Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

Personality traits are associated with acute major depression across the age spectrum.

Objectives: Psychological predictors, such as personality traits, have aroused growing interest as possible predictors of late-life depression outcome in old age. It remains, however, unclear whether the cross-sectional relationship between personality traits and depression occurrence reported in younger samples is also present in the elderly. Methods: Comparisons amongst 79 outpatients with DSM-IV major depression and 102 healthy controls included assessment of the five-factor model of personality (NEO PI-R), socio-demographic variables, physical health status, as well as depression features. Two sub-groups were considered, defined as young (25-50 years) and old (60-85 years) patients. Results: Depressed patients showed significantly higher levels of Neuroticism and lower levels of Extraversion, Openness to Experience and Conscientiousness compared to controls. Sequential logistic regression models confirmed that the combination of increased physical burden, levels of dependency, and increased Neuroticism strongly predicts the occurrence of acute depressive symptoms. In contrast, the levels of Neuroticism did not allow for differentiating late-life from young age depression. Increased physical burden and decreased depression severity were the main predictors for this distinction. Conclusion: Our data indicate that personality factors and depression are related, independently of patients' age. Differences in this relationship are mainly due to the intensity of depressive symptoms rather than the patients' life period. They also stress the need to consider physical health, level of dependency and severity of symptoms when studying the relationship between personality traits and mood disorders.

Comorbidity and nutritional indices as predictors of morbidity after transurethral procedures: A prospective cohort study.

INTRODUCTION: Preoperative scores are widely used predictors of complications after major surgery. These scores, however, are not widely used in transurethral procedures. The aim of this study was to assess the value of the Charlson Comorbidity Index (CCI), the age-adjusted CCI, the American Society of Anesthesiologist score (ASA) and the Nutritional Risk Score (NRS) in predicting early morbidity after transurethral urological procedures. METHODS: Consecutive patients undergoing transurethral resection of the bladder or the prostate were prospectively enrolled. The scores were calculated preoperatively; 30-day complications were prospectively recorded according to the Dindo-Clavien classification. Univariate logistic regression was performed to investigate the value of each score and of other factors (i.e., age, sex, body mass index, anemia, smoking habit, type of operation and anaesthesia) as predictors of complications. A multivariate model was then calculated using these predictors. RESULTS: Overall, 197 patients were included. The mean age was 72 (standard deviation ± 10). In total, 26.9% patients had at least 1 complication. Using univariate analysis, we found that each score significantly predicted complications. In multivariate analysis, only the ASA (odds ration [OR] 2.11; 95% confidence interval [CI] 1.01-4.43) and the NRS (OR 2.42; 95% CI 1.56-3.74) remained independent predictors. The best model incorporated ASA, NRS and gender, and predicted morbidity with an area under the curve of 76%. Our study's main limitations are population heterogeneity and limited sample size. CONCLUSION: The ASA and the NRS are important and independent determinants of early morbidity after transurethral procedures. The use of these indices may assist clinicians in the decision-making process to balance the possible benefits of transurethral procedures with the potential risks.

Prevalencia de la discapacidad en España por comunidades autónomas: el papel de los factores individuales y del entorno geográfico en su variabilidad

Fundamento: La prevalencia de discapacidad en la población general presenta una gran variabilidad geográfica, de manera que identificar aquellos factores que pudieran explicarla será importante para la planificación de políticas sociales. En este trabajo se analiza la variabilidad de la discapacidad por comunidades autónomas desde una doble vertiente, los factores individuales y del entorno. Métodos: Los datos proceden principalmente de la Encuesta de Discapacidad, Deficiencias y Estado de Salud de 1999 y del Inebase, ambas del Instituto Nacional de Estadística (INE). Se calculó la prevalencia de discapacidad simple y ajustada por edad de las CCAA. Se analizan los factores individuales asociados a la discapacidad mediante una regresión logística y los factores individuales y de la comunidad autónoma conjuntamente con una regresión logística de dos niveles. Resultados: La prevalencia de discapacidad muestra una diferencia máxima de 5,75 puntos entre las comunidades autónomas. En la regresión logística la comunidad de residencia fue estadísticamente significativa (OR: 3,35 en la de mayor prevalencia respecto a la de menor) junto con otras variables individuales: edad (OR de 40-64= 1,78 OR de 65-79= 1,87 y OR de >79= 3,34), sexo (OR mujer= 0,66), situación laboral (OR sin trabajo=2,25 OR amas casa/estudiante=1,39 y OR otros=2,03), estado de salud (OR regular= 1,69 OR malo/muy malo= 2,05) y enfermedades crónicas (OR 1-3=1,56 OR4-6=1,82 OR>6=2,59). En la regresión de dos niveles las variables individuales explican poca varianza (s=0,261) y ninguna de las variables relativas a las CCAA mejora el modelo. Conclusiones: Las características individuales no explican suficientemente la variabilidad de la discapacidad entre CCAA y no se han identificado variables del entorno que sean significativas.

