SEARCH · PubMed Health

Results for “External validation”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10Linked to original sources

PubMed1993

An examination of cluster-based classification schemes for DUI offenders.

This study examines the utility of cluster-based classification schemes for DUI offenders. Variables from previous empirical typologies and multiple domains were used in a series of cluster analyses in order to examine replicability across independent samples, across clustering algorithms and across sets of psychometric indicators. The arbitrary nature of cluster solutions and the external validity of cluster-based schemes, with respect to an outcome criterion constructed synthetically from earlier research, was examined. Only three of eight cluster techniques (Ward's, K means, and complete linkage) yielded meaningful results. For these techniques, replicability was poor across samples, algorithms and sets of psychometric indicators. Results indicated that identified clusters were arbitrary. Although external validity analysis yielded positive results, the possibility that external validity was a function of underlying dimensions was discussed, as were other implications of the findings.

Adult↗

PubMed2003

German multicenter study group for adult ALL (GMALL): recruitment in comparison to ALL incidence and its impact on study results.

Due to eligibility criteria not all patients with the disease under investigation can be recruited for therapeutic studies. Thus, the external validity of study results cannot per se be taken for granted. The representativity of the admitted patients is the most relevant determinant for external validity and has to be assessed. As an example we examined the representativity of the patients recruited for the German multicenter study group for adult acute lymphoblastic leukemia (ALL) (GMALL). Lacking nationwide ALL incidence figures available in Germany, a methodology was developed to estimate incidence figures, too. All relevant study groups, hospitals, and diagnostic labs were asked to provide data about patients with ALL newly diagnosed between 1997 and 1998. A matching procedure was developed, as heterogeneous databases had to be pooled and checked for duplicates. Age- and sex-specific incidences of ALL were estimated and compared with the number of patients recruited for the GMALL in the same time period. The purpose was to develop a methodology for estimating incidence figures and evaluating the representativity of patients of the GMALL. The combination of various data sources allowed estimation of reliable incidence data for ALL in Germany. Comparisons with the incidence figures for ALL in other countries and crosschecks within Germany confirm our results. Sixty-two percent of all ALL patients in Germany were admitted to the GMALL study. The recruitment rate of more than 60% of the annual incidence of ALL to the GMALL suggests a high external validity as well as an impact of the study on the patterns of treatment and referral of ALL in adults in Germany. There is no selection bias of patients admitted to the GMALL compared to those patients not included in the study.

Adolescent↗

PubMed2002

Prediction of VO(2peak) in wheelchair-dependent athletes from the adapted Léger and Boucher test.

PURPOSE: :The purpose of this study was to provide a predictive peak oxygen uptake ([V]O(2) peak) equation in wheelchair-dependent athletes using the Adapted Léger and Boucher test. SUBJECTS AND PROTOCOL: :Fifty-six wheelchair-dependent athletes, 47 males and nine females (30.3+/-4 years), underwent a clinical examination to assess their anthropometric characteristics: height, mass, body mass index (BMI), lean body mass, arm length, and muscular arm volume. They performed a deceleration field test to assess the subject-wheelchair resistance defined as a mechanical variable, and they then performed the Adapted Léger and Boucher test to assess physiological data at maximal exercise ([V]O(2) peak, heart rate max) concomitantly with biomechanical (number of pushes) and performance variables (maximal aerobic velocity Va(max) and maximal distance). The [V]O(2) peak was measured directly using a portable telemetric oxygen analyzer. Subjects were then randomly assigned to an experimental group (n=49) to determine the predictive equation, and a validation group (n=7) to check the external validity of the equation. RESULTS: A stepwise multiple regression with [V]O(2) peak (l min(-1)) as the dependent variable led to the following equation: [V]O(2) peak=0.22 Va(max) - 0.63 log(age)+0.05 BMI 0.25 level+0.52, with r(2)=0.81 and SEE=0.01. Paraplegic subjects with high and low lesion level spinal injuries were attributed the coefficient of 1 and 0, respectively. The external validity of the equation was positive since the predicted [V]O(2) peak values did not significantly differ from directly measured [V]O(2) peak (P>0.05). CONCLUSION: We concluded that [V]O(2) peak in wheelchair-dependent athletes was predictable using the equation of the present study and the described incremental test.

