Serum electrolyte imbalance in severely malnourished children at hospitals in North-central Ethiopia

doi:10.21203/rs.3.rs-3008642/v1

Background – Severe acute malnutrition (SAM) raises the risk of death and disability associated with diarrhea owing to electrolyte depletion. Children with SAM have severely disrupted physiology and metabolism, and if vigorous refeeding begins before metabolic and electrolyte imbalances have been resolved, fatality rates are significant. No study has been conducted in Ethiopia on this topic, so this study was aimed at assessing electrolyte imbalance and its associated factors in under-5 children with severe acute malnutrition.

Methods – Hospital-based case control study was conducted at south Gondar Hospitals from October to December, 2021. Children under-went physical examination and had blood drawn for serum glucose, hemoglobin and electrolytes investigation. A semi-structured questionnaire consisting socio-demographic, clinical and personal variable as well as associated factors for electrolyte imbalance was applied. Both bi-variable and multivariable binary logistic regression analyses was performed. Both bi-variable and multivariable logistic regression were done. We performed crude odds ratio and adjusted odds ratio at 95% CI. In the final model, variables with a p-value < 0.05 was declared as statistically significant.

Result – We enrolled 232 children (116 cases and 116 controls). The mean age was 38.0 (SD±12.8) for cases and 37.1 (SD±13.1) for controls respectively. Sixty-one (52.6%) cases and 66 (56.9%) controls were female participants respectively. Hypokalemia [26.7%,16.4%]) and hyponatremia [25%, 14.7%] were frequently seen among cases and controls respectively. Death was recorded in 11 (9.5%) of cases. Edema (AOR=2.3; 1.4-4.7), not-vaccinated (AOR=1.2; 0.3-2.4) and diarrhea (AOR: 3.02; 1.09–8.63) were significantly associated with electrolyte derangement.

Conclusion: Electrolyte derangements, specifically hypokalemia and hyponatremia, were common in malnourished children. Having edema, not being fully vaccinated, and diarrhea were independent determinants of electrolyte derangement in malnourished children. Electrolyte levels should be measured in all severely malnourished cases to detect asymptomatic electrolyte imbalance.

electrolyte imbalance

edema

diarrhea

severe acute malnutrition

associated factors

Malnutrition involves an imbalance between the availability of nutrients and energy and their requirements by the body for normal growth and body tissue functions (1,2). Protein energy malnutrition (PEM) is one of the significant public health concerns that contributes to the global burden of children’s diseases, affecting 50 to 150 million children under the age of five worldwide. Severe acute malnutrition (SAM) in children under five is defined by the following three anthropometric parameters: Weight-for-height/length ratio < 70% of median or less than – 3 z - score, by MUAC < 115 mm with Length > 65 cm and/or by the presence of bilateral pitting edema with medical complications or a fail in the appetite test (3,4).

Children with SAM have profoundly disturbed physiology and metabolism, such that if intensive refeeding is started before metabolic and electrolyte imbalances have been corrected, mortality rates are high (5). An electrolyte is a substance in the bloodstream that regulates important body functions. Of these, potassium, magnesium, sodium, phosphorous, and calcium are the most abundant. Muscles, organs (e.g., the heart), and organ systems (e.g., the nervous system) are disrupted without electrolytes. After a blood drowning, if the levels are too high or too low, it's called an electrolyte imbalance (6). Potassium and magnesium are the electrolyte deficiencies seen in all SAM children, particularly severely ill children, and can take 2-6 weeks to rectify. Edema develops in children as a result of potassium insufficiency and sodium retention. There is extra body sodium, as opposed to serum sodium, and delivering sodium doses without strict follow-up kills the youngsters (4). Hence, electrolyte loss has been considered a better predictor of poor outcome in patients with SAM than other features of severity (7).

Globally, an estimated nearly 20 million children under the age of five suffer from SAM at any one point in time (8,9),and majority of them are from African and South-East Asia (10). Children with SAM often have electrolyte imbalances. When electrolyte imbalance is also accompanied by diarrhea and supplies are not replaced promptly, the fatality rate increases (11,12). Children who are malnourished and edematous have excess body sodium despite having low serum sodium levels, which covers the salt overload (4). In contrast to body sodium, vital electrolytes like potassium (K), calcium (Ca), and magnesium (Mg) are depleted, even at normal serum levels (12,13).