Stratification of the severity of critically ill patients with classification trees

Background: Development of three classification trees (CT) based on the CART (Classification and Regression Trees), CHAID (Chi-Square Automatic Interaction Detection) and C4.5 methodologies for the calculation of probability of hospital mortality; the comparison of the results with the APACHE II, SAPS II and MPM II-24 scores, and with a model based on multiple logistic regression (LR). Methods: Retrospective study of 2864 patients. Random partition (70:30) into a Development Set (DS) n = 1808 and Validation Set (VS) n = 808. Their properties of discrimination are compared with the ROC curve (AUC CI 95%), Percent of correct classification (PCC CI 95%); and the calibration with the Calibration Curve and the Standardized Mortality Ratio (SMR CI 95%). Results: CTs are produced with a different selection of variables and decision rules: CART (5 variables and 8 decision rules), CHAID (7 variables and 15 rules) and C4.5 (6 variables and 10 rules). The common variables were: inotropic therapy, Glasgow, age, (A-a)O2 gradient and antecedent of chronic illness. In VS: all the models achieved acceptable discrimination with AUC above 0.7. CT: CART (0.75(0.71-0.81)), CHAID (0.76(0.72-0.79)) and C4.5 (0.76(0.73-0.80)). PCC: CART (72(69- 75)), CHAID (72(69-75)) and C4.5 (76(73-79)). Calibration (SMR) better in the CT: CART (1.04(0.95-1.31)), CHAID (1.06(0.97-1.15) and C4.5 (1.08(0.98-1.16)). Conclusion: With different methodologies of CTs, trees are generated with different selection of variables and decision rules. The CTs are easy to interpret, and they stratify the risk of hospital mortality. The CTs should be taken into account for the classification of the prognosis of critically ill patients.

A genetic risk score combining 32 SNPs is associated with body mass index and improves obesity prediction in people with major depressive disorder.

BACKGROUND: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P <0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P <0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.

Problematic Internet use is associated with substance use in young adolescents.

AIM: This study examined whether problematic Internet use was associated with substance use among young adolescents and assessed whether this association accounted for the use of tobacco, alcohol, cannabis and other drugs. METHODS: Using the Internet Addiction Test, we divided a representative sample of 3067 adolescents in Switzerland (mean age 14 years) into regular and problematic Internet users. We performed a bivariate analysis and two logistic regression models, to analyse substances separately and simultaneously, and developed a log-linear model to define the associations between significant variables. RESULTS: Problematic Internet users were more likely to be female, to use substances, to come from nonintact families, to report poor emotional well-being and to be below average students. The first model showed significant associations between problematic users and each substance, with adjusted odds ratios of 2.05 for tobacco, 1.72 for alcohol, 1.94 for cannabis and 2.73 for other drugs. Only smoking remained significant in the second model, with an adjusted odds ratio of 1.71. CONCLUSION: Problematic Internet use is associated with other risky behaviours and may be an important early predictor of adolescent substance use. Therefore, it should be included in the psychosocial screening of adolescents.

Being Small for Gestational Age: Does it Matter for the Neurodevelopment of Premature Infants? A Cohort Study.

BACKGROUND: Whether being small for gestational age (SGA) increases the risk of adverse neurodevelopmental outcome in premature infants remains controversial. OBJECTIVE: to study the impact of SGA (birthweight < percentile 10) on cognition, behavior, neurodevelopmental impairment and use of therapy at 5 years old. METHODS: This population-based prospective cohort included infants born before 32 weeks of gestation. Cognition was evaluated with the K-ABC, and behavior with the Strengths and Difficulties Questionnaire (SDQ). Primary outcomes were cognitive and behavioral scores, as well as neurodevelopmental impairment (cognitive score < 2SD, hearing loss, blindness, or cerebral palsy). The need of therapy, an indirect indicator of neurodevelopmental impairment, was a secondary outcome. Linear and logistic regression models were used to analyze the association of SGA with neurodevelopment. RESULTS: 342/515 (76%) premature infants were assessed. SGA was significantly associated with hyperactivity scores of the SDQ (coefficient 0.81, p < 0.04), but not with cognitive scores, neurodevelopmental impairment or the need of therapy. Gestational age, socio-economic status, and major brain lesions were associated with cognitive outcome in the univariate and multivariate model, whereas asphyxia, sepsis and bronchopulmonary dysplasia were associated in the univariate model only. Severe impairment was associated with fetal tobacco exposition, asphyxia, gestational age and major brain lesions. Different neonatal factors were associated with the use of single or multiple therapies: children with one therapy were more likely to have suffered birth asphyxia or necrotizing enterocolitis, whereas the need for several therapies was predicted by major brain lesions. DISCUSSION: In this large cohort of premature infants, assessed at 5 years old with a complete panel of tests, SGA was associated with hyperactive behavior, but not with cognition, neurodevelopmental impairment or use of therapy. Birthweight <10th percentile alone does not appear to be an independent risk factor of neurodevelopmental adverse outcome in preterm children.

