Interpretive reporting of laboratory data

Survival in Sickle Cell Disease: Data from a Well-Resourced, National Health System Setting

<p>Experiences and Lessons from a Multicountry NIDIAG Study on Persistent Digestive Disorders in the Tropics</p>

An empirical correlation for predicting tubular friction pressure for CO2-energized fluids has been derived from both field and laboratory data. This correlation takes into account the effect of crosslinking behavior of the liquid phase on friction pressure. Therefore, it can be used for treatments where CO2-energized fluids are used in conjunction with delayed or rapid crosslinked fluids. The correlation was incorporated into a real time computer program used to calculate bottomhole treating pressure on-site during fracturing treatments with CO2-energized fluids. Several case histories were used to evaluate the correlation. The results presented in this paper have shown significant improvement in predicting the friction pressure for CO2-energized fluids as compared to existing correlations being used in the oil industry.

A mobile, diode-array NIR spectrometer was integrated into the spout of a self-propelled forage harvester to measure crop moisture. Spectra and moisture reference samples were collected in 2004 and 2005 for the development of laboratory and field-based moisture calibrations. Moisture prediction models for whole-plant corn silage (WPCS) developed using laboratory data had a root mean standard error of cross-validation (RMSECV) of 1.1% using five principle components (PCs), while a calibration developed using field data had an RMSECV of 3.3% using four PCs. Alfalfa validation results produced RMSECVs of 2.5% using four PCs and 3.7% using three PCs for models using laboratory and field data, respectively. Field data were predicted with calibrations developed using laboratory data with similar error levels, but more spectral information was required. A laboratory-based alfalfa model predicted field data with a root mean standard error of prediction (RMSEP) of 3.4% using three PCs as compared to the field model's RMSECV of 3.7% using three PCs. Similar trends were found with WPCS models. Predicting data independent of type of crop resulted in the utilization of more PCs but with higher RMSEPs than the cross-validation results of the predicted dataset. The sensor and associated calibrations were able to predict forage moisture adequately, although more diverse data and further calibration development are needed to improve sensor accuracy to the desired range of 2.0 percentage units.

Xylophagous insects: developments in feeding assays

Clinical and Laboratory Characteristics of Prefibrotic and Overt Primary Myelofibrosis in Azerbaijan

To compare ECG, laboratory, comorbid disease and angiography data of patients diagnosed with acute coronary syndrome according to young, middle and old age groups. Demographic data such as age, gender and time of admission were analysed. Patients included in the study were over 18 years of age and were categorised into young (18-44), middle (45-64) and elderly (≥ 65) age groups. Data were accessed from the hospital electronic data system. Patients' comorbidity status, COVID-19 status and laboratory data were analysed, and comparisons were made according to age groups. 780 patients were analysed in the study. 74% of the patients were male. The mean age was 63.60 ± 12.26 years. Most patients were in the middle age group (51.6%). According to ECG findings at admission, most cases were without ST elevation. LAD (67.9%) and RCA (58.5%) were the most frequently occluded vessels. The age at onset of acute coronary syndrome was lower in patients with COVID-19. Acute coronary syndrome is most common in males gender and at older ages, but most commonly in patients without ST elevation. The incidence of acute coronary syndrome in patients with COVID-19 is higher, especially in the young-middle-aged age group.

Environmental investigations typically entail broad data gathering efforts which include field screening surveys and laboratory analyses. Although usually collected extensively, data from field screening surveys are rarely used in the actual delineation of media contamination. On the other hand, laboratory analyses, which are used in the delineation, are minimized to avoid potentially high cost. Multivariate geostatistical techniques, such as indicator cokriging, were employed to incorporate volatile organic screening and laboratory data in order to better estimate soil contamination concentrations at a underground storage tank site. In this work, the direct and cross variographies are based on a multi-scale approach. The results indicate that soil gas measurements show good correlations with laboratory data at large scales. These correlations, however, can be masked by poor correlations at micro-scale distances. Consequently, a classical direct correlation analysis between the two measured values is very likely to fail. In contrast, the presented multi-scale co-estimation procedure provides tools for a cost-effective and reliable assessment of soil contamination based on a combined use of laboratory and field screening data.

