775 resultados para fixed-width confidence interval
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BACKGROUND: We examined the role of aerosol transmission of influenza in an acute ward setting. METHODS: We investigated a seasonal influenza A outbreak that occurred in our general medical ward (with open bay ward layout) in 2008. Clinical and epidemiological information was collected in real time during the outbreak. Spatiotemporal analysis was performed to estimate the infection risk among patients. Airflow measurements were conducted, and concentrations of hypothetical virus-laden aerosols at different ward locations were estimated using computational fluid dynamics modeling. RESULTS: Nine inpatients were infected with an identical strain of influenza A/H3N2 virus. With reference to the index patient's location, the attack rate was 20.0% and 22.2% in the "same" and "adjacent" bays, respectively, but 0% in the "distant" bay (P = .04). Temporally, the risk of being infected was highest on the day when noninvasive ventilation was used in the index patient; multivariate logistic regression revealed an odds ratio of 14.9 (95% confidence interval, 1.7-131.3; P = .015). A simultaneous, directional indoor airflow blown from the "same" bay toward the "adjacent" bay was found; it was inadvertently created by an unopposed air jet from a separate air purifier placed next to the index patient's bed. Computational fluid dynamics modeling revealed that the dispersal pattern of aerosols originated from the index patient coincided with the bed locations of affected patients. CONCLUSIONS: Our findings suggest a possible role of aerosol transmission of influenza in an acute ward setting. Source and engineering controls, such as avoiding aerosol generation and improving ventilation design, may warrant consideration to prevent nosocomial outbreaks.
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Global efforts to mitigate climate change are guided by projections of future temperatures1. But the eventual equilibrium global mean temperature associated with a given stabilization level of atmospheric greenhouse gas concentrations remains uncertain1, 2, 3, complicating the setting of stabilization targets to avoid potentially dangerous levels of global warming4, 5, 6, 7, 8. Similar problems apply to the carbon cycle: observations currently provide only a weak constraint on the response to future emissions9, 10, 11. Here we use ensemble simulations of simple climate-carbon-cycle models constrained by observations and projections from more comprehensive models to simulate the temperature response to a broad range of carbon dioxide emission pathways. We find that the peak warming caused by a given cumulative carbon dioxide emission is better constrained than the warming response to a stabilization scenario. Furthermore, the relationship between cumulative emissions and peak warming is remarkably insensitive to the emission pathway (timing of emissions or peak emission rate). Hence policy targets based on limiting cumulative emissions of carbon dioxide are likely to be more robust to scientific uncertainty than emission-rate or concentration targets. Total anthropogenic emissions of one trillion tonnes of carbon (3.67 trillion tonnes of CO2), about half of which has already been emitted since industrialization began, results in a most likely peak carbon-dioxide-induced warming of 2 °C above pre-industrial temperatures, with a 5–95% confidence interval of 1.3–3.9 °C.
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Objective To determine the prevalence and nature of prescribing and monitoring errors in general practices in England. Design Retrospective case note review of unique medication items prescribed over a 12 month period to a 2% random sample of patients. Mixed effects logistic regression was used to analyse the data. Setting Fifteen general practices across three primary care trusts in England. Data sources Examination of 6048 unique prescription items prescribed over the previous 12 months for 1777 patients. Main outcome measures Prevalence of prescribing and monitoring errors, and severity of errors, using validated definitions. Results Prescribing and/or monitoring errors were detected in 4.9% (296/6048) of all prescription items (95% confidence interval 4.4 - 5.5%). The vast majority of errors were of mild to moderate severity, with 0.2% (11/6048) of items having a severe error. After adjusting for covariates, patient-related factors associated with an increased risk of prescribing and/or monitoring errors were: age less than 15 (Odds Ratio (OR) 1.87, 1.19 to 2.94, p=0.006) or greater than 64 years (OR 1.68, 1.04 to 2.73, p=0.035), and higher numbers of unique medication items prescribed (OR 1.16, 1.12 to 1.19, p<0.001). Conclusion Prescribing and monitoring errors are common in English general practice, although severe errors are unusual. Many factors increase the risk of error. Having identified the most common and important errors, and the factors associated with these, strategies to prevent future errors should be developed based on the study findings.
