Limitations of calculated ionised calcium & adjusted calcium in critically ill patients: Time to consider measured ionised calcium.

INTRODUCTION: Ionised calcium is a good prognostic and diagnostic tool as opposed to total calcium in critical patients but is not available in most central laboratories and non-intensive care units. To date, four equations to calculate ionised calcium in critical patients have been published. 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).

Albumin adjusted calcium: Study in a tertiary care hospital.

INTRODUCTION: One commonly used equation which continues to be widely mentioned in text books and hence familiar to clinical people is total calcium + 0.02 (40 - albumin). This equation was derived using cresophthalein complexone and bromocresol green (BCG) methods for measuring serum total calcium and serum albumin respectively. However this equation maybe invalid when applied to calcium and albumin results generated by alternative assays. Hence we aim to derive an albumin-adjusted calcium equation specific to our laboratory's total calcium and albumin methodologies. 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.

Importance of screening for macroprolactin in all hyperprolactinaemic sera.

INTRODUCTION: Prolactin (PRL) exists in different forms in human serum. The predominant form is monomeric PRL (molecular mass 23 kDa) with smaller amounts of big PRL (molecular mass 50-60 kDa) and at times macroprolactin (molecular mass 150-170 kDa). Macroprolactin, generally considered to be biologically inactive, accounts for the major part of prolactin in some patients. Different immunoassays for prolactin differ in reactivity with this macromolecular complex. AIM: The present study was undertaken to assess the incidence of macroprolactinaemia in our cohort of hyperprolactinemic patients. METHOD: 204 samples with hyperprolactinemia were evaluated for macroprolactinemia by polyethylene glycol (PEG) precipitation and gel filtration chromatography (GFC). Recoveries ≤60% after PEG precipitation were considered to have macroprolactinaemia. RESULTS: A total of 43 (21%) of these patients had less than 60% recovery after PEG precipitation. GFC confirmed that in seven of these patients macroprolactin was the major part of the prolactin. Recoveries were < 40% PEG precipitation in these samples. Combined macro and hyperprolactinemia was observed in two samples and the recovery after PEG precipitation was >40% but ≤50%. The incidence of macroprolactinemia in our cohort of hyperprolactinaemic patients was noted to be 4.4%. CONCLUSION: Macroprolactin is a significant cause of misdiagnosis, unnecessary investigation, and inappropriate treatment and hence it is useful to screen all patients with high PRL levels with PEG precipitation and to apply GFC to samples with recoveries <50%.