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PubMed2005

An improved biclustering algorithm and its application to gene expression spectrum analysis.

Cheng and Church algorithm is an important approach in biclustering algorithms. In this paper, the process of the extended space in the second stage of Cheng and Church algorithm is improved and the selections of two important parameters are discussed. The results of the improved algorithm used in the gene expression spectrum analysis show that, compared with Cheng and Church algorithm, the quality of clustering results is enhanced obviously, the mining expression models are better, and the data possess a strong consistency with fluctuation on the condition while the computational time does not increase significantly.

Algorithms↗

PubMed2003

An EM algorithm for mapping binary disease loci: application to fibrosarcoma in a four-way cross mouse family.

Many diseases show dichotomous phenotypic variation but do not follow a simple Mendelian pattern of inheritance. Variances of these binary diseases are presumably controlled by multiple loci and environmental variants. A least-squares method has been developed for mapping such complex disease loci by treating the binary phenotypes (0 and 1) as if they were continuous. However, the least-squares method is not recommended because of its ad hoc nature. Maximum Likelihood (ML) and Bayesian methods have also been developed for binary disease mapping by incorporating the discrete nature of the phenotypic distribution. In the ML analysis, the likelihood function is usually maximized using some complicated maximization algorithms (e.g. the Newton-Raphson or the simplex algorithm). Under the threshold model of binary disease, we develop an Expectation Maximization (EM) algorithm to solve for the maximum likelihood estimates (MLEs). The new EM algorithm is developed by treating both the unobserved genotype and the disease liability as missing values. As a result, the EM iteration equations have the same form as the normal equation system in linear regression. The EM algorithm is further modified to take into account sexual dimorphism in the linkage maps. Applying the EM-implemented ML method to a four-way-cross mouse family, we detected two regions on the fourth chromosome that have evidence of QTLs controlling the segregation of fibrosarcoma, a form of connective tissue cancer. The two QTLs explain 50-60% of the variance in the disease liability. We also applied a Bayesian method previously developed (modified to take into account sex-specific maps) to this data set and detected one additional QTL on chromosome 13 that explains another 26% of the variance of the disease liability. All the QTLs detected primarily show dominance effects.

Algorithms↗

PubMed2001

A data analysis algorithm for programmed field-flow fractionation.

An algorithm that employs numerical integration for analysis of field-flow fractionation (FFF) data is presented. The algorithm utilizes detector response, field strength, and channel flow rate data, monitored at discrete time intervals during sample elution to generate a distribution of sample components according to particle size or molecular weight. The field strength and channel flow rate may either be held constant or programmed as functions of time, and it is not necessary for these programs to follow specific mathematical functions. If experimental conditions are monitored during a run, the algorithm can account for any deviation from nominal set conditions. The algorithm also allows calculation of fractionating power for the actual conditions as monitored during the run. The method provides greatly increased flexibility in the application of the FFF family of techniques. It removes the limitations on experimental conditions incurred by adherence to analytically available solutions to FFF theory, allowing ad hoc variation of field strength and other experimental parameters as necessary to increase sensitivity and specificity of the method. An implementation of the algorithm is described that is independent of the FFF technique (i.e., independent of field type) and mode of operation. To reduce computation time, it uses mathematical techniques to reduce the required number of numerical integrations. This is of particular importance when the perturbations to ideal FFF theory, such as those due to the effects of hydrodynamic lift forces, particle-wall or particle-particle interactions, and secondary relaxation, necessitate relatively lengthy numerical calculations.

Algorithms↗

PubMed2006

Automated intensity descent algorithm for interpretation of complex high-resolution mass spectra.

This paper describes a new automated intensity descent algorithm for analysis of complex high-resolution mass spectra. The algorithm has been successfully applied to interpret Fourier transform mass spectra of proteins; however, it should be generally applicable to complex high-resolution mass spectra of large molecules recorded by other instruments. The algorithm locates all possible isotopic clusters by a novel peak selection method and a robust cluster subtraction technique according to the order of descending peak intensity after global noise level estimation and baseline correction. The peak selection method speeds up charge state determination and isotopic cluster identification. A Lorentzian-based peak subtraction technique resolves overlapping clusters in high peak density regions. A noise flag value is introduced to minimize false positive isotopic clusters. Moreover, correlation coefficients and matching errors between the identified isotopic multiplets and the averagine isotopic abundance distribution are the criteria for real isotopic clusters. The best fitted averagine isotopic abundance distribution of each isotopic cluster determines the charge state and the monoisotopic mass. Three high-resolution mass spectra were interpreted by the program. The results show that the algorithm is fast in computational speed, robust in identification of overlapping clusters, and efficient in minimization of false positives. In approximately 2 min, the program identified 611 isotopic clusters for a plasma ECD spectrum of carbonic anhydrase. Among them, 50 new identified isotopic clusters, which were missed previously by other methods, have been discovered in the high peak density regions or as weak clusters by this algorithm. As a result, 18 additional new bond cleavages have been identified from the 50 new clusters of carbonic anhydrase.

