Search

Objective: To assess the frequency of stress hyperglycemia and mortality in patients with hyperglycemia admitted in medical Intensive Care Unit. Study Design: Cross-sectional study. Place and Duration of Study: Medical Intensive Care Unit, Combined Military Hospital Quetta, from Nov 2018 to Jun 2019. Methodology: A total of 150 adult patients of age between 18-80 years, of both genders, with Intensive Care Unit stay >24 hours, who were treated in medical Intensive Care Unit during study period, were included in the study. Those patients with duration of stay

Objective: To find an association between Hyperuricemia and Hypertension in patients presenting in outpatients department for regular check-up. Study design and Setting: Case Control Study design conducted at Pak Emirates Military Hospital Rawalpindi (PEMH), Medical Outpatient department (OPD) from 4th Feb, 2017 to 4th Aug, 2017. Methodology: A total of 200 patients, with 100 cases and 100 controls fulfilling the selection criteria were included in the study, which were selected from Medical OPD of PEMH. An informed written consent was taken. The Demographic such as age, gender were obtained. Veriable upon selection into study group, the blood samples were taken and two groups of patients were made on the basis of normal or raised uric acid levels. The Serum Uric Acid (SUA) was measured in the patients. Then blood pressure was measured by using sphygmomanometer by researchers themselves. If BP level was >140/90mmHg on 2 separate occasions, or patient is already a known case of hypertension, then hypertension was labeled. Results: The mean age (years) in the study was 54.79 + 8.96. There were 136 (68%) male and 64 (32%) female patients. The frequency and percentage of hypertension in cases and control groups was (84%) and (41%) patients respectively which was statistically significant with a p-value of 0.000. The Odds ratio was found to be 7.55. Conclusion: It was concluded that there was an association found between Hyperuricemia and Hypertension

IntroductionThe opioid epidemic is a modern public health emergency. Common interventions to alleviate the opioid epidemic aim to discourage excessive prescription of opioids. However, these methods often take place over large municipal areas (state-level) and may fail to address the diversity that exists within each opioid case (individual-level). An intervention to combat the opioid epidemic that takes place at the individual-level would be preferable.MethodsThis research leverages computational tools and methods to characterize the opioid epidemic at the individual-level using the electronic health record data from a large, academic medical center. To better understand the characteristics of patients with opioid use disorder (OUD) we leveraged a self-controlled analysis to compare the healthcare encounters before and after an individual’s first overdose event recorded within the data. We further contrast these patients with matched, non-OUD controls to demonstrate the unique qualities of the OUD cohort.ResultsOur research confirms that the rate of opioid overdoses in our hospital significantly increased between 2006 and 2015 (P ConclusionsInformatics-based methodologies, like those presented here, may play a role in better understanding those individuals who suffer from opioid dependency and overdose, and may lead to future research and interventions that could successfully prevent morbidity and mortality associated with this epidemic.

The study is presenting the partial shading effects on Photovoltaic arrays. In recent study we are focusing on the photovoltaic array affecting our Solar out of all other atmospheric conditions. Different factors such as atmospheric conditions, configuration of PV cells, shades of nearby objects affects the parameters of Photovoltaic arrays. While harvesting maximum energy from photovoltaic panel it is greatly affected by the partial shading due to different manmade and natural structures. Many of the available models are studied to attain the objectives of maximum power point but two diode model is the most efficient in order to succeed in harvesting concentrated energy through photovoltaic panel. Software to compile the research study will be MATLAB which is very useful for learners and it is a hardest to achieve the MPPT in such conditions. Different studies performed for getting maximum power point but results are unsatisfactory. Many of the available models are studied to attain the goal of MPPT but double diode model is the most efficient because its make possible to get maximum power through PV panel.

PURPOSE: Lung protective ventilation (LPV), defined as a tidal volume (Vt) ≤8cc/kg of predicted body weight, reduces ventilator-induced lung injury but is applied inconsistently. MATERIALS AND METHODS: We conducted (1) a prospective, quasi-experimental, cohort study of adults mechanically ventilated admitted to intensive care units (ICU) in the year before, year after, and second year after implementation of an electronic medical record based LPV order, and (2) a cross-sectional qualitative study of ICU providers regarding their perceptions of the order. We applied the Reach, Efficacy, Adoption, Implementation, and Maintenance (RE-AIM) framework to evaluate the implementation. RESULTS: There were 1405, 1424, and 1342 in the control, adoption, and maintenance cohorts, representing 95% of mechanically ventilated adult ICU patients. The overall prevalence of LPV increased from 65% to 73% (p

