What Causes High Ammonia Levels In Adults – Background and aims: Hyperammonemia usually develops due to liver disease, but can occur in patients with non-hepatic hyperammonemia (NHH). But studies on the prognosis and possible risk factors for this disorder are lacking. The aim of this study was to find possible prognostic and risk factors for NHH in critically ill patients.

Methods: Data were extracted from the MIMIC III database. Survival was analyzed by the Kaplan-Meier method. Univariate and multivariate analyzes were performed to identify prognostic factors.

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Results: Valproic acid, carbamazepine, corticosteroids, recent orthopedic surgery, epilepsy, disorders of urea cycle metabolism and obesity were found to be risk factors for NHH. Patients in the hyperammonemia group had a higher 30-day mortality than those in the nonhyperammonemia group. After final regression analysis, ammonia was found to be an independent predictor of mortality.

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Conclusion: Ammonia was an independent prognostic predictor of 30-day mortality for critical care patients without liver disease.

Ammonia is the main metabolite of amino acids. Elevated levels of ammonia in the blood can cause encephalopathy (1). Hyperammonemia is most common in patients with acute liver failure or chronic liver disease, but can occur in patients without liver problems (2-4). Elevated blood ammonia levels without a history of liver disease are defined as non-hepatic hyperammonemia (NHH). NHH can be quite common in critically ill patients (up to 73% in a recent study) (5). NHH can occur in patients with a variety of serious conditions, such as intracranial hypertension (6) or congestive heart failure, malnutrition, infectious enterocolitis, or lung transplantation (7-11). Patients with severe heart disease and low serum ammonia levels have significantly lower mortality than patients with persistently high ammonia levels (12). In addition, the inflammatory response and multi-organ dysfunction in patients with sepsis are exacerbated by higher blood ammonia levels (13, 14). NHH prolongs intensive care unit (ICU) stay and is associated with higher mortality (6).

Past studies have mainly focused on hyperammonemia caused by liver disease. Clinically, hyperammonemia caused by a non-black disease can be ignored or misdiagnosed. There have been few studies with small samples and case reports of NHH (15). NHH is associated with organ failure, prolonged fasting, and urinary tract infections (16), but studies investigating prognostic or risk factors on this topic are scarce. The aim of this retrospective cohort study was to determine which risk factors are associated with the development of NHH after hospital admission in critical care patients.

Data from the MIMIC (Medical Information Mart for Intensive Care) critical care database (17) were used to conduct this study. Patients admitted to the Beth Israel Deaconess Medical Center ICU from 2001 to 2012 were enrolled (17). The project was approved by the institutional review boards of the Massachusetts Institute of Technology and Beth Israel Deaconess Medical Center; there was no requirement for individual patient consent as the project did not affect clinical care and all protected health information was identified. Raw data were extracted using Structured Query Language (SQL) with Navicat and further processed with R software. A blood ammonia level >35 μmol/L was defined as hyperammonemia in the MIMIC -III database. The MIMIC III database (version 1.4) is publicly available from https://mmic.physionet.org/.

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Establishment of the database was approved by the Massachusetts Institute of Technology (Cambridge, MA) and Beth Israel Deaconess Medical Center (Boston, MA) Institutional Review Boards. This work was performed according to the Code of Ethics of the World Medical Association (Declaration of Helsinki).

Inclusion criteria were as follows: patients (1) ≥18 and ≤89 years, (2) ICU admission time >24 hours, and (3) the record contained blood ammonia levels.

Exclusion criteria: (1) patients with acute and chronic liver diseases including: hepatitis, liver cirrhosis, hepatic encephalopathy, hepatorenal syndrome, liver injury or other chronic liver diseases were excluded using the International Classification of Diseases, Ninth revision (ICD-9) diagnosis codes at patient discharge (see Supplementary Material), (2) patients lacking vital signs or ICD 9 diagnosis code(s) were also excluded.

R statistical software (R Foundation for Statistical Computing, Vienna, Austria) was used to obtain patient information from the MIMIC III database. The following basic patient data were collected from each patient: age, gender, heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), respiratory rate (RR), and temperature (T). The following biochemical test results were also collected from each patient: alanine aminotransferase (ALT), aspartate aminotransferase (AST), partial thromboplastin time (PTT), international normalized ratio (INR), prothrombin time (PT), white blood cell count (WBC). ), hemoglobin, platelets, blood urea nitrogen (BUN), creatinine (Cr), and glucose. Simplified Acute Patient Physiology Score (SAPSII), Quick Sequential Organ Failure Assessment (qSOFA) score, Sequential Organ Failure Assessment (SOFA), Glasgow Coma Scale (GCS) were also recorded. Patients’ first care unit (ie, the type of ICU in which they were treated) was recorded based on data obtained during the first 24 hours of each patient’s stay: intensive care unit (ICU). Peak and trough sodium and potassium values ​​were taken during the first 24 hours of each patient’s ICU stay. The peak ammonia value was obtained during each patient’s ICU stay, and the worst scores and laboratory parameters as well as the mean value of vital signs during the first 24 hours of ICU admission were used in this study.

