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Biomedical subjects

V Kairisto

Publications and source records attributed to V Kairisto.

At least 19 recordsLinked to original sources
PubMed2006

Hippocampal volume, brain atrophy, and APOE genotype after traumatic brain injury.

OBJECTIVE: To examine the association between hippocampal volumes, general brain atrophy, and apolipoprotein E (APOE) polymorphism in patients with a remote traumatic brain injury (TBI). METHODS: MRI-based volumetric analyses of the hippocampus and lateral ventricles were performed in 58 patients with TBI of varying severity on average 31.3 years after the trauma. The APOE genotype was determined using standard methods and correlated with the MRI volumetric measurements. RESULTS: Hippocampal or lateral ventricle volumes did not differ significantly in those patients with the APOE-epsilon4 allele (APOE4) vs those without this allele. CONCLUSIONS: The APOE-epsilon4 allele was not associated with the development of hippocampal or ventricular atrophy after traumatic brain injury. If the APOE-epsilon4 allele is associated with an unfavorable outcome after traumatic brain injury as proposed, this association may involve mechanisms other than those responsible for the development of brain atrophy.

Aged↗
PubMed2005

The occurrence of dominant spinocerebellar ataxias among 251 Finnish ataxia patients and the role of predisposing large normal alleles in a genetically isolated population.

OBJECTIVES: Frequency and distribution of dominant ataxias caused by dynamic mutations may vary in different populations, which has been explained on the basis of relative frequency of predisposing normal alleles. The aim of the study was to evaluate the occurrence of spinocerebellar ataxias (SCAs) and dentatorubral-pallidoluysian atrophy (DRPLA) in Finland, and to investigate the role of predisposing normal alleles in a genetically homogenous population. MATERIAL AND METHODS: Mutation analyses for SCA1, 2, 3, 6, 7, 8, 10, 12, 17, and DRPLA and frataxin genes were performed for 251 unrelated Finnish patients who presented with progressive ataxia disorder. RESULTS: Expansions of SCA1, SCA2, SCA6, SCA7, SCA8, and SCA17 genes were detected in 2, 1, 1, 7, 22, and 1 patients, respectively. Altogether, 39 and 7% of dominant and sporadic SCA patients, respectively, harboured expansions at some of the investigated loci. Normal variation, collected from 477 to 502 chromosomes at each disease loci, revealed that Finns were different from the Japanese but largely similar to other Caucasians. CONCLUSIONS: Lack of SCA3 and excess of SCA8 are characteristic to the Finnish population. Homozygosity for the SCA8 expansion increases penetrance. Frequencies of large normal alleles at the SCA loci predict poorly prevalence of the respective diseases in Finland. Prioritization in DNA testing, based on ethnic origin and geographical location, is recommendable in Finland, and analogous approach may be applied to other countries as well.

Ataxin-1↗
PubMed2004

APOE-epsilon4 predicts dementia but not other psychiatric disorders after traumatic brain injury.

The authors studied the association between APOE-epsilon4 genotype and axis I and II psychiatric disorders an average of 30 years after traumatic brain injury. Sixty patients were dichotomized into subjects with and without APOE-epsilon4 allele. Dementia and subclinical dementia were significantly more common with the presence of APOE-epsilon4. The occurrence of other psychiatric disorders did not differ between patients with and without APOE-epsilon4 allele.

Aged↗
PubMed2004

A multicentre study of reference intervals for haemoglobin, basic blood cell counts and erythrocyte indices in the adult population of the Nordic countries.

Eight haematological quantities were measured in EDTA anticoagulated venous blood specimens collected from 1826 healthy male and female individuals between 18 and 90 years of age in the Nordic countries (Denmark, Finland, Iceland, Norway and Sweden). The samples, collected between November 1999 and November 2001 as part of the Nordic Reference Interval Project (NORIP), were analysed on 12 different types of modern automated haematology instruments currently in use among the 60 laboratories participating in the study. Non-parametric reference intervals (between 2.5 and 97.5 percentiles) have been calculated for B-Haemoglobin (females 117-153 g/L, males 134-170 g/L), B-Erythrocytes (females 3.94-5.16 x 10(12)/L, males 4.25-5.71 x 10(12)/L), B-EVF (females 0.348-0.459, males 0.395-0.500), B-MCV (82-98 fL), Erc-MCH (27.1-33.3 pg), Erc-MCHC (317-357 g/L), B-Trc (females 165-387 x 10(9)/L, males 145 x 348 x 10(9)/L) and B-Lkc (3.5-8.8 x 10(9)/L). Partitioning of data according to age and gender was done according to a standardized procedure. For most variables the calculated reference intervals corresponded well with older and less well-defined reference intervals. The mean concentration of B-Haemoglobin increased by 0.08 g/L per year of age in women, and decreased by 0.1 g/L per year of age in men. B-Haemoglobin increased with body mass index in both men and women. Smoking increased the mean of B-Lkc by 1.1 x 10(9)/L and regular use of alcohol increased the mean of B-MCV by 0.8 fL. The influence of these factors was small overall and did not promote specific reference intervals.