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To calculate the potential wind loading on a tall building in an urban area, an accurate representation of the wind speed profile is required. However, due to a lack of observations, wind engineers typically estimate the characteristics of the urban boundary layer by translating the measurements from a nearby reference rural site. This study presents wind speed profile data obtained from a Doppler lidar in central London, UK, during an 8 month observation period. Used in conjunction with wind speed data measured at a nearby airport, the data have been used to assess the accuracy of the predictions made by the wind engineering tools currently available. When applied to multiple changes in surface roughness identified from morphological parameters, the non-equilibrium wind speed profile model developed by Deaves (1981) provides a good representation of the urban wind speed profile. For heights below 500 m, the predicted wind speed remains within the 95% confidence interval of the measured data. However, when the surface roughness is estimated using land use as a proxy, the model tends to overestimate the wind speed, particularly for very high wind speed periods. These results highlight the importance of a detailed assessment of the nature of the surface when estimating the wind speed above an urban surface.
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We present projections of winter storm-induced insured losses in the German residential building sector for the 21st century. With this aim, two structurally most independent downscaling methods and one hybrid downscaling method are applied to a 3-member ensemble of ECHAM5/MPI-OM1 A1B scenario simulations. One method uses dynamical downscaling of intense winter storm events in the global model, and a transfer function to relate regional wind speeds to losses. The second method is based on a reshuffling of present day weather situations and sequences taking into account the change of their frequencies according to the linear temperature trends of the global runs. The third method uses statistical-dynamical downscaling, considering frequency changes of the occurrence of storm-prone weather patterns, and translation into loss by using empirical statistical distributions. The A1B scenario ensemble was downscaled by all three methods until 2070, and by the (statistical-) dynamical methods until 2100. Furthermore, all methods assume a constant statistical relationship between meteorology and insured losses and no developments other than climate change, such as in constructions or claims management. The study utilizes data provided by the German Insurance Association encompassing 24 years and with district-scale resolution. Compared to 1971–2000, the downscaling methods indicate an increase of 10-year return values (i.e. loss ratios per return period) of 6–35 % for 2011–2040, of 20–30 % for 2041–2070, and of 40–55 % for 2071–2100, respectively. Convolving various sources of uncertainty in one confidence statement (data-, loss model-, storm realization-, and Pareto fit-uncertainty), the return-level confidence interval for a return period of 15 years expands by more than a factor of two. Finally, we suggest how practitioners can deal with alternative scenarios or possible natural excursions of observed losses.
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OBJECTIVE: Studies have shown that common single-nucleotide polymorphisms (SNPs) in the serotonin 5-HT-2C receptor (HTR2C) are associated with antipsychotic agent-induced weight gain and the development of behavioural and psychological symptoms. We aimed to analyse whether variation in the HTR2C is associated with obesity- and mental health-related phenotypes in a large population-based cohort. METHOD: Six tagSNPs, which capture all common genetic variation in the HTR2C gene, were genotyped in 4978 men and women from the European Prospective Investigation into Cancer (EPIC)-Norfolk study, an ongoing prospective population-based cohort study in the United Kingdom. To confirm borderline significant associations, the -759C/T SNP (rs3813929) was genotyped in the remaining 16 003 individuals from the EPIC-Norfolk study. We assessed social and psychological circumstances using the Health and Life Experiences Questionnaire. Genmod models were used to test associations between the SNPs and the outcomes. Logistic regression was performed to test for association of SNPs with obesity- and mental health- related phenotypes. RESULTS: Of the six HTR2C SNPs, only the T allele of the -759C/T SNP showed borderline significant associations with higher body mass index (BMI) (0.23 kg m(-2); (95% confidence interval (CI): 0.01-0.44); P=0.051) and increased risk of lifetime major depressive disorder (MDD) (Odds ratio (OR): 1.13 (95% CI: 1.01-1.22), P=0.02). The associations between the -759C/T and BMI and lifetime MDD were independent. As associations only achieved borderline significance, we aimed to validate our findings on the -759C/T SNP in the full EPIC-Norfolk cohort (n=20 981). Although the association with BMI remained borderline significant (beta=0.20 kg m(-2); 95% CI: 0.04-0.44, P=0.09), that with lifetime MDD (OR: 1.01; 95% CI: 0.94-1.09, P=0.73) was not replicated. CONCLUSIONS: Our findings suggest that common HTR2C gene variants are unlikely to have a major role in obesity- and mental health-related traits in the general population.