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Data distribution was tested using the Shapiro-Wilk test. Patient characteristics were described using median (P25, P75) (interquartile range [IQR]), or frequency and percentage, as appropriate. A non-parametric test (Mann-Whitney U test or Kruskal-Wallis test) was applied for data with non-normal distribution or heterogeneity of variances. Categorical data were compared using the Pearson Chi-square test, Kaplan-Meier curves were analyzed using log-rank tests. A Cox regression model was used to analyze the independent effects of different parameters on 30-day mortality. Statistical significance was defined as p < 0.05. All statistical analyzes were performed with R software (version 3.4.3).

A total of 1,051 patients were included in this study. Patients were divided into either a hyperammonemia group (n = 443) or a non-hyperammonemia group (n = 608). Variables with missing data are relatively common in the MIMIC III database. The percentage of missing values ​​for lactate (33.2%), albumin (45.6%), bilirubin (71.3%), pH (25.7%), SpO2 (27.2%) were significant, which were excluded from this study. The percentage of missing values ​​of PTT (11.23%), INR (10.6%), PT (10.6%), ALT (12.3), AST (12.3) were <13% and the rest included variables were <2%. We replaced all missing values ​​of the included variables by multiple imputation. The detailed data extraction process is shown in Figure 1 .

Baseline characteristics, vital signs, laboratory parameters, diagnoses, microbiology results, types of drugs used, surgeries performed, and patient outcomes are summarized in Table 1. Differences in age, sex, systolic blood pressure, INR, PT, and ammonia between the hyperammonemia group and the group without hyperammonemia were statistically significant. The incidence of obesity (8.8 vs. 4.8%) and orthopedic surgery (4.5 vs. 2.5%), corticosteroids (61.6 vs. 44.4%), carbamazepine (8.1 vs. 3.1%) , valproic acid (9.7 vs. 5.9%), epilepsy (19.0 vs. 10.9%), and urea cycle metabolism disorders (0.9 vs. 0.0%) were significantly higher in patients with hyperammonemia than in patients with non-hyperammonemia. In our cohort, ammonia levels showed no correlation with sepsis, gastrointestinal bleeding, intestinal infections, urinary tract infections, anemia, heart failure, renal failure, microbiological results, or surgery on other parts of the body.

Table 2 shows the results for the hyperammonemia and hyperammonemia groups. There were no significant differences in patients with delirium, encephalopathy, cerebral edema, coma, severity of illness scores, length of hospital or ICU stay. Patients in the nonhyperammonemia group had better outcomes (30-day mortality, 18.1 vs. 23.0%; renal replacement therapy, 4.8 vs. 7.4%) than the hyperammonemia group, but there were no significant differences in patient mortality 90 days or 1-year mortality (see Table 2, Supplementary Materials 2, 3 for more details).

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A survival analysis was performed to investigate the impact of ammonia on prognosis. Patients in the non-hepatic hyperammonemia group had better short-term survival (30-day mortality) rates (Figure 2). Furthermore, we performed univariate analysis of baseline variables (age, gender, primary care unit) and laboratory tests. Age, sex, ALT, AST, Cr, BUN, glucose, hemoglobin, platelets, PTT, INR, PT, WBC, sodium, potassium, and ammonia were analyzed in univariate analysis, and factors significantly correlated with overall survival were adjusted for in multivariate analysis. . According to our results, ammonia, age, hemoglobin remained independent prognostic factors for NHH patients (p < 0.01 or p < 0.05) (see Table 3).

Figure 2. Kaplan-Meier curves of 30-day survival for patients without liver disease. Group 1 = hyperammonemia group, Group 2 = group without hyperammonemia.

In this study, we found that the incidence of non-hepatic hyperammonemia was 42.2% in critical care patients. NHH patients had higher 30-day mortality than non-hyperammonemic patients, and serum ammonia level was an independent predictor of mortality in patients without liver disease. Moreover, we found that obesity, orthopedic surgery, corticosteroids, carbamazepine, valproic acid, epilepsy, and disorders of urea cycle metabolism are common risk factors for NHH.

In this study, we found that the incidence of hyperammonemia in critical care patients without liver disease was 42.2%. A recent prospective observational study with one hundred patients found, after

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