2.5, 95% CI 1.2-5.4), recanalization (p_0.001, OR_4.1, 95% CI 1.9-8.9), lower NIHSS (p_0.001, OR_0.84, 95% CI 0.78-0.91), male gender (p_0.01, OR_2.8, 95% CI 1.3-5.9), mRS prior to stroke (p_0.02, OR_0.5, 95% CI 0.28-0.9) and good collateral status (p_0.005, OR_3, 95% CI 1.4-6.4). Nor penumbra, nor core, nor stroke index were significant in the multivariate model, even if an association was present in the univariate model between good functional outcome and penumbra (p_0.004, OR_1.008, 95% CI 1.003-1.01), core (p_0.001, OR_0.98, 95% CI 0.976-0.99) and strokeindex (p_0.001, OR_16.7, 95% CI 4.6 59.9).Conclusion: MCA recanalization is the best predictor for good functional outcome, followed by collateral status. CTP data did not predict the functional outcome in our large group of M1 occlusion. Author Disclosures: C. Odier: None. P. Michel: Research Grant; Significant; Paion, Lundbeck. Speakers; Modest; Boehringer-Ingelheim. Consultant/Advisory Board; Modest; Boehringer- Ingelheim. Consultant/Advisory Board; Significant; Servier, Lundbeck.

Relationship of imatinib-free plasma levels and target genotype with efficacy and tolerability

Imatinib has revolutionised the treatment of chronic myeloid leukaemia (CML) and gastrointestinal stromal tumours (GIST). Using a nonlinear mixed effects population model, individual estimates of pharmacokinetic parameters were derived and used to estimate imatinib exposure (area under the curve, AUC) in 58 patients. Plasma-free concentration was deduced from a model incorporating plasma levels of alpha(1)-acid glycoprotein. Associations between AUC (or clearance) and response or incidence of side effects were explored by logistic regression analysis. Influence of KIT genotype was also assessed in GIST patients. Both total (in GIST) and free drug exposure (in CML and GIST) correlated with the occurrence and number of side effects (e.g. odds ratio 2.7+/-0.6 for a two-fold free AUC increase in GIST; P<0.001). Higher free AUC also predicted a higher probability of therapeutic response in GIST (odds ratio 2.6+/-1.1; P=0.026) when taking into account tumour KIT genotype (strongest association in patients harbouring exon 9 mutation or wild-type KIT, known to decrease tumour sensitivity towards imatinib). In CML, no straightforward concentration-response relationships were obtained. Our findings represent additional arguments to further evaluate the usefulness of individualizing imatinib prescription based on a therapeutic drug monitoring programme, possibly associated with target genotype profiling of patients.

Cannabis dependence in Swiss adolescents: An exploration of the role of anxiety, coping styles and psychosocial difficulties

This naturalistic cross-sectional study explores how and to what extent cannabis dependence was associated with intrapersonal aspects (anxiety, coping styles) and interpersonal aspects of adolescent functioning (school status, family relationships, peer relationships, social life). A convenience sample of 110 adolescents (aged 12 to 19) was recruited and subdivided into two groups (38 with a cannabis dependence and 72 nondependent) according to DSM-IV-TR criteria for cannabis dependence. Participants completed the State-Trait Anxiety Inventory (STAI-Y), the Coping Across Situations Questionnaire (CASQ), and the Adolescent Drug Abuse Diagnosis (ADAD) interview investigating psychosocial and interpersonal problems in an adolescent's life. Factors associated with cannabis dependence were explored with logistic regression analyses. The results indicated that severity of problems in social life and peer relationships (OR = 1.68, 95% CI = 1.21 - 2.33) and avoidantcoping (OR = 4.22, 95% CI = 1.01 - 17.73) were the only discriminatory factors for cannabis dependence. This model correctly classified 84.5% of the adolescents. These findings are partially consistent with the "self-medication hypothesis" and underlined the importance of peer relationships and dysfunctional coping strategies in cannabis dependence in adolescence. Limitations of the study and implications for clinical work with adolescents are discussed.

