Severe acute respiratory syndrome (SARS), a new disease with symptoms similar to those of atypical pneumonia, raised a global alert in March 2003. Because of its relatively high transmissibility and mortality upon infection, probable SARS patients were quarantined and treated with special and intensive care. Therefore, instant and accurate laboratory confirmation of SARS-associated coronavirus (SARS-CoV) infection has become a worldwide interest. For this need, we purified recombinant proteins including the nucleocapsid (N), envelope (E), membrane (M), and truncated forms of the spike protein (S1-S7) of SARS-CoV in Escherichia coli. The six proteins N, E, M, S2, S5, and S6 were used for Western blotting (WB) to detect various immunoglobulin classes in 90 serum samples from 54 probable SARS patients. The results indicated that N was recognized in most of the sera. In some cases, S6 could be recognized as early as 2 or 3 days after illness onset, while S5 was recognized at a later stage. Furthermore, the result of recombinant-protein-based WB showed a 90% agreement with that of the whole-virus-based immunofluorescence assay. Combining WB with existing RT-PCR, the laboratory confirmation for SARS-CoV infection was greatly enhanced by 24.1%, from 48.1% (RT-PCR alone) to 72.2%. Finally, our results show that IgA antibodies against SARS-CoV can be detected within 1 week after illness onset in a few SARS patients.

BackgroundThe increasing prevalence of multiple chronic conditions has accentuated the importance of coordinating and integrating health care services. Patients with better continuity of care (COC) have a lower utilization rate of emergency department (ED) services, lower hospitalization and better care outcomes. Previous COC studies have focused on the care outcome of patients with a single chronic condition or that of physician-patient relationships; few studies have investigated the care outcome of patients with multiple chronic conditions. Using multi-chronic patients as subjects, this study proposes an integrated continuity of care (ICOC) index to verify the association between COC and care outcomes for two scopes of chronic conditions, at physician and medical facility levels.MethodsThis study used a dataset of 280,840 subjects, obtained from the Longitudinal Health Insurance Database (LHID 2005), compiled by the National Health Research Institutes, of the National Health Insurance Bureau of Taiwan. Principal Component Analysis (PCA) was used to integrate the indices of density, dispersion and sequence into ICOC to measure COC outcomes - the utilization rate of ED services and hospitalization. A Generalized Estimating Equations model was used to verify the care outcomes.ResultsWe discovered that the higher the COC at medical facility level, the lower the utilization rate of ED services and hospitalization for patients; by contrast, the higher the COC at physician level, the higher the utilization rate of ED services (odds ratio > 1; Exp(β) = 2.116) and hospitalization (odds ratio > 1; Exp(β) = 1.688). When only those patients with major chronic conditions with the highest number of medical visits were considered, it was found that the higher the COC at both medical facility and physician levels, the lower the utilization rate of ED services and hospitalization.ConclusionsThe study shows that ICOC is more stable than single indices and it can be widely used to measure the care outcomes of different chronic conditions to accumulate empirical evidence. Concentrated care of multi-chronic patients by a single physician often results in unsatisfactory care outcomes. This highlights the need for referral mechanisms and integration of specialties inside or outside medical facilities, in order to optimize patient-centered care.

Physicians have to deal with a broad range of medical problems in clinical practice, thus making the timely acquisition of relevant information is a critical skill for physicians to improve care quality. The current national study investigates how physicians search for medical information and analyses how they use online medical databases. A structured questionnaire survey was conducted, with 457 valid returns collected. Internet-based resources (Web portals, online databases, and electronic journals) were more often accessed by physicians to look for medical information than personal or paper ones. Almost universally, physicians have accessed online databases. MEDLINE was the most frequently accessed database. Furthermore, physicians under 50 years old tended to access online databases more often than their elder colleagues (OR = 5.27, 95% CI = 1.96-14.14 for age <35; OR = 4.68, 95% CI = 2.07-10.60 for ages 35-50). In addition, physicians with faculty position were more often accessing online databases (OR = 3.32; 95% CI = 1.75-6.30). Other factors - including clinical experience, administrative position, gender, academic degree, and professional specialty - carried no significant differences. These data may assist in determining how to promote the use of online evidence-based medical information for clinical services.

