Can Patients with Dementia Be Identified in Primary Care Electronic Medical Records Using Natural Language Processing?

Dementia and mild cognitive impairment can be underrecognized in primary care practice and research. Free-text fields in electronic medical records (EMRs) are a rich source of information which might support increased detection and enable a better understanding of populations at risk of dementia. We used natural language processing (NLP) to identify dementia-related features in EMRs and compared the performance of supervised machine learning models to classify patients with dementia. We assembled a cohort of primary care patients aged 66 + years in Ontario, Canada, from EMR notes collected until December 2016: 526 with dementia and 44,148 without dementia. We identified dementia-related features by applying published lists, clinician input, and NLP with word embeddings to free-text progress and consult notes and organized features into thematic groups. Using machine learning models, we compared the performance of features to detect dementia, overall and during time periods relative to dementia case ascertainment in health administrative databases. Over 900 dementia-related features were identified and grouped into eight themes (including symptoms, social, function, cognition). Using notes from all time periods, LASSO had the best performance (F1 score: 77.2%, sensitivity: 71.5%, specificity: 99.8%). Model performance was poor when notes written before case ascertainment were included (F1 score: 14.4%, sensitivity: 8.3%, specificity 99.9%) but improved as later notes were added. While similar models may eventually improve recognition of cognitive issues and dementia in primary care EMRs, our findings suggest that further research is needed to identify which additional EMR components might be useful to promote early detection of dementia. Supplementary Information: The online version contains supplementary material available at 10.1007/s41666-023-00125-6.

Developing a reference standard for pertussis by applying a stratified sampling strategy to electronic medical record data.

PURPOSE: Pertussis surveillance remains essential in Canada, but ascertainment bias limits the accuracy of surveillance data. Introducing other sources to improve detection has highlighted the importance of validation. However, challenges arise due to low prevalence, and oversampling suspected cases can introduce partial verification bias. The aim of this study was to build a reference standard for pertussis validation studies that provides adequate analytic precision and minimizes bias. METHODS: We used a stratified strategy to sample the reference standard from a primary care electronic medical record cohort. We incorporated abstractor notes into definite, possible, ruled-out, and no mention of pertussis classifications which were based on surveillance case definitions. RESULTS: We abstracted eight hundred records from the cohort of 404,922. There were 208 (26%) definite and 261 (32.6%) possible prevalent pertussis cases. Classifications demonstrated a wide variety of case severities. Abstraction reliability was moderate to substantial based on Cohen's kappa and raw percent agreement. CONCLUSIONS: When conducting validation studies for pertussis and other low prevalence diseases, this stratified sampling strategy can be used to develop a reference standard using limited resources. This approach mitigates verification and spectrum bias while providing sufficient precision and incorporating a range of case severities.

Validating pertussis data measures using electronic medical record data in Ontario, Canada 1986-2016.

Background: Pertussis is a reportable disease in many countries, but ascertainment bias has limited data accuracy. This study aims to validate pertussis data measures using a reference standard that incorporates different suspected case severities, allowing for the impact of case severity on accuracy and detection to be explored. Methods: We evaluated 25 pertussis detection algorithms in a primary care electronic medical record database between January 1, 1986 and December 30, 2016. We estimated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). We used sensitivity analyses to explore areas of uncertainty and evaluated reasons for lack of detection. Results: The algorithm including all data measures achieved the highest sensitivity at 20.6%. Sensitivity increased to 100% after reclassifying symptom-only cases as non-cases, but the PPV remained low. Age at first episode was significantly associated with detection in half of the tested scenarios, and false negatives often had some history of immunization. Conclusions: Sensitivity improved by reclassifying symptom-only cases but remained low unless multiple data sources were used. Results demonstrate a trade-off between PPV and sensitivity. EMRs can enhance detection through patient history and clinical note data. It is essential to improve case identification of older individuals with vaccination history to reduce ascertainment bias.

Development of algorithms to identify individuals with Neurofibromatosis type 1 within administrative data and electronic medical records in Ontario, Canada.