Evaluating thermal treeline indicators based on air and soil temperature using an air-to-soil temperature transfer model

In recent research, both soil (root-zone) and air temperature have been used as predictors for the treeline position worldwide. In this study, we intended to (a) test the proposed temperature limitation at the treeline, and (b) investigate effects of season length for both heat sum and mean temperature variables in the Swiss Alps. As soil temperature data are available for a limited number of sites only, we developed an air-to-soil transfer model (ASTRAMO). The air-to-soil transfer model predicts daily mean root-zone temperatures (10cm below the surface) at the treeline exclusively from daily mean air temperatures. The model using calibrated air and root-zone temperature measurements at nine treeline sites in the Swiss Alps incorporates time lags to account for the damping effect between air and soil temperatures as well as the temporal autocorrelations typical for such chronological data sets. Based on the measured and modeled root-zone temperatures we analyzed. the suitability of the thermal treeline indicators seasonal mean and degree-days to describe the Alpine treeline position. The root-zone indicators were then compared to the respective indicators based on measured air temperatures, with all indicators calculated for two different indicator period lengths. For both temperature types (root-zone and air) and both indicator periods, seasonal mean temperature was the indicator with the lowest variation across all treeline sites. The resulting indicator values were 7.0 degrees C +/- 0.4 SD (short indicator period), respectively 7.1 degrees C +/- 0.5 SD (long indicator period) for root-zone temperature, and 8.0 degrees C +/- 0.6 SD (short indicator period), respectively 8.8 degrees C +/- 0.8 SD (long indicator period) for air temperature. Generally, a higher variation was found for all air based treeline indicators when compared to the root-zone temperature indicators. Despite this, we showed that treeline indicators calculated from both air and root-zone temperatures can be used to describe the Alpine treeline position.

Smoking and adolescence: Exploring tobacco consumption and related attitudes in three different age groups in Switzerland

The present study constitutes an investigation of tobacco consumption, related attitudes and individual differences in smoking or non-smoking behaviors in a sample of adolescents of different ages in the French-speaking part of Switzerland. We investigated three school-age groups (7th-grade, 9th-grade, and the second-year of high school) for differences in attitude and social and cognitive dimensions. We present both descriptive and inferential statistics. On an inferential level, we present a binary logistic regression-based model predicting risk of smoking. The resulting model most importantly suggests a strong relationship between smoking and alcohol consumption (both regular and sporadic). We interpret this result in terms of both the impact of the actual campaigns and the cognitive processes associated with adolescence.

Toll-like receptor 2 (TLR2) polymorphisms are associated with reversal reaction in leprosy.

BACKGROUND: Leprosy is characterized by a spectrum of clinical manifestations that depend on the type of immune response against the pathogen. Patients may undergo immunological changes known as "reactional states" (reversal reaction and erythema nodosum leprosum) that result in major clinical deterioration. The goal of the present study was to assess the effect of Toll-like receptor 2 (TLR2) polymorphisms on susceptibility to and clinical presentation of leprosy. METHODS: Three polymorphisms in TLR2 (597C--&gt;T, 1350T--&gt;C, and a microsatellite marker) were analyzed in 431 Ethiopian patients with leprosy and 187 control subjects. The polymorphism-associated risk of developing leprosy, lepromatous (vs. tuberculoid) leprosy, and leprosy reactions was assessed by multivariate logistic regression models. RESULTS: The microsatellite and the 597C--&gt;T polymorphisms both influenced susceptibility to reversal reaction. Although the 597T allele had a protective effect (odds ratio [OR], 0.34 [95% confidence interval {CI}, 0.17-0.68]; P= .002 under the dominant model), homozygosity for the 280-bp allelic length of the microsatellite strongly increased the risk of reversal reaction (OR, 5.83 [95% CI, 1.98-17.15]; P= .001 under the recessive model). These associations were consistent among 3 different ethnic groups. CONCLUSIONS: These data suggest a significant role for TLR-2 in the occurrence of leprosy reversal reaction and provide new insights into the immunogenetics of the disease.

