Comparison of intraocular lens power prediction accuracy of formulas in American Society of Cataract and Refractive Surgery post-refractive surgery calculator in eyes with prior radial keratotomy

Purpose: To evaluate the accuracy of intraocular lens (IOL) power prediction of the formulas available on the American Society of Cataract and Refractive Surgery (ASCRS) post?refractive calculator in eyes with prior radial keratotomy (RK) for myopia. Methods: This retrospective study included 25 eyes of 18 patients whose status was post?RK for treatment of myopia, which had undergone cataract extraction with IOL implantation. Prediction error was calculated as the difference between implanted IOL power and predicted power by various formulae available on ASCRS post?refractive calculator. The formulas compared were Humphrey Atlas method, IOLMaster/Lenstar method, Barrett True?K no?history formula, ASCRS Average power, and ASCRS Maximum power on ASCRS post?refractive calculator. Results: Median absolute errors were the least for Barrett True?K and ASCRS Maximum power, that is, 0.56 (0.25, 1.04) and 0.56 (0.25, 1.06) D, respectively, and that of Atlas method was 1.60 (0.85, 2.28) D. Median arithmetic errors were positive for Atlas, Barrett True?K, ASCRS Average (0.86 [?0.17, 1.61], 0.14 [?0.22 to 0.54], and 0.23 [?0.054, 0.76] D, respectively) and negative for IOLMaster/Lenstar method and ASCRS Maximum power (?0.02 [?0.46 to 0.38] and ? 0.48 [?1.06 to ? 0.22] D, respectively). Multiple comparison analysis of Friedman抯 test revealed that Atlas formula was significantly different from IOLMaster/ Lenstar, Barrett True?K, and ASCRS Maximum power; ASCRS Maximum power was significantly different from all others (P < 0.00001). Conclusion: In post?RK eyes, Barrett True?K no?history formula and ASCRS Maximum power given by the ASCRS calculator were more accurate than other available formulas, with ASCRS Maximum leading to more myopic outcomes when compared to others

Comparative evaluation of intraoperative aberrometry and Barrett’s toric calculator in toric intraocular lens implantation

Purpose: Barrett toric calculator (BTC) is known for its accuracy in toric IOL (tIOL) calculation over standard calculators; however, there is no study in literature to compare it with real?time intraoperative aberrometry (IA). The aim was to compare the accuracy of BTC and IA in predicting refractive outcomes in tIOL implantation. Methods: This was an institution?based prospective, observational study. Patients undergoing routine phacoemulsification with tIOL implantation were enrolled. Biometry was obtained from Lenstar?LS 900 and IOL power calculated using online BTC; however, IOL was implanted as per IA (Optiwave Refractive Analysis, ORA, Alcon) recommendation. Postoperative refractive astigmatism (RA) and spherical equivalent (SE) were recorded at one month, and respective prediction errors (PEs) were calculated using predicted refractive outcomes for both methods. The primary outcome measure was a comparison between mean PE with IA and BTC, and secondary outcome measures were uncorrected distance visual acuity (UCDVA), postoperative RA, and SE at one month. SPSS Version?21 was used; P < 0.05 considered significant. Results: Thirty eyes of 29 patients were included. Mean arithmetic and mean absolute PEs for RA were comparable between BTC (?0.70 ± 0.35D; 0.70 ± 0.34D) and IA (0.77 ± 0.32D; 0.80 ± 0.39D) (P = 0.09 and 0.09, respectively). Mean arithmetic PE for residual SE was significantly lower for BTC (?0.14 ± 0.32D) than IA (0.001 ± 0.33D) (?0.14 ± 0.32D; P = 0.002); however, there was no difference between respective mean absolute PEs (0.27 ± 0.21 D; 0.27 ± 0.18; P = 0.80). At one?month, mean UCDVA, RA, and SE were 0.09 ± 0.10D, ?0.57 ± 0.26D, and ?0.18 ± 0.27D, respectively. Conclusion: Both IA and BTC give reliable and comparable refractive results for tIOL implantation.