ASTRAL-R score predicts non-recanalisation after intravenous thrombolysis in acute ischaemic stroke.

Intravenous thrombolysis (IVT) as treatment in acute ischaemic strokes may be insufficient to achieve recanalisation in certain patients. Predicting probability of non-recanalisation after IVT may have the potential to influence patient selection to more aggressive management strategies. We aimed at deriving and internally validating a predictive score for post-thrombolytic non-recanalisation, using clinical and radiological variables. In thrombolysis registries from four Swiss academic stroke centres (Lausanne, Bern, Basel and Geneva), patients were selected with large arterial occlusion on acute imaging and with repeated arterial assessment at 24 hours. Based on a logistic regression analysis, an integer-based score for each covariate of the fitted multivariate model was generated. Performance of integer-based predictive model was assessed by bootstrapping available data and cross validation (delete-d method). In 599 thrombolysed strokes, five variables were identified as independent predictors of absence of recanalisation: Acute glucose > 7 mmol/l (A), significant extracranial vessel STenosis (ST), decreased Range of visual fields (R), large Arterial occlusion (A) and decreased Level of consciousness (L). All variables were weighted 1, except for (L) which obtained 2 points based on β-coefficients on the logistic scale. ASTRAL-R scores 0, 3 and 6 corresponded to non-recanalisation probabilities of 18, 44 and 74 % respectively. Predictive ability showed AUC of 0.66 (95 %CI, 0.61-0.70) when using bootstrap and 0.66 (0.63-0.68) when using delete-d cross validation. In conclusion, the 5-item ASTRAL-R score moderately predicts non-recanalisation at 24 hours in thrombolysed ischaemic strokes. If its performance can be confirmed by external validation and its clinical usefulness can be proven, the score may influence patient selection for more aggressive revascularisation strategies in routine clinical practice.

4B.05: Plasma Lasma copeptin is associated with insulin resistance in a Swiss population-based study

OBJECTIVE: Previous studies suggest that arginine vasopressin may have a role in metabolic syndrome (MetS) and diabetes by altering liver glycogenolysis, insulin, and glucagon secretion and pituitary ACTH release. We tested whether plasma copeptin, the stable C-terminal fragment of arginine vasopressin prohormone, was associated with insulin resistance and MetS in a Swiss population-based study. DESIGN AND METHOD: We analyzed data from the population-based Swiss Kidney Project on Genes in Hypertension. Copeptin was assessed by an immunoluminometric assay. Insulin resistance was derived from the HOMA model and calculated as follows: (FPI x FPG)/22.5, where FPI is fasting plasma insulin concentration (mU/L) and FPG fasting plasma glucose (mmol/L). Subjects were classified as having the MetS according to the National Cholesterol Education Program Adult Treatment Panel III criteria. Mixed multivariate linear regression models were built to explore the association of insulin resistance with copeptin. In addition, multivariate logistic regression models were built to explore the association between MetS and copeptin. In the two analyses, adjustment was done for age, gender, center, tobacco and alcohol consumption, socioeconomic status, physical activity, intake of fruits and vegetables and 24 h urine flow rate. Copeptin was log-transformed for the analyses. RESULTS: Among the 1,089 subjects included in this analysis, 47% were male. Mean (SD) age and body mass index were 47.4 (17.6) years 25.0 (4.5) kg/m2. The prevalence of MetS was 10.5%. HOMA-IR was higher in men (median 1.3, IQR 0.7-2.1) than in women (median 1.0, IQR 0.5-1.6,P < 0.0001). Plasma copeptin was higher in men (median 5.2, IQR 3.7-7.8 pmol/L) than in women (median 3.0, IQR 2.2-4.3 pmol/L), P < 0.0001. HOMA-IR was positively associated with log-copeptin after full adjustment (β (95% CI) 0.19 (0.09-0.29), P < 0.001). MetS was not associated with copeptin after full adjustment (P = 0.92). CONCLUSIONS: Insulin resistance, but not MetS, was associated with higher copeptin levels. Further studies should examine whether modifying pharmacologically the arginine vasopressin system might improve insulin resistance, thereby providing insight into the causal nature of this association.

