Method of Detecting System Function by Measuring Frequency Response

Real-time battery impedance spectrum is acquired using a one-time record. Fast Summation Transformation (FST) is a parallel method of acquiring a real-time battery impedance spectrum using a one-time record that enables battery diagnostics. An excitation current to a battery is a sum of equal amplitude sine waves of frequencies that are octave harmonics spread over a range of interest. A sample frequency is also octave and harmonically related to all frequencies in the sum. The time profile of this signal has a duration that is a few periods of the lowest frequency. The voltage response of the battery, average deleted, is the impedance of the battery in the time domain. Since the excitation frequencies are known and octave and harmonically related, a simple algorithm, FST, processes the time record by rectifying relative to the sine and cosine of each frequency. Another algorithm yields real and imaginary components for each frequency.

Early loading of nonsubmerged titanium implants with a chemically modified sand-blasted and acid-etched surface: 6-month results of a prospective case series study in the posterior mandible focusing on peri-implant crestal bone changes and implant stability quotient (ISQ) values

PURPOSE: The aim of this prospective case series study was to evaluate the short-term success rates of titanium screw-type implants with a chemically modified sand-blasted and acid-etched (mod SLA) surface after 3 weeks of healing. MATERIAL AND METHODS: A total of 56 implants were inserted in the posterior mandible of 40 partially edentulous patients exhibiting bone densities of class I to III. After a healing period of 3 weeks, all implants were functionally loaded with a screw-retained crown or fixed dental prosthesis. The patients were recalled at weeks 4, 7, 12, and 26 for monitoring and assessment of clinical and radiological parameters, including implant stability quotient (ISQ) measurements. RESULTS: None of the implants failed to integrate. However, two implants were considered "spinners" at day 21 and left unloaded for an extended period. Therefore, 96.4% of the inserted implants were loaded according to the protocol tested. All 56 implants including the "spinners" showed favorable clinical and radiographic findings at the 6-month follow-up examination. The ISQ values increased steadily throughout the follow-up period. At the time of implant placement, the range of ISQ values exhibited a mean of 74.33, and by week 26, a mean value of 83.82 was recorded. Based on strict criteria, all 56 implants were considered successfully integrated, resulting in a 6-month survival and success rate of 100.0%. CONCLUSION: This prospective study using an early-loading protocol after 3 weeks of healing demonstrated that titanium implants with the modified SLA surface can achieve and maintain successful tissue integration over a period of at least 6 months. The ISQ method seems feasible to monitor implant stability during the initial wound-healing period.

Gingival fluid cytokine expression and subgingival bacterial counts during pregnancy and postpartum: a case series

OBJECTIVES The aim of this study was to assess gingival fluid (GCF) cytokine messenger RNA (mRNA) levels, subgingival bacteria, and clinical periodontal conditions during a normal pregnancy to postpartum. MATERIALS AND METHODS Subgingival bacterial samples were analyzed with the checkerboard DNA-DNA hybridization method. GCF samples were assessed with real-time PCR including five proinflammatory cytokines and secretory leukocyte protease inhibitor. RESULTS Nineteen pregnant women with a mean age of 32 years (S.D. ± 4 years, range 26-42) participated in the study. Full-mouth bleeding scores (BOP) decreased from an average of 41.2% (S.D. ± 18.6%) at the 12th week of pregnancy to 26.6% (S.D. ± 14.4%) at the 4-6 weeks postpartum (p < 0.001). Between week 12 and 4-6 weeks postpartum, the mean probing pocket depth changed from 2.4 mm (S.D. ± 0.4) to 2.3 mm (S.D. ± 0.3) (p = 0.34). Higher counts of Eubacterium saburreum, Parvimonas micra, Selenomonas noxia, and Staphylococcus aureus were found at week 12 of pregnancy than at the 4-6 weeks postpartum examinations (p < 0.001). During and after pregnancy, statistically significant correlations between BOP scores and bacterial counts were observed. BOP scores and GCF levels of selected cytokines were not related to each other and no differences in GCF levels of the cytokines were observed between samples from the 12th week of pregnancy to 4-6 weeks postpartum. Decreasing postpartum counts of Porphyromonas endodontalis and Pseudomonas aeruginosa were associated with decreasing levels of Il-8 and Il-1β. CONCLUSIONS BOP decreased after pregnancy without any active periodontal therapy. Associations between bacterial counts and cytokine levels varied greatly in pregnant women with gingivitis and a normal pregnancy outcome. Postpartum associations between GCF cytokines and bacterial counts were more consistent. CLINICAL RELEVANCE Combined assessments of gingival fluid cytokines and subgingival bacteria may provide important information on host response.

