Title:Impaired renal function and associated risk factors in newly diagnosed HIV-infected Adults in Gulu Hospital, Northern Uganda

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Author's response to reviews Title:Impaired renal function and associated risk factors in newly diagnosed HIV-infected Adults in Gulu Hospital, Northern Uganda Authors: Pancras Odongo (odongopancras@gmail.com) Ronald Wanyama (rwanyama@gmail.com) James H Obol (obolh@yahoo.com) Paska Apiyo (apiyopaska2004@yahoo.co.uk) Pauline K Byakika (pbyakika@gmail.com) Version:3Date:29 December 2014 Author's response to reviews: see over

Author's response to reviews Title: Impaired Renal Function and its Predictors among Newly Diagnosed HIV-infected Adults in Gulu Regional Referral Hospital, Northern Uganda Authors: Pancras Odongo: odongopancras@gmail.com Ronald Wanyama: rwanyama@gmail.com James Henry Obol: obolh@yahoo.com Paska Apiyo: apiyopaska2004@yahoo.co.uk Pauline Byakika-Kibwika: pbyakika@gmail.com Version: 2 Date: 28 December 2014 Author's response to reviews: see over

Reviewer's report Title:Impaired Renal Function and its Predictors among Newly Diagnosed HIV-infected Adults in Gulu Regional Referral Hospital, Northern Uganda Version:2Date:5 November 2014 Reviewer:Rebecca Scherzer Reviewer's report: Comments on BMC Nephrology Manuscript Number: n/a Title: Impaired Renal Function and its Predictors among Newly Diagnosed HIV infected Adults in Gulu Regional Referral Hospital, Northern Uganda General comments This manuscript prepared by Pancras Odongo and colleagues determines the rate of impaired renal function and associated factors in a cross-sectional study of 361 newly diagnosed HIV-infected men and women in northern Uganda. This is an important clinical question to address given the high prevalence of HIV infection in this resourcelimited region. HIV infection is associated with early onset of kidney disease, and yet the cost to screen all newly infected persons for kidney disease would be prohibitive. The paper is well-written, but the analyses could be strengthened and some points could be clarified: Introduction: This section is well-written, but could use a bit more context for the statement that In Uganda, HIV-associated renal disease is a growing concern. Are you seeing higher rates of ESRD or an uptick in clinical presentation of kidney disease in HIV-infected persons in Uganda? If this is premature to characterize, you might reword: In Uganda, the incidence of renal disease in HIV-infected persons is expected to increase, even though highly effective antiretroviral therapy is increasingly available. Indeed we are not seeing higher rates of ESRD or an uptick in clinical presentation of kidney disease in HIV-infected persons in Uganda and we have reworded the sentence (lines 53-54) as the reviewer indicates Methods: 1. It is worth noting that the rate of renal dysfunction would likely have been even higher if you had included persons with hypertension and diabetes in your study population. I think it would be worth mentioning in the abstract that these conditions were excluded. This has been mentioned in the abstract (lines 26-27) as the reviewer indicates 2. Please clarify which anthropometric parameters were assessed. Do you mean BMI? This has been clarified (lines 109-110)

3. Consider recalculating egfr using the newer Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula. It is more accurate than the older MDRD formula, especially in populations (such as HIV infected persons) where muscle mass may be reduced. Use of this newer formula should improve your ability to identify persons who should be screened for renal disease. The equation is given here: http://nkdep.nih.gov/lab-evaluation/gfr/estimating.shtml Reference: Levey et al. A new equation to estimate glomerular filtration rate. Ann Intern Med (2009) vol. 150 (9) pp. 604-12. We recalculated egfr using CKD-EPI formula as the reviewer indicates and the egfr results now presented in these manuscript are base on CKD-EPI formula 4. It is unclear which variables were included as candidate covariates in the analysis of impaired renal function. I suggest including traditional kidney risk factors (age, gender, glucose, systolic and diastolic blood pressure, lipids, history of cardiovascular disease, BMI, smoking, illicit drug use, proteinuria) and HIV-related factors (Hepatitis C infection status, CD4 cell count, and HIV RNA level), where available. For screening purposes, it could also be useful to learn whether sociodemographic factors are associated with renal function. We did not collect data on glucose, systolic and diastolic blood pressure, lipids, history of cardiovascular disease, illicit drug use but patients who had been previous diagnosed with these conditions were excluded from the study. We also did not collect data on Hepatitis C infection status and HIV RNA level. Traditional kidney risk factors such as age, gender, BMI, smoking, alcohol consumption, proteinuria, serum urea and HIV-related factors, CD4 cell count were the covariates used in the analysis of impaired renal function. Socio-demographic factors, as the reviewer indicates, were analyzed for their association with renal function and only age was significant (tables 1 and 3). 5. Consider adding egfr<60 as a more stringent definition of impaired renal function for consistency with other definitions of CKD, including those you cite (Wyatt et al; Ekat et al). It would be of interest to report both egfr<60 and egfr<90. We have added egfr<60 as a more stringent definition of impaired renal function and reported both egfr<60 and egfr<90 as the reviewer indicates 6. As a secondary analysis, consider using multivariable linear regression to evaluate predictors of egfr as a continuous outcome. This will give you more power to identify associated factors and will enable you to quantify the degree of impairment associated with low CD4 cell count and other factors. Results: 1. The second paragraph of the results section states which statistical tests were used. This information could be moved to the methods section.

