MO994POST-TRANSPLANT DIABETES MELLITUS PREDICTORS AFTER PANCREAS-KIDNEY TRANSPLANT

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Maria Do Mar Menezes ◽  
Miguel Bigotte Vieira ◽  
Filipa Mendes ◽  
Ana Messias ◽  
Nuno Moreira Fonseca ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Hospital Discharge ◽  
Regression Models ◽  
Ldl Cholesterol ◽  
Diabetes Duration ◽  
P Value ◽  
C Peptide ◽  
Logistic Regression Models ◽  
Post Transplant

Abstract Background and Aims Pancreas-kidney transplantation (PKT) is an established treatment for selected patients with type 1 diabetes mellitus (T1DM) with either advanced or end-stage chronic kidney disease. We aimed to evaluate predictors for post-transplant diabetes mellitus (PTDM) at 24 months of follow-up after PKT. Method We analysed a longitudinal cohort of patients with chronic kidney disease and T1DM who underwent PKT at a tertiary referral centre from January 2011 to December 31, 2017. PTDM (post-transplant diabetes mellitus) was defined as the persistent need for pharmacologic treatment of diabetes mellitus after transplant. Continuous variables were recorded as means (±SD) or as medians (25-75% interquartile range), accordingly to data distribution. Categorical variables were recorded as proportions. Comparisons were made using t-tests, Wilcoxon rank-sum tests, or X2 test as appropriate. Unadjusted and adjusted multivariate logistic regression models were fitted to identify risk factors for PTDM at 24 months of follow-up. STATA 14.2 statistical package was used and p <0.05 was considered statistically significant. Results From a total of 72 patients who underwent PKT during the study period, 47 patients completed at least 24 months of follow-up. The mean age at transplantation was 37±8 years, 30 (64%) were male, 43 (91%) were white and 4 (9%) were black. At 24-months of follow-up, the prevalence of diabetes mellitus was 28% (13/47). Number of mismatches, accumulated prednisolone dose, tacrolimus levels, previous rejection episodes, body mass index, cytomegalovirus status, serum creatinine, lipase, amilase at discharge were not associated with PTDM. Patients with persistent diabetes at 24-months of follow-up had a significantly longer pretransplant diabetes duration (29±10 versus 23±6 years; p-value = 0.026), had higher pretransplant LDL-cholesterol (137±46 versus 100±27 years; p-value = 0.003), and lower C-peptide at post-transplant hospital discharge (3.0 [2.0-3.3] versus 5.8 [4.5-6.5]; p-value = 0.004). Likewise, in univariate logistic regression models, longer diabetes duration and higher pretransplant LDL-cholesterol were found to be risk factors for PTDM at 24-months (OR 1.11, CI95% 1.00-1.22, p-value = 0.041; OR 1.03, CI95% 1.01-1.06, p-value = 0.014; respectively), while higher C-peptide at post-transplant hospital discharge was found to be protector (OR 1.03, CI95% 1.01-1.06, p-value = 0.014). In a multivariate model including age, pretransplant diabetes duration, pretransplant LDL-cholesterol, and C-peptide at post-transplant hospital discharge, only C-peptide at post-transplant hospital discharge remained significant (OR: 0.41, CI95% 0.18-0.95, p-value = 0.04). Conclusion Despite previous results in other studies, and new data researched, in our multivariate model, only lower C-peptide at post-transplant hospital discharge revealed being a predictor of PTDM after PKT.

scholarly journals Ethnicity and Neonatal Lupus Erythematosus Manifestations Risk in a Large Multi-Ethnic Cohort

2021 ◽  
pp. jrheum.201338
Author(s):  
Talia Diaz ◽  
Daniela Dominguez ◽  
Edgar Jaeggi ◽  
Andrea Knight ◽  
Carl A. Laskin ◽  
...  
Keyword(s):  
Lupus Erythematosus ◽  
Regression Models ◽  
Disease Status ◽  
P Value ◽  
Neonatal Lupus ◽  
Neonatal Lupus Erythematosus ◽  
Exact Test ◽  
Logistic Regression Models ◽  
Multiethnic Cohort