An In Vitro Method to Investigate the Microbicidal Potential of Human Macrophages for Use in Psychosomatic Research

OBJECTIVE: Psychological states relate to changes in circulating immune cells, but associations with immune cells in peripheral tissues such as macrophages have hardly been investigated. Here, we aimed to implement and validate a method for measuring the microbicidal potential of ex vivo isolated human monocyte-derived macrophages (HMDMs) as an indicator of macrophage activation. METHODS: The method was implemented and validated for two blood sampling procedures (short-term cannula insertion versus long-term catheter insertion) in 79 participants (34 women, 45 men) aged between 18 and 75 years. The method principle is based on the reduction of 2-(4-iodophenyl)-3-(4-nitrophenyl)-5-(2,4-dis-ulfophenyl)-2H-tetrazolium, monosodium salt (WST-1) by superoxide anions, the first in a series of pathogen-killing reactive oxygen species produced by phorbol myristate acetate-activated HMDM. Cytochrome c reduction and current generation were measured as reference methods for validation purposes. We further evaluated whether depressive symptom severity (Beck Depression Inventory) and chronic stress (Chronic Stress Screening Scale) were associated with macrophage microbicidal potential. RESULTS: The assay induced superoxide anion responses by HMDM in all participants. Assay results depended on blood sampling procedure (cannula versus catheter insertion). Interassay variability as a measure for assay reliability was 10.92% or less. WST-1 reduction scores correlated strongly with results obtained by reference methods (cytochrome c: r = 0.57, p = .026; current generation: r values ≥ 0.47, p values <.033) and with psychological factors (depressive symptom severity: r = 0.35 [cannula insertion] versus r = -0.54 [catheter insertion]; chronic stress: r = 0.36 [cannula insertion]; p values ≤ .047). CONCLUSIONS: Our findings suggest that the implemented in vitro method investigates microbicidal potential of HMDM in a manner that is valid and sensitive to psychological measures.

Precipitation over the past four centuries in the Dieshan Mountains as inferred from tree rings: An introduction to an HHT-based method

To improve our understanding of the Asian monsoon system, we developed a hydroclimate reconstruction in a marginal monsoon shoulder region for the period prior to the industrial era. Here, we present the first moisture sensitive tree-ring chronology, spanning 501 years for the Dieshan Mountain area, a boundary region of the Asian summer monsoon in the northeastern Tibetan Plateau. This reconstruction was derived from 101 cores of 68 old-growth Chinese pine (Pinus tabulaeformis) trees. We introduce a Hilbert–Huang Transform (HHT) based standardization method to develop the tree-ring chronology, which has the advantages of excluding non-climatic disturbances in individual tree-ring series. Based on the reliable portion of the chronology, we reconstructed the annual (prior July to current June) precipitation history since 1637 for the Dieshan Mountain area and were able to explain 41.3% of the variance. The extremely dry years in this reconstruction were also found in historical documents and are also associated with El Niño episodes. Dry periods were reconstructed for 1718–1725, 1766–1770 and 1920–1933, whereas 1782–1788 and 1979–1985 were wet periods. The spatial signatures of these events were supported by data from other marginal regions of the Asian summer monsoon. Over the past four centuries, out-of-phase relationships between hydroclimate variations in the Dieshan Mountain area and far western Mongolia were observed during the 1718–1725 and 1766–1770 dry periods and the 1979–1985 wet period.

Development of a rapid bioassessment method and index of biotic integrity for estuaries located along the northwest Gulf of Mexico