Quantifying the time for accurate EEG decoding of single value-based decisions.

BACKGROUND: Recent neuroimaging studies suggest that value-based decision-making may rely on mechanisms of evidence accumulation. However no studies have explicitly investigated the time when single decisions are taken based on such an accumulation process. NEW METHOD: Here, we outline a novel electroencephalography (EEG) decoding technique which is based on accumulating the probability of appearance of prototypical voltage topographies and can be used for predicting subjects' decisions. We use this approach for studying the time-course of single decisions, during a task where subjects were asked to compare reward vs. loss points for accepting or rejecting offers. RESULTS: We show that based on this new method, we can accurately decode decisions for the majority of the subjects. The typical time-period for accurate decoding was modulated by task difficulty on a trial-by-trial basis. Typical latencies of when decisions are made were detected at ∼500ms for 'easy' vs. ∼700ms for 'hard' decisions, well before subjects' response (∼340ms). Importantly, this decision time correlated with the drift rates of a diffusion model, evaluated independently at the behavioral level. COMPARISON WITH EXISTING METHOD(S): We compare the performance of our algorithm with logistic regression and support vector machine and show that we obtain significant results for a higher number of subjects than with these two approaches. We also carry out analyses at the average event-related potential level, for comparison with previous studies on decision-making. CONCLUSIONS: We present a novel approach for studying the timing of value-based decision-making, by accumulating patterns of topographic EEG activity at single-trial level.

Systematic analysis of factors associated with progression and regression of ulcerative colitis in 918 patients.

BACKGROUND: Studies that systematically assess change in ulcerative colitis (UC) extent over time in adult patients are scarce. AIM: To assess changes in disease extent over time and to evaluate clinical parameters associated with this change. METHODS: Data from the Swiss IBD cohort study were analysed. We used logistic regression modelling to identify factors associated with a change in disease extent. RESULTS: A total of 918 UC patients (45.3% females) were included. At diagnosis, UC patients presented with the following disease extent: proctitis [199 patients (21.7%)], left-sided colitis [338 patients (36.8%)] and extensive colitis/pancolitis [381 (41.5%)]. During a median disease duration of 9 [4-16] years, progression and regression was documented in 145 patients (15.8%) and 149 patients (16.2%) respectively. In addition, 624 patients (68.0%) had a stable disease extent. The following factors were identified to be associated with disease progression: treatment with systemic glucocorticoids [odds ratio (OR) 1.704, P = 0.025] and calcineurin inhibitors (OR: 2.716, P = 0.005). No specific factors were found to be associated with disease regression. CONCLUSIONS: Over a median disease duration of 9 [4-16] years, about two-thirds of UC patients maintained the initial disease extent; the remaining one-third had experienced either progression or regression of the disease extent.

Serum Vitamin D Concentrations Are Not Associated with Insulin Resistance in Swiss Adults.

BACKGROUND: Low vitamin D status has been associated with an increased risk of developing type 2 diabetes and insulin resistance (IR), although this has been recently questioned. OBJECTIVE: We examined the association between serum vitamin D metabolites and incident IR. METHODS: This was a prospective, population-based study derived from the CoLaus (Cohorte Lausannoise) study including 3856 participants (aged 51.2 ± 10.4 y; 2217 women) free from diabetes or IR at baseline. IR was defined as a homeostasis model assessment (HOMA) index >2.6. Fasting plasma insulin and glucose were measured at baseline and at follow-up to calculate the HOMA index. The association of vitamin D metabolites with incident IR was analyzed by logistic regression, and the results were expressed for each independent variable as ORs and 95% CIs. RESULTS: During the 5.5-y follow-up, 649 (16.9%) incident cases of IR were identified. Participants who developed IR had lower baseline serum concentrations of 25-hydroxyvitamin D3 [25(OH)D3 (25-hydroxycholecalciferol); 45.9 ± 22.8 vs. 49.9 ± 22.6 nmol/L; P < 0.001], total 25(OH)D3 (25(OH)D3 + epi-25-hydroxyvitamin D3 [3-epi-25(OH)D3]; 49.1 ± 24.3 vs. 53.3 ± 24.1 nmol/L; P < 0.001), and 3-epi-25(OH)D3 (4.2 ± 2.9 vs. 4.3 ± 2.5 nmol/L; P = 0.01) but a higher 3-epi- to total 25(OH)D3 ratio (0.09 ± 0.05 vs. 0.08 ± 0.04; P = 0.007). Multivariable analysis adjusting for month of sampling, age, and sex showed an inverse association between 25(OH)D3 and the likelihood of developing IR [ORs (95% CIs): 0.86 (0.68, 1.09), 0.60 (0.46, 0.78), and 0.57 (0.43, 0.75) for the second, third, and fourth quartiles compared with the first 25(OH)D3 quartile; P-trend < 0.001]. Similar associations were found between total 25(OH)D3 and incident IR. There was no significant association between 3-epi-25(OH)D3 and IR, yet a positive association was observed between the 3-epi- to total 25(OH)D3 ratio and incident IR. Further adjustment for body mass index, sedentary status, and smoking attenuated the association between 25(OH)D3, total 25(OH)D3, and the 3-epi- to total 25(OH)D3 ratio and the likelihood of developing IR. CONCLUSION: In the CoLaus study in healthy adults, the risk of incident IR is not associated with serum concentrations of 25(OH)D3 and total 25(OH)D3.

