Impact of hyperglycemia on morbidity and mortality, length of hospitalization and rates of re-hospitalization in a general hospital setting in Brazil

<p>Abstract</p> <p>Background</p> <p>Hyperglycemia in hospitalized patients is known to be related to a higher incidence of clinical and surgical complications and poorer outcomes. Adequate glycemic control and earlier diagnosis of type 2 diabetes during hospitalization are cost-effective measures.</p> <p>Methods</p> <p>This prospective cohort study was designed to determine the impact of hyperglycemia on morbidity and mortality in a general hospital setting during a 3-month period by reviewing patients' records. The primary purposes of this trial were to verify that hyperglycemia was diagnosed properly and sufficiently early and that it was managed during the hospital stay; we also aimed to evaluate the relationship between in-hospital hyperglycemia control and outcomes such as complications during the hospital stay, extent of hospitalization, frequency of re-hospitalization, death rates and number of days in the ICU (Intensive Care Unit) after admission. Statistical analyses utilized the Kruskall-Wallis complemented by the "a posteriori" d.m.s. test, Spearman correlation and Chi-squared test, with a level of significance of 5% (p < 0.05).</p> <p>Results</p> <p>We reviewed 779 patient records that fulfilled inclusion criteria. The patients were divided into 5 groups: group (1) diabetic with normal glycemic levels according to American Diabetes Association criteria for in-hospital patients (n = 123); group (2) diabetics with hyperglycemia (n = 76); group (3) non-diabetics with hyperglycemia (n = 225); group (4)diabetics and non-diabetics with persistent hyperglycemia during 3 consecutive days (n = 57) and group (5) those with normal glucose control (n = 298). Compared to patients in groups 1 and 5, patients in groups 2, 3 and 4 had significantly higher mortality rates (17.7% vs. 2.8%) and Intensive Care Unit admissions with complications (23.3% vs. 4.5%). Patients in group 4 had the longest hospitalizations (mean 15.5 days), and group 5 had the lowest re-hospitalization rate (mean of 1.28 hospitalizations). Only 184 (51.4%) hyperglycemic patients had received treatment. An insulin "sliding-scale" alone was the most frequent treatment used, and there was a wide variation in glucose target medical prescriptions. Intra Venous insulin infusion was used in 3.8% of patients in the ICU. Glycohemoglobin(A1C) was measured in 11 patients(2.2%).</p> <p>Conclusions</p> <p>Hospital hyperglycemia was correlated with, among other parameters, morbidity/mortality, length of hospitalization and number of re-hospitalizations. Most patients did not have their glycemic levels measured at the hospital; despite the high number of hyperglycemic patients not diagnosed as diabetics, A1C was not frequently measured. Even when patients are assessed for hyperglycemia, they were not treated properly.</p

An evaluation of technical trading rules: Evidence from the New Zealand share market

This study has assessed whether an investor could follow a technical trading rule on 10 individual stocks from the New Zealand Share market and earn a superior return to a 'buy and hold' strategy of an equally weighted portfolio of those same 10 stocks. A five year sample period is used to test a range of simple and well known technical trading rules, with the best performing technical trading rule then applied to the post sample period to determine if a superior performance can be earned. A range of practical implementation issues, including brokerage costs and capital gains tax, were introduced and accounted for in the assessment of the two strategies. The results have been consistent with technical analysis being unable to generate returns in excess of a buy and hold strategy in an out of sample period. Several issues relating directly to technical analysis are subsequently discussed and applied in a New Zealand setting.UnpublishedBrock, W., J., Lakonishok and B., LeBaron, 1992, "Simple Technical Trading Rules and Stochastic Properties of Stock Returns", Journal of Finance, Vol- 47, pp. 1731-1764, DeBondt, W.F.M., and R.H. Thaler, 1985, "Does the Stock Market Overreact?", Journal of Finance, Vol. 40, 793-805. Duffy, M-N, 1988, "Projecting the Future with Technical Analysis", Wall Street Computer Review (WSC) 5, pp: 38-48. Dukas, S, and J. Park, 1995, "Trading activity indicators and market timing", Applied Financial Economics [APF] 5, pp: 337-344. Fama, E., and M., Blume, 1966, "Filter Rules and Stock-Market Trading", Journal of Business 39, pp. 226-241. Francis, JC., 1972, "Investments: Analysis and Management", 3 r d Edition, McGraw Hill Publishing Company- Gencay, R, 1996, "Non-linear prediction of security returns with moving average rules", Journal of Forecasting [JOF] 15, pp: 165-174. Gifford, B., 1995, "Investors Guide to Technical Analysis; Predicting Price Reaction in the Markets", Pitman Publishing. Hudson, R., M. Dempsey, and K. Keasey, 1996, "A note on the weak form efficiency of capital markets: The application of simple technical trading rules to UK stock prices - 1935 to 1994", Journal of Banking & Finance [JBA] 20, pp: 1121-1132. Levich, R. M, and L-R. Thomas III, 1993, "The significance of technical trading-rule profits in the foreign exchange market: A bootstrap approach", Journal of International Money & Finance (JMF) 12, pp: 451-474. Laderman, J.M, 1987, "Watching the Bull Through a Technician's Eyes", Business Week (BWE), pp: 88-89. Lukac, L.P, and B.W. Brorsen, 1989, "The Usefulness of Historical Data in Selecting Parameters for Technical Trading Systems", Journal of Futures Markets (JFU) 9, pp: 55-65. Levy, R.A., 1967, "Relative Strength as a Criterion for Investment Selection", Journal of Finance 22, pp. 595-610. Neftci, S., 1991. "Naïve Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of 'Technical Analysis' ", Journal of Business 64, pp.549-571. Pring, M.J., 1985, "Technical Analysis Explained: The successful Investors Guide to Spotting Investment Trends and Turning Points", 2nd Edition, McGraw Hill Publishing Company. Proterba, J.M., and L.H. Summers, 1988, "Mean Reversion in Stock Prices: Evidence and Implications", Journal of Financial Economics 22, pp. 27-59. Sharma, R, 1987, "Simple Technical Analysis of Stocks and Stock Index Futures", InterMarket (ITM) 4, pp: 50-51. Stewart, T.H., 1996, "How Charts Can Make You Money: Technical Analysis for Investors", 3' d Edition, Woodhead Publishing Limited. Strong, R.A, 1988, "A Behavioral Investigation of Three Paradigms in Finance", Northeast Journal of Business & Economics (NEJ) 14, pp: 1-28. Sullivan R., A. Timmermann, and H. White, 1997, "Data-Snooping, Technical Trading Rule Performance, and the Bootstrap", Discussion Paper. Sweeney R.J., 1986, "Beating the Foreign Exchange Market", Journal of Finance 41, pp. 163- 182. Sweeney R.J., 1988, "Some New Filter Rule Tests: Methods and Results", Journal of Financial and Quantitative Analysis 23, pp. 285-300. Tvede, L, 1992, "What 'Chaos' Really Means in Financial Markets", Futures: The Magazine of Commodities & Options (CMM) 21, pp: 34-36

