Online Data Management System Research Articles

To Study Outcomes in Young CML Treated with TKI. a Registry Data from Hematological Cancer Consortium (HCC) of India

Background: Chronic Myeloid Leukemia (CML) is a hematological malignancy characterized by the abnormal proliferation of white blood cells. While CML is primarily a disease of middle and old age, a significant proportion of cases are diagnosed in adolescents and young adults. The incidence of CML in India is relatively low (0.53 to 0.71 / 100,000), but the country's large population means that even a small increase in incidence can translate to a significant disease burden. The prognosis of CML has improved dramatically with the advent of tyrosine kinase inhibitors (TKIs) such as imatinib, dasatinib, and nilotinib, which have transformed CML from a fatal disease to a chronic, manageable condition. However, the optimal management of CML in adolescents and young adults (AYA) is still a matter of debate, and there is limited data on the outcome of this disease in this age group in India. Hematology Cancer Consortium (HCC) is a group of premier hematology and oncology institutes from India created for collecting and collating data of various hematologic malignancies in a central online data management system. Design and methods: Retrospective data from 01 Jan 2020 to 01 June 2022, of all CML patients treated with TKI at 11 member institutions of HCC were analysed. The cohort was divided into AYA (15 to 29 years) and others ( 30 years or more). The objective of this study was to determine the disease outcome of adolescents and young adults (AYA) with CML in India as measured by event free survival (EFS), overall survival (OS) and transformation free survival (TFS) . Events were defined as death from any cause, progression to accelerated phase (AP) or blast crisis (BC) and change to second generation TKI from imatinib while on therapy. We also compared the outcome of AYA with others. Results: Total of 1070 patients diagnosed with CML were included in the study. The patients of age group 15-29 years were 273/1070 (25.5%). Most were in chronic phase (249/273, 95.04%). The low-risk CML cases by Sokal score were 61 (26.75%) cases in 15-29 years age group in comparison to 69 (11.11%) cases in the older group and the difference was statistically significant (p<0.001).Low-risk cases by ELTS and EUTO score were seen in 32.51% and 61.30% cases in 15-29 years age group and it was comparable to other group (24.9 % and 62.1%). The type of transcript were P210 in 202 (97.58%) cases in AYA group. Spleen size, hemoglobin, WBC, Platelet, blasts (%), quantitative BCR ABL (%) were comparable in both the groups. Imatinib was used as first TKI in 193 (71.75%) cases. Significantly more number of patients in AYA group were treated upfront with second generation TKI (28.2%) in comparison to others (23.3%) (p= 0.02). The median doses missed by patients in 15-29 years group during first 03 months were 5, while in other group it was 13 and it was statistically significant (p=0.002). Median duration of therapy was 13 (0-28) months in AYA and 12 (0-38) months in other group. Progression to blast crisis was seen in 3/273 (0.01%) patients in the AYA group. While OS and transformation free survival were comparable in both groups, event free survival (EFS) was significantly better in AYA group (Fig-1A-B). Conclusion: While the AYA group had a significantly less low risk cases by Sokal score, more numbers were treated upfront with second generation TKI. EFS was significantly better in AYA group. Major shortcoming of this registry data is short follow up duration and very less number of evaluable patients for assessing molecular and cytogenetic response.

Induction Related Mortality Score in Acute Myeloid Leukemia: Prospective Validation Study (pRISM) of the Hematology Cancer Consortium (HCC)