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BACKGROUND: The gene encoding for uncoupling protein-1 (UCP1) is considered to be a candidate gene for type 2 diabetes because of its role in thermogenesis and energy expenditure. The objective of the study was to examine whether genetic variations in the UCP1 gene are associated with type 2 diabetes and its related traits in Asian Indians. METHODS: The study subjects, 810 type 2 diabetic subjects and 990 normal glucose tolerant (NGT) subjects, were chosen from the Chennai Urban Rural Epidemiological Study (CURES), an ongoing population-based study in southern India. The polymorphisms were genotyped using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Linkage disequilibrium (LD) was estimated from the estimates of haplotypic frequencies. RESULTS: The three polymorphisms, namely -3826A-->G, an A-->C transition in the 5'-untranslated region (UTR) and Met229Leu, were not associated with type 2 diabetes. However, the frequency of the A-C-Met (-3826A-->G-5'UTR A-->C-Met229Leu) haplotype was significantly higher among the type 2 diabetic subjects (2.67%) compared with the NGT subjects (1.45%, P < 0.01). The odds ratio for type 2 diabetes for the individuals carrying the haplotype A-C-Met was 1.82 (95% confidence interval, 1.29-2.78, P = 0.009). CONCLUSIONS: The haplotype, A-C-Met, in the UCP1 gene is significantly associated with the increased genetic risk for developing type 2 diabetes in Asian Indians.
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BACKGROUND: The aim of this study was to evaluate the association of polymorphisms of the peroxisome proliferator-activated receptor gamma (PPARG) gene and peroxisome proliferators-activated receptor gamma co-activator 1 alpha (PPARGC1A) gene with diabetic nephropathy (DN) in Asian Indians. METHODS: Six common polymorphisms, 3 of the PPARG gene [-1279G/A, Pro12Ala, and His478His (C/T)] and 3 of the PPARGC1A gene (Thr394Thr, Gly482Ser, and +A2962G) were studied in 571 normal glucose-tolerant (NGT) subjects, 255 type 2 diabetic (T2D) subjects without nephropathy, and 141 DN subjects. Genotypes were determined by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and direct sequencing. Logistic regression analysis was performed to assess the covariables associated with DN. RESULTS: Among the 6 polymorphisms examined, only the Gly482Ser of the PPARGC1A gene was significantly associated with DN. The genotype frequency of Ser/Ser genotype of the PPARGC1A gene was 8.8% (50/571) in NGT subjects, 7.8% (20/255) in T2D subjects, and 29.8% (42/141) in DN subjects. The odds ratios (ORs) for DN for the susceptible Gly/Ser and Ser/Ser genotype after adjusting for age, sex, body mass index, and duration of diabetes were 2.14 [95% confidence interval (CI), 1.23-3.72; P = 0.007] and 8.01 (95% CI, 3.89-16.47; P < 0.001), respectively. The unadjusted OR for DN for the XA genotype of the Thr394Thr polymorphism was 1.87 (95% CI, 1.20-2.92; P = 0.006) compared to T2D subjects. However, the significance was lost (P = 0.061) when adjusted for age, sex, BMI, and duration of diabetes. The +A2962G of PPARGC1A and the 3 polymorphisms of PPARG were not associated with DN. CONCLUSION: The Gly482Ser polymorphism of the PPARGC1A gene is associated with DN in Asian Indians.