Objective To evaluate the association between ethnicity and neonatal lupus erythematosus (NLE), as well as specific NLE manifestations in a large multi-ethnic population. Methods We conducted a cohort study of the children (≤1 year of age) seen in the NLE clinic at SickKids, between January 2011 and April 2019. The cohort was divided into European, non-European and Mixed European–Non-European groups according to parent reported child’s ethnicity (Canada census categories). Outcomes were NLE and specific NLE manifestations (cardiac, cutaneous, cytopenias, transaminitis and macrocephaly). The frequency of NLE and specific manifestations were compared between ethnic groups (Fisher’s exact test). We tested the association between ethnicity and 1) NLE risk and 2) specific NLE manifestations with logistic regression models, including covariates for child’s sex, maternal rheumatic disease status during pregnancy, and maternal use of antimalarials during pregnancy (multiple comparisons threshold p-value<0.008). Results We included 324 children born to 270 anti-Ro antibody positive mothers. Median age at first visit: 1.8 months (IQR: 1.4, 2.3 months). Median follow-up time: 12 months (IQR: 2,24months). The majority were non-European (48%), with 34% European, and 18% Mixed European–Non-European. There was no significant association between non-European ethnicity (OR 1.14, 95% CI:0.69-1.89, p=0.59), Mixed European-Non-European ethnicity (OR 1.06, 95% CI:0.55-2.06, p=0.84) and NLE risk compared with European ethnicity. We also did not find an association between ethnicity and specific NLE manifestations, in univariate or multivariable adjusted models. Conclusion In a large multiethnic cohort, there was no association between child’s ethnicity and NLE risk, nor specific NLE manifestations.

Pro-Neurotensin/Neuromedin N and Risk of Incident Metabolic Syndrome and Diabetes Mellitus in the REGARDS Cohort

2021 ◽  
Author(s):  
Charles D Nicoli ◽  
April P Carson ◽  
Timothy B Plante ◽  
D Leann Long ◽  
Leslie A McClure ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Racial Differences ◽  
Regression Models ◽  
Logistic Regression Models ◽  
Low Hdl ◽  
Regards Study ◽  
Neuromedin N

Abstract Context The peptide neurotensin is implicated in insulin resistance, diabetes mellitus (DM), and cardiovascular disease. Objective We studied the association of neurotensin’s stable precursor, pro-neurotensin/neuromedin N (pro-NT/NMN) with incident metabolic syndrome (MetS) and DM. Design/Setting/Participants We included 3,772 participants from the REasons for Geographic And Racial Differences in Stroke (REGARDS) study who completed the baseline exam (2003-2007), the follow-up exam (2013-2016), and had pro-NT/NMN measured by immunoassay. Weighted logistic regression models were fitted to incident DM, incident MetS, and each MetS component, separately, incorporating demographics, metabolic risk factors, HOMA-IR, and diet scores. Main Outcome Measures Incident MetS was defined by ≥3 harmonized criteria at follow-up in those with &lt;3 at baseline. Incident DM was defined by use of hypoglycemic drugs/insulin, fasting glucose ≥126 mg/dL, or random glucose ≥200 mg/dL, in those without these at baseline. Results Median [IQR] plasma pro-NT/NMN was 160 [118-218] pmol/L. 564 (of 2,770 without baseline MetS) participants developed MetS and 407 (of 3,030 without baseline DM) developed DM. Per standard deviation (SD) higher log-Pro-NT/NMN, the demographic-adjusted odds ratio (OR) and 95% confidence interval (CI) of incident MetS was 1.22 (1.11-1.35); 1.16 (1.00-1.35) for incident low HDL, and 1.25 (1.11-1.40) for incident dysglycemia. The association of pro-NT/NMN with MetS was attenuated in the model adding HOMA-IR (OR per SD log-pro-NT/NMN 1.14, 95% CI 1.00-1.30). There was no association with incident DM (OR per SD log-pro-NT/NMN 1.06, 95% CI 0.94-1.19). Conclusions Pro-NT/NMN was associated with MetS and two components, dysglycemia and low HDL, likely explained by insulin resistance.

scholarly journals Diabetes mellitus as a risk factor for compression neuropathy: a longitudinal cohort study from southern Sweden

