Busadee Pratumvinit

Background: Dyscalcemia is associated with significant clinical complications, and the demand for calcium testing is rising disproportionately. Objectives: This study aimed to develop machine learning (ML) models to predict total calcium abnormalities using routine available demographic and laboratory data to optimize laboratory test utilization. Materials and Methods: This retrospective study analyzed data from 7,951 patients at Siriraj Hospital between April 2023 and March 2024. Feature selection identified ten predictors, including patient status, absolute lymphocyte count, albumin, bicarbonate, hematocrit, hemoglobin, platelet count, potassium, red blood cell count, and total protein. Seven ML algorithms were developed and validated using an 80:20 training-testing split with 10-fold cross-validation and hyperparameter tuning. The Synthetic Minority Oversampling Technique was applied to address class imbalance. Additionally, model calibration was evaluated using Brier scores, and Platt scaling was applied to ensure the reliability of predicted probabilities. Results: XGBoost achieved the highest AUC (0.84), indicating slightly better discriminative performance, and the highest specificity (0.86), reflecting a stronger ability to correctly identify normal cases. Random forest yielded the highest F1 score (0.71) and recall (0.76), indicating a better balance between precision and recall, with higher sensitivity for detecting abnormal cases.Following Platt scaling, the calibrated models achieved robust Brier scores (e.g., 0.1496 for random forest and 0.1497 for XGBoost), demonstrating highly accurate probability risk estimation. SHAP analysis identified albumin as the most influential feature, followed by total protein and hemoglobin. Conclusion: ML models utilizing demographic and laboratory data can accurately predict plasma total calcium status, and probability calibration ensures reliable risk estimates. XGBoost and random forest demonstrated robust performance with complementary strengths. These models show promise as screening tools for identifying high-risk patients and optimizing rational laboratory utilization.

Purpose: The optimal plasma lipoprotein(a) [Lp(a)] cutoff level for predicting atherosclerotic cardiovascular disease (ASCVD) in Southeast Asian populations remains limited. Therefore, our study aimed to identify the optimal plasma Lp(a) cutoff for predicting ASCVD in Thai patients. Patients and Methods: We conducted a retrospective analysis of patients who underwent Lp(a) measurement at Siriraj Hospital between January 2019 and August 2024. Inclusion criteria included Thai ethnicity and age ≥ 15 years. Baseline characteristics, comorbidities, laboratory data, and Lp(a) levels were extracted from medical records. Lp(a) levels were compared between ASCVD and non-ASCVD groups. Odds ratios (OR) for ASCVD and coronary artery disease (CAD) were calculated using Lp(a)< 25 nmol/L as the reference. Results: A total of 2341 patients (age 54.4± 17.7 years, 42.0% male) were included. Among them, 413 (17.6%) had ASCVD, 254 (10.9%) had CAD, 186 (7.9%) had ischemic stroke, 21 (0.9%) had peripheral arterial disease (PAD), and 14 (0.6%) had abdominal aortic aneurysm. Median Lp(a) levels (nmol/L) were significantly higher in patients with ASCVD [37.2 vs 24.4, p< 0.001], CAD [43.8 vs 24.5, p< 0.001], and AS [51.6 vs 25.3, p=0.002] compared to those without diseases. After adjusting for other risk factors, Lp(a)≥ 40 nmol/L was associated with increased risks of ASCVD [OR 1.538 (1.203– 1.958)] and CAD [OR 1.877 (1.407– 2.505)]. A multivariate model incorporating Lp(a)≥ 40 nmol/L with other risk factors demonstrated 70– 80% sensitivity and specificity for predicting ASCVD and CAD. Conclusion: Elevated plasma Lp(a) levels are significantly associated with ASCVD and CAD. An Lp(a) cutoff of≥ 40 nmol/L predicted ASCVD and CAD risk in Thai.

The World Health Organization and the Centers for Disease Control and Prevention (CDC) have established guidelines recommending the performance of hand hygiene routines for healthcare workers following glove removal. However, the completion of frequent hygiene routines can cause allergic and adverse skin reactions. This double-blind, randomized study aimed to address this concern by developing and evaluating a modified glove removal technique that minimizes contamination risk during routine phlebotomy procedures. Furthermore, this study used fluorescent detection to compare the frequency of contamination associated with the CDC-recommended technique and the modified technique using fluorescent detection. One hundred healthcare personnel were enrolled and divided into two groups: one group followed the CDC technique, while the other group implemented the modified technique. Participants received instructional videos and practiced under supervision. They subsequently performed blood collection using a simulation arm covered with fluorescent cream as a contamination marker. After removing gloves, hand contamination was assessed under a black light. The median time required for glove removal in the modified group was four seconds longer than that in the group that followed the CDC technique (p < 0.001). Contamination was observed in 2% (1/50) of subjects using the CDC-recommended technique, while no contamination was detected with the modified technique (p ≥ 0.05). Both the group that followed the CDC technique and the group that used modified glove removal techniques demonstrated the potential to prevent contamination during phlebotomy, thereby reducing the need for hand hygiene and the occurrence of contamination and adverse skin reactions. These findings prompt further exploration into whether proper glove removal can reduce the frequency of completing a hand hygiene routine after each glove removal, specifically within the context of phlebotomy. However, it is essential to note that hand hygiene following glove removal is still recommended to prevent contamination. Further research is warranted to validate these findings.