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Peroxisome proliferator-activated receptor-gamma2 (PPARG2) is a nuclear hormone receptor of ligand-dependent transcription factor involved in adipogenesis and a molecular target of the insulin sensitizers thiazolidinediones. We addressed the question of whether the 3 variants (-1279G/A, Pro12Ala, and His478His) in the PPARG2 gene are associated with type 2 diabetes mellitus and its related traits in a South Indian population. The study subjects (1000 type 2 diabetes mellitus and 1000 normal-glucose-tolerant subjects) were chosen randomly from the Chennai Urban Rural Epidemiology Study, an ongoing population-based study in southern India. The variants were screened by single-stranded conformational variant, direct sequencing, and restriction fragment length polymorphism. Linkage disequilibrium was estimated from the estimates of haplotypic frequencies. The -1279G/A, Pro12Ala, and His478His variants of the PPARG2 gene were not associated with type 2 diabetes mellitus. However, the 2-loci analyses showed that, in the presence of Pro/Pro genotype of the Pro12Ala variant, the -1279G/A promoter variant showed increased susceptibility to type 2 diabetes mellitus (odds ratio, 2.092; 95% confidence interval, 1.22-3.59; P = .008), whereas in the presence of 12Ala allele, the -1279G/A showed a protective effect against type 2 diabetes mellitus (odds ratio, 0.270; 95% confidence interval, 0.15-0.49; P < .0001). The 3-loci haplotype analysis showed that the A-Ala-T (-1279G/A-Pro12Ala-His478His) haplotype was associated with a reduced risk of type 2 diabetes mellitus (P < .0001). Although our data indicate that the PPARG2 gene variants, independently, have no association with type 2 diabetes mellitus, the 2-loci genotype analysis involving -1279G/A and Pro12Ala variants and the 3-loci haplotype analysis have shown a significant association with type 2 diabetes mellitus in this South Indian population.
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The protein encoded by the PPARGC1A gene is expressed at high levels in metabolically active tissues and is involved in the control of oxidative stress via reactive oxygen species detoxification. Several recent reports suggest that the PPARGC1A Gly482Ser (rs8192678) missense polymorphism may relate inversely with blood pressure. We used conventional meta-analysis methods to assess the association between Gly482Ser and systolic (SBP) or diastolic blood pressures (DBP) or hypertension in 13,949 individuals from 17 studies, of which 6,042 were previously unpublished observations. The studies comprised cohorts of white European, Asian, and American Indian adults, and adolescents from South America. Stratified analyses were conducted to control for population stratification. Pooled genotype frequencies were 0.47 (Gly482Gly), 0.42 (Gly482Ser), and 0.11 (Ser482Ser). We found no evidence of association between Gly482Ser and SBP [Gly482Gly: mean = 131.0 mmHg, 95% confidence interval (CI) = 130.5-131.5 mmHg; Gly482Ser mean = 133.1 mmHg, 95% CI = 132.6-133.6 mmHg; Ser482Ser: mean = 133.5 mmHg, 95% CI = 132.5-134.5 mmHg; P = 0.409] or DBP (Gly482Gly: mean = 80.3 mmHg, 95% CI = 80.0-80.6 mmHg; Gly482Ser mean = 81.5 mmHg, 95% CI = 81.2-81.8 mmHg; Ser482Ser: mean = 82.1 mmHg, 95% CI = 81.5-82.7 mmHg; P = 0.651). Contrary to previous reports, we did not observe significant effect modification by sex (SBP, P = 0.966; DBP, P = 0.715). We were also unable to confirm the previously reported association between the Ser482 allele and hypertension [odds ratio: 0.97, 95% CI = 0.87-1.08, P = 0.585]. These results were materially unchanged when analyses were focused on whites only. However, statistical evidence of gene-age interaction was apparent for DBP [Gly482Gly: 73.5 (72.8, 74.2), Gly482Ser: 77.0 (76.2, 77.8), Ser482Ser: 79.1 (77.4, 80.9), P = 4.20 x 10(-12)] and SBP [Gly482Gly: 121.4 (120.4, 122.5), Gly482Ser: 125.9 (124.6, 127.1), Ser482Ser: 129.2 (126.5, 131.9), P = 7.20 x 10(-12)] in individuals <50 yr (n = 2,511); these genetic effects were absent in those older than 50 yr (n = 5,088) (SBP, P = 0.41; DBP, P = 0.51). Our findings suggest that the PPARGC1A Ser482 allele may be associated with higher blood pressure, but this is only apparent in younger adults.