Comparing IOLM700 TK, Berdahl and Hardten astigmatism fix calculator and Barrett Rx formula in managing residual astigmatism due to toric intraocular lens misalignment

Purpose: To compare the accuracy in astigmatism reduction by using IOLM 700 steep total keratometry (TK) axis, Berdahl and Hardten astigmatism fix, and Barrett Rx formula following misaligned toric intraocular lens (IOL). Methods: Ten patients with residual refractive astigmatism due to misalignment following toric IOL implantation were included in this retrospective study. They were analyzed at days 4, 7/8, and 10/11 following primary cataract surgery on the platform of Berdahl and Hardten astigmatism fix, Barrett Rx formula, and IOLM 700 to determine the optimum axis of repositioning, and underwent IOL realignment on the steep TK axis of IOLM 700 assisted by the Callisto eye. The final outcome parameters were subjective refraction and orientation of toric IOL assessed 22 ± 1 days following repositioning surgery. These parameters were fed in the Barrett Rx formula and its vector analysis graph was utilized to determine the predicted ideal axis with the least residual astigmatism and the estimated residual astigmatism if the toric IOL was realigned according to the axis suggested by Berdahl and Hardten astigmatism fix and Barrett Rx formula. Results: Realigning the toric IOL on IOLM 700 steep TK axis along with the Callisto eye reduces the residual refractive astigmatism significantly (P = 0.003) from 2.00 ± 0.78 D to 0.18 ± 0.12 D (90.5 ± 7.6%) in comparison to the estimated 0.57 ± 0.31 D (68.4 ± 21.9%) by Berdahl and Hardten astigmatism fix and 0.61 ± 0.33 D (66.4 ± 23.5%) by Barrett Rx formula. Conclusion: Realigning the misaligned toric IOL on the IOLM 700 steep TK axis gives a better reduction in the residual refractive astigmatism in comparison to Berdahl and Hardten astigmatism fix and Barrett Rx formula

Diagnostic accuracy of the neonatal early onset sepsis calculator in screening for early onset sepsis in neonates more than 35 weeks age of gestation

Background@#Early-onset sepsis (EOS) is a leading cause of morbidity and mortality among neonates. Diagnosis of EOS can be difficult as clinical signs are subtle. The use of the Neonatal EOS Calculator (NEOSC) may help screen high-risk neonates for EOS and may result in a significant reduction in unnecessary antibiotic use. @*Objective@#To determine the diagnostic accuracy of the NEOSC in screening for EOS in neonates more than 35 weeks age of gestation. @*Methodology@#This was a retrospective, case-control study where 245 septic (cases) and 245 non-septic (controls) neonatal and maternal medical records were reviewed. The EOS risk classification from the NEOSC was compared with the actual clinical outcome. An online statistical software (medcalc.org) was used to compute for the sensitivity (Sn), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), negative likelihood ratio (NLR) and accuracy of the NEOSC. @*Results@#Based on the NEOSC, only 64 of 245 clinically septic neonates were truly positive for sepsis while 181 were falsely negative for sepsis. Of the 245 non-septic neonates, 3 were falsely positive for sepsis, while 242 were truly negative for sepsis. With a 95% confidence interval, the computed variables showed a Sn 26.12%, Sp 98.78%, PPV 76.12%, NPV 89.95%, PLR 21.33, and NLR 0.75. The accuracy of the NEOSC is 89.33%.@*Conclusion@#The NEOSC had poor sensitivity and is not recommended in screening for EOS in neonates more than 35 weeks age of gestation. It may be used as an adjunct in EOS diagnosis due to its high specificity and accuracy.