Treatment of Acute Myeloid Leukemia (AML) should be initiated at the earliest to improve outcomes. The standard induction regimen (3+7) is associated with significant risk of induction mortality, especially in resource limited settings. Hence there is a need to develop risk prediction model for our patient cohorts. Treatment related mortality (TRM) scoring systems developed and used in developed country, mostly for the elderly, may not be directly applicable to population of young adults in developing countries, many of whom have poor general condition and infections at baseline. We developed a multivariate model of induction mortality score in 2019, from a retrospective AML cohort of the Indian acute leukemia research database [INwARD] established by the Hematology Cancer Consortium (HCC). In the present study we have validated the approach and recalibrated the induction mortality score on a multicenter prospective cohort. Prospective data for adult AML, for a period of 20 months, starting July 2020 to February 2022, was received from 17 member institutions in a central online data management system. Potential variables that would predict mortality were selected based on clinical and statistical significance. Eleven variables relating to baseline patient and disease characteristics (age, ECOG performance status, duration of symptoms in days, albumin, creatinine, bilirubin, white cell count, platelet, hemoglobin, peripheral blood blast percentage, and presence of infection requiring intravenous antibiotic within one week prior of starting induction), were considered for the predictive model using machine learning (ML) algorithms: Logistic regression (LR), Support Vector Machine (SVM) and eXtreme Gradient Boosting (XGB). Of the various ML algorithms, the best model was chosen based on area under curve (AUC) from the training dataset and validity statistics from the test dataset. We also used the same approach to predict intensive care unit (ICU) admission. R software was used to analyze the data. Of the 779 treated cases during the study period, 438 received intensive induction, '3+7' being the most common regimen in 80%. The median age of this cohort was 37 years (IQR 28, 46), male to female ratio 1.2. European Leukemia Net (ELN) risk group was good in 31.3 % (n= 137), intermediate in 44% (n=192), high in 13.7% (n=60), and unknown in 11% (n=48). Complete remission was attained in 56.3%. Overall induction mortality was 13.0%, ranging from 7.1% to 40% across different centers. Infection was the most common cause of death in 52%. For predicting induction mortality using 11 covariates, SVM provided the best threshold as 0.126, with an AUC of 94.71%, sensitivity (92.50%), and specificity (96.11%). A comparison of the ML algorithms is shown in Fig 1 and statistics for the SVM model in Table 1. ICU admission was observed in 22.8%; a cut-off threshold of 0.231, with an AUC of 93.3% in the SVM model predicted ICU admission with sensitivity of 93.15% and specificity of 89.7%. Induction mortality prediction score developed in a retrospective cohort was effectively applied to contemporary prospective data from major centers across the country, with diverse resources and patient profiles. Thus, we have validated the machine learning approach of predicting induction mortality with variables relevant to regional clinical settings including baseline infection. The SVM model predicted the risk of both induction mortality as well as morbidity with high accuracy. An online calculator is being developed to help clinicians use this score in regular practice for guiding treatment intensity as per an individual patient's risk and in directing appropriate resource utilization. Further, the approach of risk-adapted induction intensity, especially for young adult AML, based on the score adjusted to center-specific prevalence of mortality rates, is under consideration for a prospective clinical trial. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Developing an online system to support algebra progress monitoring: Teacher use and feedback

A brief overview of the development of an online system to support algebra progress monitoring across several years of an iterative process of development, feedback, and revision is provided. Online instructional modules addressed progress monitoring concepts and procedures; administration and scoring of three types of algebra measures, including teacher accuracy with scoring; and navigation and use of the online data management system, including data entry, graphing, and skills analyses. In the final year of this federally funded research project, a test of the functionality of the completed system as well as an evaluation of teachers’ knowledge, accuracy, and satisfaction with the online professional development was evaluated. Specifically, 29 general and special education secondary school teachers completed 11 fully developed online instructional modules independently and administered weekly two of three types of algebra measures across 10 weeks with one of their classes of students. Data analysis included teacher accuracy in the scoring of the measures; change in their knowledge of student progress monitoring and data-based decision making; and teacher satisfaction with the online system, including instructional content, feasibility, and usability for data-based decision making. Directions for future research and implications for classroom use of this online system are discussed.

LAI-NOS: An automatic network observation system for leaf area index based on hemispherical photography

The leaf area index (LAI) is an important indicator reflecting the growth status of vegetation and is widely used in agriculture, ecology, climate change, and other fields. The shortcomings of the currently available methods for manually measuring LAI include labor-intensive, low sampling frequency, and asynchronous data collection. Focusing on these issues, a LAI sensor based on hemispherical photogrammetry and an automatic network observation system (LAI-NOS) for LAI were developed, which consists of four parts: LAI sensor, sensor node, sink node, and online data management system. The LAI sensor measures LAI values based on hemispherical photography. The sensor node is responsible for controlling the sensor and obtaining the data measured by the LAI sensor. The sink node is responsible for local networking and communication with the remote server. Data storage, data management, data display, and sampling frequency are managed by the online data management system. Comparative studies with LAI-2200C and satellite products were also conducted in this study. The comparative study with LAI-2200C showed that the LAI measurements of different vegetation types from both sources were highly significantly correlated whether based on Pearson regression or Passing & Bablok regression. A preliminary study comparing LAI-NOS measurements with Sentinel-2 inversion LAI and MODIS LAI products (MOD15A2H) showed (1) all LAI-NOS nodes measurements agreed very well with Sentinel-2 inversion LAI in the experimental period (average R2=0.94, RMSE=0.41); (2) the possible overestimate of Sentinel-2 inversion LAI was found in the middle stage of wheat (jointing-anthesis); (3) MOD15A2H and LAI-NOS measurements showed similar crop growth trends in long-term observations.