Cannabis use and other predictors of the onset of daily cigarette use in young men: what matters most? Results from a longitudinal study.

BACKGROUND: According to the gateway hypothesis, tobacco use is a gateway of cannabis use. However, there is increasing evidence that cannabis use also predicts the progression of tobacco use (reverse gateway hypothesis). Unfortunately, the importance of cannabis use compared to other predictors of tobacco use is less clear. The aim of this study was to examine which variables, in addition to cannabis use, best predict the onset of daily cigarette smoking in young men. METHODS: A total of 5,590 young Swiss men (mean age = 19.4 years, SD = 1.2) provided data on their substance use, socio-demographic background, religion, health, social context, and personality at baseline and after 18 months. We modelled the predictors of progression to daily cigarette smoking using logistic regression analyses (n = 4,230). RESULTS: In the multivariate overall model, use of cannabis remained among the strongest predictors for the onset of daily cigarette use. Daily cigarette use was also predicted by a lifetime use of at least 50 cigarettes, occasional cigarette use, educational level, religious affiliation, parental situation, peers with psychiatric problems, and sociability. CONCLUSIONS: Our results highlight the relevance of cannabis use compared to other potential predictors of the progression of tobacco use and thereby support the reverse gateway hypothesis.

Biomarkers of Host Response Predict Primary End-Point Radiological Pneumonia in Tanzanian Children with Clinical Pneumonia: A Prospective Cohort Study.

BACKGROUND: Diagnosing pediatric pneumonia is challenging in low-resource settings. The World Health Organization (WHO) has defined primary end-point radiological pneumonia for use in epidemiological and vaccine studies. However, radiography requires expertise and is often inaccessible. We hypothesized that plasma biomarkers of inflammation and endothelial activation may be useful surrogates for end-point pneumonia, and may provide insight into its biological significance. METHODS: We studied children with WHO-defined clinical pneumonia (n = 155) within a prospective cohort of 1,005 consecutive febrile children presenting to Tanzanian outpatient clinics. Based on x-ray findings, participants were categorized as primary end-point pneumonia (n = 30), other infiltrates (n = 31), or normal chest x-ray (n = 94). Plasma levels of 7 host response biomarkers at presentation were measured by ELISA. Associations between biomarker levels and radiological findings were assessed by Kruskal-Wallis test and multivariable logistic regression. Biomarker ability to predict radiological findings was evaluated using receiver operating characteristic curve analysis and Classification and Regression Tree analysis. RESULTS: Compared to children with normal x-ray, children with end-point pneumonia had significantly higher C-reactive protein, procalcitonin and Chitinase 3-like-1, while those with other infiltrates had elevated procalcitonin and von Willebrand Factor and decreased soluble Tie-2 and endoglin. Clinical variables were not predictive of radiological findings. Classification and Regression Tree analysis generated multi-marker models with improved performance over single markers for discriminating between groups. A model based on C-reactive protein and Chitinase 3-like-1 discriminated between end-point pneumonia and non-end-point pneumonia with 93.3% sensitivity (95% confidence interval 76.5-98.8), 80.8% specificity (72.6-87.1), positive likelihood ratio 4.9 (3.4-7.1), negative likelihood ratio 0.083 (0.022-0.32), and misclassification rate 0.20 (standard error 0.038). CONCLUSIONS: In Tanzanian children with WHO-defined clinical pneumonia, combinations of host biomarkers distinguished between end-point pneumonia, other infiltrates, and normal chest x-ray, whereas clinical variables did not. These findings generate pathophysiological hypotheses and may have potential research and clinical utility.