2020 ◽  
Vol 8 (1) ◽  
pp. e001298 ◽  
Author(s):  
Mattias Rydberg ◽  
Malin Zimmerman ◽  
Anders Gottsäter ◽  
Peter M Nilsson ◽  
Olle Melander ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factor ◽  
Plasma Glucose ◽  
Regression Models ◽  
Cox Regression ◽  
Binary Logistic Regression ◽  
Population Based ◽  
Logistic Regression Models ◽  
Increased Risk

IntroductionCompression neuropathies (CN) in the upper extremity, the most common being carpal tunnel syndrome (CTS) and ulnar nerve entrapment (UNE), are frequent among patients with diabetes mellitus (DM). Earlier studies have shown contradicting results regarding DM as a risk factor for CN. Thus, the aim of the present population-based, longitudinal study was to explore potential associations between DM, CTS, and UNE during long-term follow-up.Research design and methodsA total of 30 466 participants aged 46–73 years, included in the population-based Malmö Diet and Cancer Study during 1991–1996, were followed up in Swedish national registries regarding incident CTS and UNE until 2016. Associations between prevalent DM at baseline and incident CTS or UNE were calculated using Cox proportional hazard models, adjusted for baseline confounders, such as sex, age at study entry, smoking, hypertension, use of antihypertensive treatment, alcohol consumption, and body mass index (BMI). HbA1c and fasting plasma glucose levels had been measured at baseline in a subgroup of 5508 participants and were related to incident CTS and UNE in age and sex-adjusted binary logistic regression models.ResultsA total of 1081 participants developed CTS and 223 participants developed UNE during a median follow-up of 21 years. Participants with incident CTS or UNE had higher prevalence of DM and higher BMI at baseline. Using multivariate Cox regression models, prevalent DM at baseline was independently associated with both incident CTS (HR 2.10; 95% CI 1.65 to 2.70, p<0.0001) and incident UNE (HR 2.20; 95% CI 1.30 to 3.74, p=0.003). Higher levels of HbA1c and plasma glucose were associated with an increased risk for CTS, but not for UNE.ConclusionThis study establishes DM as a major risk factor in the development of both CTS and UNE. Furthermore, a higher BMI is associated with both CTS and UNE. Finally, hyperglycemia seems to affect the median and ulnar nerves differently.

The impact of SPY angiography on intraoperative decision making and outcomes for post-mastectomy reconstruction

2019 ◽  
pp. 1-5
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Skin Necrosis ◽  
Regression Models ◽  
Multivariable Analysis ◽  
P Value ◽  
Flap Necrosis ◽  
Single Institution ◽  
Logistic Regression Models ◽  
The Impact

Objective: While the use of intraoperative laser angiography (SPY) is increasing in mastectomy patients, its impact in the operating room to change the type of reconstruction performed has not been well described. The purpose of this study is to investigate whether SPY angiography influences post-mastectomy reconstruction decisions and outcomes. Methods and materials: A retrospective analysis of mastectomy patients with reconstruction at a single institution was performed from 2015-2017.All patients underwent intraoperative SPY after mastectomy but prior to reconstruction. SPY results were defined as ‘good’, ‘questionable’, ‘bad’, or ‘had skin excised’. Complications within 60 days of surgery were compared between those whose SPY results did not change the type of reconstruction done versus those who did. Preoperative and intraoperative variables were entered into multivariable logistic regression models if significant at the univariate level. A p-value <0.05 was considered significant. Results: 267 mastectomies were identified, 42 underwent a change in the type of planned reconstruction due to intraoperative SPY results. Of the 42 breasts that underwent a change in reconstruction, 6 had a ‘good’ SPY result, 10 ‘questionable’, 25 ‘bad’, and 2 ‘had areas excised’ (p<0.01). After multivariable analysis, predictors of skin necrosis included patients with ‘questionable’ SPY results (p<0.01, OR: 8.1, 95%CI: 2.06 – 32.2) and smokers (p<0.01, OR:5.7, 95%CI: 1.5 – 21.2). Predictors of any complication included a change in reconstruction (p<0.05, OR:4.5, 95%CI: 1.4-14.9) and ‘questionable’ SPY result (p<0.01, OR: 4.4, 95%CI: 1.6-14.9). Conclusion: SPY angiography results strongly influence intraoperative surgical decisions regarding the type of reconstruction performed. Patients most at risk for flap necrosis and complication post-mastectomy are those with questionable SPY results.