The value of PCPT-RC high risk probability combined with Gleason score for predicting the risk of metastasis in newly diagnosed prostate cancer / 西安交通大学学报(医学版)

【Objective】 To investigate the value of prostate cancer prevention trial risk calculator （PCPT-RC） combined with biopsy Gleason score for predicting the risk of metastasis in newly diagnosed prostate cancer patients. 【Methods】 We retrospectively collected the data of 74 patients with newly diagnosed prostate cancer confirmed by biopsy from April 2019 to August 2021， concurrent with 18F-PSMA-1007 PET/CT whole body imaging in the same period. Based on this， a binary logistic regression model was established to obtain the high risk probability of PCPT. We calculated the receiver operating characteristic curve （ROC） was drawn and the area under the curve， Yuden index， sensitivity， specificity， positive predictive value and negative predictive value. We compared the predictive value of the prostate cancer prevention trial risk calculator and Gleason score alone or in combination in predicting the risk of prostate cancer metastasis. 【Results】 Based on the PSMA PET/CT results， 74 patients were divided into non-metastatic group （46/74） and metastatic group （28/74）. PCPT high risk probability ［41.14% （16%-67%）］ vs. ［30.89% （5%-65%）］， Gleason score ［8.5（6-10） score］ vs. ［7.7（6-9） score］， tPSA ［26.24（5.70-42.32） ng/mL］ vs. ［19.58（2.47-49.35） ng/mL］， and fPSA ［3.94（0.82-12.00） ng/mL］ vs. ［2.33（0.35-10.20） ng/mL］ were significantly higher in metastatic group than in non-metastatic group. Binary Logistic regression analysis showed that Gleason score and PCPT low risk probability may be independent predictors of prostate cancer metastasis. PCPT low risk probability alone did not predict the risk of prostate cancer metastasis （P=0.172）. The predictive accuracy of Gleason score and high probability of PCPT in predicting prostate cancer metastasis were 0.715 and 0.679， respectively， and the accuracy of the combined prediction was 0.809. 【Conclusion】 PCPT-RC combined with Gleason score is valuable for predicting the metastasis risk of newly diagnosed prostate cancer patients， which has certain guiding significance for clinical individualized treatment.

Retrospective study on assessment of risk for gestational diabetes using fetal medicine foundation’s gestational diabetes risk assessment calculator in a tertiary care hospital in coastal Karnataka, India

Background: Gestational diabetes is defined as impaired glucose tolerance with onset or first recognition during pregnancy. Undiagnosed or inadequately treated gestational diabetes can lead to significant maternal and fetal complications. Even though there are guidelines for diagnosis of GDM (gestational diabetes mellitus) by the Government of India, there is poor penetration of the implementation throughout the nation.Methods: The study was conducted in A. J. Institute of Medical Sciences between April to June 2019. 56 patients were evaluated with the fetal medicine foundation GDM risk calculator to assess the risk for gestational diabetes in a retrospective approach.Results: Incidence of GDM in the study was 15.9%. At a cut-off of 1/80, the calculator predicted increased risk for 37 out of 56 patients. There was a sensitivity of 91.6% and specificity of 63.6% with a negative predictive value of 96.5% and positive predictive value of 29.5%. there was a false positive rate of 43.2%.Conclusions: The fetal medicine foundation GDM risk calculator will prove to be an invaluable tool to predict high risk patients who need closer monitoring of blood glucose into the third trimester.

The challenges of neonatal sepsis management / Os desafios no manejo da sepse neonatal

Abstract Objectives To present current evidence on the etiology, risk factors, diagnosis, and management of early and late neonatal sepsis. Source of data Non-systematic review of the Medline (PubMed), Scopus, Web of Science, Cochrane, and Google Scholar databases regarding the following terms: neonatal sepsis, early neonatal sepsis, late neonatal sepsis, empirical antibiotic therapy, sepsis calculator, vancomycin, newborn, preterm newborn. Data synthesis Neonatal sepsis is a frequent cause of neonatal morbidity and mortality. Its diagnosis is difficult. Continuous observation of the patient is critical to diagnostic suspicion. When neonatal sepsis is suspected, bacteriological tests should be collected. Vancomycin should not be routinely using in the empirical antibiotic regimen in late neonatal sepsis, and the main protective mechanisms against neonatal sepsis are handwashing and the use of breast milk. Conclusions Newborns constitute a group that is more vulnerable to sepsis. Knowledge of risk factors and etiological agents allows a better approach to the newborn with sepsis.