To evaluate the impact of pharmacotherapy on efficacy and safety by providing laboratory data information linked to medicines on outpatient prescriptions from the hospital to the community pharmacy. Beginning on October 28, 2014, standardized laboratory data and drug-linking laboratory data were included with outpatient prescriptions at our hospital. We have created a database of drug-linking laboratory data for all drugs that can be prescribed in Japan. We counted the number of prescription inquiries related to laboratory data from community pharmacies, including those leading to prescription changes. Before laboratory data were listed on outpatient prescriptions, 4 prescription inquiries from community pharmacies per year were related to laboratory data. After our hospital started to list laboratory data, this number rose to 643, 576, 563, and 847 in the first, second, third, and fourth year (P < .05). Of these, 132, 143, 152, and 224 inquiries resulted in prescription changes. Listing laboratory data on outpatient prescriptions avoided 153 contraindications and 84 exacerbations of adverse drug reactions in four years by a prescription inquiry that had never been done before. The efficacy and safety of pharmacotherapy can be improved by listing relevant laboratory data on outpatient prescriptions.

e23017 Background: Electronic data capture (EDC) has the potential to improve data accuracy and efficiency. As an initial step toward improvement in the accuracy and completeness of data acquisition for clinical trials, PEP-CTN and PBTC conducted a pilot project to assess the feasibility of automated transfer of laboratory data from participating institutions’ electronic health records to the NCI Medidata Rave EDC that is housed within each consortium’s Uniform Resource Locator (URL). The pilot aimed to assess feasibility of automated laboratory data extraction and transfer and to evaluate discrepancies between laboratory data obtained retrospectively through automated extraction and data manually ascertained during the original conduct of the study. Methods: Data from patients treated on 7 completed PEP-CTN or PBTC trials at 7 sites were included. Each consortium created a Rave EDC study to receive data. Sites used the ExtractEHR R package or local methods to map and extract laboratory data for designated patients. Post-extraction data were uploaded via a file transfer protocol (FTP) periodically polled by the Rave Batch Uploader (BU) that uploaded data into Rave EDC. After successful upload, extracted data (EHR) were compared to laboratory data that had been manually reported when patients were enrolled on the trials (MANUAL) and discrepancies were identified. Discrepancy types were categorized and 2 sites reviewed discrepancies at their sites to identify reasons. Results: Preparation and support for automated extraction and upload required significant central operations and local site effort. All sites successfully extracted specified laboratory data and had at least one complete upload via BU to Rave EDC. There were more laboratory data in the EHR datasets than MANUAL datasets across most sites. These results were due to multiple EHR results on a given day or from additional days in the study window than specified in MANUAL. Sites verified that laboratory data in MANUAL and not EHR were stored in un-extractable formats (e.g. PDFs) or outside laboratories. Most discrepant results in both EHR and MANUAL were mismatched values or units. Conclusions: This pilot demonstrated the feasibility of implementing automated laboratory data extraction and transfer in the cooperative group setting. Automated data transfer requires significant central operational support as well as detailed protocols, data specifications, and case report forms and engagement of site technical teams to be successful, but also permits collection of more comprehensive data with reduced manual data entry. Clinical trial information: NCT05020951 .

Annoyance due to urban road traffic noise combined with aircraft noise was studied using both laboratory and field survey data. Laboratory data were used to propose (i) partial annoyance models considering psychoacoustic indices and noise sensitivity, and (ii) total annoyance models considering noise indices or partial annoyance models. To predict partial and total annoyance in field, a methodology was proposed to estimate the different psychoacoustic indices, involved in annoyance models, from Ldenvalues. This methodology, interesting from a practical point of view, and the proposed annoyance models enable a good prediction of the field partial and total annoyance ratings compared to models based on Lden only. These results show that there is a need to develop the methodology of psychoacoustic index estimation from noise map Lden and also partial and total annoyance models.

Chronic liver disease is a progressive disease, most of the time asymptomatic, and potentially fatal. In this chapter, an automatic procedure to stage the disease is proposed based on ultrasound (US) liver images, clinical and laboratorial data.