Protocol for surgical and non-surgical treatment for metacarpal shaft fractures in adults: an observational feasibility study

IntroductionMetacarpal shaft fractures (MSF) are common traumatic hand injuries that usually affect young people of working age. They place a significant burden on healthcare resources and society; however, there is...

Assessing the effect of tagging and the vulnerability to predation in tigerfish (Hydrocynus vittatus, Castelnau 1861) in a water-stressed system using telemetry methods

Increase in anthropogenic pressures on freshwater ecosystems, globally and locally in South Africa, has made it difficult to meet environmental flow requirements and maintain these systems. The Letaba-Olifants catchment is one such example, where the upstream water demands place pressure on the river downstream as it flows through the Kruger National Park. We used the activity rates of Hydrocynus vittatus as a line of evidence to assess (1) the effects of telemeter tagging on their activity rates in three potential post-tagging recovery periods and (2) their vulnerability to predation and the causality related to the environmental stressors placed on the river catchment in the Olifants River Gorge, Kruger National Park, South Africa. We determined H. vittatus activity rates as locomotive movement using radio telemetry methods linked remotely to an online data management system. We telemeter tagged nine individuals from 08 May to 28 June 2018. However, only seven fish were successfully tracked for the duration of our study, and two individuals moved out of range of the remote network shortly after release and could not be located. The tagged H. vittatus individuals were found to have reduced activity at least within the first 7 days after tagging compared with the time after that. The results showed that three individuals were preyed on by predators after the tagging procedure recovery period. This coincided with abnormal low flow conditions, where the Letaba River ran dry. African fish eagles Haliaeestus vocifer were the only confirmed predator, whilst predation by other species was also evident.Conservation implications: Monitoring of H. vittatus using telemetry is a viable tool to use when assessing environmental stressors in remote locations. The abnormally low water levels in the Olifants and Letaba Rivers (cessation of flow in the Letaba River) during our study may have compromised the predator avoidance strategies of tagged H. vittatus and may further be affecting the viability of the H. vittatus populations in Kruger National Park. The synergistic effects of natural and anthropogenic stressors impact negatively H. vittatus populations and potentially other aquatic biotas.

Quality in Use of an Android-based Mobile Application for Calculation of Bone Mineral Density with the Standard ISO/IEC 25022

One of the most critical bone diseases is osteoporosis, which can be evaluated through measurements of bone mineral density. Though there is a lot of commercialized portable about health in general, few are oriented towards bone health and with a lack of user-friendly interface and data management system. This paper presents a mobile application development for the calculation of the Bone Mineral density, which integrates with Google technology. The Mobile-D methodology for the development of mobile applications, due to the sequentially in the processes or stages is used. Bone mineral density (BMD) was calculated using anthropometric regression equations, and an Android-based Mobile Application with Google technology was developed. By using Firebase Authentication and Firebase Storage provided by Google technology, it allows admin to have full control over database management. In short, this mobile application allows the calculation of the BMD of the students and data storage and data uploading to cloud storage for post-processing, online data management system with user authentication. In addition, the Internacional Organization for Standardization / International Electrotechnical Commission (ISO/IEC) 25022 standard was used to evaluate the quality in use of the mobile app, resulting in 93% of quality in use, this app being able to be used by health professionals for better decision-making.