Malnutrition is a significant factor in almost one-third of the nearly 8 million deaths among children under the age of 5 (14). By 2018 alone, 5.3 million children under the age of 5 died, and 45% of the children's deaths were attributed to nutrition-related factors (2). A meta-analysis study in low and middle-income settings among admitted cases for treatment of complicated SAM revealed a 14% (range 5–30%) case fatality rate (15). In another study, the fatality rate fell between 30 and 50%, and it could be substantially reduced when physiological and metabolic changes were taken into account (5).

Severe malnutrition not only increases morbidity and mortality, but it can also affect physical growth as well as psychological and intellectual development, such as delayed motor skill acquisition and brain development (16). These outcomes can have severe consequences in later life, such as significant functional impairment that can affect a person’s economic productivity (17). The prevalence of hyponatremia and hypokalemia in Pakistan (31.1%, 61.1%), Multan (22.6%, 13.7%), Bangladesh (52%, 46%), Congo (79.2%, 66.7%), Bahawalpur (10%, 24%) and India (31,57%, 51%), (18–23) respectively. Hypocalcemia also present in Pakistan (13.3%)(11), Bangladesh (35.4%) (13), India (28%)(24) and Nepal (46.7%) (25). Factors such as diarrhea (13,18,26–28), age <12 month(29), Sex (12), parents’ educational status (12) were associated factors for electrolyte derangements.

In low- and middle-income countries, poverty and poor health services are responsible for the deaths of millions of people yearly, particularly children due to malnutrition (30). Some electrolyte abnormalities caused by SAM are exacerbated by a lack of meals. The consequences can be severe, leading to a multi-organ failure syndrome or even death. As a result, it is beneficial to understand the physio-pathological characteristics of this illness in order to prevent its start as early as possible and thereby lower the associated catastrophic risk (31).

Although there are limited studies across the globe on electrolyte imbalance in children with SAM, there is no local study regarding this topic. Therefore, the intent of this study was to examine electrolyte derangement in severely malnourished children admitted to hospitals.

2.1 Study Area and setting

This study was conducted in south Gondar zone hospitals. South Gondar Zone is one of the administrative zones in Amhara region, Ethiopia. The zone has 15 districts and five administrative cities. Debre tabor is the capital city of the zone situated about 667 km North of Addis Ababa (the capital city of Ethiopia). In south Gondar zone, there are 8 hospitals (one specialized and 7 districts) which serves for 2,484,929 populations reside in the zone (CSA-2017/18), of which 183, 525 are under age 5. The study was conducted from October to December 2021.

2.2 Study design

Hospital based case control study was employed in under 5 children with SAM

3.3 Population

3.3.1 Source population

Source populations were All 12 up to 60 months’ children with SAM visiting south Gondar hospitals

3.3.2 Study population

All 12 up to 60 months’ children with SAM who was admitted in hospitals and matched (similar sex and age) controls were study population

3.4 Eligibility criteria

3.4.1 Inclusion criteria

All 12 up to 60 months’ children with SAM who were admitted in hospitals and matched controls on the same day during data collection period

3.4.2 Exclusion criteria

Those admitted children with SAM who were below 6month of age, severely ill and who had incomplete electrolyte result were excluded from the study

4. Study variables

4.3.1 Dependent variable

Electrolyte imbalance

4.3.2 Independent variables

Socio-demographic and personal characteristics: child (age, sex, residence) care givers/ parents (educational level) and family size

Behavioral and clinical: co-morbidities (diarrhea, vomiting, pneumonia, Vit-A deficiency), edema, outcome, medical history (including SAM), hospitalization, vaccination and maternal education

Anthropometric: MUAC (#)

5. Sample size determination and sampling technique

5.3.1. Sample size determination

Sample size was determined using a double population proportion formula by considering the following assumptions: Proportion for cases(P1) =61.2% and P2 for controls (33%) (23) (previous international study on similar topic), 95% confidence interval, power=80%, ratio of cases to control=1:1. Then using Epi info 7.2.2.6, the total calculated sample size of 110. In consideration of 5% non-response rate the sample size adjusted to be 116. As the ratio of cases to controls was one to one, similar number of controls were recruited in the study and the total sample size recalculated to 232.