Adolescent↗

PubMed2001

Validity of the five-item WHO Well-Being Index (WHO-5) in an elderly population.

BACKGROUND: Depression has a high prevalence in the elderly population; however it often remains undetected. The WHO 5-item Well-Being Index (WHO-5) is a short screening instrument for the detection of depression in the general population, which has not yet been evaluated. The goals of the present study were: 1) to assess the internal and external validity of WHO-5 and 2) to compare the two recent versions of WHO-5. STUDY POPULATION AND METHODS: 367 subjects above 50 years of age were examined with the WHO-5. ICD-10 diagnoses were made using a structured interview (CIDI). The internal validity of the well-being index was evaluated by calculating Loevinger's and Mokken's homogeneity coefficients. External validity for detection of depression was evaluated by ROC analysis. RESULTS: The scale was sufficiently homogeneous (Loevinger's coefficient: version 1 = 0.38, version 2 = 0.47; Mokken coefficient > 0.3 in nearly all items). ROC analysis showed that both versions adequately detected depression. Version 1 additionally detected anxiety disorders, version 2 being more specific for detection of depression. CONCLUSION: The WHO-5 showed a good internal and external validity. The second version is a stronger scale and was more specific for the detection of depression. The WHO-5 is an useful instrument for identifying elderly subjects with depression.

Aged↗

PubMed2003

Methodological index for non-randomized studies (minors): development and validation of a new instrument.

BACKGROUND: Because of specific methodological difficulties in conducting randomized trials, surgical research remains dependent predominantly on observational or non-randomized studies. Few validated instruments are available to determine the methodological quality of such studies either from the reader's perspective or for the purpose of meta-analysis. The aim of the present study was to develop and validate such an instrument. METHODS: After an initial conceptualization phase of a methodological index for non-randomized studies (MINORS), a list of 12 potential items was sent to 100 experts from different surgical specialties for evaluation and was also assessed by 10 clinical methodologists. Subsequent testing involved the assessment of inter-reviewer agreement, test-retest reliability at 2 months, internal consistency reliability and external validity. RESULTS: The final version of MINORS contained 12 items, the first eight being specifically for non-comparative studies. Reliability was established on the basis of good inter-reviewer agreement, high test-retest reliability by the kappa-coefficient and good internal consistency by a high Cronbach's alpha-coefficient. External validity was established in terms of the ability of MINORS to identify excellent trials. CONCLUSIONS: MINORS is a valid instrument designed to assess the methodological quality of non-randomized surgical studies, whether comparative or non-comparative. The next step will be to determine its external validity when used in a large number of studies and to compare it with other existing instruments.

Clinical Trials as Topic↗

PubMed1981

[Quasi experimental evaluation of public health interventions (author's transl)].

The classic experiment, the randomised controlled trial, is the best known and most revered of evaluation research methods. Randomization in community-based intervention trials, however, is not always possible because of ethical problems arising from with holding the experimental treatment from the control groups or the difficulties in conducting experiments in field settings which do not approach controlled laboratory conditions. In such circumstances, quasi-experimental or observational designs must be used. Two major principles are involved in using quasi-experimental methods: (1) the logic for establishing causality between treatment and effect is the same as that for randomised experiments, but the problems of assessing causality or internal validity are greater, and (2) assessment of the external validity or generalizability of quasi-experimental findings crucial to the interpretation of results. Selected quasi-experimental designs using time series and comparison groups are described with examples from public health intervention trials where threats to internal validity have been assessed by using different analytic techniques or gathering additional evidence. Quasi-experimental evaluations are most useful when opportunities exist for testing rival hypotheses concerning the internal and external validity, or the findings can be used to complement true experiments.

Epidemiologic Methods↗

PubMed2002

Discriminant and quantitative PLS analysis of competitive CYP2C9 inhibitors versus non-inhibitors using alignment independent GRIND descriptors.