Induction Related Mortality in Acute Myeloid Leukemia: Multivariate Model of Predictive Score from the Indian Acute Leukemia Research Database (INwARD) of the Hematology Cancer Consortium (HCC)

Background: Remission induction is the most intensive phase of acute myeloid leukemia (AML) treatment, associated with significant morbidity and mortality. Collaborative research and advances in supportive care have steadily improved outcomes in developed countries with induction mortality less than 5%. Challenges for treatment in resource limited settings are varied including delayed presentation, higher disease burden, baseline infections and poor general condition precluding standard intensive therapy, higher rates of resistant infections, and several social and financial constraints. Consequently, a significant proportion of patients do not receive definitive therapy and for those who are treated there is a considerably high risk of induction mortality. In an attempt to identify the subset of patients with highest risk of death during induction, we have developed a multivariate model of induction mortality score using baseline features relevant to our clinical setting by utilizing Indian acute leukemia research database [INwARD] established in 2018 by Hematology Cancer Consortium (HCC). Method: Retrospective data from January 2018 to May 2019 for adult AML was collected from 11 member institutions in a central online data management system. Selection of potential variables that would predict mortality was based on clinical and statistical significance. Thus, 10 variables defining baseline patient and disease characteristics (age, ECOG performance status, duration of symptoms in days, albumin, creatinine, bilirubin, white cell count, platelet, peripheral blood blast percentage, and presence of infection requiring intravenous antibiotic within one week prior of starting induction), were considered for the predictive model using machine learning algorithms: Logistic regression (LR) and Support Vector Machine (SVM). SVM was chosen as the best algorithm based on the AUCs. In order to get robust threshold, sensitivity, specificity and predictive values bootstrapping was done 10,000 times. The final statistics were based on the mean (SD) of bootstrapped sample. R software was used to bootstrap and analyze the data. Result: Of the 611 adult AML cases available during study period, 392 treated with the intensive '3+7' or its abbreviated regimen were considered for analysis. Median age of this cohort was 36 years (range 18 - 67), male to female ratio 1.34. European Leukemia Net (ELN) risk group distribution is shown in Fig 1a. Complete remission was attained in 52.8%. Induction mortality was 16.9 % ranging from 6.1% to 43% across different centers. Most common cause of death was infection (66.7%). Multi-drug resistant blood stream infection was documented in 25.4% cases. For the SVM model for predicting induction mortality using 10 covariates, the AUC based on the bootstrap validation was 91.3% with the best threshold probability being 0.262 (Fig 1b). Thus, a cut off score of 0.262 in the SVM model predicted induction death with sensitivity of 93.6% and specificity of 87.7%. Performance of each variable in the SVM model is shown in Fig 1c and comparison of the LR and SVM model in Fig 1d. Conclusion: Score predicting induction death with high accuracy will be a valuable tool in guiding clinicians against the use of intensive induction therapy, in tailoring of treatment as per individual patients' risk and proper resource allocation. Despite the limitations of retrospective data, wide disparity in resources, patient profile and treatment costs across centers accounting for variability in mortality rates, this study represents one major attempt to find answer to a locally relevant clinical problem of high induction mortality in a cohort of young adult AML, utilizing contemporary pooled data through multi-center collaboration. Optimal cut off point for the score needs to be validated in independent patient cohorts and have to be re-calibrated periodically. Further, an online calculator is being designed on the HCC online system to work as ready reckoner for clinicians. Figure 1 a) ELN risk group distribution b) descriptive statistics of bootstrapped SVM Model c) performance of each covariate in SVM model d) ROC Curve: Comparison of LR and SVM method Figure 1 Disclosures No relevant conflicts of interest to declare.

DIAGNOSTIC ACCURACY OF A NOVEL CUFFLESS BLOOD PRESSURE MONITOR FOR ATRIAL FIBRILLATION SCREENING IN THE ELDERLY

Objective: Screening for atrial fibrillation (AF) during routine automated blood pressure (BP) monitoring in asymptomatic elderly subjects is an attractive tool. This study validated a novel cuffless BP monitor (Freescan, Maisense) for AF detection during BP measurement in elderly subjects versus reference continuous electrocardiography (ECG). Design and method: Subjects recruited from a hypertension outpatient clinic were instructed to self-measure their BP in the clinic setting using the Freescan cuffless BP monitor (up to 15 attempts until 5 valid BP readings were obtained), with simultaneous ECG monitoring using a Holter device. Data from the device were transferred via Bluetooth to an online data management system, where for each BP measurement an ‘AF’ indication was displayed in case of detected AF and ‘Arrhythmia’ in other arrhythmias. Results: 1,223 Freescan BP measurements with simultaneous automated AF detection were obtained from 132 subjects. Readings reported by the device as ‘unstable’ (uncertainty of displayed rhythm result: 31%) and those reporting error (19%) were discarded. Thus, data of 108 subjects who had 5 valid Freescan BP measurements were analyzed (age 73.9 ± 7.3 years, males 65%, treated for hypertension 85%, AF in ECG 19%). In reading-to-reading analysis (N = 540 valid Freescan readings) the sensitivity, specificity and accuracy of the Freescan device in detecting AF were 70%, 99% and 94%, respectively. In subjects’ analysis (N = 108) and by considering AF diagnosis if > = 3 of 5 Freescan readings indicated AF, the sensitivity, specificity and accuracy of Freescan in detecting AF were 76%, 100%, and 95%, respectively. When the indication ‘Arrhythmia’ was regarded as AF indication, in reading-to-reading analysis the sensitivity, specificity, and accuracy were 95%, 91%, and 92%, respectively, while when using the >=3 of 5 readings for AF diagnosis rule the sensitivity, specificity and accuracy were 100%, 92% and 94%, respectively. Conclusions: The Freescan device appears to have satisfactory diagnostic accuracy for AF screening during routine self-measurement of BP in the elderly, particularly when >=3 of 5 valid readings are considered for diagnosis.