Algorithms↗

PubMed2006

Sequence-specific retention calculator. Algorithm for peptide retention prediction in ion-pair RP-HPLC: application to 300- and 100-A pore size C18 sorbents.

Continued development of a new sequence-specific algorithm for peptide retention prediction in RP HPLC is reported. Our discovery of the large effect on the apparent hydrophobicity of N-terminal amino acids produced by the ion-pairing retention mechanism has led to the development of sequence-specific retention calculator (SSRCalc) algorithms. These were optimized for a set of approximately 2000 tryptic peptides confidently identified by off-line microHPLC-MALDI MS (MS/MS) (300-A pore size C18 sorbent, linear water/acetonitrile gradient, and trifluoroacetic acid as ion-pairing modifier). The latest version of the algorithm takes into account amino acid composition, position of the amino acid residues (N- and C-terminal), peptide length, overall hydrophobicity, pI, nearest-neighbor effect of charged side chains (K, R, H), and propensity to form helical structures. A correlation with R2 approximately 0.98 was obtained for the 2000-peptide optimization set. A flexible structure for the SSRC programming code allows easy adaptation to different chromatographic conditions. This was demonstrated by adapting the algorithm (approximately 0.98 R2 value) for a set of approximately 2500 peptides separated on a 100-A pore size C18 column. The SSRCalc algorithm has also been extensively tested for a number of real samples, providing solid support for protein identification and characterization; correlations in the range of 0.95-0.97 R2 value have normally been observed.

Acetonitriles↗

PubMedDate not supplied

A fast exchange algorithm for designing focused libraries in lead optimization.

Combinatorial chemistry is widely used in drug discovery. Once a lead compound has been identified, a series of R-groups and reagents can be selected and combined to generate new potential drugs. The combinatorial nature of this problem leads to chemical libraries containing usually a very large number of virtual compounds, far too large to permit their chemical synthesis. Therefore, one often wants to select a subset of "good" reagents for each R-group of reagents and synthesize all their possible combinations. In this research, one encounters some difficulties. First, the selection of reagents has to be done such that the compounds of the resulting sublibrary simultaneously optimize a series of chemical properties. For each compound, a desirability index, a concept proposed by Harrington,(20) is used to summarize those properties in one fitness value. Then a loss function is used as objective criteria to globally quantify the quality of a sublibrary. Second, there are a huge number of possible sublibraries, and the solutions space has to be explored as fast as possible. The WEALD algorithm proposed in this paper starts with a random solution and iterates by applying exchanges, a simple method proposed by Fedorov(13) and often used in the generation of optimal designs. Those exchanges are guided by a weighting of the reagents adapted recursively as the solutions space is explored. The algorithm is applied on a real database and reveals to converge rapidly. It is compared to results given by two other algorithms presented in the combinatorial chemistry literature: the Ultrafast algorithm of D. Agrafiotis and V. Lobanov and the Piccolo algorithm of W. Zheng et al.

Algorithms↗

PubMed2006

Combined genetic algorithm and multiple linear regression (GA-MLR) optimizer: Application to multi-exponential fluorescence decay surface.