This study describes the use of alignment-independent descriptors for obtaining qualitative and quantitative predictions of the competitive inhibition of CYP2C9 on a serie of highly structurally diverse compounds. This was accomplished by calculating alignment independent descriptors in ALMOND. These GRid INdependent Descriptors (GRIND) represent the most important GRID-interactions as a function of the distance instead of the actual position of each grid-point. The experimental data was determined under uniform conditions. The inhibitor data set consists of 35 structurally diverse competitive stereospecific inhibitors of the cytochrome P450 2C9 and the non -inhibitor data set of 46 compounds. In a PLS discriminant analysis 21 inhibitors and 21 non-inhibitors (1 and 0 as activities) were analyzed using the ALMOND program obtaining a model with an r2 of 0.74 and a cross-validation value (q2) of 0.64. The model was externally validated with 39 compounds (14 inhibitors/25 non-inhibitors). 74% of the compounds were correctly predicted and an additional 13% was assigned to a borderline cluster. Thereafter, a model for quantitative predictions was generated by a PLS analysis of the GRIND descriptors using the experimental Ki-value for 21 of the competitive inhibitors (r2 = 0.77, q2 = 0.60). The model was externally validated using 12 compounds and predicted 11 out of 12 of the Ki-values within 0.5 log units. The discriminant model will be useful in screening for CYP2C9 inhibitors from large compound collections. The 3D-QSAR model will be used during lead optimization to avoid chemistry that result in inhibition of CYP2C9.

Aryl Hydrocarbon Hydroxylases↗

PubMed2026

Risk prediction in patients with heart failure with preserved ejection fraction: the LIFE-Preserved model.

BACKGROUND AND AIMS: Heart failure (HF) with preserved ejection fraction (HFpEF) constitutes a heterogeneous disease with varying prognosis. Given the rising incidence of HFpEF, accurate risk prediction for these patients is needed to identify high-risk individuals, who may benefit the most from preventive treatments. The LIFE-Preserved model was developed and validated for the prediction of individual short-term and lifetime risk for HF hospitalization or cardiovascular (CV) death in patients with HFpEF. METHODS: LIFE-Preserved was derived in 20 332 patients aged 40-90 years with a left ventricular ejection fraction ≥ 50% from the Swedish HF Registry. Cause- and sex-specific Cox models were derived to predict the risk of HF hospitalization or CV death using 14 routinely available predictors. Use of age as the timescale allowed for predictions beyond the maximum follow-up duration in the derivation data, adjusted for competing risks. External validation was performed in two trials (EMPEROR-Preserved and TOPCAT-Americas) and three registries (NHS England Secure Data Environment, Veterans Affairs, and HF-Particles). Model performance was assessed by discrimination and calibration. RESULTS: During a median follow-up of 1.8 years (interquartile range .6-4.2, maximum 19 years), 9341 first HF hospitalizations or CV deaths (46%) were observed in Swedish HF Registry. External validation included data from 28 062 patients with HFpEF [9930 (35%) first HF hospitalizations or CV deaths]. Pooled C-statistics were .714 (95% confidence interval .652-.775) in trials and .658 (95% confidence interval .599-.717 in registries, with adequate calibration in all external validation sources. Performance was similar in men and women. An interactive calculator of the LIFE-Preserved model has been made available here. CONCLUSIONS: The LIFE-Preserved model enables prediction of short-term and lifetime risk of HF hospitalization or CV death in patients with HFpEF. The model could serve as a tool to identify high-risk HFpEF patients, guiding clinical management and shared decision-making.