5.3.2 Sampling procedure

Selection of hospitals: From a total of 8 hospitals found in south Gondar zone, three hospitals, namely Debe Tabor specialized hospital, Nefas Mewucha hospital and Mekane Eyesus hospital were selected randomly using lottery methods. The sample size propositional allocation for the studied hospitals was made.
Selection of cases: The cases were SAM children with electrolyte imbalance. The data collection process had taken until the required sample size achieved.
Selection of control; OPD attendee in the same facility with age less than 5 (age and sex matched with a respective case) were selected randomly when they came to the hospitals for different services like immunization, growth monitoring program, and/or clinical services. If the children’s caretaker refused to be involved in the study, the next eligible clinic attendee had attempted. The controls were screened by health worker assigned in under-5 OPD and exclude them from OTP.

5.4 Operational definitions

Cases: 12 up to 60 months’ children who have electrolyte imbalance
Controls: 12 up to 60 months’ children without electrolyte imbalance
Electrolyte imbalance: after blood withdrawal taken, and analysis implies either too high or too low levels (32). These were: -
- Hyponatremia – [Na+] <135 mEq/L
- Hypernatremia – [Na+] >146 mEq/L
- Hypokalemia – [ K] < 3.5 mmol/L.
- Hyperkalemia – [ K⁺] >5.8 mmol/L.
Anemia: Hemoglobin <11g/dl
Hypoglycemia: blood sugar < 60mg/dl
Fully vaccinated: when a child received one dose of BCG, three dose of pentavalent and polio, two dose of rotavirus, three dose of PCV and one dose of MCV1. If one of it is missed, he/she is not fully vaccinated.

Data collection procedure and tools

In line with Ethiopian SAM management protocols, SAM children without comorbidities and with good appetite would be linked to the outpatient management program. All SAM children with co-morbidities and poor appetite would be admitted to the SAM inpatient management program and were our study participants. Care-takers were interviewed using semi-structured questionnaires to collect socio-demographic and clinical information. Children under five underwent physical examination and blood drawn for serum electrolytes investigation. Blood drown had taken by laboratory experts and sent for analysis. Children’s inpatient registry book which contained the admission, patient history and discharge information was used as the main data source. Regarding the controls, matched (similar age and sex) children was recruited, and their care givers was interviewed.

Data processing and statistical analysis

After completing the data collection process, it was entered into Epi info version 7 by the researcher, then exported into STATA-14 for analysis. Data completeness, consistency and outliers was checked. Skewness was described by median and interquartile range while frequency with percent and mean with standard deviation was performed to describe categorical and continuous variables respectively. A two-by-two table for cases and controls was construct and compute odds ratio to determine strength of association. Bi-variable logistic regression analysis had performed to select potential candidate variables for the final model with cut-off point p-value ≤ 0.25. Model fitness was checked by Hosmer and Lemeshow goodness of fit test. Multivariable logistic regression analysis was done to estimate the independent effect of determinant factors on electrolyte imbalance. In the final model, variables with p-value < 0.05 was considered as statistically significant.

4.1 Socio-demographic and personal characteristics of participants

A total of 232 participants (116 cases and 116 controls) were included in the study. The mean age was 38 years (SD±12.8) for cases and 37.1 (SD±13.1) for controls respectively. More than half of the children 61 (52.6%) and 66(56.9%) were female for cases and controls respectively. Over four-fifth of cases 106 (91.4%) and controls 99 (85.3%) had primary and above educational background. Majority of parents’/care givers 82(70.7%) and 81(69.8%) had four and above family size for cases and controls respectively. The mean (±SD) MUAC of cases was 9.8(0.7%) and 11.2(0.7%) for controls (Table 1).

Table 1. Socio-demographic and personal characteristics of children with electrolyte imbalance.

