MATERIALS AND METHODS: A total of 3,175 adult University Malaya Medical Centre (UMMC) patients deemed free of any calcium metabolism disorders were selected and divided into two groups for derivation and validation. Simple linear regression associating total calcium and albumin was constructed from the data in the derivation group. The new albumin-adjusted calcium equation was validated in the validation group. Differences in calcium status classification following adjustments based on existing and new albumin-adjusted calcium equation was compared in a 469 hypoalbuminaemic patients.
RESULT: The new albumin adjusted calcium equation was: total calcium + 0.014 x (39-albumin). Of the 469 hypoalbuminemic patients, 78 were classified differently based on new equation. Based on the new equation, 55 normocalcemic patients were classified as hypocalcemic and 22 were classified as normocalcemic instead of hyperclacaemic.
CONCLUSION: Based on the newly derived albuminadjusted calcium equation 17% of patients had different adjusted calcium classifications. This could potentially impact in the management. It is recommended that laboratories derive equations specific to their calcium/albumin methods and analytical platforms.
OBJECTIVES: (1) Evaluate the four published equations' performance in estimating ionised calcium; (2) Determine the accuracy of calculated ionised and adjusted total calcium in classifying patients according to calcium states; and (3) Identify factors associated with hypocalcaemia in the critically ill population.
MATERIALS AND METHODS: This is a cross-sectional study involving 281 critically ill patients aged 18-80 years of both genders in a Malaysian tertiary intensive care unit. Performance of the four equations was analysed using Bland-Altman difference plot and Passing Bablok regression analysis. Crosstabulation was conducted to assess classification accuracy. Mann-Whitney U or Pearson Chi-Square tests were performed to identify variables associated with hypocalcaemia.
RESULTS: Calculated ionised calcium using all four equations significantly overestimated ionised calcium. Calculated ionised and adjusted total calcium had poor accuracies in classifying hypocalcaemic patients. pH was significantly higher in hypocalcaemics.
CONCLUSION: Calculated ionised and adjusted total calcium significantly overestimate ionised calcium in the critically ill. In this specific population, calcium status should only be confirmed with ionised calcium measured by direct ion-selective electrode (ISE).
METHODS: In this single-centre retrospective study, comparative analysis on clinical presentations and laboratory findings was performed between confirmed leptospirosis versus non-leptospirosis cases.
RESULTS: In multivariate logistic regression evidenced by a Hosmer-Lemeshow significance value of 0.979 and Nagelkerke R square of 0.426, the predictors of a leptospirosis case are hypocalcemia (calcium <2.10mmol/L), hypochloremia (chloride <98mmol/L), and eosinopenia (absolute eosinophil count <0.040×109/L). The proposed diagnostic scoring model has a discriminatory power with area under the curve (AUC) 0.761 (p<0.001). A score value of 6 reflected a sensitivity of 0.762, specificity of 0.655, a positive predictive value of 0.38, negative predictive value of 0.91, a positive likelihood ratios of 2.21, and a negative likelihood ratios of 0.36.
CONCLUSION: With further validation in clinical settings, implementation of this diagnostic scoring model is helpful to manage presumed leptospirosis especially in the absence of leptospirosis confirmatory tests.
METHODS: Retrospective data on serum calcium and infusion rates was collected from 2011-2015. The relationship between peak calcium efflux (PER) and time was determined using a scatterplot and linear regression. A comparison between regimens was made based on treatment efficacy (hypocalcaemia duration, total infusion amount and time) and calcium excursions (outside target range, peak and trough calcium) using bar charts and an unpaired t-test.
RESULTS: Fifty-one and 34 patients on the original and new regimens respectively were included. Mean PER was lower (2.16 vs 2.56 mmol/h; P = 0.03) and occurred earlier (17.6 vs 23.2 h; P = 0.13) for the new regimen. Both scatterplot and regression showed a large correlation between PER and time (R-square 0.64, SE 1.53, P