METHODS: A cross-sectional, hospital-based study: 25 AD subjects and 25 controls were recruited. Candidates who fulfil the criteria with normal ocular examinations were made to proceed with scanning laser polarimetry, pattern electroretinogram (PERG), and pattern visual evoked potential (PVEP) examinations of the right eye. RNFL thickness, PERG, and PVEP readings were evaluated.
RESULTS: In AD, the mean of average RNFL thickness was 45.28 μm, SD = 3.61, P < 0.001 (P < 0.05), while the superior RNFL thickness was 54.44 μm, SD = 2.85, P < 0.001 (P < 0.05) and inferior RNFL thickness was 47.11 μm, SD = 4.52, P < 0.001 (P < 0.05). For PERG, the mean P50 latency was 63.88 ms, SD = 7.94, P < 0.001 (P < 0.05) and the mean amplitudes of P50 waves were 1.79 μV, SD = 0.64, P < 0.001 (P < 0.05) and N95 waves were 2.43 μV, SD = 0.90, P < 0.001 (P < 0.05). For PVEP, the mean latency of P100 was 119.00 ms, SD = 9.07, P < 0.001 (P < 0.05), while the mean latency of N135 was 145.20 ms, SD = 8.53, P < 0.001 (P < 0.05). The mean amplitude of P100 waves was 3.71 μV, SD = 1.60, P < 0.001 (P < 0.05), whereas the mean amplitude of N135 waves was 3.67 μV, SD = 2.02, P < 0.001 (P < 0.05). RNFL thickness strongly correlates with PERG readings, with P50 latency R = 0.582, R2 = 0.339, P=0.002 (P < 0.05), amplitude of P50 wave at R = 0.749, R2 = 0.561, P ≤ 0.001 (P < 0.05), and amplitude of N95 wave at R = 0.500, R2 = 0.250, P=0.011 (P < 0.05). No significant difference and correlation were observed on PVEP readings.
CONCLUSION: The mean of the average, superior and inferior RNFL thickness were significantly lower in the AD group compared with control. There is also significant difference of PERG and PVEP parameters between AD and controls. Regression analysis showed average RNFL thickness having significantly linear relationship with the PERG parameters.
METHODS: Six master dies were duplicated from the prepared maxillary first premolar tooth using nonprecious metal alloy (Wiron 99). Thirty copings (Procera AllCeram) of 0.6-mm thickness were manufactured. Three types of luting media were used: zinc phosphate cement (Elite), glass ionomer cement (Fuji I), and dual-cured composite resin cement (Panavia F). Ten copings were cemented with each type. Two master dies were used for each group, and each of them was used to lute five copings. All groups were cemented according to manufacturer's instructions and received a static load of 5 kg during cementation. After 24 hours of distilled water storage at 37 degrees C, the copings were vertically compressed using a universal testing machine at a crosshead speed of 1 mm/min.
RESULTS: ANOVA revealed significant differences in the load at fracture among the three groups (p < 0.001). The fracture strength results showed that the mean fracture strength of zinc phosphate cement (Elite), glass ionomer cement (Fuji I), and resin luting cement (Panavia F) were 1091.9 N, 784.8 N, and 1953.5 N, respectively.
CONCLUSION: Different luting agents have an influence on the fracture resistance of Procera AllCeram copings.
METHODS: A steering group was formed to review the existing guideline and propose amendments to the 17-item checklist. A Delphi consensus exercise was utilised to determine agreement across a list of proposed modifications to the STROCSS 2017 guideline. An expert panel of 46 surgeons were invited to assess the proposed updates via Google Forms.
RESULTS: The response rate was 91% (n = 42/46). High agreement was reached across all the items and the guideline was finalised in the first round. The checklist maintained 17-items, with modifications primarily considered to improve content and readability.
CONCLUSIONS: The STROCSS 2019 guideline is hereby presented as a considered update to improve reporting of cohort, cross-sectional and case-control studies in surgery.
Patients and Methods: STAR proposes 1-3 hours treatment based on individual insulin sensitivity variation and history of blood glucose, insulin, and nutrition. A total of 136 patients recorded data from STAR pilot trial in Malaysia (2017-quarter of 2019*) were used in the study to identify the gap between chosen administered insulin and nutrition intervention as recommended by STAR, and the real intervention performed.
Results: The results show the percentage of insulin compliance increased from 2017 to first quarter of 2019* and fluctuated in feed administrations. Overall compliance amounted to 98.8% and 97.7% for administered insulin and feed, respectively. There was higher average of 17 blood glucose measurements per day than in other centres that have been using STAR, but longer intervals were selected when recommended. Control safety and performance were similar for all periods showing no obvious correlation to compliance.
Conclusion: The results indicate that STAR, an automated model-based protocol is positively accepted among the Malaysian ICU clinicians to automate glycemic control and the usage can be extended to other hospitals already. Performance could be improved with several propositions.
METHODS: Questionnaire-based data was gathered from internal medicine doctors (209), general practitioners (206), chest physicians (152) and pediatricians (58) from 232 locations from across the five countries.
RESULTS: Of the 816 physicians, 374 physicians encountered at least 5 asthma patients daily. Approximately, 38% physicians always used spirometry for diagnosis and only 12% physicians always recommended Peak flow meter (PFM) for home-monitoring. Salmeterol/fluticasone (71%) followed by formoterol/budesonide (38%) were the most preferred ICS/long-acting beta2-agonists (LABA); Salbutamol (78%) was the most preferred reliever medication. 60% physicians said >40% of their patients were apprehensive to use inhalers. 72% physicians preferred a pressurized metered-dose inhaler (pMDI) to a dry powder inhaler (DPI) with only a third of them using a spacer with the pMDI. 71% physicians believed that using similar device for controller and reliever can be beneficial to patients. Skipping medicines in absence of symptoms (64%), incorrect inhaler technique (48%) and high cost of medication (49%) were considered as major reasons for non-adherence by most physicians. Incorrect inhaler technique (66%) and nonadherence (59%) were considered the most common causes of poor asthma control.
CONCLUSIONS: There are opportunities to improve the use of diagnostic and monitoring tools for asthma. Non-adherence, incorrect inhaler technique and cost remain a challenge to achieve good asthma control. Asthma education, including correct demonstration of inhaler, can potentially help to improve inhaler adherence.