Adolescent↗
PubMed2004

The Nordic Reference Interval Project 2000: recommended reference intervals for 25 common biochemical properties.

Each of 102 Nordic routine clinical biochemistry laboratories collected blood samples from at least 25 healthy reference individuals evenly distributed for gender and age, and analysed 25 of the most commonly requested serum/plasma components from each reference individual. A reference material (control) consisting of a fresh frozen liquid pool of serum with values traceable to reference methods (used as the project "calibrator" for non-enzymes to correct reference values) was analysed together with other serum pool controls in the same series as the project samples. Analytical data, method data and data describing the reference individuals were submitted to a central database for evaluation and calculation of reference intervals intended for common use in the Nordic countries. In parallel to the main project, measurements of commonly requested haematology properties on EDTA samples were also carried out, mainly by laboratories in Finland and Sweden. Aliquots from reference samples were submitted to storage in a central bio-bank for future establishment of reference intervals for other properties. The 25 components were, in alphabetical order: alanine transaminase, albumin, alkaline phosphatase, amylase, amylase pancreatic, aspartate transaminase, bilirubins, calcium, carbamide, cholesterol, creatine kinase, creatininium, gamma-glutamyltransferase, glucose, HDL-cholesterol, iron, iron binding capacity, lactate dehydrogenase, magnesium, phosphate, potassium, protein, sodium, triglyceride and urate.

Biomarkers↗
PubMed2004

Reference individuals, blood collection, treatment of samples and descriptive data from the questionnaire in the Nordic Reference Interval Project 2000.

The rules for recruitment of reference individuals, inclusion and preparation of individuals, blood collection, treatment of samples (and control materials) and analysis at the 102 medical laboratories attending the Nordic Reference Interval Project (NORIP) are given as well as the rules for central exclusion of reference individuals. The individuals (18-91-year-olds) should be evenly distributed on age and gender groups. The 3002 reference individuals who contributed at least one reference value to the finally suggested reference intervals were characterized using the information in the questionnaire. Gender, age and country are the main entries in the tables. Other variables in the cross-tables or figure are height, weight, body mass index, ethnic origin, heredity for diabetes, chronic disease, oestrogens or oral contraceptives, other medication, hard physical activity, previous blood donations, smoking habits, use of alcohol, hours since last meal and time of blood collection (hour, day of week, month, year). The Danes had the highest alcohol consumption and the Icelanders had the highest body mass index. The information in this article may interest potential users of the Nordic Reference Interval Project bio-bank and database (NOBIDA) in which serum, Li-heparin plasma and EDTA buffy coat from the mentioned individuals are stored below -80 degrees C.

Adolescent↗
PubMed2000

Rapid single-tube screening of the C282Y hemochromatosis mutation by real-time multiplex allele-specific PCR without fluorescent probes.

BACKGROUND: An accurate determination of the major HFE mutation (C282Y), which is associated with hereditary hemochromatosis, is important in diagnosis and risk assessment for this disease. We report a single-tube high-throughput PCR method for the detection of C282Y. METHODS: We combined three previously described principles: allele-specific PCR, mutagenically separated PCR, and amplicon identification by specific dissociation curves. PCR amplification was performed with fluorescence detection or conventional thermocycler using the same primers, reactant constituents, and cycling protocol. Primer cross-reactions were prevented by deliberate primer:primer and primer:template mismatches. RESULTS: PCR products were identified by their characteristic melting temperatures based on SYBR Green I fluorescence. For each of the 256 random and 17 known HFE C282Y samples, mutant homozygous, wild-type, and heterozygous samples were unequivocally distinguished. CONCLUSIONS: This homogeneous assay is rapid, reproducible, does not require fluorescent oligonucleotide probes, and correctly identifies HFE genotypes.

Alleles↗
PubMed1998

Biological day-to-day variation and daytime changes of testosterone, follitropin, lutropin and oestradiol-17beta in healthy men.