Right Iliac Fossa Pain Treatment (RIFT) Study: protocol for an international, multicentre, prospective observational study

IntroductionPatients presenting with right iliac fossa (RIF) pain are a common challenge for acute general surgical services. Given the range of potential pathologies, RIF pain creates diagnostic uncertainty and there...

Provision of medical abortion by midlevel healthcare providers in Kyrgyzstan: testing an intervention to expand safe abortion services to underserved rural and periurban areas

ObjectiveTo demonstrate the feasibility and safety of training midlevel healthcare providers (midwives and family nurses) to provide medical abortion and postabortion contraception in underserved areas in Kyrgyzstan. Study designThis was an implementation study at four referral facilities and 28 Felsher Obstetric Points in two districts to train their midwives and family nurses to deliver safe and effective abortion care with co-packaged mifepristone–misoprostol and provide contraceptives postabortion. The outcome of abortion — complete abortion, incomplete abortion or o-going pregnancy — was the primary end point measured. An international consultant trained 18 midwives and 14 family nurses (with midwifery diplomas) to provide medical abortion care. Supervising gynecologists based in the referral centers and study investigators based in Bishkek provided monthly monitoring of services and collection of patient management forms. A voluntary self-administered questionnaire at the follow-up visit documented women's acceptability of medical abortion services. All study data were cross-checked and entered into an online data management system for descriptive analysis. ResultsBetween August 2014 and September 2015, midwives provided medical abortion to 554 women with a complete abortion rate of 97.8%, of whom 62% chose to use misoprostol at home. No women were lost to follow-up. Nearly all women (99.5%) chose a contraceptive method postabortion; 61% of women receiving services completed the acceptability form, of whom more than 99% indicated a high level of satisfaction with the service and would recommend it to a friend. ConclusionThis study demonstrates that trained Kyrgyz midwives and nurses can provide medical abortion safely and effectively. This locally generated evidence can be used by the Kyrgyz Ministry of Health to reduce unintended pregnancy and expand safe abortion care to women in underserved periurban and rural settings. ImplicationsSuccess in scaling up midwife/nurse provision of medical abortion in Kyrgyzstan will require registration of mifepristone–misoprostol, regulations permanently allowing midwife/nurse provision, strengthened procurement and distribution systems to prevent stockouts of supplies, preservice training of midwives/nurses and their involvement in district level supervision, monitoring and reporting, and support from supervisors.