The optimization approach based on the genetic algorithm (GA) combined with multiple linear regression (MLR) method, is discussed. The GA-MLR optimizer is designed for the nonlinear least-squares problems in which the model functions are linear combinations of nonlinear functions. GA optimizes the nonlinear parameters, and the linear parameters are calculated from MLR. GA-MLR is an intuitive optimization approach and it exploits all advantages of the genetic algorithm technique. This optimization method results from an appropriate combination of two well-known optimization methods. The MLR method is embedded in the GA optimizer and linear and nonlinear model parameters are optimized in parallel. The MLR method is the only one strictly mathematical "tool" involved in GA-MLR. The GA-MLR approach simplifies and accelerates considerably the optimization process because the linear parameters are not the fitted ones. Its properties are exemplified by the analysis of the kinetic biexponential fluorescence decay surface corresponding to a two-excited-state interconversion process. A short discussion of the variable projection (VP) algorithm, designed for the same class of the optimization problems, is presented. VP is a very advanced mathematical formalism that involves the methods of nonlinear functionals, algebra of linear projectors, and the formalism of Fréchet derivatives and pseudo-inverses. Additional explanatory comments are added on the application of recently introduced the GA-NR optimizer to simultaneous recovery of linear and weakly nonlinear parameters occurring in the same optimization problem together with nonlinear parameters. The GA-NR optimizer combines the GA method with the NR method, in which the minimum-value condition for the quadratic approximation to chi(2), obtained from the Taylor series expansion of chi(2), is recovered by means of the Newton-Raphson algorithm. The application of the GA-NR optimizer to model functions which are multi-linear combinations of nonlinear functions, is indicated. The VP algorithm does not distinguish the weakly nonlinear parameters from the nonlinear ones and it does not apply to the model functions which are multi-linear combinations of nonlinear functions.

Algorithms↗

PubMed1998

The application of a modified proportional-derivative control algorithm to arterial pressure alarms in anesthesiology.

OBJECTIVE: We have developed an arterial pressure alarm system based on a modified proportional-derivative (PD) controller algorithm, and prospectively tested its ability to predict significant hypotensive episodes, defined as systolic arterial pressure < 80 mmHg, in comparison to conventional limit alarms. METHODS: The alarm algorithm was tuned to detect hypotension using selected invasive arterial pressure traces taken from ten patients who had large intra-operative arterial pressure changes. The algorithm's performance was then tested prospectively in comparison to conventional limit alarms and median filtered limit alarms, set at 85 mmHg and 90 mmHg, for its ability to predict hypotensive episodes in a further 100 patients who required invasive arterial pressure monitoring. RESULTS: For the PD alarm algorithm, onset times for significant hypotensive episodes were between those of limit alarms set at 85 mmHg and 90 mmHg. Offset times were similar to the 85 mmHg limit alarms. The false positive rate was 34% compared with 45-64% for the other alarms (p < 0.01). Using our definitions, there was one false negative in the PD group, being a 15 second drop in observed arterial pressure, when a non invasive blood pressure cuff was inflated above the arterial line. CONCLUSIONS: An arterial pressure alarm system design based on a closed loop control algorithm offered improved perform ance over conventional limit alarms and in addition provided a graded output of severity of the hypotension.

Adolescent↗

PubMed1997

Evaluation of a programming algorithm for the third tachycardia zone in a fourth-generation implantable cardioverter-defibrillator.

The clinical efficacy of electrical algorithms for termination of slow ventricular tachycardia (VT) and ventricular fibrillation (VF) in implantable cardioverter-defibrillators (ICDs) is well established. Such algorithms have not been equally well defined for fast VT reversion. We report the testing of a prospectively designed algorithm for ICDs to treat fast VT that is inherently less responsive to antitachycardia pacing than slow VT. Fourth-generation ICD devices were programmed to three prospectively defined tachycardia detection zones as follows: cycle lengths < or = 260 ms for VF, 270-330 ms for fast VT, and > 330 ms for slow VT. The initial selected therapy for the VF zone was a high-energy biphasic shock (> 15 J), while a 3- or 5-J biphasic shock was usually administered for fast VT, and antitachycardia pacing was initially attempted for slow VT. Initial therapy was followed by backup therapy with high-energy shocks. Twenty-eight patients, 24 of whom were males, all with organic heart disease, with a mean age of 65 +/- 9 years, received either a Medtronic 7219D (23 patients), 7219C (2 patients), 7218SP1 (2 patients), or 7218C (1 patient) ICD with a nonthoracotomy lead system. The defibrillation threshold was 10 +/- 5 J. At predischarge electrophysiologic testing, a single 3- or 5-J shock terminated all episodes of fast VT tested. During a follow-up of 18 +/- 9 months, there were four nonarrhythmic deaths. Fourteen patients (50%) had a total of 21 VF, 44 fast VT, and 202 slow VT episodes. Twenty-three of 24 (96%) VF, 33 of 39 (84%) fast VT, and 193 of 202 (95.5%) slow VT episodes were terminated with the first delivered therapy in each therapy algorithm (p = NS). The overall efficacy of the entire electrical therapy algorithm was 100% for VF, 100% for fast VT, and 98% for slow VT episodes (p = NS). No patient experienced syncope or presyncope during fast VT or VF in this study. We conclude that a third detection and therapy zone can be successfully programmed in ICDs to define a range of fast VT episodes that can be effectively terminated with lower energy cardioversion shocks with comparable success and freedom from arrhythmic symptoms to electrical therapies used for slow VT and VF.

