A pilot project informing the design of a web-based dynamic nomogram in order to predict survival one year after hip fracture surgery (Preprint)

BACKGROUND Hip fracture is associated with high mortality. Identification of individual risk informs anesthetic and surgical decision making and can reduce the risk of death. However, interpretation of data, and application of research findings can be difficult, and there is a need to simplify risk indices for clinicians and lay-people alike. Results Twenty-four (7.3%) patients died within 30 days, 65 (19.8%) within 120 days and 94 (28.6%) within 365 days of surgery. Independent predictors of mortality common to all models were admission Age, BMI, and creatinine, lactate and their combination. Age and BMI inversely correlated with mortality. Presentation with a creatinine level of 90 mol.L-1 increased the odds of death OR 2.9 (1.4 - 6.0) 365 days after surgery compared to an admission level of 60 mol. L-1 Presentation with a plasma lactate level of 2 mmol. L-1 increased the odds of death OR 2.2 (1.1 - 4.5) 365 days after surgery compared to a plasma lactate level of 1 mmol. L-1. Patients presenting to hospital with a BMI of 30 kg.m-2 were less likely to die within 365 days OR 0.41 (0.17 - 0.99) after surgery compared to patients with a BMI of 20 kg.m-2. We presented four models in Shiny. Data entry created Kaplan-Meier graphs and outcome measures (95%CI). Conclusion We developed easy to read and interpretable web-based nomograms for prediction of survival after hip fracture surgery. OBJECTIVE Our primary objective was to develop a web-based nomogram for prediction of survival 365 days after fracture hip surgery. METHODS We collected data from 329 patients up to 365 days after hip fracture surgery and built four models using packages in RStudio. A global Cox Proportional Hazards Model was developed from all covariates. Covariates included sex, age, BMI, white cell count, lactate, creatinine, hemoglobin, C-reactive protein, ASA status, socio-economic status, duration of surgery, total time in the operating room, side of surgery and procedure urgency. We also developed a Cox proportional hazards model (CPH). a logistic regression model (LRM), and a generalized linear model (GLM) for binomial response data using iterative data reduction and elimination. We wrote an app in Shiny in order to present the models in a user-friendly way. The app consists of a drop-down box for model selection, horizontal sliders for data entry, model summaries, and prediction and survival plots. A slider selects patient follow-up over 365 days. RESULTS Twenty-four (7.3%) patients died within 30 days, 65 (19.8%) within 120 days and 94 (28.6%) within 365 days of surgery. Independent predictors of mortality common to all models were admission Age, BMI, and creatinine, lactate and their combination. Age and BMI inversely correlated with mortality. Presentation with a creatinine level of 90 mol.L-1 increased the odds of death OR 2.9 (1.4 - 6.0) 365 days after surgery compared to an admission level of 60 mol. L-1 Presentation with a plasma lactate level of 2 mmol. L-1 increased the odds of death OR 2.2 (1.1 - 4.5) 365 days after surgery compared to a plasma lactate level of 1 mmol. L-1. Patients presenting to hospital with a BMI of 30 kg.m-2 were less likely to die within 365 days OR 0.41 (0.17 - 0.99) after surgery compared to patients with a BMI of 20 kg.m-2. We presented four models in Shiny. Data entry created Kaplan-Meier graphs and outcome measures (95%CI). CONCLUSIONS We developed easy to read and interpretable web-based nomograms for prediction of survival after hip fracture surgery. CLINICALTRIAL Nil