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Adiponectin is an adipose tissue specific protein that is decreased in subjects with obesity and type 2 diabetes. The objective of the present study was to examine whether variants in the regulatory regions of the adiponectin gene contribute to type 2 diabetes in Asian Indians. The study comprised of 2,000 normal glucose tolerant (NGT) and 2,000 type 2 diabetic, unrelated subjects randomly selected from the Chennai Urban Rural Epidemiology Study (CURES), in southern India. Fasting serum adiponectin levels were measured by radioimmunoassay. We identified two proximal promoter SNPs (-11377C-->G and -11282T-->C), one intronic SNP (+10211T-->G) and one exonic SNP (+45T-->G) by SSCP and direct sequencing in a pilot study (n = 500). The +10211T-->G SNP alone was genotyped using PCR-RFLP in 4,000 study subjects. Logistic regression analysis revealed that subjects with TG genotype of +10211T-->G had significantly higher risk for diabetes compared to TT genotype [Odds ratio 1.28; 95% Confidence Interval (CI) 1.07-1.54; P = 0.008]. However, no association with diabetes was observed with GG genotype (P = 0.22). Stratification of the study subjects based on BMI showed that the odds ratio for obesity for the TG genotype was 1.53 (95%CI 1.3-1.8; P < 10(-7)) and that for GG genotype, 2.10 (95% CI 1.3-3.3; P = 0.002). Among NGT subjects, the mean serum adiponectin levels were significantly lower among the GG (P = 0.007) and TG (P = 0.001) genotypes compared to TT genotype. Among Asian Indians there is an association of +10211T-->G polymorphism in the first intron of the adiponectin gene with type 2 diabetes, obesity and hypoadiponectinemia.
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The intestinal fatty acid-binding protein gene is proposed as a candidate gene for diabetes because the protein it codes is involved in fatty acid absorption and metabolism. This study investigates the association of the Ala54Thr variant of the intestinal fatty acid-binding protein gene on type 2 diabetes mellitus and other related metabolic traits in Asian Indians. Ala54Thr polymorphism was genotyped by using polymerase chain reaction-restriction fragment length polymorphism in unrelated 773 type 2 diabetic and 899 normal glucose-tolerant (NGT) subjects, randomly chosen from the Chennai Urban Rural Epidemiology Study, an ongoing population-based study in South India. The Ala54Thr polymorphism was not associated with type 2 diabetes mellitus or obesity. However, genotype-phenotype study revealed that the NGT subjects carrying the Thr54 allele had significantly higher 2-hour plasma glucose (P = .007), glycated hemoglobin (P = .004), 2-hour insulin (P = .027), and fasting low-density lipoprotein cholesterol (P = .032) levels compared with those with the Ala54 allele. Normal glucose-tolerant subjects with Ala54Thr and Thr54Thr genotypes had significantly higher fasting serum triglyceride levels (P = .003) compared with those with Ala54Ala. The subjects were stratified into those with hypertriglyceridemia (serum triglyceride levels >or=150 mg/dL) and those without. The odds ratio for hypertriglyceridemia for the individuals carrying the Ala54Thr genotype was 1.491 (95% confidence interval [CI], 1.22-1.83, P < .0001), and for those carrying the Thr54Thr genotype, it was 1.888 (95% CI, 1.34-2.67; P < .0001). Subjects were also stratified into those with metabolic syndrome (MS) and those without, according to modified Adult Treatment Panel III guidelines. The odds ratio (adjusted for age and sex) for MS for the individuals carrying the Ala54Thr genotype was 1.240 (95% CI, 1.02-1.51; P = .03), whereas for those carrying the Thr54Thr genotype, it was 1.812 (95% CI, 1.28-2.57; P = .001). Carriers of the Thr54 allele have associations with MS and hypertriglyceridemia in this urban South Indian population.