BACKGROUND: There is limited population-based data on Neurofibromatosis type 1 (NF1) in North America. We aimed to develop and validate algorithms using administrative health data and electronic medical records (EMRs) to identify individuals with NF1 in Ontario, Canada. METHODS: We conducted an electronic free-text search of 15 commonly-used terms related to NF1 in the Electronic Medical Records Primary Care Database. Records were reviewed by two trained abstractors who classified them as confirmed, possible, and not NF1. An investigator with clinical expertise performed final NF1 classification. Patients were classified as confirmed if there was a documented diagnosis, meeting NIH criteria. Patients were classified as possible if (1) NF1 was recorded in the cumulative patient profile, but no clinical information to support the diagnosis; (2) only one criterion for diagnosis (e.g. child of confirmed case) but no further data to confirm or rule out. We tested different combinations of outpatient and inpatient billing codes, and applied a free-text search algorithm to identify NF1 cases in administrative data and EMRs, respectively. RESULTS: Of 273,440 eligible patients, 2,058 had one or more NF1 terms in their medical records. The terms "NF", "café-au-lait", or "sheath tumour" were constrained to appear in combination with another NF1 term. This resulted in 837 patients: 37 with possible and 71 with confirmed NF1. The population prevalence ranged from 1 in 3851 (confirmed NF1) to 1 in 2532 (possible and confirmed NF1). Billing code algorithms had poor performance, with overall low PPV (highest being 71%). The accuracy of the free-text EMR algorithm in identifying patients with NF1 was: sensitivity 85% (95% CI 74-92%), specificity 100% (95% CI 100-100%), positive predictive value 80% (95% CI 69-88%), negative predictive value 100% (95% CI 100-100%), and false positive rate 20% (95% CI 11-33%). Of false positives, 53% were possible NF1. CONCLUSIONS: A free-text search algorithm within the EMR had high sensitivity, specificity and predictive values. Algorithms using billing codes had poor performance, likely due to the lack of NF-specific codes for outpatient visits. While NF1 ICD-9 and 10 codes are used for hospital admissions, only ~ 30% of confirmed NF1 cases had a hospitalization associated with an NF1 code.

Development and validation of an ensemble machine learning framework for detection of all-cause advanced hepatic fibrosis: a retrospective cohort study.

BACKGROUND: Cirrhosis is the result of advanced scarring (or fibrosis) of the liver, and is often diagnosed once decompensation with associated complications has occurred. Current non-invasive tests to detect advanced liver fibrosis have limited performance, with many indeterminate classifications. We aimed to identify patients with advanced liver fibrosis of all-causes using machine learning algorithms (MLAs). METHODS: In this retrospective study of routinely collected laboratory, clinical, and demographic data, we trained six MLAs (support vector machine, random forest classifier, gradient boosting classifier, logistic regression, artificial neural network, and an ensemble of all these algorithms) to detect advanced fibrosis using 1703 liver biopsies from patients seen at the Toronto Liver Clinic (TLC) between Jan 1, 2000, and Dec 20, 2014. Performance was validated using five datasets derived from patient data provided by the TLC (n=104 patients with a biopsy sample taken between March 24, 2014, and Dec 31, 2017) and McGill University Health Centre (MUHC; n=404). Patients with decompensated cirrhosis were excluded. Performance was benchmarked against aspartate aminotransferase-to-platelet ratio index (APRI), fibrosis-4 index (FIB-4), non-alcoholic fatty liver disease fibrosis score (NFS), transient elastography, and an independent panel of five hepatology experts (MB, GS, HK, KP, and RSK). MLA performance was evaluated using the area under the receiver operating characteristic curve (AUROC) and the percentage of determinate classifications. FINDINGS: The best MLA was an ensemble algorithm of support vector machine, random forest classifier, gradient boosting classifier, logistic regression, and neural network algorithms, which achieved 100% determinate classifications (95% CI 100·0-100·0), an AUROC score of 0·870 (95% CI 0·797-0·931) on the TLC validation set (fibrosis stages F0 and F1 vs F4), and an AUROC of 0·716 (95% CI 0·664-0·766) on the MUHC validation set (fibrosis stages F0, F1, and F2 vs F3 and F4). The ensemble MLA outperformed all routinely used biomarkers and achieved comparable performance to hepatologists as measured by AUROC and percentage of indeterminate classifications in both the TLC validation dataset (APRI AUROC score 0·719 [95% CI 0·611-0·820], 83·7% determinate [95% CI 76·0-90·4]; FIB-4 AUROC score 0·825 [95% CI 0·730-0·912], 72·1% determinate [95% CI 63·5-80·8]) and the MUHC validation dataset (APRI AUROC score 0·618 [95% CI 0·548-0·691], 75·5% determinate [95% CI 71·5-79·2]; FIB-4 AUROC score 0·717 (95% CI 0·652-0·776), 75·5% determinate [95% CI 0·713-0·797]), and achieving only slightly lower AUROC than transient elastography (0·773 [95% CI 0·699-0·834] vs 0·826 [95% CI 0·758-0·889]). INTERPRETATION: We have shown that an ensemble MLA outperforms non-imaging-based methods in detecting advanced fibrosis across different causes of liver disease. Our MLA was superior to APRI, FIB-4, and NFS with no indeterminate classifications, while achieving performance comparable to an independent panel of experts. MLAs using routinely collected data could identify patients at high-risk of advanced hepatic fibrosis and cirrhosis among patients with chronic liver disease, allowing intervention before onset of decompensation. FUNDING: Toronto General Hospital Foundation.

