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Nicolette F de Keizer

Publications and source records attributed to Nicolette F de Keizer.

9 recordsLinked to original sources
PubMed2006

The use of a registry database in clinical trial design: assessing the influence of entry criteria on statistical power and number of eligible patients.

Randomized clinical trials (RCTs) are prospective empirical studies used to investigate the effect of a particular medical intervention. The design of a clinical trial is a delicate decision process, as each of the decisions that are taken in this process influences the eventual result of the clinical trial. Despite the efforts that are put into trial design, many trials fail to show an effect of the intervention. In some of these situations the intervention may be truly ineffective, however, more often this is caused by problems with the inclusion of patients and a resulting lack of statistical power to show the effect. To avoid this problem, in the design of a trial, the statistical power that can be achieved with the current design choices is calculated and balanced with economic considerations. In the choice of the entry criteria however, an important step in the design process, the influence of the chosen criteria on statistical power and number of eligible patients is not quantified. As these criteria influence the characteristics of the study population and the number of patients that will be eligible for the trial, and thereby the chances of finding an effect of the intervention, we believe that also in the choice of entry criteria explicit estimates of the number of eligible patients should be made. This paper presents a method to arrive at precise, objective estimates of statistical power and the number of eligible patients, using a registry database. Furthermore, we describe how this method is incorporated in the process of choosing entry criteria for a clinical trial. We illustrate the method with an example in the area of severe sepsis.

Humans↗
PubMed2006

Errors associated with applying decision support by suggesting default doses for aminoglycosides.

BACKGROUND: Medication errors, and the resultant adverse drug events (ADEs), are one of the main preventable causes of morbidity and mortality. Computerised physician order entry (CPOE) is reported to reduce the frequency of these errors. However, CPOE systems themselves may be associated with errors. The aim of this study was to investigate the effects of a CPOE system that displays an initial default dose for gentamycin and tobramycin administration on the frequency of medication errors and potential ADEs in patients with renal insufficiency. METHODS: Gentamycin and tobramycin prescriptions from the CPOE records of a Dutch tertiary adult intensive care unit were retrospectively compared with doses recommended by a locally developed guideline. The default dose for gentamycin and tobramycin in the CPOE system is 240 mg/day. A dose prescribing error was defined as an administered dose that exceeded the recommended dose by >10%. RESULTS: Three hundred and ninty two prescriptions, relating to 253 patients (of whom 184 had renal insufficiency), were analysed. There was a high frequency (58%, 227 of 392) of prescriptions that used the CPOE system's default dose of 240 mg/day. The dose was wrong in 73% (165) of these orders. Default orders for patients with renal insufficiency amounted to 52% (132 of 259). A total of 86% (113 of 132) of these resulted in potential ADEs compared with 53% (66 of 124) for the rest of orders (p < 0.0001). DISCUSSION: A markedly high frequency of prescriptions followed the default dose value and, in patients with renal insufficiency, there was a high frequency of doses exceeding the guideline recommendation (+10%), amounting to potential ADEs. CONCLUSION: Initial CPOE dose values for prescribing gentamycin and tobramycin, which are based on a fixed default value, form a source of potential ADEs for patients with renal insufficiency.

Adult↗
PubMed2006

Ten years of teledermatology.

Using telemedicine health professionals can communicate with each other and with their patients over a distance. Teledermatology, dermatology application of telemedicine, is one of the most often applied telemedicine applications worldwide. Various studies have been performed to evaluate the effectiveness and efficiency of and satisfaction with teledermatology. Up to now no or limited valid scientific evidence has been found that teledermatology is beneficial for any group of users. This study aimed to perceive insight into the evolution of evaluation studies of teledermatology over the past ten years in terms of the telemedicine evaluation framework by Holle and Zahlmann consisting of four continuous phases. We added the phase "post implementation studies" that evaluate teledermatology as a fully integrated service in regular care. Retrieved literature from Medline was reviewed by two reviewers independently in order to include studies and classify them into the five phases. Ninety-nine studies out of 372 found unique references were included and classified into the phases. Most represented phase was phase II with 72 (72%) studies. The number of phase II studies is continuously growing since the introduction of evaluation in teledermatology. There were eight reported RCTs found (two in phase III, six in phase IV). The number of phase III and IV studies is too low to draw conclusions about the trends in their publication and stress the need for more such studies. Phase I and post implementations studies are probably under-represented as they might often not be published separately in scientific journal papers.

Dermatology↗
PubMed2006

A Markov model to describe daily changes in organ failure for patients at the ICU.

As the support and stabilization of organ function is a major goal of treatment in the Intensive Care Unit (ICU), changes in the function of organ systems are an important indicator of the progression of the disease and recovery. This paper presents how to construct a model that describes changes in organ failure of ICU patients on a day-to-day basis. The model is based on the daily Sequential Organ Failure Assessment (SOFA) scores for six organ systems and predicts, for each of these organ systems, whether failure or recovery is due on the next day, using six logistic regression equations. The joint set of equations, extended with equations for predicting ICU discharge and death, constitutes a firstorder multivariate Markov model. We applied the procedure on a dataset and found that most types of organ failure are highly persistent.

Humans↗
PubMed2005

Performance of prognostic models in critically ill cancer patients - a review.

