Structure and function of the kidney: organ physiology

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An Application of ARDL Approach

The paper examines the relationship between financial development and income inequality; and also explores if the Greenwood and Jovianvich (GJ) hypothesis applies to Pakistan. Using data from 1971 to 2005, the paper implements the Auto Regressive Distributed Lag (ARDL) bounds testing approach to cointegration to examine the existence of long run; and the error correction model (ECM) for the short run relationships. Stationarity properties of the series are checked by the ADF method. The findings indicate that financial development reduces income inequality while financial instability aggravates it. Contrary to the conventional wisdom, we find economic growth worsens income distribution and that the latter is deteriorated further by trade openness. The paper does not find support for the GJ relation. Appropriate reforms aimed at developing a well-organized financial sector in Pakistan can help reduce income inequality

Follow-up in women with breast cancer: the patients' perspective

We surveyed the opinions of patients on routine follow-up for early breast cancer to assess their satisfaction with current breast cancer follow-up arrangements, establish the issues that are important to patients in this setting and to assess their opinions on different models of care in breast cancer follow-up. A self-completion questionnaire was issued to 134 women attending an outpatient breast cancer follow-up clinic at a central teaching hospital in Glasgow. Most women (84%) considered follow-up ‘important’ and 90% were satisfied with current follow-up practice. Almost all patients (91%) were content with both the current frequency and duration of their appointments. Risk of recurrence and effects of treatment were considered the most important topics for discussion. Two-thirds of patients felt it was important to see the same member of staff at each follow-up appointment. The majority (64%) would have been satisfied with a nurse-led system of follow-up, whereas only 38% would be happy with General Practitioner-led care. Although patients are generally satisfied with current follow-up arrangements, most would accept the involvement of specialist nurses in conjunction with a consultant

Risk scores for predicting outcomes in patients with type 2 diabetes and nephropathy: The RENAAL study

Diabetic nephropathy is the most important cause of ESRD. The aim of this study was to develop a risk score from risk predictors for ESRD, with and without death, in the Reduction of Endpoints in NIDDM with the Angiotensin II Antagonist Losartan (RENAAL) study and to compare ability of the ESRD risk score and its components to predict ESRD. The risk score was developed from coefficients of independent risk factors from multivariate analysis of baseline variables and equals (1.96 X log [urinary albumin:creatinine ratio]) - (0.78 serum albumin [g/dl]) + (1.28 X serum creatinine [mg/dl] - (0.11 X hemoglobin [g/dl]). It was robust with respect to severity of nephropathy, gender, race, and treatment group. The risk score for ESRD or death was comparable. The four risk predictors for progression of kidney disease were independent of therapy. For combined treatment groups, the hazard ratio between the fourth and first quartiles of the ESRD risk score was 49.0, as compared with the corresponding hazard ratios for each component: 14.7 for urinary albumin:creatinine ratio, 9.2 for serum creatinine, 5.5 for hemoglobin, and 10.2 for serum albumin. The RENAAL risk scores for ESRD with or without death emphasize the importance of identification of level of albuminuria, serum albumin, serum creatinine, and hemoglobin to predict development of ESRD in patients with type 2 diabetes and nephropathy. Although albuminuria is a strong risk factor for ESRD, the contribution of serum albumin, serum creatinine, and hemoglobin level further enhances prediction of ESRD. Future trials with a similar patient population and outcomes measures should consider adjusting analyses for baseline risk factor