The receipt of information by family physicians about their patient's emergency department visits: a record linkage study of electronic medical records to health administrative data.

BACKGROUND: Canadians are known to be frequent users of emergency department (ED) care. However, the exchange of information from ED visits to family physicians (FPs) is not well known. Our objectives were to determine whether Canadian FPs received information about their patient's ED visit and the patient characteristics related to the receipt of ED information. METHODS: This study was a descriptive record linkage study of FP Electronic Medical Record (EMR) data linked to health administrative data. Our study cohort included patients who had at least one ED visit in 2010 or 2015 in Ontario, Canada. An ED visit could include a transfer to or from another ED. The receipt of information from an ED note was examined in relation to patient age, sex, neighbourhood income quintiles, rurality and comorbidity. RESULTS: There were 26,609 patients in 2010 and 50,541 patients in 2015 with at least one ED visit. In 2010, 53.3% of FPs received an ED note for patients having a single ED visit compared to 41.0% in 2015. For patients with multiple ED visits, 58.2% of FPs received an ED note in 2010 compared to 45.7% in 2015. FPs were more likely to receive an ED note for patients not living in low income neighbourhoods, older patients, patients living in small urban areas and for patients having moderate comorbidity. FPs were less likely to receive a note for patients living in rural areas. CONCLUSIONS: Community-based FPs are more likely to get information after an ED visit for their older and sicker patients. However, FPs do not receive any information from EDs for over half their patients. Electronic health record technologies and their adoption by ED providers need to improve the seamless transfer of information about the care provided in EDs to FPs in the community.

Association of pre-existing comorbidities with mortality and disease severity among 167,500 individuals with COVID-19 in Canada: A population-based cohort study.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) has infected 1.9% of the world population by May 2, 2021. Since most previous studies that examined risk factors for mortality and severity were based on hospitalized individuals, population-based cohort studies are called for to provide evidence that can be extrapolated to the general population. Therefore, we aimed to examine the associations of comorbidities with mortality and disease severity in individuals with COVID-19 diagnosed in 2020 in Ontario, Canada. METHODS AND FINDINGS: We conducted a retrospective cohort study of all individuals with COVID-19 in Ontario, Canada diagnosed between January 15 and December 31, 2020. Cases were linked to health administrative databases maintained in the ICES which covers all residents in Ontario. The primary outcome is all-cause 30-day mortality after the first COVID-19 diagnosis, and the secondary outcome is a composite severity index containing death and hospitalization. To examine the risk factors for the outcomes, we employed Cox proportional hazards regression models and logistic regression models to adjust for demographic, socio-economic variables and comorbidities. Results were also stratified by age groups. A total of 167,500 individuals were diagnosed of COVID-19 in 2020 and included in the study. About half (43.8%, n = 73,378) had at least one comorbidity. The median follow-up period were 30 days. The most common comorbidities were hypertension (24%, n = 40,154), asthma (16%, n = 26,814), and diabetes (14.7%, n = 24,662). Individuals with comorbidity had higher risk of mortality compared to those without (HR = 2.80, 95%CI 2.35-3.34; p<0.001), and the risk substantially was elevated from 2.14 (95%CI 1.76-2.60) to 4.81 (95%CI 3.95-5.85) times as the number of comorbidities increased from one to five or more. Significant predictors for mortality included comorbidities such as solid organ transplant (HR = 3.06, 95%CI 2.03-4.63; p<0.001), dementia (HR = 1.46, 95%CI 1.35-1.58; p<0.001), chronic kidney disease (HR = 1.45, 95%CI 1.34-1.57; p<0.001), severe mental illness (HR = 1.42, 95%CI%, 1.12-1.80; p<0.001), cardiovascular disease (CVD) (HR = 1.22, 95%CI, 1.15-1.30), diabetes (HR = 1.19, 95%, 1.12-1.26; p<0.001), chronic obstructive pulmonary disease (COPD) (HR = 1.19, 95%CI 1.12-1.26; p<0.001), cancer (HR = 1.17, 95%CI, 1.09-1.27; p<0.001), hypertension (HR = 1.16, 95%CI, 1.07-1.26; p<0.001). Compared to their effect in older age groups, comorbidities were associated with higher risk of mortality and severity in individuals under 50 years old. Individuals with five or more comorbidities in the below 50 years age group had 395.44 (95%CI, 57.93-2699.44, p<0.001) times higher risk of mortality compared to those without. Limitations include that data were collected during 2020 when the new variants of concern were not predominant, and that the ICES databases do not contain detailed individual-level socioeconomic and racial variables. CONCLUSION: We found that solid organ transplant, dementia, chronic kidney disease, severe mental illness, CVD, hypertension, COPD, cancer, diabetes, rheumatoid arthritis, HIV, and asthma were associated with mortality or severity. Our study highlights that the number of comorbidities was a strong risk factor for deaths and severe outcomes among younger individuals with COVID-19. Our findings suggest that in addition of prioritizing by age, vaccination priority groups should also include younger population with multiple comorbidities.