INTRODUCTION: Prognostic models, such as the Acute Physiology and Chronic Health Evaluation (APACHE) II or III, the Simplified Acute Physiology Score (SAPS) II, and the Mortality Probability Models (MPM) II were developed to quantify the severity of illness and the likelihood of hospital survival for a general intensive care unit (ICU) population. Little is known about the performance of these models in specific populations, such as patients with cancer. Recently, specific prognostic models have been developed to predict mortality for cancer patients who are admitted to the ICU. The present analysis reviews the performance of general prognostic models and specific models for cancer patients to predict in-hospital mortality after ICU admission. METHODS: Studies were identified by searching the Medline databases from 1994 to 2004. We included studies evaluating the performance of mortality prediction models in critically ill cancer patients. RESULTS: Ten studies were identified that evaluated prognostic models in cancer patients. Discrimination between survivors and non-survivors was fair to good, but calibration was insufficient in most studies. General prognostic models uniformly underestimate the likelihood of hospital mortality in oncological patients. Two versions of a specific oncological scoring systems (Intensive Care Mortality Model (ICMM)) were evaluated in five studies and showed better discrimination and calibration than the general prognostic models. CONCLUSION: General prognostic models generally underestimate the risk of mortality in critically ill cancer patients. Both general prognostic models and specific oncology models may reliably identify subgroups of patients with a very high risk of mortality.

APACHE↗
PubMed2005

Influence of entry criteria on mortality risk and number of eligible patients in recent studies on severe sepsis.

OBJECTIVE: To understand the impact of patient selection criteria used in recent sepsis trials on baseline mortality risk and number of eligible patients. DESIGN: Observational cohort study, with retrospective analysis of prospectively collected data. METHODS AND MAIN RESULTS: Using a MEDLINE search, we selected recent randomized controlled trials in patients with severe sepsis and studied the mortality rate in the control groups of these trials. Nine articles fulfilled the search criteria and were used in our analyses. The 28-day mortality rate in the control groups of these trials varied between 28.0% and 89.0%. Differences in this mortality rate might be due to the use of different entry criteria but also to other factors that vary between the trials. To eliminate the influence of these confounding factors when studying the effect of the use of entry criteria on baseline mortality risk and number of eligible patients, we projected the entry criteria of these nine trials on a large independent database of >70,000 Dutch intensive care patients admitted between 1996 and 2003. This yielded nine groups of patients who would have been eligible for the respective trials. The percentage of patients who would have been eligible for these trials varied between 1.5% and 6.0%. Six of these groups had a similar intensive care mortality rate (between 25.0% and 28.9%). The projection of the entry criteria of the three other trials onto the database resulted in groups of patients with considerably higher intensive care mortality. For in-hospital mortality rate in these groups, similar results were found. CONCLUSIONS: The majority of the trials we studied used entry criteria that select patients with a similar mortality risk. This suggests that differences in baseline mortality risk reported in recent sepsis trials are to be attributed to other factors that vary between trials rather than to differences in entry criteria. However, entry criteria do have an important influence on the number of eligible patients for sepsis trials without influencing baseline mortality rate.

Adolescent↗
PubMed2004

Overcoming barriers to evaluation of terminological systems.

Evaluation of terminological systems has been demonstrated to be a complicated task. This is due to the broad range of terminological systems, their application, and the clinical contexts in which they can be applied. We propose an evaluation framework that explicitly distinguishes an application-independent description of terminological systems, methods to determine application-dependent requirements, and methods to assess the applicability. In order to support a systematic application-independent description of terminological systems, we present a categorization of characteristics, including explicit questions. The answers to these questions can be mapped to the requirements for a certain application of a terminological system. This framework aims at reducing the efforts for determining which terminological system is applicable for a certain clinical setting.

Evaluation Studies as Topic↗
PubMed2003

Training in data definitions improves quality of intensive care data.

BACKGROUND: Our aim was to assess the contribution of training in data definitions and data extraction guidelines to improving quality of data for use in intensive care scoring systems such as the Acute Physiology and Chronic Health Evaluation (APACHE) II and Simplified Acute Physiology Score (SAPS) II in the Dutch National Intensive Care Evaluation (NICE) registry. METHODS: Before and after attending a central training programme, a training group of 31 intensive care physicians from Dutch hospitals who were newly participating in the NICE registry extracted data from three sample patient records. The 5-hour training programme provided participants with guidelines for data extraction and strict data definitions. A control group of 10 intensive care physicians, who were trained according the to train-the-trainer principle at least 6 months before the study, extracted the data twice, without specific training in between. RESULTS: In the training group the mean percentage of accurate data increased significantly after training for all NICE variables (+7%, 95% confidence interval 5%-10%), for APACHE II variables (+6%, 95% confidence interval 4%-9%) and for SAPS II variables (+4%, 95% confidence interval 1%-6%). The percentage data error due to nonadherence to data definitions decreased by 3.5% after training. Deviations from 'gold standard' SAPS II scores and predicted mortalities decreased significantly after training. Data accuracy in the control group did not change between the two data extractions and was equal to post-training data accuracy in the training group. CONCLUSION: Training in data definitions and data extraction guidelines is an effective way to improve quality of intensive care scoring data.

APACHE↗