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Background Factors related to parents and parenting capacities are important predictors of the development of behavioural problems in children. Recently, there has been an increasing research focus in this field on the earliest years of life, however, relatively few studies have addressed the role of fathers, despite this appearing to be particularly pertinent to child behavioural development. This study aimed to examine whether father–infant interactions at age 3 months independently predicted child behavioural problems at 1 year of age. Method A sample of 192 families was recruited from two maternity units in the United Kingdom. Father–infant interactions were assessed in the family home and coded using the Global Rating Scales. Child behaviour problems were assessed by maternal report. Hierarchical and logistic regression analyses were used to examine associations between father–infant interaction and the development of behavioural problems. Results Disengaged and remote interactions between fathers and their infants were found to predict externalising behavioural problems at the age of 1 year. The children of the most disengaged fathers had an increased risk of developing early externalising behavioural problems [disengaged (nonintrusive) interactions – adjusted Odds Ratio 5.33 (95% Confidence Interval; 1.39, 20.40): remote interactions adj. OR 3.32 (0.92, 12.05)] Conclusions Disengaged interactions of fathers with their infants, as early as the third month of life, predict early behavioural problems in children. These interactions may be critical factors to address, from a very early age in the child’s life, and offer a potential opportunity for preventive intervention.
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Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism’s phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The whole genomes of 501 unrelated Staphylococcus aureus isolates were sequenced, and the assembled genomes were interrogated using BLASTn for a panel of known resistance determinants (chromosomal mutations and genes carried on plasmids). Results were compared with phenotypic susceptibility testing for 12 commonly used antimicrobial agents (penicillin, methicillin, erythromycin, clindamycin, tetracycline, ciprofloxacin, vancomycin, trimethoprim, gentamicin, fusidic acid, rifampin, and mupirocin) performed by the routine clinical laboratory. We investigated discrepancies by repeat susceptibility testing and manual inspection of the sequences and used this information to optimize the resistance determinant panel and BLASTn algorithm. We then tested performance of the optimized tool in an independent validation set of 491 unrelated isolates, with phenotypic results obtained in duplicate by automated broth dilution (BD Phoenix) and disc diffusion. In the validation set, the overall sensitivity and specificity of the genomic prediction method were 0.97 (95% confidence interval [95% CI], 0.95 to 0.98) and 0.99 (95% CI, 0.99 to 1), respectively, compared to standard susceptibility testing methods. The very major error rate was 0.5%, and the major error rate was 0.7%. WGS was as sensitive and specific as routine antimicrobial susceptibility testing methods. WGS is a promising alternative to culture methods for resistance prediction in S. aureus and ultimately other major bacterial pathogens.
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Aim To develop a brief, parent-completed instrument (‘ERIC’) for detection of cognitive delay in 10-24 month-olds born preterm, or with low birth weight, or with perinatal complications, and to establish its diagnostic properties. Method Scores were collected from parents of 317 children meeting ≥1 inclusion criteria (birth weight <1500g; gestational age <34 completed weeks; 5-minute Apgar <7; presence of hypoxic-ischemic encephalopathy) and meeting no exclusion criteria. Children were assessed for cognitive delay using a criterion score on the Bayley Scales of Infant and Toddler Development Cognitive Scale III1 <80. Items were retained according to their individual associations with delay. Sensitivity, specificity, Positive and Negative Predictive Values were estimated and a truncated ERIC was developed for use <14 months. Results ERIC detected 17 out of 18 delayed children in the sample, with 94.4% sensitivity (95% CI [confidence interval] 83.9-100%), 76.9% specificity (72.1-81.7%), 19.8% positive predictive value (11.4-28.2%); 99.6% negative predictive value (98.7-100%); 4.09 likelihood ratio positive; and 0.07 likelihood ratio negative; the associated Area under the Curve was .909 (.829-.960). Interpretation ERIC has potential value as a quickly-administered diagnostic instrument for the absence of early cognitive delay in preterm or premature infants of 10-24 months, and as a screen for cognitive delay. Further research may be needed before ERIC can be recommended for wide-scale use.