Variables	Categories	Cases (n=116)	Controls (n=116)
Variables	Categories	N%	N%
Age (months)	12-23	21(18.1)	21(18.1)
	24-35	27(23.3)	33(28.4)
	36-47	32(27.6)	29(25.0)
	48-60	36(31.0)	33(28.4)
Sex	Male	55(47.4)	50(43.1)
Sex	Female	61(52.6)	66(56.9)
Residence	Urban	110(94.8)	105(90.5)
Residence	Rural	6(5.2)	11(9.5)
Educational status of parents/care givers	No formal education	10(8.6)	17(14.7)
Educational status of parents/care givers	Primary and above	106(91.4)	99(85.3)
Family size	<4	34(29.3)	35(30.2)
Family size	≥4	82(70.7)	81(69.8)
MUAC mean (±SD)		9.8(0.7)	11.2(0.7)

4.2 Behavioral and clinical characteristics of participants

In this study, seventy-seven (66.4%) cases and ninety-five (81.9%) controls were fully vaccinated. Nearly half 48(41.4%) of cases were edematous while all of controls were non-edematous. Forty-eight (41.4%) cases and 16(13.8%) controls had diarrhea. More than quarter 33(28.4%) and 28(24.1%) of cases and controls were anemic respectively. Hypoglycemia is prevalent in 30(25.9%) of cases and 11(9.5%) of controls. The prevalence of at least one type of electrolyte derangement was 59.5% and 33.6% for cases and controls respectively. Specifically, the most frequent electrolyte derangement for cases was hypokalemia 31(26.7%) and hyponatremia 29(25%). Similarly, 19(16.4%) and 17(14.7%) of controls had hypokalemia and hyponatremia respectively. Death was recorded in 11 (9.5%) of cases while none of the controls died (Table 2).

Table 2. Behavioral and clinical characteristics of children with electrolyte imbalance

Variables	Categories	Cases (n=116)	Controls (n=116)
Variables	Categories	N%	N%
History of similar attack	Yes	22(19.0)	10(8.6)
History of similar attack	No	94(81.0)	106(91.4)
Vaccination status	Fully vaccinated	77(66.4)	95(81.9)
Vaccination status	Not fully vaccinated	39(33.6)	21(18.1)
Edema	Yes	48(41.4)	0(0.0)
Edema	No	68(58.6)	116(100.0)
Comorbidities	Pneumonia	25(21.6)	9(7.8)
	Diarrhea	48(41.4)	16(13.8)
	Vit-A deficiency	26(22.4)	0(0.0)
	None	17(14.7)	91(78.4)
Anemia	Yes	33(28.4)	28(24.1)
Anemia	No	83(71.6)	88(75.9)
Hypoglycemia	Yes	30(25.9)	11(9.5)
Hypoglycemia	No	86(74.1)	105(90.5)
Hyponatremia	Yes	29(25.0)	17(14.7)
Hyponatremia	No	87(75.0)	99(85.3)
Hypernatremia	Yes	13(11.2)	9(7.8)
Hypernatremia	No	103(88.8)	107(92.2)
Hypokalemia	Yes	31(26.7)	19(16.4)
Hypokalemia	No	85(73.3)	97(83.6)
Hospitalization stay	>3 days	88(75.9)	5(4.3)
	2-3 days	17(14.6)	10(8.6)
	<2 days	11(9.5)	10(8.6)
	Not admitted	0(0.0)	91(78.5)
Out come	Death	11(9.5)	0(0.0)
Out come	Discharge	111(95.7)	116(100.0)

According to table 3, there is significant difference between edematous and non-edematous children in baseline characteristics and electrolyte derangements. Accordingly, nearly half 20(41.7%) of edematous cases were found between the age 48 and 60 months. likewise, more than half 38(55.8%) non edematous controls were found between the age 24 and 47 months. Females were victims of being edematous 25(52.1%) and non-edematous 36(53.0%). Hypokalemia was the common electrolyte imbalance in 23(47.9%) of edematous children while 24(35.3%) of non-edematous children had hyponatremia. The mean (±SD) of MUAC for edematous children was 9.78(0.7) and 9.81(0.8) for non-edematous children.

Table 3. Comparison of edematous and non-edematous children with SAM.