Clinical consequences of imatinib plasma concentrations variability in hemato-oncologic patients

Background: Imatinib has revolutionized the treatment of chronic myeloid leukemia (CML) and gastrointestinal stromal tumors (GIST). Considering the large inter-individual differences in the function of the systems involved in its disposition, exposure to imatinib can be expected to vary widely among patients. This observational study aimed at describing imatinib pharmacokinetic variability and its relationship with various biological covariates, especially plasma alpha1-acid glycoprotein (AGP), and at exploring the concentration-response relationship in patients. Methods: A population pharmacokinetic model (NONMEM) including 321 plasma samples from 59 patients was built up and used to derive individual post-hoc Bayesian estimates of drug exposure (AUC; area under curve). Associations between AUC and therapeutic response or tolerability were explored by ordered logistic regression. Influence of the target genotype (i.e. KIT mutation profile) on response was also assessed in GIST patients. Results: A one-compartment model with first-order absorption appropriately described the data, with an average oral clearance of 14.3 L/h (CL) and volume of distribution of 347 L (Vd). A large inter-individual variability remained unexplained, both on CL (36%) and Vd (63%), but AGP levels proved to have a marked impact on total imatinib disposition. Moreover, both total and free AUC correlated with the occurrence and number of side effects (e.g. OR 2.9±0.6 for a 2-fold free AUC increase; p<0.001). Furthermore, in GIST patients, higher free AUC predicted a higher probability of therapeutic response (OR 1.9±0.5; p<0.05), notably in patients with tumor harboring an exon 9 mutation or wild-type KIT, known to decrease tumor sensitivity towards imatinib. Conclusion: The large pharmacokinetic variability, associated to the pharmacokinetic-pharmacodynamic relationship uncovered are arguments to further investigate the usefulness of individualizing imatinib prescription based on TDM. For this type of drug, it should ideally take into consideration either circulating AGP concentrations or free drug levels, as well as KIT genotype for GIST.

Predictive factors of adrenal insufficiency in patients admitted to acute medical wards: a case control study.

BACKGROUND: Adrenal insufficiency is a rare and potentially lethal disease if untreated. Several clinical signs and biological markers are associated with glucocorticoid failure but the importance of these factors for diagnosing adrenal insufficiency is not known. In this study, we aimed to assess the prevalence of and the factors associated with adrenal insufficiency among patients admitted to an acute internal medicine ward. METHODS: Retrospective, case-control study including all patients with high-dose (250 μg) ACTH-stimulation tests for suspected adrenal insufficiency performed between 2008 and 2010 in an acute internal medicine ward (n = 281). Cortisol values <550 nmol/l upon ACTH-stimulation test were considered diagnostic for adrenal insufficiency. Area under the ROC curve (AROC), sensitivity, specificity, negative and positive predictive values for adrenal insufficiency were assessed for thirteen symptoms, signs and biological variables. RESULTS: 32 patients (11.4%) presented adrenal insufficiency; the others served as controls. Among all clinical and biological parameters studied, history of glucocorticoid withdrawal was the only independent factor significantly associated with patients with adrenal insufficiency (Odds Ratio: 6.71, 95% CI: 3.08 -14.62). Using a logistic regression, a model with four significant and independent variable was obtained, regrouping history of glucocorticoid withdrawal (OR 7.38, 95% CI [3.18 ; 17.11], p-value <0.001), nausea (OR 3.37, 95% CI [1.03 ; 11.00], p-value 0.044), eosinophilia (OR 17.6, 95% CI [1.02; 302.3], p-value 0.048) and hyperkalemia (OR 2.41, 95% CI [0.87; 6.69], p-value 0.092). The AROC (95% CI) was 0.75 (0.70; 0.80) for this model, with 6.3 (0.8 - 20.8) for sensitivity and 99.2 (97.1 - 99.9) for specificity. CONCLUSIONS: 11.4% of patients with suspected adrenal insufficient admitted to acute medical ward actually do present with adrenal insufficiency, defined by an abnormal response to high-dose (250 μg) ACTH-stimulation test. A history of glucocorticoid withdrawal was the strongest factor predicting the potential adrenal failure. The combination of a history of glucocorticoid withdrawal, nausea, eosinophilia and hyperkaliemia might be of interest to suspect adrenal insufficiency.

