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      Anion Gap Was Associated with Inhospital Mortality and Adverse Clinical Outcomes of Coronary Care Unit Patients

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          Abstract

          Background

          Anion gap (AG) has been proved to be associated with prognosis of many cardiovascular diseases. This study is aimed at exploring the association of AG with inhospital all-cause mortality and adverse clinical outcomes in coronary care unit (CCU) patients.

          Method

          All data of this study was extracted from Medical Information Mart for Intensive Care III (MIMIC-III, version 1.4) database. All patients were divided into four groups according to AG quartiles. Primary outcome was inhospital all-cause mortality. Lowess smoothing curve was drawn to describe the overall trend of inhospital mortality. Binary logistic regression analysis was performed to determine the independent effect of AG on inhospital mortality.

          Result

          A total of 3593 patients were enrolled in this study. In unadjusted model, as AG quartiles increased, inhospital mortality increased significantly, OR increased stepwise from quartile 2 (OR, 95% CI: 1.01, 0.74-1.38, P = 0.958) to quartile 4 (OR, 95% CI: 2.72, 2.08-3.55, P < 0.001). After adjusting for possible confounding variables, this association was attenuated, but still remained statistically significant (quartile 1 vs. quartile 4: OR, 95% CI: 1.02, 0.72-1.45 vs. 1.49, 1.07-2.09, P = 0.019). Moreover, CCU mortality ( P < 0.001) and rate of acute kidney injury ( P < 0.001) were proved to be higher in the highest AG quartiles. Length of CCU ( P < 0.001) and hospital stay ( P < 0.001) prolonged significantly in higher AG quartiles. Maximum sequential organ failure assessment score (SOFA) ( P < 0.001) and simplified acute physiology score II (SAPSII) ( P < 0.001) increased significantly as AG quartiles increased. Moderate predictive ability of AG on inhospital (AUC: 0.6291), CCU mortality (AUC: 0.6355), and acute kidney injury (AUC: 0.6096) was confirmed. The interactions were proved to be significant in hypercholesterolemia, congestive heart failure, chronic lung disease, respiratory failure, oral anticoagulants, Beta-blocks, angiotensin-converting enzyme inhibitor (ACEI)/angiotensin receptor blocker (ARB), and vasopressin treatment subgroups.

          Conclusion

          AG was an independent risk factor of inhospital all-cause mortality and was associated with adverse clinical outcomes in CCU patients.

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          Most cited references25

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          A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study.

          J R Le Gall, S Lemeshow, F Saulnier (1993)
          To develop and validate a new Simplified Acute Physiology Score, the SAPS II, from a large sample of surgical and medical patients, and to provide a method to convert the score to a probability of hospital mortality. The SAPS II and the probability of hospital mortality were developed and validated using data from consecutive admissions to 137 adult medical and/or surgical intensive care units in 12 countries. The 13,152 patients were randomly divided into developmental (65%) and validation (35%) samples. Patients younger than 18 years, burn patients, coronary care patients, and cardiac surgery patients were excluded. Vital status at hospital discharge. The SAPS II includes only 17 variables: 12 physiology variables, age, type of admission (scheduled surgical, unscheduled surgical, or medical), and three underlying disease variables (acquired immunodeficiency syndrome, metastatic cancer, and hematologic malignancy). Goodness-of-fit tests indicated that the model performed well in the developmental sample and validated well in an independent sample of patients (P = .883 and P = .104 in the developmental and validation samples, respectively). The area under the receiver operating characteristic curve was 0.88 in the developmental sample and 0.86 in the validation sample. The SAPS II, based on a large international sample of patients, provides an estimate of the risk of death without having to specify a primary diagnosis. This is a starting point for future evaluation of the efficiency of intensive care units.
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            Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions in a unique dually coded database.

