Context:Metabolic acidosis is frequently found in patients with severe sepsis. An understanding of types of acidosis in sepsis and their evolution over the course of treatment may give us insight into the behavior of acid–base balance in these patients.Aims:To describe at Intensive Care Unit (ICU) admission and over the first 5 days the composition of metabolic acidosis in patients with sepsis and to evaluate and compare acidosis patterns in survivors and nonsurvivors.Settings and Design:A prospective study conducted at Amrita Institute of Medical Sciences, Kochi, Kerala, in the Department of Internal Medicine.Subjects and Methods:Seventy-five consecutive patients admitted in the medical ICU with sepsis and metabolic acidosis were assessed. Arterial blood gas and serum electrolytes were measured during the first five days of admission or until death, renal replacement or discharge supervened.Statistical Analysis:To test the statistical significance of the difference in mean values of different study variables at day 1 and last day between survivors and non survivors, Mann–Whitney U-test was applied. To test the statistical significance of the difference in mean changes in different study parameters from day 1 to last day, paired t-test was done in the survivor group and Mann–Whitney U-test in the non survivor group.Results:Regardless of survival status, on day 1 of admission, 37 had High Anion Gap metabolic acidosis (HAGMA), 21 had predominant lactic acidosis (LA), 8 had Normal anion gap metabolic acidosis (NAGMA), and 9 had both HAGMA and LA [Figure 1]. When we compared this to the last day, 25 had HAGMA, 3 had LA, 3 had both HAGMA and LA, and 22 patients had resolution of acidosis. Sixty–four patients survived for up to 5 days of admission. Fifteen of these patients underwent hemodialysis on the day of admission itself in view of HAGMA. The remaining 49 comprised of HAGMA (31), Lactic acidosis (12), and a combination (6) on day 1. On the last day in this group, 25 had HAGMA, 2 had LA, and 22 patients had resolution of acidosis. In survivors, over the observation period, changes seen were: mean pH: 7.25–7.34 (P < 0.001), mean serum bicarbonate: 13.9 mEq to 17.2 mEq (P < 0.001), and mean serum lactate: 3.18–1.9 (P = 0.002). The changes in serum albumin and pCO2 were not significant. Eleven patients in the study population succumbed. Seven patients underwent hemodialysis on day 1 and the remaining four were followed up for more than 1 day. On day 1, 7 had lactic acidosis and 5 had HAGMA. Over the observation period, changes seen were mean pH: 7.15–7.14, mean serum lactate: 6.3–7.3 mEq.Conclusions:In patients with sepsis and septic shock, high anion gap metabolic acidosis is the dominant blood gas anomaly. Fall in lactate levels over the first 5 days of admission is a good prognostic marker of survival. Evolution of the blood gas profile over time suggests that a fall in lactate levels and a rise in bicarbonate levels correlate with a better outcome. The role of the anion gap as a prognostic marker holds promise an...

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Background There are many cardiovascular disease (CVD) risk score calculators in practice, which are not based on Indian population data. Objectives To identify the best CVD risk score calculator applicable in the Indian population. Materials and methods A total of 1000 patients presenting with acute coronary syndrome (ACS) were included in the study and their CVD risk score, had they presented before the event, was calculated. The Framingham risk score (FRS–body mass index [BMI], FRS–fasting lipid profile [FLP]), the American College of Cardiology/American Heart Association pooled cohort equation risk calculator (ACC/AHA PCE), Joint British Society risk calculator 3 (JBS3) and the World Health Organization (WHO) risk prediction charts (WHO TC and WHO without TC [WHO NO TC]) were used. Results It was seen that among the 1000 people included in the study, the FRS-BMI (59.2%), FRS-FLP (61.5%), ACC/AHA (70.1%) and the JBS3 (62.5%) identified a majority as having a risk of ≥20%, whereas both the WHO TC (65.3%) and the WHO NO TC (64.5%) identified a majority of the ACS patients as having a risk of <20%. The sensitivity was highest for the ACC/AHA (87.8%), FRS-FLP (85.1%) and then JBS3 (80.1%), whereas the specificity was highest for the WHO TC (83.6%) and the WHO NO TC (82.1%). When looking at the accuracy, the FRS-FLP was the most accurate with 80.1%, whereas the ACC/AHA and the JBS3 followed at 74.7% and 73.1%, respectively. Conclusion The ACC/AHA seems to be an acceptable risk prediction system to be used in the Indian population and is also relatively easy and cheap to use.

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