Recently it has been proposed that the evaluation of effects of pollutants on aquatic organisms can provide an early warning system of potential environmental and human health risks (NRC 1991). Unfortunately there are few methods available to aquatic biologists to conduct assessments of the effects of pollutants on aquatic animal community health. The primary goal of this research was to develop and evaluate the feasibility of such a method. Specifically, the primary objective of this study was to develop a prototype rapid bioassessment technique similar to the Index of Biotic Integrity (IBI) for the upper Texas and Northwestern Gulf of Mexico coastal tributaries. The IBI consists of a series of "metrics" which describes specific attributes of the aquatic community. Each of these metrics are given a score which is then subtotaled to derive a total assessment of the "health" of the aquatic community. This IBI procedure may provide an additional assessment tool for professionals in water quality management.^ The experimental design consisted primarily of compiling previously collected data from monitoring conducted by the Texas Natural Resource Conservation Commission (TNRCC) at five bayous classified according to potential for anthropogenic impact and salinity regime. Standardized hydrological, chemical, and biological monitoring had been conducted in each of these watersheds. The identification and evaluation of candidate metrics for inclusion in the estuarine IBI was conducted through the use of correlation analysis, cluster analysis, stepwise and normal discriminant analysis, and evaluation of cumulative distribution frequencies. Scores of each included metric were determined based on exceedances of specific percentiles. Individual scores were summed and a total IBI score and rank for the community computed.^ Results of these analyses yielded the proposed metrics and rankings listed in this report. Based on the results of this study, incorporation of an estuarine IBI method as a water quality assessment tool is warranted. Adopted metrics were correlated to seasonal trends and less so to salinity gradients observed during the study (0-25 ppt). Further refinement of this method is needed using a larger more inclusive data set which includes additional habitat types, salinity ranges, and temporal variation. ^

A Modification of the Response Method of Tidal Analysis

An easily implemented extension of the standard response method of tidal analysis is outlined. The modification improves the extraction of both the steady and the tidal components from problematic time series by calculating tidal response weights uncontaminated by missing or anomalous data. Examples of time series containing data gaps and anomalous events are analyzed to demonstrate the applicability and advantage of the proposed method.

A new method to facilitate valid and consistent grading cardiac events in childhood cancer survivors using medical records

BACKGROUND Cardiac events (CEs) are among the most serious late effects following childhood cancer treatment. To establish accurate risk estimates for the occurrence of CEs it is essential that they are graded in a valid and consistent manner, especially for international studies. We therefore developed a data-extraction form and a set of flowcharts to grade CEs and tested the validity and consistency of this approach in a series of patients. METHODS The Common Terminology Criteria for Adverse Events version 3.0 and 4.0 were used to define the CEs. Forty patients were randomly selected from a cohort of 72 subjects with known CEs that had been graded by a physician for an earlier study. To establish whether the new method was valid for appropriate grading, a non-physician graded the CEs by using the new method. To evaluate consistency of the grading, the same charts were graded again by two other non-physicians, one with receiving brief introduction and one with receiving extensive training on the new method. We calculated weighted Kappa statistics to quantify inter-observer agreement. RESULTS The inter-observer agreement was 0.92 (95% CI 0.80-1.00) for validity, and 0.88 (0.79-0.98) and 0.99 (0.96-1.00) for consistency with the outcome assessors who had the brief introduction and the extensive training, respectively. CONCLUSIONS The newly developed standardized method to grade CEs using data from medical records has shown excellent validity and consistency. The study showed that the method can be correctly applied by researchers without a medical background, provided that they receive adequate training.

Time-Series Panel Analysis (TSPA): Multivariate Modeling of Temporal Associations in Psychotherapy Process.

Objective: Processes occurring in the course of psychotherapy are characterized by the simple fact that they unfold in time and that the multiple factors engaged in change processes vary highly between individuals (idiographic phenomena). Previous research, however, has neglected the temporal perspective by its traditional focus on static phenomena, which were mainly assessed at the group level (nomothetic phenomena). To support a temporal approach, the authors introduce time-series panel analysis (TSPA), a statistical methodology explicitly focusing on the quantification of temporal, session-to-session aspects of change in psychotherapy. TSPA-models are initially built at the level of individuals and are subsequently aggregated at the group level, thus allowing the exploration of prototypical models. Method: TSPA is based on vector auto-regression (VAR), an extension of univariate auto-regression models to multivariate time-series data. The application of TSPA is demonstrated in a sample of 87 outpatient psychotherapy patients who were monitored by postsession questionnaires. Prototypical mechanisms of change were derived from the aggregation of individual multivariate models of psychotherapy process. In a 2nd step, the associations between mechanisms of change (TSPA) and pre- to postsymptom change were explored. Results: TSPA allowed a prototypical process pattern to be identified, where patient's alliance and self-efficacy were linked by a temporal feedback-loop. Furthermore, therapist's stability over time in both mastery and clarification interventions was positively associated with better outcomes. Conclusions: TSPA is a statistical tool that sheds new light on temporal mechanisms of change. Through this approach, clinicians may gain insight into prototypical patterns of change in psychotherapy.