Resumo Objetivos Apresentar evidências atuais na etiologia, fatores de risco, diagnóstico e manejo da sepse neonatal precoce e tardia. Fontes de dados Revisão não sistemática feita nas bases de dados Medline (PubMed), Scopus, Web of Science, Cochrane, Google Scholar sobre os temas sepse neonatal, sepse neonatal precoce, sepse neonatal tardia, antibioticoterapia empírica, sepsis calculator, vancomicina, recém-nascido, recém-nascido pré-termo. Síntese de dados A sepse neonatal é uma causa frequente de morbimortalidade neonatal. O seu diagnóstico é difícil. A observação contínua do paciente é fundamental para uma suspeição diagnóstica. Ao se suspeitar de sepse neonatal devem-se coletar exames bacteriológicos. Não usar, rotineiramente, vancomicina no esquema empírico de antibiótico na sepse neonatal tardia. Os principais mecanismos protetores da sepse neonatal são a lavagem de mãos e o uso do leite materno. Conclusões Os recém-nascidos constituem um grupo mais vulnerável à sepse. O conhecimento dos fatores de risco e dos agentes etiológicos permite uma melhor abordagem do recém-nascido séptico.

Phi-based risk calculators performed better in the prediction of prostate cancer in the Chinese population / 亚洲男科学杂志(英文版)

Risk prediction models including the Prostate Health Index (phi) for prostate cancer have been well established and evaluated in the Western population. The aim of this study is to build phi-based risk calculators in a prostate biopsy population and evaluate their performance in predicting prostate cancer (PCa) and high-grade PCa (Gleason score ≥7) in the Chinese population. We developed risk calculators based on 635 men who underwent initial prostate biopsy. Then, we validated the performance of prostate-specific antigen (PSA), phi, and the risk calculators in an additional observational cohort of 1045 men. We observed that the phi-based risk calculators (risk calculators 2 and 4) outperformed the PSA-based risk calculator for predicting PCa and high-grade PCa in the training cohort. In the validation study, the area under the receiver operating characteristic curve (AUC) for risk calculators 2 and 4 reached 0.91 and 0.92, respectively, for predicting PCa and high-grade PCa, respectively; the AUC values were better than those for risk calculator 1 (PSA-based model with an AUC of 0.81 and 0.82, respectively) (all P < 0.001). Such superiority was also observed in the stratified population with PSA ranging from 2.0 ng ml-1to 10.0 ng ml-1. Decision curves confirmed that a considerable proportion of unnecessary biopsies could be avoided while applying phi-based risk calculators. In this study, we showed that, compared to risk calculators without phi, phi-based risk calculators exhibited superior discrimination and calibration for PCa in the Chinese biopsy population. Applying these risk calculators also considerably reduced the number of unnecessary biopsies for PCa.

Phi-based risk calculators performed better in the prediction of prostate cancer in the Chinese population / 亚洲男科学杂志(英文版)