The Association Between High and Unnecessary Antibiotic Prescribing: A Cohort Study Using Family Physician Electronic Medical Records.

BACKGROUND: Approximately 25% of outpatient antibiotic prescriptions are unnecessary among family physicians in Canada. Minimizing unnecessary antibiotics is key for community antibiotic stewardship. However, unnecessary antibiotic prescribing is much harder to measure than total antibiotic prescribing. We investigated the association between total and unnecessary antibiotic use by family physicians and evaluated inter-physician variability in unnecessary antibiotic prescribing. METHODS: This was a cohort study based on electronic medical records of family physicians in Ontario, Canada, between April 2011 and March 2016. We used predefined expected antibiotic prescribing rates for 23 common primary care conditions to calculate unnecessary antibiotic prescribing rates. We used multilevel Poisson regression models to evaluate the association between total antibiotic volume (number of antibiotic prescriptions per patient visit), adjusted for multiple practice- and physician-level covariates, and unnecessary antibiotic prescribing. RESULTS: There were 499 570 physician-patient encounters resulting in 152 853 antibiotic prescriptions from 341 physicians. Substantial inter-physician variability was observed. In the fully adjusted model, we observed a significant association between total antibiotic volume and unnecessary prescribing rate (adjusted rate ratio 2.11 per 10% increase in total use; 95% CI 2.05-2.17), and none of the practice- and physician-level variables were associated with unnecessary prescribing rate. CONCLUSIONS: We demonstrated substantial inter-physician variability in unnecessary antibiotic prescribing in this cohort of family physicians. Total antibiotic use was strongly correlated with unnecessary antibiotic prescribing. Total antibiotic volume is a reasonable surrogate for unnecessary antibiotic use. These results can inform community antimicrobial stewardship efforts.

An approach to estimating the environmental burden of cancer from known and probable carcinogens: application to Ontario, Canada.