            Hude Quan, Bing Li, L. Duncan Saunders … (2008)
            The goal of this study was to assess the validity of the International Classification of Disease, 10th Version (ICD-10) administrative hospital discharge data and to determine whether there were improvements in the validity of coding for clinical conditions compared with ICD-9 Clinical Modification (ICD-9-CM) data. We reviewed 4,008 randomly selected charts for patients admitted from January 1 to June 30, 2003 at four teaching hospitals in Alberta, Canada to determine the presence or absence of 32 clinical conditions and to assess the agreement between ICD-10 data and chart data. We then re-coded the same charts using ICD-9-CM and determined the agreement between the ICD-9-CM data and chart data for recording those same conditions. The accuracy of ICD-10 data relative to chart data was compared with the accuracy of ICD-9-CM data relative to chart data. Sensitivity values ranged from 9.3 to 83.1 percent for ICD-9-CM and from 12.7 to 80.8 percent for ICD-10 data. Positive predictive values ranged from 23.1 to 100 percent for ICD-9-CM and from 32.0 to 100 percent for ICD-10 data. Specificity and negative predictive values were consistently high for both ICD-9-CM and ICD-10 databases. Of the 32 conditions assessed, ICD-10 data had significantly higher sensitivity for one condition and lower sensitivity for seven conditions relative to ICD-9-CM data. The two databases had similar sensitivity values for the remaining 24 conditions. The validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions was generally similar though validity differed between coding versions for some conditions. The implementation of ICD-10 coding has not significantly improved the quality of administrative data relative to ICD-9-CM. Future assessments like this one are needed because the validity of ICD-10 data may get better as coders gain experience with the new coding system.
            Article 0 comments Cited 265 times – based on 0 reviews     Review now
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              Acid-Base Homeostasis

              L. Lee Hamm, Nazih Nakhoul, Kathleen Hering‐Smith (2015)
              Acid-base homeostasis and pH regulation are critical for both normal physiology and cell metabolism and function. The importance of this regulation is evidenced by a variety of physiologic derangements that occur when plasma pH is either high or low. The kidneys have the predominant role in regulating the systemic bicarbonate concentration and hence, the metabolic component of acid-base balance. This function of the kidneys has two components: reabsorption of virtually all of the filtered HCO3(-) and production of new bicarbonate to replace that consumed by normal or pathologic acids. This production or generation of new HCO3(-) is done by net acid excretion. Under normal conditions, approximately one-third to one-half of net acid excretion by the kidneys is in the form of titratable acid. The other one-half to two-thirds is the excretion of ammonium. The capacity to excrete ammonium under conditions of acid loads is quantitatively much greater than the capacity to increase titratable acid. Multiple, often redundant pathways and processes exist to regulate these renal functions. Derangements in acid-base homeostasis, however, are common in clinical medicine and can often be related to the systems involved in acid-base transport in the kidneys.
              Article 0 comments Cited 95 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Yujie Zhou:
                ORCID: https://orcid.org/0000-0002-9545-1984
                Journal
                Journal ID (nlm-ta): Biomed Res Int
                Journal ID (iso-abbrev): Biomed Res Int
                Journal ID (publisher-id): BMRI
                Title: BioMed Research International
                Publisher: Hindawi
                ISSN (Print): 2314-6133
                ISSN (Electronic): 2314-6141
                Publication date Collection: 2020
                Publication date (Electronic): 27 August 2020
                Volume: 2020
                Electronic Location Identifier: 4598462
                Affiliations
                1Beijing Anzhen Hospital Affiliated to Capital Medical University, Beijing, China
                2Beijing Institute of Heart, Lung and Blood Vessel Disease, Beijing, China
                Author notes

                Academic Editor: Giuseppe Piccione

                Author information
                https://orcid.org/0000-0002-1718-2571
                https://orcid.org/0000-0003-4535-4470
                https://orcid.org/0000-0002-1418-8839
                https://orcid.org/0000-0002-2053-6692
                https://orcid.org/0000-0002-5388-2321
                https://orcid.org/0000-0002-9545-1984
                Article
                DOI: 10.1155/2020/4598462
                PMC ID: 7474740
                PubMed ID: 32908890
                SO-VID: 2487f4ff-dc66-4608-8b7e-ad6188995f3a
                Copyright © Copyright © 2020 Tienan Sun et al.
                License:

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 25 June 2020
                Date revision received : 18 August 2020
                Date accepted : 19 August 2020
                Categories
                Subject: Research Article

                Data availability:

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