Aged↗

PubMed2001

A genetic algorithm for structure-based de novo design.

Genetic algorithms have properties which make them attractive in de novo drug design. Like other de novo design programs, genetic algorithms require a method to reduce the enormous search space of possible compounds. Most often this is done using information from known ligands. We have developed the ADAPT program, a genetic algorithm which uses molecular interactions evaluated with docking calculations as a fitness function to reduce the search space. ADAPT does not require information about known ligands. The program takes an initial set of compounds and iteratively builds new compounds based on the fitness scores of the previous set of compounds. We describe the particulars of the ADAPT algorithm and its application to three well-studied target systems. We also show that the strategies of enhanced local sampling and re-introducing diversity to the compound population during the design cycle provide better results than conventional genetic algorithm protocols.

Algorithms↗

PubMed1997

Application of a genetic algorithm in the conformational analysis of methylene-acetal-linked thymine dimers in DNA: comparison with distance geometry calculations.

The three-dimensional spatial structure of a methylene-acetal-linked thymine dimer present in a 10 basepair (bp) sense-antisense DNA duplex was studied with a genetic algorithm designed to interpret NOE distance restraints. Trial solutions were represented by torsion angles. This means that bond angles for the dimer trial structures are kept fixed during the genetic algorithm optimization. Bond angle values were extracted from a 10 bp sense-antisense duplex model that was subjected to energy minimization by means of a modified AMBER force field. A set of 63 proton-proton distance restraints defining the methylene-acetal-linked thymine dimer was available. The genetic algorithm minimizes the difference between distances in the trial structures and distance restraints. A large conformational search space could be covered in the genetic algorithm optimization by allowing a wide range of torsion angles. The genetic algorithm optimization in all cases led to one family of structures. This family of the methylene-acetal-linked thymine dimer in the duplex differs from the family that was suggested from distance geometry calculations. It is demonstrated that the bond angle geometry around the methylene-acetal linkage plays an important role in the optimization.

Algorithms↗

PubMed2004

Exact solutions for internuclear vectors and backbone dihedral angles from NH residual dipolar couplings in two media, and their application in a systematic search algorithm for determining protein backbone structure.

We have derived a quartic equation for computing the direction of an internuclear vector from residual dipolar couplings (RDCs) measured in two aligning media, and two simple trigonometric equations for computing the backbone (phi,psi) angles from two backbone vectors in consecutive peptide planes. These equations make it possible to compute, exactly and in constant time, the backbone (phi,psi) angles for a residue from RDCs in two media on any single backbone vector type. Building upon these exact solutions we have designed a novel algorithm for determining a protein backbone substructure consisting of alpha-helices and beta-sheets. Our algorithm employs a systematic search technique to refine the conformation of both alpha-helices and beta-sheets and to determine their orientations using exclusively the angular restraints from RDCs. The algorithm computes the backbone substructure employing very sparse distance restraints between pairs of alpha-helices and beta-sheets refined by the systematic search. The algorithm has been demonstrated on the protein human ubiquitin using only backbone NH RDCs, plus twelve hydrogen bonds and four NOE distance restraints. Further, our results show that both the global orientations and the conformations of alpha-helices and beta-strands can be determined with high accuracy using only two RDCs per residue. The algorithm requires, as its input, backbone resonance assignments, the identification of alpha-helices and beta-sheets as well as sparse NOE distance and hydrogen bond restraints.

Algorithms↗

PubMed2002

Insulin dose during glucocorticoid treatment for fetal lung maturation in diabetic pregnancy: test of an algorithm [correction of analgoritm].