Association of different lipid measures for atherogenic lipid fractions and risk of coronary events in patients receiving combination antiretroviral therapy: the Swiss HIV Cohort Study

Background: Evidence for a better performance of different highly atherogenic versus traditional lipid parameters for coronary heart disease (CHD) risk prediction is conflicting. We investigated the association of the ratios of sma11 dense low density lipoprotein(LDL)/apoplipoprotein A, aolipoprotein B/apolipoprotein A-I and total cholesterol! HDL-cholesterol and CHD events in patients on combination antiretroviral therapy (cART).Methods: Case control study nested into the Swiss HIV Cohort Study: for each cART-treated patient with a first coronary event between April 1, 2000 and July 31, 2008 (case) we selected four control patients (1) that were without coronary events until the date of the event of the index case, (2) had a plasma sample within ±30 days of the sample date of the respective case, (3) received cART and (4) were then matched for age, gender and smoking status. Lipoproteins were measured by ultracentrifugation. Conditional logistic regression models were used to estimate the independent effects of different lipid ratios and the occurrence of coronary events.Results: In total, 98 cases (19 fatal myocardial infarctions [MI] and 79 non-fatal coronary events [53 definite MIs, 15 possible MIs and 11 coronary angioplasties or bypassesJ) were matched with 392 controls. Cases were more often injecting drug users, less likely to be virologically suppressed and more often on abacavir-containing regimens. In separa te multivariable models of total cholesterol, triglycerides, HDL-cholesterol, systolic blood pressure, abdominal obesity, diabetes and family history of CHD, small dense-LDL and apolipoprotein B were each statistically significantly associated with CHD events (for 1 mg/dl increase: odds ratio [OR] 1.05, 95% CI 1.00-1.11 and 1.15, 95% CI 1.01-1.31, respectively), but the ratiosof small dense-LDLlapolipoprotein A-I (OR 1.26, 95% CI 0.95-1.67), apolipoprotein B/apolipoprotein A-I (OR 1.02, 95% CI 0.97-1.07) and HDL-cholesterol! total cholesterol (OR 0.99 95% CI 0.98-1.00) were not. Following adjustment for HIV related and cART variables these associations were weakened in each model: apolipoprotein B (OR 1.27, 95% CI 1.00-1.30), sd-LDL (OR 1.04, 95% CI 0.99-1.20), small dense-LDLlapolipoprotein A-I (OR 1.17, 95% CI 0.87-1.58), apolipoprotein B/apolipoprotein A-I (OR 1.02, 95% CI 0.97-1.07) and total cholesterolJHDL- cholesterol (OR 0.99, 95% CI 0.99-1.00).Conclusions: In patients receiving cART, small dense-LDL and apolipoprotein B showed the strongest associations with CHD events in models controlling for traditional CHD risk factors including total cholesterol and triglycerides. Adding small dense LDLlapoplipoprotein A-l, apolipoprotein B/apolipoprotein A-I and total cholesterol! HDL-cholesterol ratios did not further improve models of lipid parameters and associations of increased risk for CHD events.

Early multimodal outcome prediction after cardiac arrest in patients treated with hypothermia.