2. Table 2 states that median and IQR are tabulated, but I don t think this is correct. For age, the result is given as 30 (18-61). If 18 is the lower quartile, this means that 25% of the population was below age 18, which means that children were included. But the title and methods say that only adults were included. Likewise, I don t think the lower quartile for CD4 count was 6. Actually our IQR were not correct as the reviewer indicates. We had used minimum and maximum values. We have reanalyzed and corrected (table 3). For example now median age (IQR) is 30 (24.0 37.5) years. 3. The last paragraph of the results section states that decreasing CD4 count and increasing age were associated with impaired renal function. Please indicate how these were modelled. The odds ratio for age is 0.69, which would suggest that the odds of impaired renal function drop by 31% with each increment of higher age. That cannot be correct. We have reanalyzed using the variables as continuous variables and the results are now in table 4. The odds ratio (95% confidence interval, P valve) for age and CD4 cell count are 0.956 (0.927 0.987, 0.005), 1.003 (1.001 1.004, <0.001) respectively. Discussion: 1. Paragraph 1 of discussion states that Wyatt et al found a prevalence of only 2.7%. A couple of points should be noted: (1) this was a population of HIV+ women; (2) they defined impaired renal function as <60 whereas you are defining it as <90; (3) their median egfr of 90 is the same as yours. Ekat et al also used egfr<60 to define impaired renal function. Their prevalence was 7.9%. I would insert that finding into your discussion. We have included these statements in paragraph 2 of our discussion: Wyatt et al and Ekat et al both used egfr<60ml/min/1.73m 2 to define renal impairment like us and their median egfr of 90 was the same as ours of 89.7. However, Wyatt et al study involved a population of only HIV positive women while our study included both men and women. 2. I think your conclusions could be strengthened if you could give a more specific recommendation of which categories of patients should be screened for renal disease. A fuller multivariable analysis would inform this recommendation. Indeed our recommendation has been strengthened. Minor points: 1. Table 1: consider reordering the education categories from low to high, starting with no education. 2. Table 2: It is unclear why the N is only 15 (according to the table header). Corrected now N=361 3. Table 3: the sign is reversed for low CD4 (should be < not >)

4. Table 4: please add the units or categories used to model CD4 count and age. For example, if you defined low CD4 count as <350, then you would label it in this table as CD4 count < 350., CD4 count (cells/μl) and age (years) Level of interest: An article of importance in its field Quality of written English: Acceptable Statistical review: No, the manuscript does not need to be seen by a statistician. Declaration of competing interests: I received an honorarium from Merck for participating in a Renal Expert Input Forum; this honorarium was donated to NCIRE to support kidney research.