Variable		Edematous (n=48)	Non-edematous (n=68)
Age (months)	12-23	7(14.6%)	14(20.7%)
	24-35	8(16.7%)	19(27.9%)
	36-47	13(27.0%)	19(27.9%)
	48-60	20(41.7%)	16(23.5%)
Sex	Male	23(47.9%)	32(47.0%)
Sex	Female	25(52.1%)	36(53.0%)
MUAC mean (±SD)		9.78(0.7)	9.81(0.8)
Hyponatremia	Yes	5(10.4%)	24(35.3%)
Hyponatremia	No	43(89.6%)	44(64.7%)
Hypernatremia	Yes	10(20.8%)	3(4.4%)
Hypernatremia	No	38(79.2%)	65(95.6%)
Hypokalemia	Yes	23(47.9%)	8(11.8%)
Hypokalemia	No	25(52.1%)	60(88.2%)

Determinants of electrolyte imbalance in severe malnourished children

Both bivariable and multivariable logistic regression was done to identify associated variables for electrolyte derangement. From bivariable logistic regression, factors such as age, residence, edema, vaccination history, comorbidities, hospitalization and children’s MUAC had p-value≤ 0.25 and were potential variable for multiple logistic regression. In the final model, the presence of edema, not fully vaccinated children, and diarrhea were significantly associated variables with electrolyte imbalance in malnourished children (Table 4).

Table 4. Bivariable and multivariable association of electrolyte derangement and independent factors among severely malnourished children

Variables		Cases	Controls	COR (95%CI)	AOR (95%CI)
Age	12-23	21(18.1)	21(18.1)	1.1(0.4, 3.3)	1.2(0.3, 4.7)
	24-35	27(23.3)	33(28.4)	1.9(0.7, 5.2)	1.1(0.3, 3.5)
	36-47	32(27.6)	29(25.0)	2.0(0.8, 5.3)	0.9(0.2, 4.0)
	48-60	36(31.0)	33(28.4)	1	1
Residence	Rural	6(5.2)	11(9.5)	1.3(0.2, 4.1)	1.2(0.1, 3.4)
Residence	Urban	110(94.8)	105(90.5)	1	1
Edema	Yes	48(41.4)	0(0.0)	0.5(0.2, 1.1)	2.3(1.4, 4.7)*
Edema	No	68(58.6)	116(100)	1	1
Vaccination history	Not fully vaccinated	39(33.6)	21(18.1)	1.3(0.4, 1.7)	1.2(0.3, 2.4)*
Vaccination history	Fully vaccinated	77(66.4)	95(81.9)	1	1
Comorbidities	Pneumonia	25(21.6)	9(7.8)	1.2(0.7, 4.2)	1.4(0.9, 6.2)
	Diarrhea	48(41.4)	16(13.8)	2.5(1.1, 6.3)	1.9(0.8, 10.0)*
	Vit-A deficiency	26(22.4)	0(0.0)	1.3(0.9, 3.4)	1.0(0.4, 5.6)
	None	17(14.7)	91(78.4)	1	1
Hospitalization stay	<2 days	11(9.5)	10(8.6)	1.3(0.4, 4.6)	1.2(0.3, 6.2)
	2-3 days	17(14.6)	10(8.6)	1.4(0.5, 4.0)	1.7(0.4, 6.5)
	>3 days	88(75.9)	5(4.3)	1	1
MUAC mean (±SD)		9.78(0.7)	9.81(0.8)	0.8(0.5, 1.4)	0.7(0.4, 1.4)

Child mortality is still escalating in low- and middle-income countries where poverty and poor health services are responsible for the deaths of millions of children yearly, and malnutrition is one of the causes of child mortality. Some electrolyte disturbances accompany malnutrition. The increasing number of child deaths in health institutions is a significant indicator of the quality of health care services (postnatal, nutritional, medical, and general health services quality). This study was intended to explain the electrolyte profile of severely malnourished children admitted to hospitals in north-central Ethiopia.

In the current study, the prevalence of at least one electrolyte derangement was 59.5% and 33.6% for cases and controls respectively. Hypokalemia was frequently seen in 26.7%, hypernatremia 11.2% and hyponatremia 25% of severely malnourished children. The frequency of hyponatremia is consistent with Multan, Pakistan (28%) (24), Iran (23.6%) (33), and India (27.4%) (34) while that of hypokalemia is comparable with Bahawalpur, Pakistan (26.9%) (22), and Multan, Pakistan (23%) (24). However, the prevalence of hypokalemia (26.7%) in the current finding is lower than studies in Bangladesh (46±0.84%) (20), Democratic Republic of the Congo (66.7%) (21), and India (51%) (23) but it is higher than Iran (13%) (33), and India (13.9%) (34) . On the other hand, hyponatremia (25%) in the current study is lower than studies in Bangladesh (52±0.55%) (20), Congo (79.2%) (21), and India (31.57%) (23) but higher than studies in Bahawalpur, Pakistan (10.4%) (22).