An evaluation of technical trading rules: Evidence from the New Zealand share market

This study has assessed whether an investor could follow a technical trading rule on 10 individual stocks from the New Zealand Share market and earn a superior return to a 'buy and hold' strategy of an equally weighted portfolio of those same 10 stocks. A five year sample period is used to test a range of simple and well known technical trading rules, with the best performing technical trading rule then applied to the post sample period to determine if a superior performance can be earned. A range of practical implementation issues, including brokerage costs and capital gains tax, were introduced and accounted for in the assessment of the two strategies. The results have been consistent with technical analysis being unable to generate returns in excess of a buy and hold strategy in an out of sample period. Several issues relating directly to technical analysis are subsequently discussed and applied in a New Zealand setting.UnpublishedBrock, W., J., Lakonishok and B., LeBaron, 1992, "Simple Technical Trading Rules and Stochastic Properties of Stock Returns", Journal of Finance, Vol- 47, pp. 1731-1764, DeBondt, W.F.M., and R.H. Thaler, 1985, "Does the Stock Market Overreact?", Journal of Finance, Vol. 40, 793-805. Duffy, M-N, 1988, "Projecting the Future with Technical Analysis", Wall Street Computer Review (WSC) 5, pp: 38-48. Dukas, S, and J. Park, 1995, "Trading activity indicators and market timing", Applied Financial Economics [APF] 5, pp: 337-344. Fama, E., and M., Blume, 1966, "Filter Rules and Stock-Market Trading", Journal of Business 39, pp. 226-241. Francis, JC., 1972, "Investments: Analysis and Management", 3 r d Edition, McGraw Hill Publishing Company- Gencay, R, 1996, "Non-linear prediction of security returns with moving average rules", Journal of Forecasting [JOF] 15, pp: 165-174. Gifford, B., 1995, "Investors Guide to Technical Analysis; Predicting Price Reaction in the Markets", Pitman Publishing. Hudson, R., M. Dempsey, and K. Keasey, 1996, "A note on the weak form efficiency of capital markets: The application of simple technical trading rules to UK stock prices - 1935 to 1994", Journal of Banking & Finance [JBA] 20, pp: 1121-1132. Levich, R. M, and L-R. Thomas III, 1993, "The significance of technical trading-rule profits in the foreign exchange market: A bootstrap approach", Journal of International Money & Finance (JMF) 12, pp: 451-474. Laderman, J.M, 1987, "Watching the Bull Through a Technician's Eyes", Business Week (BWE), pp: 88-89. Lukac, L.P, and B.W. Brorsen, 1989, "The Usefulness of Historical Data in Selecting Parameters for Technical Trading Systems", Journal of Futures Markets (JFU) 9, pp: 55-65. Levy, R.A., 1967, "Relative Strength as a Criterion for Investment Selection", Journal of Finance 22, pp. 595-610. Neftci, S., 1991. "Naïve Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of 'Technical Analysis' ", Journal of Business 64, pp.549-571. Pring, M.J., 1985, "Technical Analysis Explained: The successful Investors Guide to Spotting Investment Trends and Turning Points", 2nd Edition, McGraw Hill Publishing Company. Proterba, J.M., and L.H. Summers, 1988, "Mean Reversion in Stock Prices: Evidence and Implications", Journal of Financial Economics 22, pp. 27-59. Sharma, R, 1987, "Simple Technical Analysis of Stocks and Stock Index Futures", InterMarket (ITM) 4, pp: 50-51. Stewart, T.H., 1996, "How Charts Can Make You Money: Technical Analysis for Investors", 3' d Edition, Woodhead Publishing Limited. Strong, R.A, 1988, "A Behavioral Investigation of Three Paradigms in Finance", Northeast Journal of Business & Economics (NEJ) 14, pp: 1-28. Sullivan R., A. Timmermann, and H. White, 1997, "Data-Snooping, Technical Trading Rule Performance, and the Bootstrap", Discussion Paper. Sweeney R.J., 1986, "Beating the Foreign Exchange Market", Journal of Finance 41, pp. 163- 182. Sweeney R.J., 1988, "Some New Filter Rule Tests: Methods and Results", Journal of Financial and Quantitative Analysis 23, pp. 285-300. Tvede, L, 1992, "What 'Chaos' Really Means in Financial Markets", Futures: The Magazine of Commodities & Options (CMM) 21, pp: 34-36

Records of subantarctic fur seals Arctocephalus tropicalis in Australia.

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