Demographic factors associated with missed follow-up among solid tumor patients treated at a large multi-site academic institution

2020 ◽  
Vol 16 (32) ◽  
pp. 2635-2643
Author(s):  
Samantha L Freije ◽  
Jordan A Holmes ◽  
Saleh Rachidi ◽  
Susannah G Ellsworth ◽  
Richard C Zellars ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Odds Ratio ◽  
Regression Models ◽  
Tumor Patients ◽  
Logistic Regression Models ◽  
Factors Associated ◽  
Follow Up Care ◽  
Risk Patients ◽  
African American Race

Aim: To identify demographic predictors of patients who miss oncology follow-up, considering that missed follow-up has not been well studies in cancer patients. Methods: Patients with solid tumors diagnosed from 2007 to 2016 were analyzed (n = 16,080). Univariate and multivariable logistic regression models were constructed to examine predictors of missed follow-up. Results: Our study revealed that 21.2% of patients missed ≥1 follow-up appointment. African–American race (odds ratio [OR] 1.33; 95% CI: 1.17–1.51), Medicaid insurance (OR 1.59; 1.36–1.87), no insurance (OR 1.66; 1.32–2.10) and rural residence (OR 1.78; 1.49–2.13) were associated with missed follow-up. Conclusion: Many cancer patients miss follow-up, and inadequate follow-up may influence cancer outcomes. Further research is needed on how to address disparities in follow-up care in high-risk patients.

scholarly journals Low HbA1c levels and all-cause or cardiovascular mortality among people without diabetes: the US National Health and Nutrition Examination Survey 1999–2015

2020 ◽  
Author(s):  
Kosuke Inoue ◽  
Roch Nianogo ◽  
Donatello Telesca ◽  
Atsushi Goto ◽  
Vahe Khachadourian ◽  
...  
Keyword(s):  
Cardiovascular Mortality ◽  
Regression Models ◽  
Machine Learning Algorithms ◽  
Logistic Regression Models ◽  
Health And Nutrition ◽  
Increased Risk ◽  
The Us ◽  
All Cause Mortality ◽  
Hba1c Levels

Abstract Objective It is unclear whether relatively low glycated haemoglobin (HbA1c) levels are beneficial or harmful for the long-term health outcomes among people without diabetes. We aimed to investigate the association between low HbA1c levels and mortality among the US general population. Methods This study includes a nationally representative sample of 39 453 US adults from the National Health and Nutrition Examination Surveys 1999–2014, linked to mortality data through 2015. We employed the parametric g-formula with pooled logistic regression models and the ensemble machine learning algorithms to estimate the time-varying risk of all-cause and cardiovascular mortality by HbA1c categories (low, 4.0 to &lt;5.0%; mid-level, 5.0 to &lt;5.7%; prediabetes, 5.7 to &lt;6.5%; and diabetes, ≥6.5% or taking antidiabetic medication), adjusting for 72 potential confounders including demographic characteristics, lifestyle, biomarkers, comorbidities and medications. Results Over a median follow-up of 7.5 years, 5118 (13%) all-cause deaths, and 1116 (3%) cardiovascular deaths were observed. Logistic regression models and machine learning algorithms showed nearly identical predictive performance of death and risk estimates. Compared with mid-level HbA1c, low HbA1c was associated with a 30% (95% CI, 16 to 48) and a 12% (95% CI, 3 to 22) increased risk of all-cause mortality at 5 years and 10 years of follow-up, respectively. We found no evidence that low HbA1c levels were associated with cardiovascular mortality risk. The diabetes group, but not the prediabetes group, also showed an increased risk of all-cause mortality. Conclusions Using the US national database and adjusting for an extensive set of potential confounders with flexible modelling, we found that adults with low HbA1c were at increased risk of all-cause mortality. Further evaluation and careful monitoring of low HbA1c levels need to be considered.

scholarly journals CANTARE: finding and visualizing network-based multi-omic predictive models

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Janet C. Siebert ◽  
Martine Saint-Cyr ◽  
Sarah J. Borengasser ◽  
Brandie D. Wagner ◽  
Catherine A. Lozupone ◽  
...  
Keyword(s):  
Random Forests ◽  
Predictive Models ◽  
Regression Models ◽  
Dynamic Range ◽  
P Value ◽  
Published Data ◽  
Logistic Regression Models ◽  
Pairwise Models ◽  
Biological Insight ◽  
Analytical Approaches