Risk prediction models including the Prostate Health Index (phi) for prostate cancer have been well established and evaluated in the Western population. The aim of this study is to build phi-based risk calculators in a prostate biopsy population and evaluate their performance in predicting prostate cancer (PCa) and high-grade PCa (Gleason score ≥7) in the Chinese population. We developed risk calculators based on 635 men who underwent initial prostate biopsy. Then, we validated the performance of prostate-specific antigen (PSA), phi, and the risk calculators in an additional observational cohort of 1045 men. We observed that the phi-based risk calculators (risk calculators 2 and 4) outperformed the PSA-based risk calculator for predicting PCa and high-grade PCa in the training cohort. In the validation study, the area under the receiver operating characteristic curve (AUC) for risk calculators 2 and 4 reached 0.91 and 0.92, respectively, for predicting PCa and high-grade PCa, respectively; the AUC values were better than those for risk calculator 1 (PSA-based model with an AUC of 0.81 and 0.82, respectively) (all P < 0.001). Such superiority was also observed in the stratified population with PSA ranging from 2.0 ng ml-1to 10.0 ng ml-1. Decision curves confirmed that a considerable proportion of unnecessary biopsies could be avoided while applying phi-based risk calculators. In this study, we showed that, compared to risk calculators without phi, phi-based risk calculators exhibited superior discrimination and calibration for PCa in the Chinese biopsy population. Applying these risk calculators also considerably reduced the number of unnecessary biopsies for PCa.

The comparison between management recommendations of the Neonatal Early Onset Sepsis Calculator and CDC/AAP guidelines among culture-proven early onset sepsis admitted at University of East Ramon Magsaysay Memorial Medical Center from January 2013 to December 2017 / The Health Sciences Journal

INTRODUCTION Early onset sepsis is difficult to diagnose due to nonspecific symptoms and a lack ofreliable tests. It can progress quickly, and lead to neurodevelopmental consequences or be fatal if nottreated. However, approximately 10-fold more newborns are treated with antibiotics empirically and oftenunnecessarily. This study aimed to compare the management recommendations of the Neonatal EarlyOnset Sepsis Calculator with those of the Centers for Disease Control/American Academy of Pediatricsguidelines.METHODS Neonatal Early Onset Sepsis Calculator was applied to the data set to examine how an alternativemodel would perform compared to current guidelines published by the CDC and compared to currentpractice within the institution. Chi square and kappa value agreement was used to determine the differencebetween treatment recommendations of NEOS calculator and AAP guideline.RESULTS Of the 330 patients who received therapy, only 14.2% were recommended empiric antibiotics bythe EOS calculator, compared to the 39% recommended by the CDC guidelines (p Eleven patients were identified to have culture-positive sepsis.CONCLUSION The number of infants suspected with EOS and subsequently require antibiotic use at birthmay be dramatically reduced with the use of the neonatal EOS calculator.

Prostate Cancer Prevention Trial risk calculator for evaluating the risk of prostate cancer in the high-risk Chinese population / 中华男科学杂志

Objective@#The Prostate Cancer Prevention Trial risk calculator (PCPT-RC) is an online tool for assessing the risk of prostate cancer (PCa) based on age, race, serum PSA, biopsy history, family history, and other factors. This study aimed to investigate the value, sensitivity and specificity of the PCPT-RC 2.0 in assessing the risk of PCa in the Chinese high-risk population.@*METHODS@#This study included 622 patients with the high risk of PCa characterized by high serum PSA (PSA >3 μg/L) or abnormality in digital rectal examination or imaging of the prostate. According to the results of prostate biopsy, we divided the patients into a PCa and a non-PCa group and used the PCPT-RC 2.0 for evaluation of all the cases followed by statistical analysis.@*RESULTS@#PCa was detected in 264 (42.4%) of the 622 patients, including 126 cases of high-grade malignancy. Compared with the non-PCa group, the PCa patients showed a significantly older age (［68.40 ± 7.30］ vs ［72.80 ± 7.20］ yr, P 0.05).@*CONCLUSIONS@#The PCPT risk score is valuable in predicting the risk of PCa in China, which may play a better role than the serum PSA level in screening PCa and avoid unnecessary prostate biopsy, though its advantage is not so obvious in identifying high-grade malignancy. A prediction tool needs to be established for evaluating the risk of PCa in the Chinese population.