In the current study factors such as edema, vaccination history and diarrhea were significantly associated with electrolyte derangement.

The likelihood of electrolyte imbalance for edematous children was 2.3 times (AOR=2.3; 1.4-4.7) higher relative to non-edematous children, which is in line with Democratic Republic of the Congo (21). The probable reason is that there was a relative excess of water in comparison to salts during edema, resulting in extracellular hyper-hydration. This circumstance appeared to emphasize the significance of edema in confiscating water and salt in the extracellular fluid(ECF) (hypernatremia) (35). Indeed, children with edema prone to have additional comorbidities such as diarrhea, pneumonia, anemia and sepsis that accelerate electrolyte derangement, dehydration, shock, and metabolic acidosis, which subsequently increases the risk of mortality (36).

The odds of electrolyte derangement were 1.2 times higher (AOR=1.2; 0.3-2.4) in children with incomplete vaccination history compared to their counterparts. This is probably due to incomplete immunizations increased the prevalence of all types of malnutrition associated with reduced immunity, infection, and diarrhea (37).

Those children with diarrhea had 1.9 times (AOR: 3.02; 1.09–8.63) risk of acquiring electrolyte derangement as compared to those children without diarrhea. This is in line with Bangladesh (20), Bahawalpur, Pakistan (22), India (23), Multan, Pakistan (24), and Iran (13%) (33). This is because diarrhea induces hypokalemia as a result of potassium leakage into ECF (38). Children with chronic and persistent diarrhea causes profound malnutrition that leads to lowering immunity and recurrent infection. Moreover, managing severely dehydrating malnourished children in resource limited setting is the most difficult lifesaving issue (39).

This study was not free from limitation and its major shortcoming was sample size. Since we used smaller sample size, generalization might not be ideal for the entire populations. Recall bias is the expected limitation.

In malnourished children, electrolyte imbalances, notably hypokalemia and hyponatremia, were prevalent. Edema, not being fully immunized, and diarrhea were all independent predictors of electrolyte imbalance in malnourished children. Electrolyte levels should be checked in all severely malnourished patients to detect asymptomatic electrolyte imbalances that could lead to a life-threatening incident. It is strongly advised to adapt current childhood illness treatment protocols and to provide health professionals with relevant intervention skills. Furthermore, pediatric fluid regimes should be optimal for the critically unwell child with impaired sodium, glucose, and fluid homoeostasis.

MUAC; Middle Upper Aram Circumference, Na; Sodium, OPD; Outpatient department, OTP; Oral Therapeutics, PEM; Protein energy malnutrition, SAM; Severe Acute Malnutrition, SD; Standard Deviation

Ethics approval and consent to participate

The study was conducted after getting ethical clearance letter from the ethical review committee of Debre Tabor University (Ref No. CHS/3215/21). The study was consistent with Helsinki’s declaration. The actual data was collected after obtaining permission from study Hospitals. Informed consent was obtained from each care givers or parents after explaining the purpose of the study. The name of the study participants was not recorded for the assurance of confidentiality.

Consent for publication

Not applicable

Availability of data and materials

In addition to the data and materials described in the manuscript, someone can get the dataset from the corresponding author (MAS) upon rational request.

Competing interests

No conflict of interest to disclose

Funding

Authors didn’t receive any fund.

Author Contributions

All authors made a significant contribution to the whole work of this paper, starting with the conception, study design, execution, acquisition of data, analysis, and interpretation. Similarly, all authors were involved in drafting, revising, or critically reviewing the article; they gave final approval of the version to be published. All authors agreed to the journal to which the article was submitted and agreed to be responsible for all aspects of the work.