Repeated electrical stimulations as a tool to evoke temporal summation of nociceptive inputs in healthy, non-medicated experimental sheep.

The nociceptive withdrawal reflex (NWR) model is used in animal pain research to quantify nociception. The aim of this study was to evaluate the NWR evoked by repeated stimulations in healthy, non-medicated standing sheep. Repeated electrical stimulations were applied at 5Hz for 2s to the digital nerves of the right thoracic and the pelvic limbs of 25 standing sheep. The stimulation intensities applied were fractions (0.5, 0.6, 0.7, 0.8, 0.9 and 1) of the individual previously determined nociceptive threshold (It) after single stimulation. Surface-electromyographic activity (EMG) was recorded from the deltoid, the femoral biceps or the peroneus tertius muscles. The repeated stimulation threshold (RS It) was reached if at least one stimulus in the train was followed by a reflex with a minimal root-mean-square-amplitude (RMSA) of 20μV. The behavioural reaction following each series of stimulations was scored on a scale from 0 (no reaction) to 5 (vigorous whole-body reaction). For the deltoid muscle, RS It was 2.3mA (1.6-3mA) with a reaction score of 2 (1-2) and at a fraction of 0.6 (0.5-0.8)×It. For the biceps femoris muscle, RS It was 2.9mA (2.6-4mA) with a reaction score of 1 (1-2) at a fraction of and 0.55 (0.4-0.7)×It while for the peroneus tertius muscle RS It was 3mA (2.8-3.5mA) with a reaction score of 1 (1-2) and at a fraction of 0.8 (0.8-0.95)×It. Both, RMSA and reaction scores increased significantly with increasing stimulation intensities in all muscles (p<0.001). The repeated application of electrical stimuli led to temporal summation of nociceptive inputs and therefore a reduction of the stimulus intensity evoking a withdrawal reaction in healthy, standing sheep. Data achieved in this study can now serve as reference for further clinical or experimental applications of the model in this species.

Lake ice phenology from AVHRR data for European lakes: An automated two-step extraction method

Several lake ice phenology studies from satellite data have been undertaken. However, the availability of long-term lake freeze-thaw-cycles, required to understand this proxy for climate variability and change, is scarce for European lakes. Long time series from space observations are limited to few satellite sensors. Data of the Advanced Very High Resolution Radiometer (AVHRR) are used in account of their unique potential as they offer each day global coverage from the early 1980s expectedly until 2022. An automatic two-step extraction was developed, which makes use of near-infrared reflectance values and thermal infrared derived lake surface water temperatures to extract lake ice phenology dates. In contrast to other studies utilizing thermal infrared, the thresholds are derived from the data itself, making it unnecessary to define arbitrary or lake specific thresholds. Two lakes in the Baltic region and a steppe lake on the Austrian–Hungarian border were selected. The later one was used to test the applicability of the approach to another climatic region for the time period 1990 to 2012. A comparison of the extracted event dates with in situ data provided good agreements of about 10 d mean absolute error. The two-step extraction was found to be applicable for European lakes in different climate regions and could fill existing data gaps in future applications. The extension of the time series to the full AVHRR record length (early 1980 until today) with adequate length for trend estimations would be of interest to assess climate variability and change. Furthermore, the two-step extraction itself is not sensor-specific and could be applied to other sensors with equivalent near- and thermal infrared spectral bands.

Certolizumab treatment during late pregnancy in patients with rheumatic diseases: Low drug levels in cord blood but possible risk for maternal infections. A case series of 13 patients

