Tsair-Wei Chien

Predicting the hyperglycemic crisis death (PHD) score: a new decision rule for emergency and critical care.

BACKGROUNDnWe investigated independent mortality predictors of hyperglycemic crises and developed a prediction rule for emergency and critical care physicians to classify patients into mortality risk and disposition groups.nnnMETHODSnThis study was done in a university-affiliated medical center. Consecutive adult patients (> 18 years old) visiting the emergency department (ED) between January 2004 and December 2010 were enrolled when they met the criteria of a hyperglycemic crisis. Data were separated into derivation and validation sets-the former were used to predict the latter. December 31, 2008, was the cutoff date. Thirty-day mortality was the primary endpoint.nnnRESULTSnWe enrolled 295 patients who made 330 visits to the ED: derivation set = 235 visits (25 deaths: 10.6%), validation set = 95 visits (10 deaths: 10.5%). We found 6 independent mortality predictors: Absent tachycardia, Hypotension, Anemia, Severe coma, Cancer history, and Infection (AHA.SCI). After assigning weights to each predictor, we developed a Predicting Hyperglycemic crisis Death (PHD) score that stratifies patients into mortality-risk and disposition groups: low (0%) (95% CI, 0-0.02%): treatment in a general ward or the ED; intermediate (24.5%) (95% CI, 14.8-39.9%): the intensive care unit or a general ward; and high (59.5%) (95% CI, 42.2-74.8%): the intensive care unit. The area under the curve for the rule was 0.946 in the derivation set and 0.925 in the validation set.nnnCONCLUSIONSnThe PHD score is a simple and rapid rule for predicting 30-day mortality and classifying mortality risk and disposition in adult patients with hyperglycemic crises.

Risk of Acute Kidney Injury after Exposure to Gadolinium-Based Contrast in Patients with Renal Impairment

Objectives: Gadolinium-based contrast media (Gd-CM) are reported to induce acute kidney injury (AKI) in a high-risk population group at the usual dose for magnetic resonance imaging (MRI) and magnetic resonance angiography (MRA) examinations. We assessed gadolinium-induced nephropathy in patients with renal impairment who underwent MRI or MRA examinations, and evaluated the risk factors. Materials and methods: In this retrospective study, 238 patients with baseline renal impairment, who received MRI or MRA examinations with Gd-CM, were recruited. After all other AKI causes—liver decompensation, severe heart failure, all kinds of shock, and severe sepsis—and patients on dialysis were excluded, 158 patients were enrolled. AKI was defined as a decrease in glomerular filtration rate (GFR) >10% of baseline data within 3 days after administration of Gd-CM. Regression analysis was used to find independent risk factors for gadolinium-induced AKI (Gd-AKI). Results: Twenty-six of the 158 patients (16.5%) developed Gd-AKI. There were no significant differences in gender, age, or baseline GFR between those who did and who did not develop AKI. Comorbid coronary artery disease, liver cirrhosis, diabetes mellitus, and hypertension were not significantly associated with the development of Gd-AKI. However, sepsis was an independent risk factor for Gd-AKI after multivariate regression analysis (adjusted odds ratio: 4.417; 95% confidence interval: 1.671–11.676, p = 0.03). Conclusions: It is potential AKI after administration of Gd-CM under sepsis condition at the dose for MRI and MRA examinations in patients with renal impairment. It is important to identify high-risk patients and closely monitor renal function after administration of Gd-CM.