The Huashan risk calculators performed better in prediction of prostate cancer in Chinese population: A training study followed by a validation study / 亚洲男科学杂志(英文版)

The performances of the Prostate Cancer Prevention Trial (PCPT) risk calculator and other risk calculators for prostate cancer (PCa) prediction in Chinese populations were poorly understood. We performed this study to build risk calculators (Huashan risk calculators) based on Chinese population and validated the performance of prostate-specific antigen (PSA), PCPT risk calculator, and Huashan risk calculators in a validation cohort. We built Huashan risk calculators based on data from 1059 men who underwent initial prostate biopsy from January 2006 to December 2010 in a training cohort. Then, we validated the performance of PSA, PCPT risk calculator, and Huashan risk calculators in an observational validation study from January 2011 to December 2014. All necessary clinical information were collected before the biopsy. The results showed that Huashan risk calculators 1 and 2 outperformed the PCPT risk calculator for predicting PCa in both entire training cohort and stratified population (with PSA from 2.0 ng ml-1 to 20.0 ng m). In the validation study, Huashan risk calculator 1 still outperformed the PCPT risk calculator in the entire validation cohort (0.849 vs 0.779 in area under the receiver operating characteristic curve [AUC] and stratified population. A considerable reduction of unnecessary biopsies (approximately 30%) was also observed when the Huashan risk calculators were used. Thus, we believe that the Huashan risk calculators (especially Huashan risk calculator 1) may have added value for predicting PCa in Chinese population.

Comparison of the Astigmatic Power of Toric Intraocular Lenses Using Three Toric Calculators

PURPOSE: To compare the astigmatic power of toric intraocular lenses (IOLs) obtained from the AcrySof, TECNIS, and iTrace toric calculator in patients with preoperative with-the-rule (WTR) or against-the-rule (ATR) corneal astigmatism. MATERIALS AND METHODS: Fifty eyes with cataract and corneal astigmatism greater than 0.75 diopters were enrolled in each group (WTR and ATR). Keratometric values were measured using autokeratometry, an IOLMaster, and an iTrace, which incorporated corneal topography and ray-tracing aberrometry. Based on measured keratometric values, the astigmatic power of each toric IOL was calculated using three toric calculators. RESULTS: Bland-Altman plots showed good agreement between six pairwise corneal astigmatism values in both groups. The TECNIS calculator tended to suggest a higher astigmatic power of the toric IOL than the AcrySof calculator. With the higher astigmatism and keratometric values from the IOLMaster, in both groups, calculations from the AcrySof and TECNIS calculators resulted in higher calculated astigmatic powers than those from same calculators with autokeratometry-measured values, demonstrating good agreement. With the higher calculated astigmatic power values, the values from the iTrace toric calculator using keratometric values obtained from iTrace ray tracing wavefront aberrometry or iTrace simulated keratometry showed fair to moderate agreement with those from the other calculator-keratometry pairs in both groups. CONCLUSION: To achieve the best refractive outcome after toric IOL implantation, understanding the differences in keratometric values between instruments and in calculated astigmatic power among toric calculator programs is necessary. Moreover, systemic analysis of each toric calculator in conjunction with postoperative data is required.

Patients’ Information Leaflets: Its’ Influence on Ophthalmic Patient Education and Medication Compliance.