OBJECTIVE: Poor glycemic control is often a serious clinical problem during glucocorticoid treatment for fetal lung maturation in pregnant women with diabetes. An algorithm for improved subcutaneous insulin treatment during glucocorticoid treatment in insulin-dependent diabetic women was developed and tested. STUDY DESIGN: The sample, divided into two cohorts, consisted of all insulin-dependent diabetic women (n=16) receiving glucocorticoid treatment (betamethasone 12 mg i.m., repeated after 24 h) from 1996 to 1999. In the first cohort the increments of insulin dose were based on the level of blood glucose obtained. Based on the first cohort an algorithm to determine increments of insulin dose was developed. In the second cohort (n = 8) the insulin dose was increased by up to 40%, according to the algorithm, starting immediately after glucocorticoid treatment; prior to a detectable increase in blood glucose. RESULTS: After betamethasone, the daily insulin dose for the following 5 days was increased by 6, 38, 36, 27 and 17% in the first cohort vs. 27, 45, 40, 31 and 11% in the second cohort. The algorithm was used in the second cohort. The median blood glucose was 6.7, 14.3, 12.3, 7.7 and 7.7 vs. 7.7, 8.2, 9.6, 7.0 and 7.4 mmol/l (p<0.05 for day 2 and 3) in the two cohorts, respectively. None developed ketoacidosis or severe hypoglycemia. CONCLUSION: An algorithm with an increasing insulin dose of up to 40% shortly after glucocorticoid treatment for fetal lung maturation in diabetic women prevents severe dysregulation of metabolic control.

Adult↗

PubMed1999

Option-4 algorithm for Florida pocket depth probe: reduction in the variance of site-specific probeable crevice depth measurements.

Clinical periodontal measurement is plagued by many sources of error which result in aberrant values (outliers). This study sets out to compare probeable crevice depth measurements (PCD) selected by the option-4 algorithm against those recorded with a conventional double-pass method and to quantify any reduction in site-specific PCD variances. A single clinician recorded full-mouth PCD at 1 visit in 32 subjects (mean age 45.5 years) with moderately advanced chronic adult periodontitis. PCD was recorded over 2 passes at 6 sites per tooth with the Florida Pocket Depth Probes, a 3rd generation probe. The option-4 algorithm compared the 1st pass site-specific PCD value (PCD1) to the 2nd pass site-specific PCD value (PCD2) and, if the difference between these values was >1.00 mm, allowed the recording of a maximum of 2 further measurements (3rd and 4th pass measurements PCD3 and PCD4): 4 site-specific measure-meets were considered to be the maximum subject and tissue tolerance. The algorithm selected the 1st 2 measurements whose difference was < or = 1.00 mm (SPCD1 and SPCD2). If no 2 measurements had a difference < or = 1.00 mm, the examiner was required to select the 2 measurements closest to the rules of the algorithm. 4600 sites were available for analysis. 3992 sites (86.8%) required 2 recordings, 564 sites (12.3%) required 3 recordings and 44 sites (1%) required 4 recordings. Correlation coefficients for PCD1 and PCD2 and SPCD1 and SPCD2 were 0.83 and 0.96, respectively (p=0.00). Site-specific variances were calculated for PCD1 and PCD2 and SPCD1 and SPCD2. The mean of the PCD1/PCD2 site-specific variances (A) was 0.41 mm2 (range 0.00 mm2 to 33.62 mm2), whilst the mean of the SPCD1/SPCD2 variances (B) was 0.1 mm2 (range 0.00 mm2 to 2.0 mm2): the respective medians were 0.08 mm2 and 0.02 mm2. The study demonstrated high intra-examiner PCD agreement. The option-4 algorithm produced a reduction of 75.6% in the mean site-specific variance of PCD1/PCD2 (Y) (Y=[(A-B)/A]X 100) and a 75% reduction in the median site-specific variance of PCD1/PCD2.

Adult↗

PubMed2005

Perceptual tests of an algorithm for musical key-finding.

Perceiving the tonality of a musical passage is a fundamental aspect of the experience of hearing music. Models for determining tonality have thus occupied a central place in music cognition research. Three experiments investigated 1 well-known model of tonal determination: the Krumhansl-Schmuckler key-finding algorithm. In Experiment 1, listeners' percepts of tonality following short musical fragments derived from preludes by Bach and Chopin were compared with predictions of tonality produced by the algorithm; these predictions were very accurate for the Bach preludes but considerably less so for the Chopin preludes. Experiment 2 explored a subset of the Chopin preludes, finding that the algorithm could predict tonal percepts on a measure-by-measure basis. In Experiment 3, the algorithm predicted listeners' percepts of tonal movement throughout a complete Chopin prelude. These studies support the viability of the Krumhansl-Schmuckler key-finding algorithm as well as a model of listeners' tonal perceptions of musical passages.