Abstract Background One goal of multi-omic studies is to identify interpretable predictive models for outcomes of interest, with analytes drawn from multiple omes. Such findings could support refined biological insight and hypothesis generation. However, standard analytical approaches are not designed to be “ome aware.” Thus, some researchers analyze data from one ome at a time, and then combine predictions across omes. Others resort to correlation studies, cataloging pairwise relationships, but lacking an obvious approach for cohesive and interpretable summaries of these catalogs. Methods We present a novel workflow for building predictive regression models from network neighborhoods in multi-omic networks. First, we generate pairwise regression models across all pairs of analytes from all omes, encoding the resulting “top table” of relationships in a network. Then, we build predictive logistic regression models using the analytes in network neighborhoods of interest. We call this method CANTARE (Consolidated Analysis of Network Topology And Regression Elements). Results We applied CANTARE to previously published data from healthy controls and patients with inflammatory bowel disease (IBD) consisting of three omes: gut microbiome, metabolomics, and microbial-derived enzymes. We identified 8 unique predictive models with AUC > 0.90. The number of predictors in these models ranged from 3 to 13. We compare the results of CANTARE to random forests and elastic-net penalized regressions, analyzing AUC, predictions, and predictors. CANTARE AUC values were competitive with those generated by random forests and  penalized regressions. The top 3 CANTARE models had a greater dynamic range of predicted probabilities than did random forests and penalized regressions (p-value = 1.35 × 10–5). CANTARE models were significantly more likely to prioritize predictors from multiple omes than were the alternatives (p-value = 0.005). We also showed that predictive models from a network based on pairwise models with an interaction term for IBD have higher AUC than predictive models built from a correlation network (p-value = 0.016). R scripts and a CANTARE User’s Guide are available at https://sourceforge.net/projects/cytomelodics/files/CANTARE/. Conclusion CANTARE offers a flexible approach for building parsimonious, interpretable multi-omic models. These models yield quantitative and directional effect sizes for predictors and support the generation of hypotheses for follow-up investigation.

scholarly journals Recommendations for Abnormal Behaviour Ethograms in Monkey Research

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1461
Author(s):  
Andrea Polanco ◽  
Brenda McCowan ◽  
Lee Niel ◽  
David L. Pearl ◽  
Georgia Mason
Keyword(s):  
Macaca Mulatta ◽  
Regression Models ◽  
Convergent Validity ◽  
P Value ◽  
Morphological Similarity ◽  
Abnormal Behaviour ◽  
Logistic Regression Models ◽  
The Third ◽  
Welfare Implications ◽  
Self Stimulation

Laboratory monkey ethograms currently include subcategories of abnormal behaviours that are based on superficial morphological similarity. Yet, such ethograms may be misclassifying behaviour, with potential welfare implications as different abnormal behaviours are likely to have distinct risk factors and treatments. We therefore investigated the convergent validity of four hypothesized subcategories of abnormal behaviours (‘motor’, e.g., pacing; ‘self-stimulation’, e.g., self-sucking; ‘postural’, e.g., hanging; and ‘self-abuse’, e.g., self-biting). This hypothesis predicts positive relationships between the behaviours within each subcategory. Rhesus macaque (Macaca mulatta) data on 19 abnormal behaviours were obtained from indoor-housed animals (n = 1183). Logistic regression models, controlling for sex, age, and the number of observations, revealed that only 1/6 ‘motor’ behaviours positively predicted pacing, while 2/3 ‘self-abuse’ behaviours positively predicted self-biting (one-tailed p-value < 0.05). Furthermore, ‘self-stimulation’ behaviours did not predict self-sucking, and none of the ‘postural’ behaviours predicted hanging. Thus, none of the subcategories fully met convergent validity. Subsequently, we created four new valid subcategories formed of comorbid behaviours. The first consisted of self-biting, self-hitting, self-injurious behaviour, floating limb, leg-lifting, and self-clasping. The second comprised twirling, bouncing, rocking, swinging, and hanging. The third comprised pacing and head-twisting, while the final subcategory consisted of flipping and eye-poking. Self-sucking, hair-plucking, threat-biting, and withdrawn remained as individual behaviours. We encourage laboratories to replicate the validation of these subcategories first, and for scientists working with other species to validate their ethograms before using them in welfare assessments.