BACKGROUND: Quantifying the potential cancer cases associated with environmental carcinogen exposure can help inform efforts to improve population health. This study developed an approach to estimate the environmental burden of cancer and applied it to Ontario, Canada. The purpose was to identify environmental carcinogens with the greatest impact on cancer burden to support evidence-based decision making. METHODS: We conducted a probabilistic assessment of the environmental burden of cancer in Ontario. We selected 23 carcinogens that we defined as "environmental" (e.g., pollutants) and were relevant to the province, based on select classifications provided by the International Agency for Research on Cancer. We evaluated population exposure to the carcinogens through inhalation of indoor/outdoor air; ingestion of food, water, and dust; and exposure to radiation. We obtained or calculated concentration-response functions relating carcinogen exposure and the risk of developing cancer. Using both human health risk assessment and population attributable fraction models in a Monte Carlo simulation, we estimated the annual cancer cases associated with each environmental carcinogen, reporting the simulation summary (e.g., mean and percentiles). RESULTS: We estimated between 3540 and 6510 annual cancer cases attributable to exposure to 23 environmental carcinogens in Ontario. Three carcinogens were responsible for over 90% of the environmental burden of cancer: solar ultraviolet (UV) radiation, radon in homes, and fine particulate matter (PM2.5) in outdoor air. Eight other carcinogens had an estimated mean burden of at least 10 annual cancer cases: acrylamide, arsenic, asbestos, chromium, diesel engine exhaust particulate matter, dioxins, formaldehyde, and second-hand smoke. The remaining 12 carcinogens had an estimated mean burden of less than 10 annual cancer cases in Ontario. CONCLUSIONS: We found the environmental burden of cancer in Ontario to fall between previously estimated burdens of alcohol and tobacco use. These results allow for a comparative assessment across carcinogens and offer insights into strategies to reduce the environmental burden of cancer. Our analysis could be adopted by other jurisdictions and repeated in the future for Ontario to track progress in reducing cancer burden, assess newly classified environmental carcinogens, and identify top burden contributors.

Assessing the completeness of infant and childhood immunizations within a provincial registry populated by parental reporting: A study using linked databases in Ontario, Canada.

INTRODUCTION: In Ontario, Canada, parents have the responsibility to report their child's routine infant and childhood vaccines to the provincial immunization registry (the Digital Health Immunization Repository; DHIR) without healthcare provider validation. Despite its use in routine immunization coverage monitoring, no study has previously examined the completeness of immunization data within the DHIR. METHODS: We assessed the completeness of DHIR immunizations, as compared to immunizations within the Electronic Medical Records-Primary Care (EMRPC) database, also known as EMRALD, a network of family physician electronic medical records (EMRs). We linked client records from the DHIR and EMRPC to a centralized population file. To create the study cohort, we examined children born during 2005-2008 and further defined the cohort based on those rostered to an EMRPC physician, visit criteria to ensure ongoing care by an EMRPC provider, and school attendance in Ontario at age 7. We calculated up-to-date (UTD) immunization coverage at age 7 for individual vaccines and overall using data from the DHIR and EMRPC separately, and compared the estimates. RESULTS: The analytic cohort to assess DHIR data completeness included 2,657 children. Overall UTD coverage (all vaccines assessed) was 82.0% in the DHIR and 67.6% in EMRPC. UTD coverage was higher in the DHIR for all vaccines assessed individually, with the exception of meningococcal C conjugate vaccine (difference = 0.3%). After excluding two EMRPC sites with irregularities in immunization data, the difference in overall UTD coverage between systems decreased from 14.4% to 6.6% INTERPRETATION: These results validate the use of DHIR for coverage assessment but also suggest that bidirectional exchange of immunization information has the potential to increase immunization data completeness in both systems.

Unnecessary antibiotic prescribing in a Canadian primary care setting: a descriptive analysis using routinely collected electronic medical record data.

BACKGROUND: Unnecessary antibiotic use in the community in Canada is not well defined. Our objective was to quantify unnecessary antibiotic prescribing in a Canadian primary care setting. METHODS: We performed a descriptive analysis in Ontario from April 2011 to March 2016 using the Electronic Medical Records Primary Care database linked to other health administrative data sets at ICES. We determined antibiotic prescribing rates (per 100 patient-physician encounters) for 23 common conditions and estimated rates of unnecessary prescribing using predefined expected prescribing rates, both stratified by condition and patient age group. RESULTS: The study included 341 physicians, 204 313 patients and 499 570 encounters. The rate of unnecessary antibiotic prescribing for included conditions was 15.4% overall and was 17.6% for those less than 2 years of age, 18.6% for those aged 2-18, 14.5% for those aged 19-64 and 13.0% for those aged 65 or more. The highest unnecessary prescribing rates were observed for acute bronchitis (52.6%), acute sinusitis (48.4%) and acute otitis media (39.3%). The common cold, acute bronchitis, acute sinusitis and miscellaneous nonbacterial infections were responsible for 80% of the unnecessary antibiotic prescriptions. Of all antibiotics prescribed, 12.0% were for conditions for which they are never indicated, and 12.3% for conditions for which they are rarely indicated. In children, 25% of antibiotics were for conditions for which they are never indicated (e.g., common cold). INTERPRETATION: Antibiotics were prescribed unnecessarily for 15.4% of included encounters in a Canadian primary care setting. Almost one-quarter of antibiotics were prescribed for conditions for which they are rarely or never indicated. These findings should guide safe reductions in the use of antibiotics for the common cold, bronchitis and sinusitis.