KIDMAP, a web based system for gathering patients' feedback on their doctors

BackgroundThe gathering of feedback on doctors from patients after consultations is an important part of patient involvement and participation. This study first assesses the 23-item Patient Feedback Questionnaire (PFQ) designed by the Picker Institute, Europe, to determine whether these items form a single latent trait. Then, an Internet module with visual representation is developed to gather patient views about their doctors; this program then distributes the individualized results by email.MethodsA total of 450 patients were randomly recruited from a 1300-bed-size medical center in Taiwan. The Rasch rating scale model was used to examine the data-fit. Differential item functioning (DIF) analysis was conducted to verify construct equivalence across the groups. An Internet module with visual representation was developed to provide doctors with the patients online feedback.ResultsTwenty-one of the 23 items met the models expectation, namely that they constitute a single construct. The test reliability was 0.94. DIF was found between ages and different kinds of disease, but not between genders and education levels. The visual approach of the KIDMAP module on the WWW seemed to be an effective approach to the assessment of patient feedback in a clinical setting.ConclusionThe revised 21-item PFQ measures a single construct. Our work supports the hypothesis that the revised PFQ online version is both valid and reliable, and that the KIDMAP module is good at its designated task. Further research is needed to confirm data congruence for patients with chronic diseases.

Using Rasch Analysis to Validate the Revised PSQI to Assess Sleep Disorders in Taiwan’s Hi-tech Workers

The Pittsburgh Sleep Quality Index (PSQI) is an effective instrument for measuring the quality of sleep in older adults. In this study, we used Rasch analysis to validate the items of the revised PSQI (SC_PSQI) that contribute to a single construct. A total of 3,742 workers agreed to participate in this study. Both the appropriateness of the scoring rubrics and the unidimensionality of the SC_PSQI scale were investigated. All nine items fit the model’s expectations rather well. These results indicate that the SC_PSQI with a 0 to 2 scoring scale can be used as a unidimensionality to assess sleep quality.

Applying the revised Chinese Job Content Questionnaire to assess psychosocial work conditions among Taiwan's hospital workers

BackgroundFor hospital accreditation and health promotion reasons, we examined whether the 22-item Job Content Questionnaire (JCQ) could be applied to evaluate job strain of individual hospital employees and to determine the number of factors extracted from JCQ. Additionally, we developed an Excel module of self-evaluation diagnostic system for consultation with experts.MethodsTo develop an Excel-based self-evaluation diagnostic system for consultation to experts to make job strain assessment easier and quicker than ever, Rasch rating scale model was used to analyze data from 1,644 hospital employees who enrolled in 2008 for a job strain survey. We determined whether the 22-item Job Content Questionnaire (JCQ) could evaluate job strain of individual employees in work sites. The respective item responding to specific groups occupational hazards causing job stress was investigated by using skewness coefficient with its 95% CI through item-by-item analyses.ResultsEach of those 22 items on the questionnaire was examined to have five factors. The prevalence rate of Chinese hospital workers with high job strain was 16.5%.ConclusionsGraphical representations of four quadrants, item-by-item bar chart plots and skewness 95% CI comparison generated in Excel can help employers and consultants of an organization focusing on a small number of key areas of concern for each worker in job strain.

Web-based computer adaptive assessment of individual perceptions of job satisfaction for hospital workplace employees

BackgroundTo develop a web-based computer adaptive testing (CAT) application for efficiently collecting data regarding workers perceptions of job satisfaction, we examined whether a 37-item Job Content Questionnaire (JCQ-37) could evaluate the job satisfaction of individual employees as a single construct.MethodsThe JCQ-37 makes data collection via CAT on the internet easy, viable and fast. A Rasch rating scale model was applied to analyze data from 300 randomly selected hospital employees who participated in job-satisfaction surveys in 2008 and 2009 via non-adaptive and computer-adaptive testing, respectively.ResultsOf the 37 items on the questionnaire, 24 items fit the model fairly well. Person-separation reliability for the 2008 surveys was 0.88. Measures from both years and item-8 job satisfaction for groups were successfully evaluated through item-by-item analyses by using t-test. Workers aged 26 - 35 felt that job satisfaction was significantly worse in 2009 than in 2008.ConclusionsA Web-CAT developed in the present paper was shown to be more efficient than traditional computer-based or pen-and-paper assessments at collecting data regarding workers perceptions of job content.