OBJECTIVE Due to reduction of immune-suppressive drugs, patients with rheumatic diseases can experience an increase in disease activity during pregnancy. In such cases, TNF-inhibitors may be prescribed. However, monoclonal antibodies with the Fc moiety are actively transported across the placenta, resulting in therapeutic drug levels in the newborn. As certolizumab (CZP) lacks the Fc moiety, it may bear a lower risk for the child. METHOD We report a case series of thirteen patients (5 with rheumatoid arthritis and 8 with spondyloarthritis) treated with CZP during late pregnancy to control disease activity. RESULT CZP measured in cord blood of eleven infants ranged between undetectable levels and 1μg/mL whereas the median CZP level of maternal plasma was 32.97μg/mL. Three women developed an infection during the third trimester, of whom one had a severe infection and one had an infection that resulted in a pre-term delivery. During the postpartum period, 6 patients remained on CZP while breastfeeding. CZP levels in the breast milk of two breastfeeding patients were undetectable. CONCLUSION The lack of the active transplacental transfer of CZP gives the possibility to treat inflammatory arthritis during late gestation without potential harm to the newborn. However, in pregnant women treated with TNF-inhibitors and prednisone, attention should be given to the increased susceptibility to infections, which might cause prematurity. CZP treatment can be continued while breastfeeding.

NONLINEAR TIME SERIES/SYSTEM ANALYSIS (STATE-SPACE, DYNAMICS, INTERVENTION, RESILIENCE, KALMAN)

A discussion of nonlinear dynamics, demonstrated by the familiar automobile, is followed by the development of a systematic method of analysis of a possibly nonlinear time series using difference equations in the general state-space format. This format allows recursive state-dependent parameter estimation after each observation thereby revealing the dynamics inherent in the system in combination with random external perturbations.^ The one-step ahead prediction errors at each time period, transformed to have constant variance, and the estimated parametric sequences provide the information to (1) formally test whether time series observations y(,t) are some linear function of random errors (ELEM)(,s), for some t and s, or whether the series would more appropriately be described by a nonlinear model such as bilinear, exponential, threshold, etc., (2) formally test whether a statistically significant change has occurred in structure/level either historically or as it occurs, (3) forecast nonlinear system with a new and innovative (but very old numerical) technique utilizing rational functions to extrapolate individual parameters as smooth functions of time which are then combined to obtain the forecast of y and (4) suggest a measure of resilience, i.e. how much perturbation a structure/level can tolerate, whether internal or external to the system, and remain statistically unchanged. Although similar to one-step control, this provides a less rigid way to think about changes affecting social systems.^ Applications consisting of the analysis of some familiar and some simulated series demonstrate the procedure. Empirical results suggest that this state-space or modified augmented Kalman filter may provide interesting ways to identify particular kinds of nonlinearities as they occur in structural change via the state trajectory.^ A computational flow-chart detailing computations and software input and output is provided in the body of the text. IBM Advanced BASIC program listings to accomplish most of the analysis are provided in the appendix. ^

Differential Activity of the KRAS Oncogene by Method of Activation: Implications for Signaling and Therapeutic Intervention

Despite having been identified over thirty years ago and definitively established as having a critical role in driving tumor growth and predicting for resistance to therapy, the KRAS oncogene remains a target in cancer for which there is no effective treatment. KRas is activated b y mutations at a few sites, primarily amino acid substitutions at codon 12 which promote a constitutively active state. I have found that different amino acid substitutions at codon 12 can activate different KRas downstream signaling pathways, determine clonogenic growth potential and determine patient response to molecularly targeted therapies. Computer modeling of the KRas structure shows that different amino acids substituted at the codon 12 position influences how KRas interacts with its effecters. In the absence of a direct inhibitor of mutant KRas several agents have recently entered clinical trials alone and in combination directly targeting two of the common downstream effecter pathways of KRas, namely the Mapk pathway and the Akt pathway. These inhibitors were evaluated for efficacy against different KRAS activating mutations. An isogenic panel of colorectal cells with wild type KRas replaced with KRas G12C, G12D, or G12V at the endogenous loci differed in sensitivity to Mek and Akt inhibition. In contrast, screening was performed in a broad panel of lung cell lines alone and no correlation was seen between types of activating KRAS mutation due to concurrent oncogenic lesions. To find a new method to inhibit KRAS driven tumors, siRNA screens were performed in isogenic lines with and without active KRas. The knockdown of CNKSR1 (CNK1) showed selective growth inhibition in cells with an oncogenic KRAS. The deletion of CNK1 reduces expression of mitotic cell cycle proteins and arrests cells with active KRas in the G1 phase of the cell cycle similar to the deletion of an activated KRas regardless of activating substitution. CNK1 has a PH domain responsible for localizing it to membrane lipids making KRas potentially amenable to inhibition with small molecules. The work has identified a series of small molecules capable of binding to this PH domain and inhibiting CNK1 facilitated KRas signaling.

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.