Identifying Transitional High Cost Users from Unstructured Patient Profiles Written by Primary Care Physicians.

Identification and subsequent intervention of patients at risk of becoming High Cost Users (HCUs) presents the opportunity to improve outcomes while also providing significant savings for the healthcare system. In this paper, the 2016 HCU status of patients was predicted using free-form text data from the 2015 cumulative patient profiles within the electronic medical records of family care practices in Ontario. These unstructured notes make substantial use of domain-specific spellings and abbreviations; we show that word embeddings derived from the same context provide more informative features than pre-trained ones based on Wikipedia, MIMIC, and Pubmed. We further demonstrate that a model using features derived from aggregated word embeddings (EmbEncode) provides a significant performance improvement over the bag-of-words representation (82.48±0.35% versus 81.85±0.36% held-out AUROC, p = 3.2 × 10-4), using far fewer input features (5,492 versus 214,750) and fewer non-zero coefficients (1,177 versus 4,284). The future HCUs of greatest interest are the transitional ones who are not already HCUs, because they provide the greatest scope for interventions. Predicting these new HCU is challenging because most HCUs recur. We show that removing recurrent HCUs from the training set improves the ability of EmbEncode to predict new HCUs, while only slightly decreasing its ability to predict recurrent ones.

Preventing alcohol-related cancer: what if everyone drank within the guidelines?

OBJECTIVES: The purpose of this study was to estimate the proportion and number of cancer cases diagnosed in Ontario in 2012 that are attributable to alcohol consumption and to compare the impact of drinking within two sets of guidelines on alcohol-attributable cancer incidence. METHODS: We estimated the proportion of cancers in Ontario attributable to alcohol consumption by calculating population-attributable fractions (PAFs) for six cancer types using drinking prevalence from the 2000/2001 Canadian Community Health Survey and relative risks from a meta-analysis. Each PAF was multiplied by the number of incident cancers in 2012, allowing for a 12-year latency period, to calculate the number of alcohol-attributable cases. We also estimated the number of alcohol-attributable cases under two scenarios: (1) assuming consumption had not exceeded the levels recommended by the Low-Risk Alcohol Drinking Guidelines (LRADG) and (2) assuming consumption had not exceeded the recommended levels by the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) guidelines. RESULTS: One thousand two hundred ninety-five (95% confidence interval 1093-1499) new cases of cancer diagnosed in Ontario during 2012 are estimated to be attributed to alcohol consumption, representing approximately 1.7% (1.4-1.9%) of all new cancer cases. If no Ontario adults had exceeded the LRADG, an estimated 321 fewer cancer cases could have been diagnosed in 2012, whereas an estimated 482 fewer cancer cases could have been diagnosed if no Ontario adults had exceeded the stricter WCRF/AICR guidelines. CONCLUSION: Strategies to limit alcohol consumption to the levels recommended by drinking guidelines could potentially reduce the cancer burden in Ontario.

Phanerogamic flora and vegetation of Itacolomi State Park, Minas Gerais, Brazil / Flora Fanerogâmica e Vegetação do Parque Estadual do Itacolomi, Minas Gerais, Brasil

Abstract Located in the municipalities of Ouro Preto and Mariana, in the Quadrilátero Ferrífero (QF) of Minas Gerais, the Itacolomi State Park (ISP) shelters more than 7,000 ha of remnants of Atlantic Forest and campos rupestres. The QF region has high biodiversity and is being highly impacted, mainly by mining activities. Aiming to organize the available floristic information and to support related research, this study presents the list of phanerogamic species of the ISP and the major vegetation types. This survey was carried out from October/1992 to July/2006, by monthly field trips. Besides authors´ personal collections, other records were assembled from herbarium databank. A total of 1623 taxons belonging to 122 families were listed. The families with higher species richness were Asteraceae, Fabaceae, Melastomataceae, Poaceae and Orchidaceae. The vegetation is represented by campos rupestres (51% of the total area), followed by montane forests (40%) and anthropogenic disturbed areas (9%). The greatest species richness occurs in campos rupestres. Several species are threatened and/or endemic. The knowledge of phanerogamic flora of ISP can help the Management Plan of this Unit of Conservation. It is also a contribution for future-related studies of the flora of ISP, Minas Gerais and Brazil.