Development of a Microsoft Excel tool for one-parameter Rasch model of continuous items: an application to a safety attitude survey

BackgroundMany continuous item responses (CIRs) are encountered in healthcare settings, but no one uses item response theory’s (IRT) probabilistic modeling to present graphical presentations for interpreting CIR results. A computer module that is programmed to deal with CIRs is required.To present a computer module, validate it, and verify its usefulness in dealing with CIR data, and then to apply the model to real healthcare data in order to show how the CIR that can be applied to healthcare settings with an example regarding a safety attitude survey.MethodsUsing Microsoft Excel VBA (Visual Basic for Applications), we designed a computer module that minimizes the residuals and calculates model’s expected scores according to person responses across items. Rasch models based on a Wright map and on KIDMAP were demonstrated to interpret results of the safety attitude survey.ResultsThe author-made CIR module yielded OUTFIT mean square (MNSQ) and person measures equivalent to those yielded by professional Rasch Winsteps software. The probabilistic modeling of the CIR module provides messages that are much more valuable to users and show the CIR advantage over classic test theory.ConclusionsBecause of advances in computer technology, healthcare users who are familiar to MS Excel can easily apply the study CIR module to deal with continuous variables to benefit comparisons of data with a logistic distribution and model fit statistics.

A reference equation for objectively adjusting dwell volume to obtain more ultrafiltration in daily practice of peritoneal dialysis.

Objectives. Few studies mention how to objectively adjust peritoneal dialysis (PD) dwell volume for adult continuous ambulatory peritoneal dialysis (CAPD) patients. We proposed a reference equation composed of parameters from the peritoneal equilibrium test (PET) for adjusting daily dialysate dwell volume to obtain more ultrafiltration volume. Better fluid control could reduce more fluid overload-related complications. Design. We used body mass index, waist circumference, intraperitoneal pressure, and other parameters from peritoneal equilibrium test to compose a reference equation for fine-tuning daily dwell volume. Patients and Setting. Eighty-eight PD patients in one center with laboratory data collected during half-yearly PET evaluations were enrolled. Instilled dialysate was composed of 2.57% glucose PD fluid, either 1500 ml or 2000 ml in volume. In addition to other demographic data, intraperitoneal pressure (IPP) was also measured twice in the supine position four hours apart. We applied statistical multivariate techniques of discrimination analysis and logistic regression to verify the most feasible and optimal formula to determine infill volumes for patients. Results. We determined a novel formula for calculating daily dialysate dwell volume, Z: Z = (0.523 × waist circumference) + (0.852 × body mass index), derived from rotating axes to obtain an accurate prediction rate of 80.68% using the multivariate approach. Conclusion. The novel formula used objective, real-time parameters for determining appropriate dwell volumes for PD patients to optimize maximal ultrafiltration volumes and reduce subjective abdominal discomfort. The novel formula makes frequent adjustment of daily dwell volume by physicians or patients easy to calculate.

Using Google Maps to display the pattern of coauthor collaborations on the topic of schizophrenia: A systematic review between 1937 and 2017

Schizophrenia is a severe mental disorder affecting more than 21 million people worldwide. Scientific collaborations are required to research schizophrenia. However, there have been limited publications to date investigating scientific collaborations in schizophrenia research or reporting individual researchers achievements(IRA) for authors. This study aimed to investigate the pattern of coauthor collaborations in schizophrenia research. We conducted a bibliometric study of international scientific publications on schizophrenia. About 57,964 abstracts were identified and downloaded from MEDLINE. All were examined using social network analysis (SNA) on February 20, 2018. The clusters of author nationalities, the authors, and the medical subject headings (MESH) terms were presented on Google Maps. A total of 36,934 articles met the inclusion criteria. The mean number of authors per article increased from 4.5 in 2008 to 6.4 in 2017. The proportion of published articles decreased in North America from 46.7% in 2008, to 32.3% in 2017. In contrast, the proportion of published articles in Asia increased from 14.5% in 1998 to 23.9% in 2017. Among the countries generating schizophrenia research the most prominent is China (corr.u202f=u202f0.98), followed by India (corr.u202f=u202f0.94), and France (corr.u202f=u202f0.93). The representative of the biggest cluster is the author Michael F Green from the United States. The top three MESH terms are physiopathology, schizophrenic psychology, and complications. The scientific interest in schizophrenia remains significant. The application of bibliometric indicators of production is evident in the growth of scientific literature on the topic of schizophrenia.