Acknowledgements

The authors would like to acknowledge the Debre Tabor University, selected hospitals and study participants.

unicef. Children, food and nutrition [Internet]. 2019. Available from: 2019.
World Health Organisation. Key fact sheets. 2021;(9 June). Available from: https://www.who.int/news-room/fact-sheets/detail/malnutrition.
Golden PM, et al. Protocol for the management of severe acute malnutrition. Addis Ababa; 2007.
WHO. Guidelines for the management of common childhood illnesses. [Internet]. 20 Avenue Appia, 1211 Geneva 27, Switzerland. ; 2013. Available from: .
WHO. Updates on the management of severe acute malnutrition in infants and children. World Heal Organ [Internet]. 2013;10–23. Available from: www.who.int.
Anderson M. Electrolyte Imbalance. Cooper. 2016.
Maitland K, Berkley JA, Shebbe M, Peshu N, English M, Newton CRJC. Children with Severe Malnutrition: Can Those at Highest Risk of Death Be Identified with the WHO Protocol ? PLoS ONE. 2006;3(12):1–10.
State THE, The OF. Executive summary Children in an Urban World [Internet]. 2012. Available from: https://www.unicef.org/publications/index_61789.html.
WHO/WFP/UNSSCN/UNCF. Community-based management of severe acute malnutrition. 2007.
UNICEF/WHO/World Bank Group. Levels and trends in child malnutrition. 2019.
Zulqarnain DA, Dr. Zeeshan Jaffar DII. Malnourished children with diarrhea. Prof Med J [Internet]. 2015;22(5):610–4. Available from: www.theprofesional.com.
Raza M, Kumar S, Ejaz M, Azim D, Azizullah S, Hussain A. Electrolyte Imbalance in Children With Severe Acute Malnutrition at a Tertiary Care Hospital in Pakistan: A Cross-Sectional Study. Cureus. 2020;12(9):1–6.
Chisti MJ, Salam MA, Ashraf H, Faruque ASG, Bardhan PK, Shahid ASMSB, et al. Prevalence, Clinical Predictors, and Outcome of Hypocalcaemia in Severely-malnourished Under- five Children Admitted to an Urban Hospital in Bangladesh : A Case-Control Study. J Heal Popul nutr. 2014;32(2):270–5.
Black RE, Victora CG, Walker SP, Bhutta ZA, Christian P, Onis M, De et al. Maternal and Child Nutrition 1. Maternal and child undernutrition and overweight in low-income and middle-income countries. Series [Internet]. 2013;382(August 3). Available from: .
Gebremichael DY. Predictors of nutritional recovery time and survival status among children with severe acute malnutrition who have been managed in therapeutic feeding centers, Southern Ethiopia : retrospective cohort study. BMC Public Health [Internet]. 2015;1–11. Available from: http://dx.doi.org/10.1186/s12889-015-2593-5.
Id TN, Id DA, Rachel L, Byonanebye JE. Predictors of in-hospital mortality among under-five children with severe acute malnutrition in South-Western Uganda. PLoS One [Internet]. 2020;(June 26):1–15. Available from: http://dx.doi.org/10.1371/journal.pone.0234343.
USAID FTA, Ethiopia. Nutrition Profile. 2018;(February):1–7.
Bilal A, Sadiq MA, Haider N. Frequency of hyponatraemia and hypokalaemia in malnourished children with. JPMA. 2016;66(9):1077–80.
Sameen I, Moorani KN. Morbidity patterns of severely malnourished children at tertiary care hospital. ResearchGate. 2016;38(March):1–9.
Article R. Effect of Protein Energy Malnutrition on the Diarrheal Electrolyte Imbalance in Children of Chittagong Region, Bangladesh. Indian J Nutr. 2014;1(1):1–5.
Maguy BL, Pierre MM, Lou Z, Michel EB. Journal of Nutritional Disorders & Electrolyte and Acid-Base Balance (Sodium, Potassium, and pH) during Severe Acute Malnutrition in Children under 5 Years Old in the Democratic Republic of the Congo. J Nutr Disord Ther. 2018;8(3):8–11.
Fatima B, Sheikh MA, Naeem MM. The Serum Sodium, Potassium and Calcium Levels in Children 6–59 Months of Age with Severe Acute Malnutrition. P J M H S. 2017;11(1):292–4.