OP0281 Survival of Biopsy-Proven Giant Cell Arteritis in Italy during A 26-Year Period: Correlation with Histological Pattern

The operation of gas-condensate fields is comparatively new and involvesphysical principles with which the industry was not previously familiar. It hasbeen necessary to devise methods for testing gas-condensate wells and tocorrelate laboratory and field data. In this paper new methods are advanced forinterpreting well G.P.M. t tests whereby dilution by dry gas can be estimatedand information supplied on revaporization of condensates by dry gas.Inaccuracies in well test data are discussed. Changes in flow rates can causechanges in the G.P.M. of the effluent and it may take some time for a well tobecome stabilized after an important change in flow rate. Retrograde tests asusually conducted cannot be directly compared with field G.P.M. data, becausethe retrograde tests usually include solution gas in the condensates, which arereported on the cumulative basis whereas field data (G.P.M.) usually reportpentanes plus on a rate or instantaneous basis. Introduction Though long known to physicists, the phenomena of retrograde condensationbecame known to the oil and gas industry only in recent years, when deeperdrilling disclosed that the behavior of vapors under changing pressures wasdifferent in high-pressure reservoirs than under the low-pressure operationswith which the industry was familiar. These deep, high-pressure reservoirs inwhich condensation and vaporization behaved inversely to the accustomed mannerbecame known as "gasdistillate," or preferably "gas-condensate"fields. Partly to prevent precipitation and retention of liquids in thereservoir, but still more to prevent the waste of residue gas, the operationknown as "recycling," or preferably "cycling," was instituted, in which the residue gas is reinjected into the reservoir, thus maintainingpressure and driving the wet gas to the producing wells. For lack of field experience to serve as a guide, the industry had to assumethat theory and laboratory experiments could accurately forecast retrogradebehaviors in operating these gas-condensate fields, but it is obvious thatthese assumptions should be checked at the first opportunities against actualfield experience. To make such checks, it is necessary to accumulate a largequantity of reliable field data, but experience has shown that it is difficultto obtain reliable field data and that the laboratory data as usually presentedare not in directly comparable form. The problems of correlation involve thecomplex phase behavior on the one hand, and a knowledge of field data and avisualization of underground conditions on the other hand. This paper is anapproach from field experience. The purposes of this article are to discuss the sources of uncertainty in thedata and to present methods of analyzing, interpreting and correlatinglaboratory and field data. Data mostly from lower Gulf Coast fields arepresented, from which some conclusions can be derived, but better data frommore sources than those available to the writer will be required beforesatisfactory answers to many questions can be obtained. This paper is presentedto stimulate the analysis and publication of data from other fields, thereexamination of field and laboratory methods, and the taking of more completeand reliable field tests. For these purposes, the writer presents somespeculations that otherwise would not be appropriate. T.P. 2053

During Ocean Drilling Program Leg 130, sonic velocity and bulk density/porosity well logs were measured in five separate holes drilled through the sequence of pelagic carbonate oozes, chalks, and limestones that comprise the thick, continuous sedimentary cover on the Ontong Java Plateau. An internally consistent and continuous suite of shipboard laboratory velocity and sediment physical properties measurements were made from the top of each hole down through the entire logged interval. Because of the high quality of the data, extensive overlap of 500 m or more between the log and laboratory measurements at each hole, and the homogeneous nature of the sediments, we have been able to compare laboratory and in-situ log measurements in detail and to evaluate factors that alter laboratory data from their in-situ values. For measurements of bulk density and porosity, differences between laboratory and in-situ log measurements are very small and remain constant over the entire range of depths studied. We have applied a simple hydraulic rebound correction to the laboratory data that compensates for pore fluid expansion after removal of a sediment sample from in-situ conditions. The small, correctable differences between the laboratory and log data imply that mechanical rebound is significantly less than previous estimates (maximum near 5%) of rebound in pelagic carbonates. Furthermore, porosity rebound cannot be used to correct laboratory sonic velocity measurements to in-situ values. Such a rebound correction implicitly requires that laboratory and in-situ data must occupy identical fields on velocity-porosity crossplots. This condition is not met for the Ontong Java Plateau results because laboratory and in-situ logging data occupy distinct trends with little overlap between the two types of measurement. Mechanical rebound in pelagic carbonates cannot be used to correct either laboratory porosity or velocity measurements to in-situ values. The complex porosity systematics of these carbonates resulting from varying abundances of hollow foraminifer grains precluded use of an empirical correction derived from the log porosity and velocity data. Laboratory sonic velocity measurements can be corrected to in-situ values at all of the Ontong Java Plateau sites using a depth-based function derived from downhole differences between log and laboratory velocities in Hole 807A. The applicability of the depth correction implies that the effect of overburden pressure reduction on sediment elastic moduli is the most significant factor affecting laboratory velocity measurements. The depth correction to laboratory velocity measurements appears to be generally applicable to pelagic carbonate oozes and chalks of the Ontong Java Plateau, regardless of depositional depth or sediment age.