Aims: To investigate the influence of patient information leaflets on Ophthalmic patients’ education and medication compliance. Study Design: Hospital-based cross- sectional survey. Place and Duration of Study: Department of Optometry, School of Physical Sciences, UCC, Cape Coast, Ghana, between September 2012 and May 2013. Methodology: A semi - structured questionnaire with sections on patient demographics, patient information leaflets impact on therapeutic education, and medication compliance, was administered to 400 ophthalmic review patients in three eye care facilities in Central Region of Ghana. Patient information leaflets (PILs) of common ophthalmic medications prescribed in these eye centers were also reviewed and assessed on their readability using the Rudolph Flesch’s readability ease calculator. Obtained data was analyzed using SPSS version 19. Pearson’s Chi-square statistical analysis was used to test for significant association between variables. Results: Of the 400 ophthalmic patients, 140 (35%) were males and 260 (65%) females The mean age was 50.2 ± 19.5. Patients had varying opinion on the purpose for the PIL: 228 (57%) thought the PIL only gives instructions on the use of the medication; 108 (27%) did not know why the PIL have been provided. The remaining 64 (16%) provided no response. There was significant association between higher educational level and reading of the leaflet (P < 0.001). The kind of ophthalmic condition one suffered had a positive influence on reading the PIL ( X2=28.594, P < 0.001). A greater proportion of the patients (88.04%) said various components of information on the leaflet were beneficial in ensuring compliance to therapy. All the PILs from the five different companies (where medication were obtained for retail) had very low readability score (0-29) except some PILs of topical analgesic drug. The low readability score indicated that the text was difficult to comprehend; the reason for which most patients did not read the leaflets. Most patients 91(99%) who read the PILs indicated that they were beneficial but were difficult to understand. Conclusion: Ophthalmic patients’ opinion on patient information leaflets was reasonably good and had a positive influence on patients’ medication compliance. It however, did not have much influence on patient education due to low readability and comprehensible.

MyRisk_Stroke Calculator: A Personalized Stroke Risk Assessment Tool for the General Population

BACKGROUND AND PURPOSE: There is a variety of stroke risk factors, and engaging individuals in reducing their own personal risk is hugely relevant and could be an optimal dissemination strategy. The aim of the present study was to estimate the stroke risk for specific combinations of health- and lifestyle-related factors, and to develop a personalized stroke-risk assessment tool for health professionals and the general population (called the MyRisk_Stroke Calculator). METHODS: This population-based, longitudinal study followed a historical cohort formed from the 1992 or 1998 Sante Quebec Health Surveys with information for linkage to health administrative databases. Stroke risk factors were ascertained at the time of survey, and stroke was determined from hospitalizations and death records. Cox proportional hazards models were used, modeling time to stroke in relationship to all variables. RESULTS: A total of 358 strokes occurred among a cohort of 17805 persons (men=8181) who were followed for approximately 11 years (i.e., -200000 person-years). The following regression parameters were used to produce 10-year stroke-risk estimates and assign risk points: for age (1 point/year after age 20 years), male sex (3 points), low education (4 points), renal disease (8 points), diabetes (7 points), congestive heart failure (5 points), peripheral arterial disease (2 points), high blood pressure (2 points), ischemic heart disease (1 point), smoking (8 points), >7 alcoholic drinks per week (3 points), low physical activity (2 points), and indicators of anger (4 points), depression (4 points), and anxiety (3 points). According to MyRisk_Stroke Calculator, a person with 75%, respectively. CONCLUSIONS: The MyRisk_Stroke Calculator is a simple method of disseminating information to the general population about their stroke risk.

What kind of medical equations and decision trees do physicians want in their daily activities? : Analysis of one-year MedCalc 3000(R) log data / 대한의료정보학회지

OBJECTIVE: Medical personnel require many evidence-based medical equations and decision trees for their daily medical practice, medical education and research. Among the hundreds of medical equations, the essential or frequently used equations are not revealed yet. We tried to reveal the most frequently used medical equations and decision trees. METHODS: A Korean version of medical equation tool was implemented on the Intranet, which provides 288 medical equations and decision trees. One year after implementation of the system, the log file was analyzed for the use status. RESULTS: Of the 288 equations and decision trees, 170 items were visited more than once. The creatinine estimation equation was most frequently used (545 times, 18.7%). Body mass index, Apache II score, diabetes screening decision tree, and unit conversion were followed. CONCLUSIONS: We found the frequently used medical equations and decision trees in practice by analyzing the server log file. The list would be a reference for incorporation of selected equations into a computerized prescriber-order entry system.