scholarly journals The Differential Effects of Caregiving Intensity on Overnight Hospitalization in the Previous 2 Years

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 76-76
Author(s):  
Kylie Meyer ◽  
Zachary Gassoumis ◽  
Kathleen Wilber
Keyword(s):  
Health Services ◽  
Fixed Effects ◽  
Regression Models ◽  
P Value ◽  
Logistic Regression Models ◽  
Spousal Caregiving ◽  
Health Insurance Status ◽  
Race Ethnicity ◽  
Self Assessed Health ◽  
Retirement Study

Abstract Caregiving for a spouse is considered a major stressor many Americans will encounter during their lifetimes. Although most studies indicate caregiving is associated with experiencing diminished health outcomes, little is known about how this role affects caregivers’ use of acute health services. To understand how spousal caregiving affects the use of acute health services, we use data from the Health and Retirement Study. We apply fixed effects (FE) logistic regression models to examine odds of experiencing an overnight hospitalization in the previous two years according to caregiving status, intensity, and changes in caregiving status and intensity. Models controlled for caregiver gender, age, race, ethnicity, educational attainment, health insurance status, the number of household residents, and self-assessed health. Overall, caregivers were no more likely to experience an overnight hospitalization compared to non-caregivers (OR 0.92; CI 0.84 to 1.00; p-value=0.057). However, effects varied according to the intensity of caregiving and the time spent in this role. Compared to non-caregivers, for example, spouses who provided care to someone with no need for assistance with activities of daily living had lower odds of experiencing a hospitalization (OR 0.77; CI 0.66 to 0.89). In contrast, caregivers who provided care to someone with dementia for 4 to &lt;6 years had 3.29 times the odds of experiencing an overnight hospitalization (CI 1.04 to 10.38; p-value=0.042). Findings indicate that, although caregivers overall appear to use acute health services about as much as non-caregivers, large differences exist between caregivers. Results emphasize the importance of recognizing diversity within caregiving experiences.

scholarly journals Ethnic differences in the incidence of pterygium in a multi-ethnic Asian population: the Singapore Epidemiology of Eye Diseases Study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiao Ling Fang ◽  
Crystal Chun Yuen Chong ◽  
Sahil Thakur ◽  
Zhi Da Soh ◽  
Zhen Ling Teo ◽  
...  
Keyword(s):  
Ethnic Differences ◽  
Regression Models ◽  
Multivariable Analysis ◽  
Anterior Segment ◽  
Asian Population ◽  
Eye Diseases ◽  
Logistic Regression Models ◽  
Income Status ◽  
Baseline Visit

AbstractWe evaluated the 6-year incidence and risk factors of pterygium in a multi-ethnic Asian population. Participants who attended the baseline visit of the Singapore Epidemiology of Eye Diseases Study (year 2004–2011) and returned six years later, were included in this study. Pterygium was diagnosed based on anterior segment photographs. Incident pterygium was defined as presence of pterygium at 6-year follow-up in either eye, among individuals without pterygium at baseline. Multivariable logistic regression models were used to determine factors associated with incident pterygium, adjusting for baseline age, gender, ethnicity, body mass index, occupation type, educational level, income status, smoking, alcohol consumption, presence of hypertension, diabetes and hyperlipidemia. The overall age-adjusted 6-year incidence of pterygium was 1.2% (95% confidence interval [CI] 1.0–1.6%); with Chinese (1.9%; 95% CI 1.4%-2.5%) having the highest incidence rate followed by Malays (1.4%; 95% CI 0.9%-2.1%) and Indians (0.3%; 95% CI 0.3–0.7%). In multivariable analysis, Chinese (compared with Indians; odds ratio [OR] = 4.21; 95% CI 2.12–9.35) and Malays (OR 3.22; 95% CI 1.52–7.45), male (OR 2.13; 95% CI 1.26–3.63), outdoor occupation (OR 2.33; 95% CI 1.16–4.38), and smoking (OR 0.41; 95% CI 0.16–0.87) were significantly associated with incident pterygium. Findings from this multi-ethnic Asian population provide useful information in identifying at-risk individuals for pterygium.

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