Reviewer's report Title:Impaired Renal Function and its Predictors among Newly Diagnosed HIV-infected Adults in Gulu Regional Referral Hospital, Northern Uganda Version:2 Date:12 November 2014 Reviewer:MASIMANGO IMANI MANNIX Reviewer's report: Reviewer: Masimango Mannix Major compulsory revisions 1. Title - We propose this title : «Impaired renal function and associated risk factors in newly HIV-infected Adults in Gulu Hospital, Northen Uganda In fact, it is a cross-sectional study; you cannot say "predictors" as in a longitudinal study. We proposed associated risk factors. Some words are removed in the title without changing message. The title of the article has been changed as the reviewer indicates. 2. Abstract - Page 21-28: background: the paragraph it is too long. We suggest this: Screening for renal diseases should be performed at the time of diagnosis of human immunodeficiency virus (HIV) infection. Despite the high prevalence of HIV/AIDS in Northern Uganda, little is known about the status of renal function and its correlates in the newly HIV-infected individuals in this resource limited region. The background has been changed as the reviewer indicates - page 29-34: Methods This paragraph is also long, try to summarize it. In methods section (see page 93), details are available. we suggest this: We conducted a cross-sectional study among newly diagnosed HIV-infected adults. Estimated glomerular filtration rate (egfr) was calculated using MDRD formula. Factors associated with renal dysfunction (egfr< 90 ml/min/1.73m2 and/or proteinuria on dipstick) was thus sought. Summarized as the reviewer suggested, page 25-29: This was a seven month cross-sectional hospital-based study, involving newly diagnosed HIV-infected patients, 18 years and older. Patients with history of diabetes mellitus, hypertension and renal disease were excluded. Estimated glomerular filtration rate (egfr) was calculated using Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula. Factors associated with impaired renal function (egfr< 60 ml/min/1.73m 2 ) were thus sought. - Results (page 35-43): relevant results are presented in this section. We suggest: We enrolled 361 participants (230, 63.7% female) with median (IQR) age of 30 (18-61) years. 126, (34.9%) had impaired renal function with 77 (61.1%) having mild renal impairment (egfr 60-89.9mL/min/1.73m2), 34 (27%) moderate impairment (egfr 30-

59.9mL/min/1.73m2) while 15 (11.9%) had severe impairment (egfr <30mL/min/1.73m2). Proteinuria was recorded in 189 (52.4%) participants 154 (42.7%) having mild (1+) and while 8 (2.2%) had severe (3+) proteinuria. Indeed have presented relavant results as the reviewer indicates and now we have the results as follows; page 30-34: We enrolled 361 participants (230, 63.7% female) with median (IQR) age of 30 (24-37.5) years. 52, (14.4%) had impaired renal function (egfr <60mL/min/1.73m 2 ) and of this 37 (71.2%) moderate renal impairment (egfr 30-59.9mL/min/1.73m 2 ) while 15 (28.8%) had severe renal impairment (egfr <30mL/min/1.73m 2 ). Proteinuria was recorded in 189 (52.4%) participants. Of these, 154 (81.5%) had mild (1+) while 8 (4.2%) had severe (3+) proteinuria. Page 41-42: remove this phrase: there was a significant.. Page 42: replace at with in 3. Methods section - page 119-120: 5 ml was sufficient for all blood tests? Complete blood count needs a tube with anticoagulant and biochemistry tests don t need it. Yes 5 ml was sufficient for all blood tests; we did not do complete blood count. Page 111-114 5mL of venous blood was drawn from each participant into a syringe for renal function tests, and CD4 count. About 1.5mL of blood for CD4 count was transferred into purple top vacutainers and blood for renal function tests was transferred into orange top vacutainers with a gel separator - Page 124: why using the cut-off < 90 ml/min/1.73m 2. According to KDIGO guidelines, in the absence of evidence of kidney damage, neither GFR category G1 (GFR >90) and nor G2 (GFR 60-89 ml/min/1.73) fulfill the criteria for CKD. The reviewer is correct and we have used the cut-off of egfr< 60 ml/min/1.73m 2 to define renal impairment - how many patients with diabetes or hypertension were excluded? Page 101-103: a total of 24 patients were excluded from this study (5 were hypertensive, 4 had diabetes mellitus type II, 6 had pyrexia (>38⁰C), 8 were pregnant and 1 had renal disease. - page 109: know CKD prior to study? How have you excluded it? Yes all patients with known CKD were excluded from our study 4. Results - page 145-146. Some discussion is made in this part. Eg: this indicates that very big percentages of adults. I suggest this phrase be removed on this section.

- Is it possible to have a double entry table with (GFR<90) and without (GFR >90) renal dysfunction and compare different characteristics (socio-demographic, clinical, biological). You mentioned this on page 151 without a table in presentation of results. According to me, if the data are presented in this way, the article will answer the research question: factors associated with renal impairment We reanalyzed the data using GFR <60 ml/min/1.73 m 2 and GFR 60 ml/min/1.73 m 2 to determine patients with and without renal impaired function respectively (table 2) Table 1 has been used to address issue raised by the reviewer about on page 151 without a table in presentation of results and indeed we were able to identify the factors associated with renal impairment - I would suggest that data on blood pressure, blood glucose appear in the results. We did not collect data on blood pressure and blood glucose 5. Discussion - This section will depend on way the results will be presented as suggest above. Level of interest: An article of importance in its field Quality of written English: Acceptable Statistical review: No, the manuscript does not need to be seen by a statistician.