Information on biological day-to-day variation is needed for detecting within-subject changes over time. In this study the daytime changes and the biological day-to-day variation of serum testosterone, follitropin, lutropin and oestradiol-17beta concentrations were investigated in 31 healthy males. To analyse daytime changes, blood specimens were taken at 0800 h, 1200 h, 1600 h and 2000 h during one day (n=31) and two days (n=8). The day-to-day variation was analysed from blood specimens collected at 0800 h on days 1 and 2 (n=31) and additionally on days 3, 4, 6 and 9 (n=8). The evaluation of the day-to-day variation was based on calculations of the within-subject (CVA+I) and between-subject (CV(G)) coefficients of variation. When the within-subject day-to-day variances were not too heterogeneous, they were used for the calculation of 95 % reference change limits. Serum testosterone and oestradiol-17beta concentrations showed a significant daytime variation; testosterone had higher serum concentrations at 0800 and 1200 h. A peak in the serum concentration of oestradiol-17beta occurred at 1200 h with a decrease towards the evening. There were no clear daytime changes in the serum concentrations of follitropin or lutropin. For different analytes the reference change limits were: serum testosterone +/- 32.0 %, serum follitropin +/- 24.1 % and serum oestradiol-17beta +/- 38.3 %. The reference change limit was not calculated for serum lutropin, as a high degree of heterogeneity and individuality was found. The interpretation of the results of hormone measurements requires recognition of the biological daytime and day-to-day changes of hormones. The reference change limits determine what changes are significant when monitoring the patient.

Adult↗
PubMed1998

Regression-based reference limits and their reliability: example on hemoglobin during the first year of life.

Calculation of reference limits by regression analysis makes it unnecessary to partition the reference data into subgroups, and age-dependent limits can be estimated within as narrow age intervals as necessary. However, the reliability of the regression-based reference limits has not been considered before. To get valid regression-based confidence intervals (CIs) for reference limits, one must evaluate the convolution of two distributions. In this study, age-dependent reference limits with corresponding CIs were produced for blood hemoglobin concentrations over the age interval from newborns to 12 months. We describe how the variance associated with the reference limits can be estimated, and present a Table from which appropriate values can be chosen for the calculation of regression-based reference limits and exact CIs. Also, an equation for the calculation of approximate CIs is given. The data were modeled by linear regression in several cumulative age groups to find the transition zone where the slope changed. After defining this cutoff point, piecewise linear regression was applied. Reference limits and their CIs calculated by conventional and piecewise linear regression methods were almost the same in older age groups but differed significantly during the period of most rapid age-dependent changes, i.e., during the 2 months after birth.

Age Factors↗
PubMed1998

Regression-based reference limits: determination of sufficient sample size.

Regression analysis is the method of choice for the production of covariate-dependent reference limits. There are currently no recommendations on what sample size should be used when regression-based reference limits and confidence intervals are calculated. In this study we used Monte Carlo simulation to study a reference sample group of 374 age-dependent hemoglobin values. From this sample, 5000 random subsamples, with replacement, were constructed with 10-220 observations per sample. Regression analysis was used to estimate age-dependent 95% reference intervals for hemoglobin concentrations and erythrocyte counts. The maximum difference between mean values of the root mean square error and original values for hemoglobin was 0.05 g/L when the sample size was > or = 60. The parameter estimators and width of reference intervals changed negligibly from the values calculated from the original sample regardless of what sample size was used. SDs and CVs for these factors changed rapidly up to a sample size of 30; after that changes were smaller. The largest and smallest absolute differences in root mean square error and width of reference interval between sample values and values calculated from the original sample were also evaluated. As expected, differences were largest in small sample sizes, and as sample size increased differences decreased. To obtain appropriate reference limits and confidence intervals, we propose the following scheme: (a) check whether the assumptions of regression analysis can be fulfilled with/without transformation of data; (b) check that the value of v, which describes how the covariate value is situated in relation to both the mean value and the spread of the covariate values, does not exceed 0.1 at minimum and maximum covariate positions; and (c) if steps 1 and 2 can be accepted, the reference limits with confidence intervals can be produced by regression analysis, and the minimum acceptable sample size will be approximately 70.

Child, Preschool↗
PubMed1997

Reference intervals for serum thyrotropin, free thyroxine and free triiodothyronine in healthy adults in Finland, measured by an immunoautomate based on time-resolved fluorescence (AutoDELFIA).