Evaluation of Kaiser Permamente Colorado’s Thriving Schools Initiative

PURPOSE: To evaluate the Kaiser Permanente Thriving Schools Initiative, a program designed to increase physical activity (PA) in Colorado public schools. METHODS: This cross-site evaluation examined 27 public school districts funded to incorporate PA into the school day, operationalized as classroom PA (CPA), before and after school PA (BAPA), and PA occurring in physical education classes or recess (PERPA). All data were collected during the 2014-15 academic year using an online data management system. CPA were collected by asking randomly selected teachers in each school to report classroom PA during a one-week period, 2-3 times each semester. Programming for BAPA was reported by each district’s health coordinator and included day·w-1 offered, min·d-1 offered, and number of students participating. PERPA schedules were collected for each school and entered into an aggregate database containing all PA. Mean minutes of PA · d-1 was calculated using the sum of CPA, BAPA, and PERPA divided by the number of school days. Descriptive and inferential statistics were calculated. RESULTS: Most districts (76%) provided ≥ 30 min · d-1 (42.9±27.6 min · d-1) of PA, though only 36% provided 60 min·d-1. There were no significant differences in the likelihood of achieving mandated PA minutes based on school characteristics. Most PA minutes were offered in PERPA (66.8%). In fact, schools that reported more minutes in these two types of PA were significantly more likely to achieve mandated PA minutes. Schools with greater percentages of free and reduced lunch eligible students reported significantly fewer min·d-1 spent on PA in classrooms, PE, recess, and in total. Finally, coefficients for PE, recess, and total minutes indicate schools with greater percentages of minority students tend to report a greater number min · d-1 in said activities. CONCLUSION: These findings support increased efforts for PA promotion in public schools, though additional research is needed to identify best practices for implementing school-based PA promotion.

Validation of XMALab software for marker-based XROMM.

Marker-based XROMM requires software tools for: (1) correcting fluoroscope distortion; (2) calibrating X-ray cameras; (3) tracking radio-opaque markers; and (4) calculating rigid body motion. In this paper we describe and validate XMALab, a new open-source software package for marker-based XROMM (C++ source and compiled versions on Bitbucket). Most marker-based XROMM studies to date have used XrayProject in MATLAB. XrayProject can produce results with excellent accuracy and precision, but it is somewhat cumbersome to use and requires a MATLAB license. We have designed XMALab to accelerate the XROMM process and to make it more accessible to new users. Features include the four XROMM steps (listed above) in one cohesive user interface, real-time plot windows for detecting errors, and integration with an online data management system, XMAPortal. Accuracy and precision of XMALab when tracking markers in a machined object are ±0.010 and ±0.043 mm, respectively. Mean precision for nine users tracking markers in a tutorial dataset of minipig feeding was ±0.062 mm in XMALab and ±0.14 mm in XrayProject. Reproducibility of 3D point locations across nine users was 10-fold greater in XMALab than in XrayProject, and six degree-of-freedom bone motions calculated with a joint coordinate system were 3- to 6-fold more reproducible in XMALab. XMALab is also suitable for tracking white or black markers in standard light videos with optional checkerboard calibration. We expect XMALab to increase both the quality and quantity of animal motion data available for comparative biomechanics research.

The distribution of clinical phenotypes of preterm birth syndrome: implications for prevention.

Preterm birth has been difficult to study and prevent because of its complex syndromic nature. To identify phenotypes of preterm delivery syndrome in the Newborn Cross-Sectional Study of the INTERGROWTH-21st Project. A population-based, multiethnic, cross-sectional study conducted at 8 geographically demarcated sites in Brazil, China, India, Italy, Kenya, Oman, the United Kingdom, and the United States. A total of 60,058 births over a 12-month fixed period between April 27, 2009, and March 2, 2014. Of these, 53,871 had an ultrasonography estimate of gestational age, among which 5828 were preterm births (10.8%). Pregnancies were prospectively studied using a standardized data collection and online data management system. Newborns had anthropometric and clinical examinations using standardized methods and identical equipment and were followed up until hospital discharge. The main study outcomes were clusters of preterm phenotypes and for each cluster, we analyzed signs of presentation at hospital admission, admission rates for neonatal intensive care for 7 days or more, and neonatal mortality rates. Twelve preterm birth clusters were identified using our conceptual framework. Eleven consisted of combinations of conditions known to be associated with preterm birth, 10 of which were dominated by a single condition. However, the most common single cluster (30.0% of the total preterm cases; n = 1747) was not associated with any severe maternal, fetal, or placental condition that was clinically detectable based on the information available; within this cluster, many cases were caregiver initiated. Only 22% (n = 1284) of all the preterm births occurred spontaneously without any of these severe conditions. Maternal presentation on hospital admission, newborn anthropometry, and risk for death before hospital discharge or admission for 7 or more days to a neonatal intensive care unit, none of which were used to construct the clusters, also differed according to the identified phenotypes. The prevalence of preterm birth ranged from 8.2% in Muscat, Oman, and Oxford, England, to 16.6% in Seattle, Washington. We identified 12 preterm birth phenotypes associated with different patterns of neonatal outcomes. In 22% of all preterm births, parturition started spontaneously and was not associated with any of the phenotypic conditions considered. We believe these results contribute to an improved understanding of this complex syndrome and provide an empirical basis to focus research on a more homogenous set of phenotypes.