Adult↗

PubMed2006

Infarct prediction and treatment assessment with MRI-based algorithms in experimental stroke models.

There is increasing interest in using algorithms combining multiple magnetic resonance imaging (MRI) modalities to predict tissue infarction in acute human stroke. We developed and tested a voxel-based generalized linear model (GLM) algorithm to predict tissue infarction in an animal stroke model in order to directly compare predicted outcome with the tissue's histologic outcome, and to evaluate the potential for assessing therapeutic efficacy using these multiparametric algorithms. With acute MRI acquired after unilateral embolic stroke in rats (n=8), a GLM was developed and used to predict infarction on a voxel-wise basis for saline (n=6) and recombinant tissue plasminogen activator (rt-PA) treatment (n=7) arms of a trial of delayed thrombolytic therapy in rats. Pretreatment predicted outcome compared with post-treatment histology was highly accurate in saline-treated rats (0.92+/-0.05). Accuracy was significantly reduced (P=0.04) in rt-PA-treated animals (0.86+/-0.08), although no significant difference was detected when comparing histologic lesion volumes. Animals that reperfused had significantly lower (P<0.01) GLM-predicted infarction risk (0.73+/-0.03) than nonreperfused animals (0.81+/-0.05), possibly reflecting less severe initial ischemic injury and therefore tissue likely more amenable to therapy. Our results show that acute MRI-based algorithms can predict tissue infarction with high accuracy in animals not receiving thrombolytic therapy. Furthermore, alterations in disease progression due to treatment were more sensitively monitored with our voxel-based analysis techniques than with volumetric approaches. Our study shows that predictive algorithms are promising metrics for diagnosis, prognosis and therapeutic evaluation after acute stroke that can translate readily from preclinical to clinical settings.

Algorithms↗

PubMed1999

A comparison of high precision F0 extraction algorithms for sustained vowels.

Perturbation analysis of sustained vowel waveforms is used routinely in the clinical evaluation of pathological voices and in monitoring patient progress during treatment. Accurate estimation of voice fundamental frequency (F0) is essential for accurate perturbation analysis. Several algorithms have been proposed for fundamental frequency extraction. To be appropriate for clinical use, a key consideration is that an F0 extraction algorithm be robust to such extraneous factors as the presence of noise and modulations in voice frequency and amplitude that are commonly associated with the voice pathologies under study. This work examines the performance of seven F0 algorithms, based on the average magnitude difference function (AMDF), the input autocorrelation function (AC), the autocorrelation function of the center-clipped signal (ACC), the autocorrelation function of the inverse filtered signal (IFAC), the signal cepstrum (CEP), the Harmonic Product Spectrum (HPS) of the signal, and the waveform matching function (WM) respectively. These algorithms were evaluated using sustained vowel samples collected from normal and pathological subjects. The effect of background noise and of frequency and amplitude modulations on these algorithms was also investigated, using synthetic vowel waveforms.

Algorithms↗

PubMed2003

Causality assessment of adverse drug reactions: comparison of the results obtained from published decisional algorithms and from the evaluations of an expert panel, according to different levels of imputability.

OBJECTIVES: To evaluate agreement between causality assessments of reported adverse drug reactions (ADRs) obtained from decisional algorithms, with those obtained from an expert panel using the WHO global introspection method (GI), according to different levels of imputability and to evaluate the influence of confounding variables. METHOD: Two hundred reports were included in this study. An independent researcher used decisional algorithms, while an expert panel assessed the same ADR reports using the GI, both aimed at evaluating causality. Reports were divided according to the presence, absence or lack of information on confounding variables. RESULTS: The rates of concordance between assessments made using the algorithms and GI according to levels of imputability were: 45% for 'certain', 61% for 'probable', 46% for 'possible' and 17% for drug unrelated terms. When confounding variables were taken into account, the rates of concordance for the 'absence of information', 'lack of information' and 'presence of confounding variables' in the 'certain' group were 49, 69 and 7%, respectively. The corresponding values for the 'probable' group were 80, 68 and 24% and 30, 51 and 51%, respectively for the 'possible' group. CONCLUSION: Full agreement with global introspection was not found for any level of causality assessment. Confounding variables were found to be associated with low levels of agreement between decision algorithms and the GI method compromising the algorithms' sensitivity and specificity.

Adverse Drug Reaction Reporting Systems↗