KORELASI KADAR LAKTAT DARAH DENGAN DERAJAT FUNGSIONAL BERDASARKAN NIHSS PADA PASIEN STROKE TROMBOTIK AKUT

Recently, lactate has been recognized as energy resources for neuron metabolism. According to ANLS hypothesis, glucose being particularly uptaken by astrocyte is eventually metabolized via glycolisis. Lactate produced in astrocyte is then released into extracelluler matrix and uptaken by neuron then converted into pyruvate that used in oxydative metabolism. That proccess is resulted more ATP than that of conventional theory. A few in vitro studies has demonstrated that there is an increased of ATP in neuron at hypoxic condition, agreed with ANLS hypothesis. This study was aimed to learn the correlation between plasma lactate level and functional scale in acute thrombotic stroke patients. Forty patients with acute thrombotic stroke were admitted to neurology ward, dr. Soetomo General Hospital Surabaya in May until July 2013. Those patients had been examined for plasma lactate level using lactate-oxydase colorimetric method and functional scale by NIHSS (National Institute of Health Stroke Scale). The results showed that mean of age was 58,98 ± 11,91 years old, plasma lactate level was 1,51 ± 0,47 mmol/L, and mean of NIHSS was 6,83 ± 2,978. There was negative correlation between plasma lactate level and functional scale measured by NIHSS in acute thrombotic stroke patients, which was statistically significant (r = - 0,366 and p = 0,020).

Use of plasma lactate level to predict 28-day mortality in non-elderly and elderly sepsis patients based on the MIMIC-III database

Purpose: We co mpared the use of lactate level for predicting 28-day mortality in non-elderly (<65 years) and elderly (≥65 years) sepsis patients who were admitted to an intensive care unit (ICU). A multivariate logistic regression model was established to predict 28-day mortality for each group. Methods: This retrospective study used the Medical Information Mart for Intensive Care Ⅲ, a publicly available database of ICUs. Eligible sepsis patients were at least 18 years-old, hospitalized for at least 24 h, and had lactate levels measured in the ICU. Univariate logistic regression analysis and step-wise multivariable logistic regression models were used to identify factors associated with 28-day mortality. Results: The 28-day mortality was 30.9% among the 2482 patients, and was significantly greater in elderly than non-elderly patients. Within each age group, the lactate level was greater for non-survivors than survivors. Among non-survivors, the lactate level was significantly higher for the non-elderly than the elderly. Adjusted logistic regression analysis showed that non-elderly patients with lactate levels of 2.0–4.0 mmol/L and above 4.0 mmol/L had greater risk of death than those with normal lactate levels. For all patients, the stepwise logistic regression model had an area under the receiver operating curve (AUROC) of 0.752; for non-elderly patients, the model had an AUROC of 0.793; for elderly patients, the model had an AUROC of 0.711. The Hosmer-Lemeshow test indicated acceptable goodness-of-fit for each group (P=0.206, P=0.646, and P= 0.482, respectively). Conclusion: In our population of sepsis patients, the lactate level was about 0.9 mmol/L lower in elderly non-survivors than non-elderly survivors. A plasma lactate level above 2.0 mmol/L was an independent risk factor for death at 28-days among non-elderly patients. Our logistic regression models effectively predicted 28-day mortality of sepsis patients in different age groups.

Use of plasma lactate level to predict 28-day mortality in non-elderly and elderly sepsis patients based on the MIMIC-III database

Purpose We compared the use of lactate level for predicting 28-day mortality in non-elderly (<65 years) and elderly (≥65 years) sepsis patients who were admitted to an intensive care unit (ICU). Methods This retrospective study used the Medical Information Mart for Intensive Care III, a publicly available database of ICUs. Eligible sepsis patients were at least 18 years-old, hospitalized for at least 24 h, and had lactate levels measured in the ICU. The relationship of lactate level with 28-day mortality was determined. Results The 28-day mortality was 30.9% among the 2482 patients, and was significantly greater in elderly than non-elderly patients. Within each age group, the lactate level was greater for non-survivors than survivors. Among non-survivors, the lactate level was significantly higher for the non-elderly than the elderly. Adjusted logistic regression analysis showed that elderly and non-elderly patients with lactate levels of 2.0–4.0 mmol/L and above 4.0 mmol/L had greater risk of death than those with normal lactate. Cirrhosis, chronic renal failure, and malignancy were independent risk factors for 28-day mortality in each age group. Based on a lactate cut-off level of 2.1 mmol/L, the area under the receiver operating characteristic curve was 0.628 (overall), 0.707 (non-elderly), and 0.585 (elderly). Conclusion In our population of sepsis patients, a plasma lactate level above 2.0 mmol/L was an independent risk factor for death at 28-days. The lactate level among elderly non-survivors was about 0.9 mmol/L lower than among non-elderly survivors. Lactate was a better prognostic indicator for non-elderly than elderly patients.