Rapid survey protocol that provides dynamic information on reef condition to managers of the Great Barrier Reef.

Managing to support coral reef resilience as the climate changes requires strategic and responsive actions that reduce anthropogenic stress. Managers can only target and tailor these actions if they regularly receive information on system condition and impact severity. In large coral reef areas like the Great Barrier Reef Marine Park (GBRMP), acquiring condition and impact data with good spatial and temporal coverage requires using a large network of observers. Here, we describe the result of ~10years of evolving and refining participatory monitoring programs used in the GBR that have rangers, tourism operators and members of the public as observers. Participants complete Reef Health and Impact Surveys (RHIS) using a protocol that meets coral reef managers' needs for up-to-date information on the following: benthic community composition, reef condition and impacts including coral diseases, damage, predation and the presence of rubbish. Training programs ensure that the information gathered is sufficiently precise to inform management decisions. Participants regularly report because the demands of the survey methodology have been matched to their time availability. Undertaking the RHIS protocol we describe involves three ~20min surveys at each site. Participants enter data into an online data management system that can create reports for managers and participants within minutes of data being submitted. Since 2009, 211 participants have completed a total of more than 10,415 surveys at more than 625 different reefs. The two-way exchange of information between managers and participants increases the capacity to manage reefs adaptively, meets education and outreach objectives and can increase stewardship. The general approach used and the survey methodology are both sufficiently adaptable to be used in all reef regions.

A portable blood analyzer that uses on-line data management to deliver higher-quality patient information

We constructed an on-line data management system and linked it to the communication protocol of a portable blood analyzer (i-STAT) in each operating room of our institution. We developed a new program that integrates circulatory dynamics data from a monitor with laboratory data from the i-STAT. Our new program permits the results to be viewed through an intranet using a novel prototype communication device for the i-STAT 300F. We verified that this system can improve the quality of patient care both bedside and in the monitoring room and compared the costs of blood testing using a conventional desktop blood-gas analyzer and using the i-STAT. We found that the novel integration of circulatory dynamics with laboratory data enhanced the quality of intraoperative patient monitoring and reduced the cost and work load of doctors working in the operating room.

Methodological considerations in implementing the WHO Global Survey for Monitoring Maternal and Perinatal Health

To set up a global system for monitoring maternal and perinatal health in 54 countries worldwide. The WHO Global Survey for Monitoring Maternal and Perinatal Health was implemented through a network of health institutions, selected using a stratified multistage cluster sampling design. Focused information on maternal and perinatal health was abstracted from hospital records and entered in a specially developed online data management system. Data were collected over a two- to three-month period in each institution. The project was coordinated by WHO and supported by WHO regional offices and country coordinators in Africa and the Americas. The initial survey was implemented between September 2004 and March 2005 in the African and American regions. A total of 125 institutions in seven African countries and 119 institutions in eight Latin American countries participated. This project has created a technologically simple and scientifically sound system for large-scale data management, which can facilitate programme monitoring in countries.

Control and quality assurance in anaesthesia with a PDMS.

This paper presents preliminary results of our experience, over the past three and half years, with an on-line data management system in the OR that charts and documents all features relevant to anaesthesia. We achieved two goals with this system: 1) There has been a considerable improvement in the quantity and quality of documentation, and 2) we have been able to contain costs within our department, despite an increase in workload, by the continuous audit of the quality process in our specialty. Finally we learned that the quality assurance features that we documented and later analyzed, revealed rather conflicting and disappointing results. We believe that this is at least partly due to the reluctance of our staff to accept the concept of quality assurance and quality control in our field.

A model system for psychotherapy research data management

An on-line data management system was developed to provide optimal access to research data. The specific application involved collecting data on four outcome measures from patients receiving brief psychotherapy to ameliorate a stress response syndrome. The on-line data management system also was designed to be transported to other research settings; a variety of other applications of this system are suggested. The need for such a system, the elements that it comprises, its operation, and its availability also are covered. The quality and timeliness of research endeavors often depend on how well the more mundane tasks are handled. Keeping track of the data is one such chore. While a few boxes of card data are readily managed, keeping track of the same respondents for up to 2 years, when each respondent is completing a multiinstrument assessment battery on several occasions throughout this period, requires consider­ able skill and effort.