Gangaraj S, Das G, Madhulata S. Electrolytes and Blood Sugar Changes in Severely Acute malnourished Children and Its Association With Diarrhoea and Vomiting. Int J Pharm Sci Invent. 2013;2(5):33–6.
Khan S, Rubab Z, Ali I, Arshad R, Abbas A, Akhtar E. The Serum Electrolyte Imbalance in Children with Severe Acute Malnutrition. JIIMC. 2021;16(1):10–3.
Article O. Biochemical nutritional indicators in children with protein energy malnutrition attending Kanti Children Hospital, Kathmandu, Nepal. Kathmandu Univ Med J. 2009;7(2):129–34.
Karasek M, Winczyk K, Diseases M. Mela tonin in humans 1. Pharmacology. 2006;19–39.
Rangasamy S, Mcguire PG, Das A. Review Article Diabetic Retinopathy and Inflammation: Novel Therapeutic Targets. Middle East Afr J Ophthalmol [Internet]. 2012;19(1):52–9. Available from: http://www.meajo.org.
Bernal ÃC, Vela C, Alcaraz G, Botero ÃJ. Treatment of Severe Malnutrition in Children: Experience in Implementing the World Health Organization Guidelines in Turbo, Colombia. J Pediatr Gastroenterol Nutr. 2008;46(March):322–8.
Okposio MM, Onyiriuka AN, Abhulimhen-iyoha BI. Point-of-Admission Serum Electrolyte Profile of Children less than Five Years Old with Dehydration due to Acute Diarrhoea. Trop Med Health. 2015;43(4):247–52.
Morris N, Stewart S, Morris NF, Stewart S, Riley MD, Maguire GP. The burden and nature of malnutrition among patients in regional hospital settings: A cross-sectional survey Clinical Nutrition ESPEN The burden and nature of malnutrition among patients in regional hospital settings : A cross-sectional survey. Clin Nutr ESPEN [Internet]. 2017;(January 2018). Available from: https://doi.org/10.1016/j.clnesp.2017.12.010.
Power L, Mullally D, Gibney ER, Clarke M, Visser M, Volkert D et al. A review of the validity of malnutrition screening tools used in older adults in community and healthcare settings - A MaNuEL study. Clin Nutr ESPEN [Internet]. 2018;24:1–13. Available from: https://doi.org/10.1016/j.clnesp.2018.02.005.
Taylor RB, Nasir LS. Family Medicine. 7th, editor. ed. Switzerland; 2017. pp. 1234–38.
Mosav F, Malekzdeh IMM. Incidence and type of electrolyte abnormalities Iranian children with acute gastroenteritis. Open J Pediatr Child Heal [Internet]. 2020;5:11–5. Available from: https://dx.doi.org/10.17352/ojpch.000024.
Panda I, Save S. Study of association of mortality with electrolyte abnormalities in children admitted in pediatric intensive care unit. Int J Contemp Pediatr. 2018;5(3):1097–103.
Benvenuti S, Deledda C, Luciani P, Modi G, Bossio A, Giuliani C, et al. Low extracellular sodium causes neuronal distress independently of reduced osmolality in an experimental model of chronic hyponatremia. NeuroMolecular Med. 2013;15(3):493–503.
Kumar D, Rao SK, Singh TB. Clinico – biochemical profile of sick children with severe acute malnutrition. J Fam Med Prim Care. 2020;2269–72.
National Association of Resident Doctors of Nigeria. Nigerian J Med Med J. 2015;24(1):17–27.
Abdel-Aziz EZ, Elfeky HAA, AboSeda AI. (2019). Electrolytes Imbalance Among Patients With Oncologic Emergencies At a University Hospital. Int Acad J Heal Med Nurs [Internet]. 2019;1(2):58–83. Available from: https://www.researchgate.net/publication/348607323.
Bwanaisa LL, Heyderman RS, Molyneux EM. The challenges of managing severe dehydrating diarrhoea in a resource-limited setting. Int Health [Internet]. 2011;3(3):147–53. Available from: http://dx.doi.org/10.1016/j.inhe.2011.03.007.

No competing interests reported.

Serum electrolyte imbalance in severely malnourished children at hospitals in North-central Ethiopia

Status:

Version 1

Abstract

Introduction

Methods and materials

Results

Discussion

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Status:

Version 1