Humans↗

PubMed2026

Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation strategies and may have overinterpreted model performance. OBJECTIVE: This study evaluated the diagnostic performance of ML and deep learning (DL) models for 3 clinically distinct SLE-related tasks: SLE classification or diagnosis, lupus nephritis (LN) diagnosis, and neuropsychiatric systemic lupus erythematosus (NPSLE) discrimination. We also assessed methodological quality and certainty of evidence. METHODS: PubMed, Embase, Cochrane Library, Web of Science, and IEEE Xplore were searched from January 2014 to April 2026. Eligible peer-reviewed diagnostic accuracy studies developed or validated ML or DL models for 1 of the 3 prespecified tasks, used an accepted reference standard, and provided data for a 2×2 contingency table. Bivariate random-effects meta-analyses with the Hartung-Knapp-Sidik-Jonkman adjustment were used to pool sensitivity and specificity. We reported 95% prediction intervals (PIs), assessed risk of bias using the Quality Assessment of Diagnostic Accuracy Studies for Artificial Intelligence tool (QUADAS-AI; Viknesh Sounderajah [Imperial College London]), and evaluated certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation framework for diagnostic test accuracy. RESULTS: Twenty-nine studies were included: 17 for SLE classification, 5 for LN diagnosis, and 7 for NPSLE discrimination. In the primary task-stratified analysis, pooled sensitivity was 0.91 (95% CI 0.86-0.94; 95% PI 0.56-0.99), and pooled specificity was 0.94 (95% CI 0.91-0.96; 95% PI 0.69-0.99), with low heterogeneity (I²=23.9% and 22.9%, respectively). DL models showed a sensitivity of 0.93 and specificity of 0.95, compared with 0.88 and 0.94 for traditional ML models. Certainty of evidence was high for most analyses but low for LN diagnosis because of inconsistency and imprecision. All studies were retrospective, and only 9 of 29 (31%) performed independent external validation. Overall risk of bias was high or unclear in 22 of 29 (75.9%) studies. No study reported model calibration, decision-curve analysis, or net clinical benefit. CONCLUSIONS: ML models showed promising diagnostic accuracy across 3 distinct SLE-related tasks, but wide PIs, limited external validation, and pervasive risk of bias restrict conclusions about real-world generalizability. Prospective multicenter studies with standardized tasks and reference standards, independent external validation, and formal assessment of calibration and clinical utility are required before clinical implementation.

Humans↗

PubMed1991

Who enrolls in prevention trials? Discordance in perception of risk by professionals and participants.

Internal and external validity problems permeate all intervention studies but are accentuated in primary preventive intervention research, particularly when studies target or recruit individuals based on their risk for psychopathology. Since many people who are at risk do not yet experience distress, they may not perceive the need for intervention. Recruitment tactics based on explaining extent of risk are unlikely to be persuasive and may have negative consequences. If respondents are not motivated to participate, a small or biased subset of the target population will participate in the intervention. Bias is of special concern when those enrolled represent only part of the continuum of risk. Selective enrollment may compromise both internal validity (the interpretation of the research results) and external validity (the generalizability of the findings) of intervention trials in primary prevention. This article discusses the effects of partial enrollment and the resultant bias. It suggests several strategies for increasing the enrollment of the target population and examines some of their ethical ramifications. It also stresses the importance of collecting systematic data documenting how the participants in the intervention differ from the target group as a whole.

Bias↗

PubMed2000

Short form of a situational temptation scale for heavy, episodic drinking.

PURPOSE: A short form for situational temptations to drink scale was developed from an original 21-item inventory by Migneault. METHODS: The form measured four hypothesized subscales of temptations on a sample of 348 college drinkers (66% female). Peer pressure, social anxiety, negative affect, and positive/social situations subscales were replicated and reduced. RESULTS: Strong empirical support was found for a hierarchical model, indicating that the four subscales can be summed to provide a global measure of situational temptations. Confirmatory factor results, internal and external validity, and high correlations with the original measures indicate that the short form was as psychometrically valid as the original measure. IMPLICATIONS: Measures of external validity demonstrated the applicability of this measure to heavy drinking prevention programs.

Adult↗

PubMed1975

Changes in obsessive/compulsive patients as measured by the Leyton Inventory before and after treatment with clomipramine.

The Leyton Obsessional Inventory has been found to be a useful measure in assessing patients before and after treatment with clomipramine. Mean scores for symptoms and interference altered significantly during the course of treatment. The Leyton Obsessional Inventory, however, lacks external validation owing to the absence of some valid alternative quantification. In the absence of such external validation it seems justifiable to use the mean Leyton score diagnostically but not as a sole indication of severity or response to treatment.

Clinical Trials as Topic↗

PubMed1999

Model validation for external doses due to environmental contaminations by the Chernobyl accident.

The objective of the present paper is to validate the deterministic JSP5 model for external exposures to population groups living in the areas contaminated with radionuclides after the Chernobyl accident. For this purpose inhabitants of contaminated areas wore TL-dosimeters for about 1 mo in the spring/summer periods of the years 1989 to 1994. External doses due to the Chernobyl accident were determined from the dosimeter readings by subtracting the natural background. 2,342 results for rural inhabitants and 420 results for inhabitants of the town Novozybkov passed reliability checks. These data show that the average dose in inhabitants of a rural settlement predicted by the model is in the range 0.69-1.55 of the measured values with a confidence level of 95%. Differences are attributed to settlement specific location factors, which are supported by the very good agreement of model and measurements in Novozybkov. In this case location factors of the model were obtained from Novozybkov directly.