Resumo O Parque Estadual do Itacolomi (PEIT) localiza-se nos municípios de Ouro Preto e Mariana, no Quadrilátero Ferrífero de Minas Gerais e abriga mais de 7.000 ha de remanescentes de mata atlântica e campos rupestres. A região do QF possui alta biodiversidade vegetal e está sobre alto impacto, principalmente pela mineração. O objetivo deste estudo foi apresentar a lista das espécies fanerogâmicas e os principais tipos vegetacionais desse Parque, no intuito de organizar a diversidade florística existente, além de servir como suporte para pesquisas correlatas subsequentes. O levantamento florístico foi realizado de outubro/1992 a julho/2006 por excursões mensais ao campo. Foram também incluídas na listagem registros ocorrentes em banco de dados de herbários. Foram identificados 1623 táxons, pertencentes à 122 famílias. As famílias mais representativas foram Asteraceae, Fabaceae, Melastomataceae, Poaceae e Orchidaceae. A vegetação do PEIT é constituída por campos rupestres (51% da área do parque), seguido pelas florestas montanas (40%) e por formações antrópicas (9%). A maior riqueza de espécies ocorre nos campos rupestres. Diversas espécies figuram em listas de espécies ameaçadas de extinção e outras são endêmicas. O conhecimento da flora fanerogâmica do Parque Estadual do Itacolomi pode subsidiar o Plano de Manejo dessa Unidade de Conservação e contribuir para futuros trabalhos correlatos nesta área, além de suprir conhecimentos para a flora de Minas Gerais e do Brasil.

Colorectal cancer incidence in the Aboriginal population of Ontario, 1998 to 2009.

BACKGROUND: Studies suggest that colorectal cancer incidence increased disproportionately among the Aboriginal population of Ontario relative to the general population. Using an ecological approach, this study examined colorectal cancer incidence for the 1998-to-2009 period among Aboriginal people living in Ontario. DATA AND METHODS: Based on their postal code when they were diagnosed, cases of colorectal cancer identified from the Ontario Cancer Registry were assigned to census geographic areas with high (33% or more) or low percentages of Aboriginal identity residents, using the Postal Code Conversion File Plus (PCCF+). To account for potential misclassification by the PCCF+, Indian reserves for which assignment through postal codes is likely to be accurate were identified. Age-standardized incidence rates and rate ratios were calculated to compare colorectal cancer incidence in high-Aboriginal identity areas or on Indian reserves with incidence in low-Aboriginal identity areas. RESULTS: Colorectal cancer incidence was significantly higher for residents of high- versus low-Aboriginal identity areas in Ontario (rate ratio for men = 1.44, 95% CI = 1.26-1.63; rate ratio for women = 1.42, 95% CI = 1.23-1.63), a disparity that persisted by age group. When the Aboriginal sample was limited to residents of Indian reserves, the difference was statistically significant only for men and for people aged 50 to 74. INTERPRETATION: The incidence of colorectal cancer differs across areas of Ontario with high and low percentages of Aboriginal identity residents.

Cervical cancer incidence in ontario women: differing sociodemographic gradients by morphologic type (adenocarcinoma versus squamous cell).