Tyng Yu Chuah, M.B., B.Ch., B.A.O., Chun Yee Lim, Ph.D., Rui Zhen Tan, Ph.D., Busadee Pratumvinit, M.B., B.S, Tze Ping Loh, M.B., B.Ch., B.A.O., Samuel Vasikaran, M.B., B.S., and Corey Markus, M.Sc. for the APFCB Harmonization of Reference Intervals Working Group. Ann Lab Med 2023;43:408-17. https://doi.org/10.3343/alm.2023.43.5.408

Context.—: Timely reperfusion improves the recovery of patients with acute ischemic stroke. Laboratory results are crucial to guide treatment decisions in patients when abnormal laboratory tests are suspected. Objective.—: To implement a new laboratory workflow for acute stroke patients and compare laboratory turnaround time (TAT) preimplementation and postimplementation. Design.—: We conducted a retrospective pre-post intervention study of patients with suspected acute stroke during the 4-month periods before and after the implementation of a new laboratory workflow process. The improvement process included relocating the specimen registration site, laboratory notification before specimen arrival, a color-coding system on tubes, timing at all processes, and eliminating the smear review if platelets were normal. TATs of the laboratory and door-to–clinical intervention times before and after the improvement process were compared. Results.—: Postintervention, median specimen transportation time decreased from 11 (interquartile range [IQR], 8.4–16.4) to 9 minutes (IQR, 6.3–12.8), P < .001. The intralaboratory and total TATs of complete blood cell count, coagulation tests, and creatinine significantly decreased (P < .001 for all). Blood drawn–to–laboratory reported time decreased from 43 (IQR, 36.0–51.5) to 33 minutes (IQR, 29.2–35.8, P < .001). However, door-to-needle time for thrombolysis and door-to-puncture time and door-to-recanalization time for mechanical thrombectomy were not statistically different (P = .11, .69, and .50, respectively). Conclusions.—: The new laboratory workflow significantly decreased transportation time, TAT of individual tests, and the blood drawn–to–laboratory reported time. However, the time to treatment of acute ischemic stroke patients was not different between preimplementation and postimplementation.

Background. Thunbergia laurifolia (TL) is a commonly used herbal medicine in Thailand and in other Asian countries. TL has been approved as a Thai traditional medicine for detoxifying poisons, and the list of possible adverse effects includes hypoglycemia. TL showed hypoglycemic effect in animals possibly due to antioxidant effect and beta‐cell preservation. However, the safety of TL herbal tea and its effects on glucose homeostasis have never been investigated in humans. Methods. Twenty healthy volunteers (10 men and 10 women) drank TL herbal tea 3 times/day for 2 weeks. Ten subjects took TL herbal tea 9 grams daily. After the safety of TL herbal tea was established, 10 more subjects took TL 12 grams daily. Clinical and biochemical tests were assessed at baseline and at 2 weeks. Results. Mean age was 34.9 ± 10.2 years, and mean body mass index was 27.5 ± 5.8 kg/m². Baseline and posttreatment plasma concentrations were as follows: fasting plasma glucose (89 ± 6 vs. 89 ± 7 mg/dL), fructosamine (213 ± 32 vs. 212 ± 33 μmol/L), fasting insulin (8.8 [IQR: 5.9–18.4] vs. 10.4 [IQR: 7.4–15.2] μU/mL), HOMA‐B (101.6 [IQR: 82.3–189.8] vs. 120.4 [IQR: 93.2–153.2]), and HOMA‐IR (1.1 [IQR: 0.8–2.3] vs. 1.4 [IQR: 0.9–2.0]), all respectively. There were no significant changes in these parameters, including body weight, blood pressure, lipid profile, and C‐reactive protein. No serious adverse events were observed during the study period. Conclusions. TL herbal tea at doses of 9 and 12 grams daily had good tolerability without any significant adverse effects on fasting plasma glucose level or other glucose homeostasis parameters measured.

Busadee Pratumvinit, M.D., Kanit Reesukumal, M.D., Sithikan Hanyongyuth, B.P.H., Sujitra Wangchaijaroenkit, B.Sc., Julaporn Pooliam, M.Sc., Gerald J. Kost, M.D. Ph.D, Panumas Kamkang, B.Sc., and Tze Ping Loh, M.D.. Ann Lab Med 2019;39:209-13. https://doi.org/10.3343/alm.2019.39.2.209