Adult↗

PubMed2003

Is the ACLS score a valid prediction rule for survival after cardiac arrest?

UNLABELLED: The ACLS (advanced cardiac life support) Score was previously developed to predict survival from out-of-hospital cardiac arrest. Whether the arrest was witnessed, initial cardiac rhythm, performance of bystander cardiopulmonary resuscitation (CPR), and the response time of the paramedic unit were determined to be predictive of survival. However, the ACLS Score has not been validated in other emergency medical services systems. OBJECTIVES: The purpose of this study was to externally validate the ACLS Score in one patient population. METHODS: This was a retrospective cohort study performed at an urban county teaching hospital. The study population consisted of consecutive adult patients treated for out-of-hospital, nontraumatic cardiac arrest, and transported to the authors' institution between November 1, 1994, and September 30, 2001. Patient records for all cardiac arrests during the study period were reviewed. Study variables included witnessed arrest, initial arrest rhythm, bystander CPR, paramedic response time, and survival to hospital discharge. Predicted probability of survival to hospital discharge was calculated for each patient using the ACLS Score. The overall predicted and observed survival rates were compared using Flora's Z score. The Hosmer-Lemeshow test was used to evaluate the model's goodness-of-fit over a range of survival probabilities. RESULTS: Of 754 cardiac arrest patients enrolled in the study period, 575 (76%) patients had documentation that allowed scoring using the ACLS Score. Twenty-five (4%) patients survived to hospital discharge. The predicted number of survivors based on the ACLS Score was 104 (18%), yielding a Flora's Z statistic of -4.46 (p < 0.0001). After categorizing predicted survival probabilities into four categories, the resulting Hosmer-Lemeshow statistic was 210 (p << 10(-6)). Both goodness-of-fit statistics demonstrated extremely poor fit of the model. A receiver operating characteristic (ROC) curve was created, yielding an area under the ROC curve of 0.33 (95% CI = 0.19 to 0.47), signifying extremely poor discrimination. CONCLUSIONS: The previously published ACLS Score was not valid when applied to an external cohort of out-of-hospital cardiac arrest patients. An externally valid model is needed to predict survival to hospital discharge following out-of-hospital cardiac arrest.

Advanced Cardiac Life Support↗

PubMed2026

Machine Learning-Driven Prediction of Coronary Artery Disease Risk Based on UK Biobank Plasma Proteomics.

BACKGROUND: Coronary artery disease (CAD) is a leading global cause of mortality, yet the predictive accuracy of conventional risk models is limited. Here, we integrate conventional risk factors, polygenic risk scores, and large-scale proteomics to develop a unified model for enhanced CAD risk prediction. METHODS: Using data from UK Biobank, participants with plasma proteomics and genetic risk data were included after excluding prevalent CAD. Participants from England were split into training (n=32 330) and internal validation (n=13 857) sets, and Scotland/Wales participants formed an external validation set (n=5775). Incident CAD was ascertained from linked health records. A 202-protein proteomic risk score was derived by least absolute shrinkage and selection operator Cox regression, and CatBoost models were trained using conventional risk factors alone and with incremental addition of polygenic risk scores and protein proteomic risk scores; Shapley Additive Explanations-guided forward selection identified a compact protein panel. RESULTS: Across cohorts, the median age was 58 years and ∼45% were men. Protein proteomic risk score was dose-dependently associated with CAD risk. Compared with conventional risk factors alone, integrating polygenic risk scores and protein proteomic risk scores improved discrimination, with the area under the curve increasing from 0.750 (95% CI, 0.732-0.767) to 0.789 (95% CI, 0.772-0.805) in internal validation and from 0.717 (95% CI, 0.683-0.750) to 0.762 (95% CI, 0.732-0.791) in external validation. A 9-protein panel (GDF15 [growth differentiation factor 15], MMP12 [matrix metalloproteinase 12], NPPB [natriuretic peptide B], PGF [placental growth factor], REN [renin], ADGRG2 [adhesion G-protein coupled receptor], ACE2 [angiotensin-converting enzyme 2], CDCP1 [CUB domain-containing protein 1], CXCL17 [C-X-C motif chemokine ligand 17)]) captured most proteomic predictive information. CONCLUSIONS: Our findings demonstrate that integrating conventional risk factors, polygenic risk scores, and proteomic data improves CAD risk prediction. This study highlights the utility of proteomics in precision cardiovascular medicine and simplified risk stratification tools.

