Hematological profile of Diabetic Patients with and without chronic kidney

disease: A Case-Controlled Study in a Rural Tertiary Health Care Hospital

Introduction
Diabetes Mellitus (DM) is a group of metabolic diseases characterized by chronic
elevated blood glucose levels resulting from defects in insulin secretion and/or action.DM
can lead to various acute and chronic complications involving multiple organ systems
including cardiovascular, renal neurological, and ocular systems. DM is an essential global
burden, with considerable morbidity and mortality rates. The International Federation of
Diabetes (IDF) estimates that around 425 million worldwide suffer from this condition with
India having an estimated 17% of the cases. [1]
The leading causes of morbidity and mortality are the micro- and macro-vascular
complications due to complex mechanisms involving hyperglycemia, insulin resistance,
chronic inflammation, and atherogenesis. One of the micro-vascular complications- Diabetic
Chronic Kidney Disease (DCKD) also known as diabetic nephropathy is a progressive
disorder characterized by reduced renal function and albuminuria. DCKD is the most
common cause of end-stage kidney disease (ESKD) and thereby increases mortality [2]. The
criteria for CKD include:
 Decreased GFR; < 60 ml/min 1.73 m2
 Albuminuria; >30 mg/g and;
 Urine sedimentation abnormalities, persistent hematuria, electrolyte abnormalities due
to tubular disorders, abnormalities detected by histology/ structural imaging, and h/o
[3].
kidney transplantation However, the above markers may still be in the normal
range and are not helpful for those at risk of progression. [4]
The underlying pathogenesis in the development of DKD involves metabolic and
hemodynamic changes caused by prolonged hyperglycemia, hypertension, and dyslipidemia
which increases inflammation, endothelial damage, free radicle damage, and fibrosis all of
which result in hyperfiltration, hypertrophy, podocyte and glomerular membrane injury. [5]
Tubulointerstitial injury due to inflammation is associated with Neutrophil
[6]
extracellular traps (NETs) which play a pivotal role in the progression of DKD . NETs are
[7]
net-like structures consisting of DNA with histones along with antimicrobial proteins ,
which implies high levels of circulating neutrophils in DKD compared to their counterparts.
Studies have also found increased levels of circulating CD4+ T cells and monocytes. [8].
 [9]
Arkew M et al found the prevalence of anemia, lymphopenia, and neutrophilia
whereas Blériot C found monocytosis and lymphocytosis.[8]
Hematological abnormalities in diabetic patients, as well as in those with chronic
kidney disease, are common, but their relationship among them remains less clear. This study
has been undertaken to measure hematological profiles in people with diabetes with CKD and
without it, taken for this research, to be helpful further in seeking an answer to the
possibilities of difference involved.
Objectives
 To determine the hematological profile in diabetic patients with CKD
 To determine the hematological profile in diabetic patients without CKD
 To compare the hematological indices in patients with and without CKD and to
determine any significant difference in both groups.

Methodology
Study Design
This will be a cross-sectional, comparative study involving diabetic patients
with(DCKD) and without CKD (W/oCKD).
Sample Size
A minimum of 200 patients will be enrolled in each group (DCKD and W/oCKD),
ensuring adequate power to detect significant differences between groups.
Sampling method: Convenient sampling
Study Population
Criteria for subject selection:
 Inclusion Criteria:
o Adults (≥18 years) diagnosed with type 2 diabetes mellitus.
o Patients with a confirmed diagnosis of CKD (stages 1-5) for the DCKD group.
o Diabetic patients without CKD for the W/oCKD group.
 Exclusion Criteria:
o Patients with acute kidney injury.
o Patients with hematological disorders unrelated to diabetes or CKD.
o Pregnant women.
Informed written consent will be obtained from the participants and institutional
ethical committee (IEC) clearance will be obtained.
Data Collection:
Participants will undergo a comprehensive clinical evaluation, including:
 Medical history and demographic information.
 Assessment of renal function (serum creatinine, eGFR, urine albumin-to-creatinine
ratio).
 Complete blood count (CBC) including hemoglobin, hematocrit, red blood cell count,
white blood cell count, and platelet count.
 Additional hematological parameters (e.g., mean corpuscular volume, mean
corpuscular hemoglobin, reticulocyte count)
Definition of variables
Serum creatinine: As per KDIGO 2024 A normal serum creatinine level varies based on a
person's age, sex, and muscle mass:
Normal range:
 Men: 0.7–1.3 mg/dL (61.9–114.9 µmol/L)
 Women: 0.6–1.1 mg/dL (53–97.2 µmol/L)
 Children: Lower levels than both men and women
It is increased in CKD: >2 mg/dl
Estimated Glomerular filtration rate(eGFR): As per KDIGO,2024
Normal level:
 eGFR: > 90ml/min/1.73 m2
It is significantly reduced in CKD: < 60 ml/min 1.73 m2
Urine albumin-to-creatinine ratio (UACR): As per KDIGO, 2024
 UACR: <30 mg/g
It is elevated in CKD: >30 mg/g
CBC: Complete Blood Count (CBC)
Normal range:
 Red blood cell (RBC) count: 3.93 to 5.69 million/mm3
 Hemoglobin (Hgb, Hb): 12.6 to 17.5 g/dL for males; 12.0 to 16 g/dL for females
 Hematocrit (HCT): 38% to 47.7%
 White blood cell (WBC) count: 3,300 to 8,700 /mm3
 Platelet (PLT) count: 150,000 to 450,000 /mm3
 There are decreased levels of RBCs along with lower HCT and HB due to Anemia in
CKD can be caused by lower-than-normal levels of erythropoietin (EPO).
Data Analysis
 Comparative Analysis: Hematological parameters will be compared between the
DCKD and W/oCKD groups using t-tests or Mann-Whitney U tests for continuous
variables, and chi-square tests for categorical variables.
 Correlation Analysis: Pearson or Spearman correlation coefficients will be
calculated to assess the relationship between renal function parameters and
hematological indices.
 Multivariate Analysis:
Regression models will be used to identify independent predictors of hematological
changes, adjusting for potential confounders such as age, sex, duration of diabetes, and
comorbidities.
Implications
Those will form part of the literature that will increase the knowledge base on the
interplay among diabetes, CKD, and hematological health, yielding essential insights that
would maximize patient outcomes with customized therapeutic approaches and timely
interventions.
1. Clinical Practice: Defining specific hematological abnormalities in individuals with
diabetes and CKD might allow the development of new diagnostic tools and
monitoring protocols for early detection and better management of CKD in people
with diabetes.
2. Patient Management: Such differences in hematological profile could thus be utilized
in personalizing treatments to suit patients with diabetes and CKD, improving their
overall health outcome and quality of life.
3. Research and Development: The study may further research the underlying
pathophysiological mechanisms that may lead to changes in the hematological system
in patients with diabetes and CKD and could eventually open up new avenues for
discovering therapeutic targets.
4. Health Policy: A better communication of policies in healthcare targeting the
management and care for diabetic patients with CKD, therefore, should reduce a lot of
health burdens, and costs associated with it.
 5. It has immense educational value as the research contains valuable data in a medical
education setup, which is quite useful for training future health professionals while
training them on the nuances of treating diabetes and CKD

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