We have established reference intervals for healthy adults of serum thyrotropin, free thyroxine and free triiodothyronine using the AutoDELFIA (Wallac, Finland) automatic measuring device. The determination of reference intervals in a proper manner is costly, and many laboratories adopt reference ranges from the literature rather than determining them alone. This is the first report on reference values in thyroidology where this automatic system based on time-resolved fluorescence has been used. The reference intervals for thyrotropin, free thyroxine and free triiodothyronine were 0.6-4.3 mIU/l, 9.6-17.1 pmol/l and 4.3-7.5 pmol/l, respectively.

Adult↗
PubMed1995

Estimation of reference change limits using patient data.

Two approaches for deriving reference change limits from patient data are described. In the direct method, hospital database information is used for the selection of appropriate reference groups. If database information is not sufficient or reliable enough, but still most of the source data can be considered as health-related, an indirect method can be applied in the calculation of rough estimates for reference change limits. A computer program developed by us, GraphROC for Windows, includes both methods for the estimation of change limits from patient data. Time between specimen collections should be included as one classifying factor in the selection of source data. When only one previous result is available for comparison, change limits based on the reference sample group form the only available guide for clinical interpretation. However, when several previous results are available and the within-subject variances for the considered analyte are known to be heterogeneous between individuals, the clinical interpretation should rather be based on application of time series analysis.

Data Interpretation, Statistical↗
PubMed1995

Software for illustrative presentation of basic clinical characteristics of laboratory tests--GraphROC for Windows.

GraphROC for Windows is a program for clinical test evaluation. It was designed for the handling of large datasets obtained from clinical laboratory databases. In the user interface, graphical and numerical presentations are combined. For simplicity, numerical data is not shown unless requested. Relevant numbers can be "picked up" from the graph by simple mouse operations. Reference distributions can be displayed by using automatically optimized bin widths. Any percentile of the distribution with corresponding confidence limits can be chosen for display. In sensitivity-specificity analysis, both illness- and health-related distributions are shown in the same graph. The following data for any cutoff limit can be shown in a separate click window: clinical sensitivity and specificity with corresponding confidence limits, positive and negative likelihood ratios, positive and negative predictive values and efficiency. Predictive values and clinical efficiency of the cutoff limit can be updated for any prior probability of disease. Receiver Operating Characteristics (ROC) curves can be generated and combined into the same graph for comparison of several different tests. The area under the curve with corresponding confidence interval is calculated for each ROC curve. Numerical results of analyses and graphs can be printed or exported to other Microsoft Windows programs. GraphROC for Windows also employs a new method, developed by us, for the indirect estimation of health-related limits and change limits from mixed distributions of clinical laboratory data.

Clinical Laboratory Techniques↗
PubMed1995

Reliability and adequacy of discharge diagnosis databases in the production of reference values.

Discharge diagnoses provide a possibility to select patients individually and then to establish reference values for both "pathological" and control groups. Currently, the available diagnostic information is still at its infancy and should be carefully evaluated before the reference values based on those groups are utilized. It is anticipated that electronic storage of diagnostic and therapeutic information will be applied more commonly in the future as the development of computers makes it easier. The advanced utilization of laboratory data challenges physicians both in the clinical and laboratory side to participate in this development in order to make the information systems serve their actual needs more closely.

Clinical Laboratory Information Systems↗
PubMed1995

Effect of platelet count on serum and plasma potassium: evaluation using database information from two hospitals.

The availability of retrospective data from potassium (K+) analyses from two hospitals, one using serum and the other plasma for electrolyte measurements, offered us the possibility to investigate the effect of blood platelet count on serum and plasma K+ concentrations. A weak correlation between plasma K+ and platelet count was observed. The in vitro increase of serum K+ in proportion to the platelet count has clinical significance in conditions, where it may impede the detection of an underlying true K+ disorder. Nomograms and correction factors, based on the correlation between platelet count and serum K+, have been suggested also in some recent reports. In the present study unselected routine patient data was used as source data. The effect of platelet count on the concentration of K+ in serum was lower than reported in previous studies, as indicated by the regression analysis. An increase of 1000 x 10(9)/l in the blood platelet count would cause an increase of about 0.7 mmol/l in the serum K+ concentration (p < 0.0001, r = 0.155). The weak correlation between platelet count and serum K+ does not support the application of platelet-count-based correction of serum K+ level in thrombocytosis. The laboratory should notify the clinician of the significance of the in vitro increase of K+ caused by increased platelet count. K+ should be measured from plasma in such cases.

Artifacts↗