Humans↗

PubMed2004

Generalizing disease management program results: how to get from here to there.

For a disease management (DM) program, the ability to generalize results from the intervention group to the population, to other populations, or to other diseases is as important as demonstrating internal validity. This article provides an overview of the threats to external validity of DM programs, and offers methods to improve the capability for generalizing results obtained through the program. The external validity of DM programs must be evaluated even before program selection and implementation are begun with a prospective new client. Any fundamental differences in characteristics between individuals in an established DM program and in a new population/environment may limit the ability to generalize.

Disease Management↗

PubMed2026

Machine learning-enabled multi-omics discovery of prognostic biomarkers and signaling targets in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains difficult to subtype using single omics layers. We conducted an exploratory investigation integrating reverse-phase protein array (RPPA) and DNA methylation data from the cancer genome atlas (TCGA)- pancreatic adenocarcinoma (PAAD) to assess the feasibility of multi-omics subtyping, alongside a supervised machine learning analysis of a small gene expression omnibus (GEO) transcriptomic cohort (n = 26) to identify candidate diagnostic genes. RPPA-based K-means clustering suggested a weak, possible two-subtype structure (silhouette ≈ 0.16) that remained unassociated with overall survival (log-rank p = 0.113) and lacked independent prognostic value. An independently performed similarity network fusion (SNF) analysis integrating RPPA and methylation data showed low concordance with RPPA-derived subtypes (Adjusted Rand Index (ARI) = 0.014), indicating limited convergence between molecular modalities. Supervised machine learning analysis of the GEO cohort using a fully nested leave-one-out cross-validation pipeline achieved a mean (area under the curve) AUC of 0.896 across four classifiers and identified four-fold-stable candidate genes (ESCO2, COL17A1, BCL2L14, and SOWAHB). However, this gene panel demonstrated limited external validity across two independent PDAC cohorts (log-rank p = 0.438 for both GSE62452 and GSE28735), indicating limited generalizability despite robust internal performance. Collectively, these findings provide limited evidence for a robust, prognostically significant multi-omics subtype or a validated diagnostic gene signature; instead, this study serves as a hypothesis-generating resource and highlights the importance of rigorous cross-validation and independent external validation in small-sample transcriptomic biomarker discovery.

Humans↗

PubMed2003

Pragmatic controlled clinical trials in primary care: the struggle between external and internal validity.

BACKGROUND: Controlled clinical trials of health care interventions are either explanatory or pragmatic. Explanatory trials test whether an intervention is efficacious; that is, whether it can have a beneficial effect in an ideal situation. Pragmatic trials measure effectiveness; they measure the degree of beneficial effect in real clinical practice. In pragmatic trials, a balance between external validity (generalizability of the results) and internal validity (reliability or accuracy of the results) needs to be achieved. The explanatory trial seeks to maximize the internal validity by assuring rigorous control of all variables other than the intervention. The pragmatic trial seeks to maximize external validity to ensure that the results can be generalized. However the danger of pragmatic trials is that internal validity may be overly compromised in the effort to ensure generalizability. We are conducting two pragmatic randomized controlled trials on interventions in the management of hypertension in primary care. We describe the design of the trials and the steps taken to deal with the competing demands of external and internal validity. DISCUSSION: External validity is maximized by having few exclusion criteria and by allowing flexibility in the interpretation of the intervention and in management decisions. Internal validity is maximized by decreasing contamination bias through cluster randomization, and decreasing observer and assessment bias, in these non-blinded trials, through baseline data collection prior to randomization, automating the outcomes assessment with 24 hour ambulatory blood pressure monitors, and blinding the data analysis. SUMMARY: Clinical trials conducted in community practices present investigators with difficult methodological choices related to maintaining a balance between internal validity (reliability of the results) and external validity (generalizability). The attempt to achieve methodological purity can result in clinically meaningless results, while attempting to achieve full generalizability can result in invalid and unreliable results. Achieving a creative tension between the two is crucial.

Blood Pressure↗