Nonsteroidal Anti-Inflammatory Drugs for Wounds: Pain Relief or Excessive Scar Formation?

The inflammatory process has direct effects on normal and abnormal wound healing. Hypertrophic scar formation is an aberrant form of wound healing and is an indication of an exaggerated function of fibroblasts and excess accumulation of extracellular matrix during wound healing. Two cytokines—transforming growth factor-β (TGF-β) and prostaglandin E2 (PGE2)—are lipid mediators of inflammation involving wound healing. Overproduction of TGF-β and suppression of PGE2 are found in excessive wound scarring compared with normal wound healing. Nonsteroidal anti-inflammatory drugs (NSAIDs) or their selective cyclooxygenase-2 (COX-2) inhibitors are frequently used as a pain-killer. However, both NSAIDs and COX-2 inhibitors inhibit PGE2 production, which might exacerbate excessive scar formation, especially when used during the later proliferative phase. Therefore, a balance between cytokines and medication in the pathogenesis of wound healing is needed. This report is a literature review pertaining to wound healing and is focused on TGF-β and PGE2

Increased spinal prodynorphin gene expression in reinflammation-associated hyperalgesia after neonatal inflammatory insult

<p>Abstract</p> <p>Background</p> <p>Neuroplasticity induced by neonatal inflammation is the consequence of a combination of activity-dependent changes in neurons. We investigated neuronal sensitivity to a noxious stimulus in a rat model of neonatal hind-paw peripheral inflammation and assessed changes in pain behaviour at the physiological and molecular levels after peripheral reinflammation in adulthood.</p> <p>Results</p> <p>A decrease in paw withdrawal latency (PWL) after a heat stimulus was documented in rats that received inflammatory injections in their left hind paws on postnatal day one (P1) and a reinflammation stimulus at postnatal 6-8 weeks of age, compared with normal rats. An increase in the expression of the prodynorphin (<it>proDYN</it>) gene was noted after reinflammation in the spinal cord ipsilateral to the afferents of the neonatally treated hind paw. The involvement of the activation of extracellular signal-regulated kinases (ERK) in peripheral inflammatory pain hypersensitivity was evidenced evident by the increase in phospho-ERK (pERK) activity after reinflammation.</p> <p>Conclusions</p> <p>Our results indicate that peripheral inflammation in neonates can permanently alter the pain processing pathway during the subsequent sensory stimulation of the region. Elucidation of the mechanism underlying the developing pain circuitry will provide new insights into the understanding of the early pain behaviours and the subsequent adaptation to pain.</p

Inferences of variance function - a parametric robust way

Tsou (2003a) proposed a parametric procedure for making robust inference for mean regression parameters in the context of generalized linear models. This robust procedure is extended to model variance heterogeneity. The normal working model is adjusted to become asymptotically robust for inference about regression parameters of the variance function for practically all continuous response variables. The connection between the novel robust variance regression model and the estimating equations approach is also provided.Generalized linear models, variance function, robust profile likelihood, normal regression,

Parametric Robust Test for Several Variances with Unknown Underlying Distributions

Normal models, Robust profile Likelihood, Adjusted score test,

Exchangeable cluster binary data correlation coefficient estimation with generalized estimating equations

This study used simulated data to evaluate the performance of distinct conditional generalized estimating equations (CGEE) for the analysis of exchangeable correlation for binary data. The CGEE differs from the usual generalized estimating equations (GEE) in that, instead of marginal expectations, the conditional expectations of the responses were used in the estimating equations. The major distinction among the CGEEs compared was the sizes of the conditioning events used in the conditional expectations. The results show that, for the estimation of correlation coefficient, the bias decreases, and the variance increases when more members in a cluster are included in the conditioning event. The increase of variance is, however, only moderate for small intracluster correlation coefficient. On the other hand, for the estimation of regression parameters, the bias and variance of the estimates both increase when the size of the conditioning event increases. The increase, however, is also insignificant when the correlation coefficient is small.Clustered binary data Generalized estimating equations Efficiency Exchangeable

Regression Diagnostic under Model Misspecification

We propose two novel diagnostic measures for the detection of influential observations for regression parameters in linear regression. Traditional diagnostic statistics focus on the effect of deletion of data points either on parameter estimates, or on predicted values. A data point is regarded as influential by the new methods if its inclusion determines a significantly different likelihood function for the parameter of interest. The concerned likelihood function is asymptotically valid for practically all underlying distributions whose second moments exist.Influential diagnostic, robust likelihood, robust normal regression, DFBETAS , DFFITS , Cook's distance,

Robust likelihood inference for regression parameters in partially linear models

A robust likelihood approach is proposed for inference about regression parameters in partially-linear models. More specifically, normality is adopted as the working model and is properly corrected to accomplish the objective. Knowledge about the true underlying random mechanism is not required for the proposed method. Simulations and illustrative examples demonstrate the usefulness of the proposed robust likelihood method, even in irregular situations caused by the components of the nonparametric smooth function in partially-linear models.Robust likelihood Generalized additive models Partially-linear models

The relationship of pain, uncertainty, and hope in Taiwanese lung cancer patients

The impact of cancer pain on the quality of life of lung cancer patients is obvious, but the relationship of cancer pain to uncertainty and level of hope in cancer patients is not clear and has been the subject of only a few studies. The purpose of this study is to look at the relationship of pain to uncertainty and hope in Taiwanese lung cancer patients. A cross-sectional and descriptive correlational design was used in this study. A convenience sample of lung cancer patients was recruited from chest medicine and oncology inpatient units at three teaching hospitals in the Taipei area of Taiwan. The research instruments included the Brief Pain Inventory-Chinese version (BPI-C), Mishel's Uncertainty Illness Scale (MUIS), and the Herth Hope Index (HHI). Data were analyzed using descriptive statistics, Pearson's correlation, and multiple regression. A total of 164 subjects were recruited, including 79 patients with cancer pain and 85 patients without cancer pain. The major findings were: 1) there were significant differences in level of uncertainty and level of hope between patients with cancer pain and those without. Patients with cancer pain reported higher levels of uncertainty and lower levels of hope than did patients without cancer pain; 2) pain severity was not significantly related to level of uncertainty; however, pain interference with daily life was positively correlated to level of uncertainty; 3) both pain severity and pain interference were negatively correlated with level of hope; and 4) after controlling for pain severity and pain interference, uncertainty was a significant predictor of level of hope. Important implications for future studies are discussed. © 2003 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.Link_to_subscribed_fulltex