OBJECTIVE: Identify patterns in cervical cancer incidence in Ontario according to neighborhood sociodemographic characteristics over time and by morphologic type. METHODS: Incident cases of cervical cancer diagnosed from 1991 to 2009 were obtained from the Ontario Cancer Registry. Population data and data on neighborhood sociodemographic characteristics were obtained from the Canadian Census. Age-standardized incidence rates (ASIR) and rate ratios (RRs) with 95% confidence intervals (CIs) were calculated for each sociodemographic characteristic, stratified by morphologic type (squamous cell carcinoma and adenocarcinoma) and time period of diagnosis. RESULTS: Incidence was 51% higher in the poorest neighborhoods compared with the richest (RR, 1.51; 95% CI, 1.42-1.61) and 7% higher in rural areas compared with urban (RR, 1.07; 95% CI, 1.01-1.13). Incidence of squamous cell carcinoma was significantly higher in the poorest neighborhoods compared with the richest (RR, 1.74; 95% CI, 1.61-1.88), a trend observed for all time periods, and in rural areas compared with urban (RR, 1.10; 95% CI, 1.02-1.18). For adenocarcinoma, ASIRs in the earlier time period (1991-1998) were higher in the poorest neighborhoods compared with richest (RR, 1.26; 95% CI, 1.01-1.57), whereas for the more recent time period (1999-2009), ASIRs were lower for women living in the poorest neighborhoods compared with the richest (RR, 0.82; 95% CI, 0.68-0.99). CONCLUSIONS: This study identified significantly higher incidence of cervical cancer in low-income neighborhoods in Ontario. The association was especially pronounced for squamous cell carcinoma and varied by time period for adenocarcinoma. Improvements to screening and prevention efforts against oncogenic human papillomavirus strains would increase the detection of cervical cancer, adenocarcinoma especially, and may further reduce cervical cancer incidence.

The relationship between need and capacity for multidisciplinary cardiovascular risk-reduction programs in Ontario.

BACKGROUND: Available evidence has demonstrated survival benefits associated with multidisciplinary cardiovascular risk-reduction (CR) (ie, cardiac rehabilitation) programs. The degree to which program capacity meets eligible service demands in Ontario is unknown. We sought to estimate the supply-need care-gap associated with CR programs across regions (Local Health Integration Networks [LHINs]) in Ontario. METHODS: We conducted a cross-sectional, population-based study during 2006. Administrative data provided estimates of the population eligible for multidisciplinary CR services due to (1) recent cardiovascular hospitalizations and (2) incident diabetes. An Ontario-wide survey of CR programs provided service supply estimates. The coverage rate and the absolute supply-need mismatch were use to quantify the care-gap by LHIN. RESULTS: Based on cardiac hospitalizations alone, 53,270 patients in Ontario in 2006 (508.7 per 100,000) were eligible for CR services; 128,869 patients (1245 per 100,000) would have been eligible if newly diagnosed (incident cases) diabetic patients were included. Capacity for CR services was 18,087 patients, corresponding to 34% coverage of the eligible population (absolute unmet needs of 35,189 individuals) if capacity was entirely dedicated to recent hospitalizations and 14% coverage (absolute unmet needs of 110,782) if services were extended to include incident diabetes patients. Marked variation in disease burden, service capacity, and supply-need mismatch was observed across regions, in which supply was not correlated with need. CONCLUSION: Despite proved benefits of multidisciplinary CR programs, unmet population needs remain high in Ontario and are unequally distributed across regions. The magnitude of unmet needs and the lack of correlation between supply and disease burden necessitate broader provincial strategies to plan, allocate, and subsidize CR programs.

Item nonresponse to psychosocial questionnaires was associated with higher mortality after acute myocardial infarction.

OBJECTIVE: To examine the relationship between selective nonresponse to a psychosocial questionnaire and mortality after acute myocardial infarction (AMI). STUDY DESIGN AND SETTING: Two thousand six hundred and ninety AMI survivors after AMI hospitalization were recruited to complete a 30-day follow-up interview. Patients were classified into four groups (survey nonparticipation and complete, partial, and no item nonresponse) according to their degree of response to the Medical Outcomes Study (MOS) Social Support Survey (MOS-SSS). Cox proportional hazard models, adjusted for baseline sociodemographic, clinical, and psychosocial (i.e., social isolation) characteristics, were used to examine all-cause mortality, 3 years post-AMI, across the response levels. RESULTS: 13.9% of the eligible patients refused follow-up participation; MOS-SSS item nonresponse was present in up to 14.7% of participants and was more frequent among the elderly, socially disadvantaged, and those with higher clinical risk. A nonresponse mortality gradient existed, ranging from 8.9% (no item nonresponse) to 18.7% (complete item nonresponse) (P<0.001). After adjusting for baseline characteristics, complete item nonresponse remained significantly associated with mortality (hazard ratio: 1.33; 95% confidence interval: 1.02-1.73). CONCLUSIONS: Item nonresponse to a social support questionnaire is associated with higher mortality post-AMI. Although explanatory factors may include age and baseline clinical risk, additional psychosocial and/or unmeasured factors may account for the poorer prognosis.