OBJECTIVES: Therapeutic hypothermia and pharmacological sedation may influence outcome prediction after cardiac arrest. The use of a multimodal approach, including clinical examination, electroencephalography, somatosensory-evoked potentials, and serum neuron-specific enolase, is recommended; however, no study examined the comparative performance of these predictors or addressed their optimal combination. DESIGN: Prospective cohort study. SETTING: Adult ICU of an academic hospital. PATIENTS: One hundred thirty-four consecutive adults treated with therapeutic hypothermia after cardiac arrest. MEASUREMENTS AND MAIN RESULTS: Variables related to the cardiac arrest (cardiac rhythm, time to return of spontaneous circulation), clinical examination (brainstem reflexes and myoclonus), electroencephalography reactivity during therapeutic hypothermia, somatosensory-evoked potentials, and serum neuron-specific enolase. Models to predict clinical outcome at 3 months (assessed using the Cerebral Performance Categories: 5 = death; 3-5 = poor recovery) were evaluated using ordinal logistic regressions and receiving operator characteristic curves. Seventy-two patients (54%) had a poor outcome (of whom, 62 died), and 62 had a good outcome. Multivariable ordinal logistic regression identified absence of electroencephalography reactivity (p < 0.001), incomplete recovery of brainstem reflexes in normothermia (p = 0.013), and neuron-specific enolase higher than 33 μg/L (p = 0.029), but not somatosensory-evoked potentials, as independent predictors of poor outcome. The combination of clinical examination, electroencephalography reactivity, and neuron-specific enolase yielded the best predictive performance (receiving operator characteristic areas: 0.89 for mortality and 0.88 for poor outcome), with 100% positive predictive value. Addition of somatosensory-evoked potentials to this model did not improve prognostic accuracy. CONCLUSIONS: Combination of clinical examination, electroencephalography reactivity, and serum neuron-specific enolase offers the best outcome predictive performance for prognostication of early postanoxic coma, whereas somatosensory-evoked potentials do not add any complementary information. Although prognostication of poor outcome seems excellent, future studies are needed to further improve prediction of good prognosis, which still remains inaccurate.

Diagnostic value of vestibulo-ocular reflex parameters in the detection and characterization of labyrinthine lesions.

OBJECTIVE: To evaluate the power of various parameters of the vestibulo-ocular reflex (VOR) in detecting unilateral peripheral vestibular dysfunction and in characterizing certain inner ear pathologies. STUDY DESIGN: Prospective study of consecutive ambulatory patients presenting with acute onset of peripheral vertigo and spontaneous nystagmus. SETTING: Tertiary referral center. PATIENTS: Seventy-four patients (40 females, 34 males) and 22 normal subjects (11 females, 11 males) were included in the study. Patients were classified in three main diagnoses: vestibular neuritis: 40; viral labyrinthitis: 22; Meniere's disease: 12. METHODS: The VOR function was evaluated by standard caloric and impulse rotary tests (velocity step). A mathematical model of vestibular function was used to characterize the VOR response to rotational stimulation. The diagnostic value of the different VOR parameters was assessed by uni- and multivariable logistic regression. RESULTS: In univariable analysis, caloric asymmetry emerged as the most powerful VOR parameter in identifying unilateral vestibular deficit, with a boundary limit set at 20%. In multivariable analysis, the combination of caloric asymmetry and rotational time constant asymmetry significantly improved the discriminatory power over caloric alone (p&lt;0.0001) and produced a detection score with a correct classification of 92.4%. In discriminating labyrinthine diseases, different combinations of the VOR parameters were obtained for each diagnosis (p&lt;0.003) supporting that the VOR characteristics differ between the three inner ear disorders. However, the clinical usefulness of these characteristics in separating the pathologies was limited. CONCLUSION: We propose a powerful logistic model combining the indices of caloric and time constant asymmetries to detect a peripheral vestibular loss, with an accuracy of 92.4%. Based on vestibular data only, the discrimination between the different inner ear diseases is statistically possible, which supports different pathophysiologic changes in labyrinthine pathologies.