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. 2024 Oct 10;16(10):e71208.
doi: 10.7759/cureus.71208. eCollection 2024 Oct.

Sodium and Hematocrit Levels' Correlation and Clinical Impacts in Jordanian Hemodialysis Patients

Mahmoud H Al Hindawi  1 , Muhannad M Asi  2 , Mohammad A Obeidat  2 , Mousa Atmeh  3 , Thaer J Al Kasasbeh  2
Affiliations

Sodium and Hematocrit Levels' Correlation and Clinical Impacts in Jordanian Hemodialysis Patients

Mahmoud H Al Hindawi et al. Cureus. .

Abstract

Aim: Given cofounders, this retrospective study investigates the correlation between hyponatremia status and hematocrit (Hct) changes, as well as the clinical utility of these two prognosticators in relation to overall health status.

Methods: The study was retrospectively conducted on adult hemodialysis (HD) patients at the King Hussein Medical Center in Amman, Jordan, from 2015 to 2022. It looked at how sodium (Na) levels, the hematocrit-to-hemoglobin ratio (HHR), and outcomes of interest were related. The study examined acute myocardial infarction, stroke, refractory hypertension, dialysis graft thrombosis, and all-cause mortality as the composite outcomes of interest (cOI). We conducted a series of receiver operating characteristics, binary logistic regression (BLgR), and sensitivity analyses between each tested prognosticator and the cOI. We constructed and illustrated a multiple logistic regression (MLgR) model to investigate the adjusted association of each prognosticator against the tested composite outcome probability.

Results: The majority of HD patients were hemolyzed for a period of four to seven years. The constructed binary regression modeling for each prognosticator was [e (109.36 - 0.849 × Na)/[1 + e (109.36 - 0.849 × Na)] and [e (16.033 - 6.388 × HHR)/[1 + e (16.033 - 6.388 ×HHR)], with a 35.57% probability of cOI at the optimal Na of 129.51 mEq/l and a 42.8% at optimal HHR of 2.555:1. When the length of hemodialysis (LOD) was introduced into the MLgR modeling all the investigated independent variables were significant except the HHR (p-value = 0.908).

Conclusion: A higher LOD, lower Na, and lower HHR all support a positive cOI probability status. Regular inspection of Na and HHR and ensuring their closet to their optimal thresholds are mandatory to mitigate the risk of higher cOI probability.

Keywords: health care outcomes; hematocrit to hemoglobin ratio; hyponatraemia; intermittent hemodialysis (ihd); jordanian; optimal threshold.

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Conflict of interest statement

Human subjects: Consent was obtained or waived by all participants in this study. Jordanian Institutional Review Board of Royal Medical Services issued approval 17_10/2023. The Jordanian Royal Medical Services committee approved this manuscript for publication on November 13, 2023. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work.

Figures

Figure 1
Figure 1. The receiver operating characteristic (ROC) test for Na levels vs. probability of cOI positivity
Na: Sodium; cOI: composite outcomes of interest; ROC: receiver operating characteristic; SEM: standard error of mean; CI: confidence interval; *: statistically significant; AUROCs: area under the ROC curves The ROC test examined the AUROCs for Na levels against the cOI. Higher %Prob of cOI values indicate stronger positive evidence for our tested prognosticators. The lower values of the independent variables suggest a more negative state (higher %Prob of naïve cOI)
Figure 2
Figure 2. Receiver operating characteristic (ROC) test for HHR vs. probability of cOI positivity
HHR: Hematocrit-to-hemoglobin ratio; ROC: receiver operating characteristic; cOI: composite outcome of interest; AUROCs: area under the ROC curves; SEM: standard error of mean; *: statistically significant The ROC test examined the AUROCs for HHR against the cOI. Higher %Prob of cOI values indicate stronger positive evidence for our tested prognosticators. The lower values of the independent variables suggest a more negative state (higher %Prob of naïve cOI)
Figure 3
Figure 3. Binary logistic regression illustration for Na vs. probability for cOI positivity
Na: Sodium; cOI: composite outcomes of interest; BLgR: binary logistic regression; KHMC: King Hussein Medical Center; HDU: hemodialysis unit; RMS: Royal Medical Services The BLgR analyses contrasted the higher probability of cOI (positive state and assigned as 1) with the lower probability (negative state and assigned as 0 for Jordanian patients who received intermittent hemodialysis at the KHMC HDU on the RMS, Amman, Jordan, between 2015 and 2022
Figure 4
Figure 4. Binary logistic regression analysis for HHR vs. probability for cOI positivity
BLgR: Binary logistic regression; HHR: hematocrit-to-hemoglobin ratio; KHMC: King Hussein Medical Center; HDU: hemodialysis unit; RMS: Royal Medical Services; cOI: composite outcomes of interest The BLgR analyses contrasted the higher probability of cOI (positive state and assigned as 1) with the lower probability (negative state and assigned as 0 for Jordanian patients who received intermittent hemodialysis at the KHMC HDU on the RMS, Amman, Jordan, between 2015 and 2022
Figure 5
Figure 5. Multiple logistic regression illustration for both sodium states against probability for cOI positivity
MLgR: Multiple logistic regression; cOI: composite outcomes of interest; Na: sodium; KHMC: King Hussein Medical Center; HDU: hemodialysis unit; RMS: Royal Medical Services Our constructed MLgR analyses’ illustration for the hemodialysis patients’ Na level against the probabilities of occurring at least one of the predefind cOI (acute myocardial infarction, stroke, refractory hypertension, thrombosis of the dialysis graft, and all-cause mortality) in the Jordanian hemodialysis patient who conducted their intermittent hemodialysis, between 2015 and 2022, at the HDU of the KHMC on the RMS, Amman, Jordan
Figure 6
Figure 6. Multiple logistic regression illustration for both HHR states against probability for cOI positivity
MLgR: Multiple logistic regression; cOI: composite outcomes of interest; KHMC: King Hussein Medical Center; HDU: hemodialysis unit; RMS: Royal Medical Services; HHR: hematocrit-to-hemoglobin ratio Our constructed MLgR analyses’ illustration for the hemodialysis patients’ HHR  against the probabilities of occurring at least one of the predefined cOI (acute myocardial infarction, stroke, refractory hypertension, thrombosis of the dialysis graft, and all-cause mortality) in the Jordanian hemodialysis patient who conducted their intermittent hemodialysis, between 2015 and 2022, at the HDU of the KHMC on the RMS, Amman, Jordan
Figure 7
Figure 7. Multiple logistic regression illustration for the length of hemodialysis days against the probability for cOI positivity
MLgR: Multiple logistic regression; cOI: composite outcomes of interest; KHMC: King Hussein Medical Center; HDU: hemodialysis unit; RMS: Royal Medical Services; LOD: length of hemodialysis Our constructed MLgR analyses’ illustration for the hemodialysis patients’ LOD, against the probabilities of occurring at least one of the predefined cOI (acute myocardial infarction, stroke, refractory hypertension, thrombosis of the dialysis graft, and all-cause mortality) in the Jordanian hemodialysis patient who conducted their intermittent hemodialysis, between 2015 and 2022, at the HDU of the KHMC on the RMS, Amman, Jordan
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