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Introduction. Length of stay (LOS) in the intensive care unit (ICU) of spontaneous intracerebral hemorrhage (sICH) patients is one of the most important issues. The disease severity, psychosocial factors, and institutional factors will influence the length of ICU stay. This study is used in the Taiwan National Health Insurance Research Database (NHIRD) to define the threshold of a prolonged ICU stay in sICH patients. Methods. This research collected the demographic data of sICH patients in the NHIRD from 2005 to 2009. The threshold of prolonged ICU stay was calculated using change point analysis. Results. There were 1599 sICH patients included. A prolonged ICU stay was defined as being equal to or longer than 10 days. There were 436 prolonged ICU stay cases and 1163 nonprolonged cases. Conclusion. This study showed that the threshold of a prolonged ICU stay is a good indicator of hospital utilization in ICH patients. Different hospitals have their own different care strategies that can be identified with a prolonged ICU stay. This indicator can be improved using quality control methods such as complications prevention and efficiency of ICU bed management. Patients' stay in ICUs and in hospitals will be shorter if integrated care systems are established.

Severe acute respiratory syndrome (SARS), a new disease with symptoms similar to those of atypical pneumonia, raised a global alert in March 2003. Because of its relatively high transmissibility and mortality upon infection, probable SARS patients were quarantined and treated with special and intensive care. Therefore, instant and accurate laboratory confirmation of SARS-associated coronavirus (SARS-CoV) infection has become a worldwide interest. For this need, we purified recombinant proteins including the nucleocapsid (N), envelope (E), membrane (M), and truncated forms of the spike protein (S1–S7) of SARS-CoV in Escherichia coli. The six proteins N, E, M, S2, S5, and S6 were used for Western blotting (WB) to detect various immunoglobulin classes in 90 serum samples from 54 probable SARS patients. The results indicated that N was recognized in most of the sera. In some cases, S6 could be recognized as early as 2 or 3 days after illness onset, while S5 was recognized at a later stage. Furthermore, the result of recombinant-protein-based WB showed a 90% agreement with that of the whole-virus-based immunofluorescence assay. Combining WB with existing RT-PCR, the laboratory confirmation for SARS-CoV infection was greatly enhanced by 24.1%, from 48.1% (RT-PCR alone) to 72.2%. Finally, our results show that IgA antibodies against SARS-CoV can be detected within 1 week after illness onset in a few SARS patients.

The predictive powers of SAPS II, APACHE II and GCS-mr were the same. The GCS-mr is more convenient for predicting mortality in neurosurgical patients. Both GCS

Background: Issuing of correct prescriptions is a foundation of patient safety. Medication errors represent one of the most important problems in health care, with 'look-alike and sound-alike' (LASA) being the lead error. Existing solutions to prevent LASA still have their limitations. Deep learning techniques have revolutionized identification classifiers in many fields. In search of better image-based solutions for blister package identification problem, this study using a baseline deep learning drug identification (DLDI) aims to understand how identification confusion of look-alike images by human occurs through the cognitive counterpart of deep learning solutions and thereof to suggest further solutions to approach them. Methods: We collected images of 250 types of blister-packaged drug from the Out-Patient Department (OPD) of a medical center for identification. The deep learning framework of You Only Look Once (YOLO) was adopted for implementation of the proposed deep learning. The commonly-used F1 score, defined by precision and recall for large numbers of identification tests, was used as the performance criterion. This study trained and compared the proposed models based on images of either the front-side or back-side of blister-packaged drugs. Results: Our results showed that the total training time for the front-side model and back-side model was 5 h 34 min and 7 h 42 min, respectively. The F1 score of the back-side model (95.99%) was better than that of the frontside model (93.72%). Conclusions:In conclusion, this study constructed a deep learning-based model for blister-packaged drug identification, with an accuracy greater than 90%. This model outperformed identification using conventional computer vision solutions, and could assist pharmacists in identifying drugs while preventing medication errors caused by look-alike blister packages. By integration into existing prescription systems in hospitals, the results of this study indicated that using this model, drugs dispensed could be verified in order to achieve automated prescription and dispensing.