BACKGROUND: Multimodal analgesia (MMA) may reduce opioid use after surgery for Chiari malformation type I. An MMA protocol was implemented after both posterior fossa decompression without dural opening (PFD) and posterior fossa decompression with duraplasty (PFDD). METHODS: Scheduled nonsteroidal antiinflammatory drugs (ketorolac or ibuprofen) and diazepam were alternated with acetaminophen, and as-needed oxycodone or intravenous morphine. The primary outcome was total opioid requirement over postoperative days 0 to 2. RESULTS: From 2012 to 2017, 49 PFD and 29 PFDD procedures were performed, and 46 of 78 patients used the protocol. Patients with PFD required less opioids than patients with PFDD. Among patients with PFDD, patients with MMA protocol usage had a lower mean opioid requirement than patients with no MMA protocol usage (0.53 ± 0.49 mgEq/kg versus 1.4 ± 1.0 mgEq/kg, P = .0142). In multivariable analysis, MMA protocol usage status independently predicted a mean decrease in opioid requirement of 0.146 mg equivalents/kg (P = .0497) after adjustment for procedure and surgeon. Statistically significant differences were not demonstrated in antiemetic requirements, discharge opioid prescriptions, total direct cost, and length of stay. CONCLUSIONS: A protocol of scheduled nonsteroidal antiinflammatory drugs alternating with scheduled acetaminophen and diazepam was associated with opioid use reductions.

Climate change can significantly affect water quality, in addition contributing non-stationarity and deep uncertainty that complicates water quality management. But most of the total maximum daily load (TMDL) implementation plans crafted to meet water quality standards in the USA are developed assuming stationary climate and at best a small number of land use futures, although neither assumption seems reliably justified. To address this challenge, this study employs robust decision making (RDM) methods, commonly used to help develop water supply plans, to stress test the proposed Enhanced Watershed Management Plan (EWMP), a TMDL implementation plan, for the Tujunga Wash, the largest subwatershed of the Los Angeles River, over a wide range of climate and land use futures. We find that climate change could significantly reduce the ability of the Tujunga EWMP to meet water quality goals; however, meeting the city’s goals for increasing permeable land cover offsets the risk of non-compliance in the face of climate change uncertainties. This study also introduces innovations in RDM analyses, including: treatment of the deeply uncertain incidence of extreme precipitation events, an explicit link between RDM scenario discovery methods and the specification of signposts for adaptive policy pathways, and the use of (imprecise) probabilistic climate projections to inform the choice among robust adaptive policy pathways. The paper also contributes to a larger debate over how to address climate and other uncertainties in regulatory processes involving water quality.

OBJECTIVES: Multimodal analgesia (MMA) may reduce opioid use among children who are hospitalized, and may contribute toward enhanced recovery after selective dorsal rhizotomy (SDR) for patients with spasticity in pediatric cerebral palsy. In this retrospective cohort study, we assess an MMA protocol consisting of scheduled nonsteroidal antiinflammatory drug doses (ketorolac or ibuprofen), alternating with scheduled acetaminophen and diazepam doses, with as-needed opioids. It was hypothesized that protocol use would be associated with reductions in opioid requirements and other clinical improvements. METHODS: Data were obtained for 52 patients undergoing SDR at an academic tertiary care pediatric hospital (2012–2017, with the protocol implemented in 2014). Using a retrospective cohort design, we compared outcomes between protocol and nonprotocol patients, employing both univariate t test and Wilcoxon rank test comparisons as well as multivariable regression methods. The primary outcome was total as-needed opioid requirements over postoperative days (PODs) 0 to 2, measured in oral morphine milligram equivalents per kilogram. Additional outcomes included antiemetic medication doses, discharge opioid prescriptions, total direct cost, and length of stay. RESULTS: Twelve patients received the MMA protocol, and 40 patients did not. POD-0 MMA initiation was independently associated with a reduction of 0.14 morphine milligram equivalents per kilogram in mean opioid requirements over PODs 0 to 2 in the multiple regression analysis (95% confidence interval 0.01 to 0.28; P = .04). No statistically significant differences were demonstrated in doses of antiemetic medications, discharge opioid prescriptions, total direct cost, and length of stay. CONCLUSIONS: This MMA protocol may help reduce opioid use after SDR. Improving protocol implementation in a prospective, multisite study will help elucidate further MMA effects on pain, costs, and recovery.

The research in this study looks at the Mergers and Acquisitions (M&A) and highlight insight about the performance impact of both financial and non-financial firms in Pakistan by using three financial ratios of Sixteen M&A in different industries have been observed from 2006-2013 reported on Karachi Stock Exchange (KSE).For quantitative techniques,SPSS 18 and data average method was used for analysis.Annual published reports of acquiring firms for the period of six years (3 years before M&A and 3 years after) combine have been used. While the acquired or merged small firms have been excluded due to the un -aviability of data concern .The study concludes that all the hypotheses of the financial performance of firms' have been rejected and identified declinig in post-M&A performance ratios. Result shows there is significant negative decline in ROA and ROE but some significant positive improvement is shown in NPM and size of firms after combination while increase in mean of both size and inflation rate has an significant negative effect on firms ROA and ROE ratios declined post M&A period.Over all result reveals the significant negative effect of M&A on the efficiency of firms in the post-M&A period.It can be said that better performance after M&A is not mandatory

This work reports the application of ensemble artificial neural networks, a machine learning technique, in the solution of short term optimal power generation on the IEEE 30-bus test system. The study, carried out using MATLAB, is being reported. The motive for using ensemble artificial neural networks has been to take advantage of multiple parallel processors computing rather than the traditional serial computation. The Bootstraps are obtained through small bags in the Bagging algorithm and are combined by averaging. Employing ensemble neural networks reduces bias and variance in machine learning so that the overall error is reduced, and hence better prediction can be achieved. The results obtained from the proposed algorithm are compared with those from the other heuristic and conventional techniques to validate the effectiveness of the proposed methodology.

Even though the role of the DICS1 gene as a risk factor for schizophrenia is still unclear, there is substantial evidence from functional and cell biology studies that supports the connection of the gene with schizophrenia. The studies associating the DISC1 gene with schizophrenia in Asian populations are limited to East-Asian populations. Our study examined several DISC1 markers of schizophrenia that were identified in the Caucasian and East-Asian populations in Malaysia and assessed the role of rs2509382, which is located at 11q14.3, the mutual translocation region of the famous DISC1 translocation [t (1; 11) (p42.1; q14.3)]. METHODS: We genotyped eleven single-neucleotide polymorphism (SNPs) within or related to DISC1 (rs821597, rs821616, rs4658971, rs1538979, rs843979, rs2812385, rs1407599, rs4658890, and rs2509382) using the PCR-RFLP methods. RESULTS: In all, there were 575 participants (225 schizophrenic patients and 350 healthy controls) of either Malay or Chinese ethnicity. The case-control analyses found two SNPs that were associated with schizophrenia [rs4658971 (p=0.030; OR=1.43 (1.35-1.99) and rs1538979-(p=0.036; OR=1.35 (1.02-1.80)] and rs2509382-susceptibility among the males schizophrenics [p=0.0082; OR=2.16 (1.22-3.81)]. This is similar to the meta-analysis findings for the Caucasian populations. CONCLUSION: The study supports the notion that the DISC1 gene is a marker of schizophrenia susceptibility and that rs2509382 in the mutual DISC1 translocation region is a susceptibility marker for schizophrenia among males in Malaysia. However, the finding of the study is limited due to possible genetic stratification and the small sample size. KEYWORDS: DISC1; SNPs; Schizophrenia; Susceptibility

Introduction The present study investigated the relationship between psychological symptoms and psychosocial function and the role of relevant sociodemographic data and antipsychotic use in the prediction of psychosocial function among multiracial schizophrenia outpatients in Malaysia. Methods A total of 223 participants were recruited in this cross-sectional study conducted from December 2010 to April 2011. Psychological symptoms were assessed using the Positive and Negative Syndrome Scale whilst the psychosocial function was assessed using the Personal and Social Performance scale. Sociodemographic and treatment variables were gathered through interview or review of the medical records. Results All dimensions of psychosocial functions were inversely correlated with Positive and Negative Syndrome Scale sub-domains. Only the disorganization sub-domain significantly predicts all dimensions of psychosocial function. For social data, body mass index and employment status were significant predictors of all dimensions of psychosocial functions. Typical antipsychotics significantly predict social function negatively as compared to sulpiride (β = −0.152, P = 0.028). Discussion We found that the relationship between psychological symptoms and psychosocial functions were relatively consistent with the findings from the Caucasian population. Additionally, disorganization was the only significant predictor of all dimensions of psychosocial functions. This further emphasized the importance of cognition in psychosocial function. The roles of sulpiride, body mass index and employment status as predictors of psychosocial function were also discussed.