Avaliação dos marcadores prognósticos de pacientes com DPOC no período de nove anos

Pós-graduação em Fisiopatologia em Clínica Médica - FMB

Desfechos intra-hospitalares e preditores de mortalidade no infarto agudo do miocárdio com choque cardiogênico tratados por angioplastia primária: dados do registro InCor

INTRODUÇÃO: O choque cardiogênico é a maior causa de morte em pacientes com infarto agudo do miocárdio com supradesnivelamento do segmento de ST (IAMCSST). O presente estudo avaliou pacientes com IAMCSST e choque cardiogênico submetidos a intervenção coronária percutânea primária com o objetivo de estabelecer seu perfil e os preditores de mortalidade hospitalar. MÉTODOS: Registro unicêntrico, incluindo 100 pacientes avaliados no período de 2001 a 2009 quanto a características clínicas, angiográficas e do procedimento, e a desfechos intra-hospitalares. Por análise multivariada foram determinados preditores independentes da mortalidade hospitalar. RESULTADOS: Com relação às características clínicas, foi observada alta prevalência de fatores de risco, sendo a taxa de sucesso angiográfico de 92%, apesar da complexidade das lesões (83,1% do tipo B2/C). A artéria mais acometida foi a descendente anterior (45%), tendo o padrão multiarterial ocorrido em 73% dos casos. A taxa de mortalidade foi de 45%, sendo seus preditores independentes o padrão multiarterial [odds ratio (OR) 2,62; intervalo de confiança de 95% (IC 95%) 1,16-5,90] e o fluxo coronário TIMI < 3 ao final do procedimento (OR 2,11, IC 95% 1,48-3,02). CONCLUSÕES: Os pacientes com IAMCSST complicado por choque cardiogênico apresentaram características clínicas e angiográficas de alto risco e, apesar do alto sucesso angiográfico do procedimento, altas taxas de mortalidade. Foram preditores independentes de mortalidade o padrão multiarterial e fluxo TIMI < 3 ao final do procedimento.

Circoli collaterali porto-sistemici all'eco-color-Doppler addominale in pazienti con ipertensione portale cirrotica: correlazione con il gradiente porto-epatico e valore prognostico

Background. Abdominal porto-systemic collaterals (APSC) on Color-Doppler ultrasound are a frequent finding in portal hypertensive cirrhotic patients. In patients with cirrhosis, an HVPG ≥ 16mmHg has been shown to be associated with increased mortality in two studies. Non-invasive indicators of HVPG ≥ 16 mmHg might define a subgroup of high-risk patients, but data on this aspect are lacking. Aims. We aimed to investigate whether HVPG predicts mortality in patients with clinically significant portal hypertension, and if APSC may predict a severe portal hypertensive state (i.e. HVPG≥16mmHg) in patients with cirrhosis and untreated portal hypertension. Methods. We analysed paired HVPG and ultrasonographic data of 86 untreated portal hypertensive cirrhotic patients. On abdominal echo-color-Doppler data on presence, type and number of APSC were prospectively collected. HVPG was measured following published guidelines. Clinical, laboratory and endoscopic data were available in all cases. First decompensation of cirrhosis and liver-disease related mortality on follow-up (mean 28±20 months) were recorded. Results. 73% of patients had compensated cirrhosis, while 27% were decompensated. All patients had an HVPG≥10 mmHg (mean 17.8±5.1 mmHg). 58% of compensated patients and 82% of decompensated patients had an HVPG over 16 mmHg. 25% had no varices, 28% had small varices, and 47% had medium/large varices. HVPG was higher in patients with esophageal varices vs. patients without varices (19.0±4.8 vs. 14.1±4.2mmHg, p<0.0001), and correlated with Child-Pugh score (R=0.494,p=0.019). 36 (42%) patients had APSC were more frequent in decompensated patients (60% vs. 35%, p=0.03) and in patients with esophageal varices (52% vs. 9%,p=0.001). HVPG was higher in patients with APSC compared with those without PSC (19.9± 4.6 vs. 16.2± 4.9mmHg, p=0.001). The prevalence of APSC was higher in patients with HVPG≥16mmHg vs. those with HVPG<16mmHg (57% vs. 13%,p<0.0001). Decompensation was significantly more frequent in patients with HVPG≥16mmHg vs. HVPG<16mmHg (35.1% vs. 11.5%, p=0.02). On multivariate analysis only HVPG and bilirubin were independent predictors of first decompensation. 10 patients died during follow-up. All had an HVPG≥16 mmHg (26% vs. 0% in patients with HVPG <16mmHg,p=0.04). On multivariate analysis only MELD score and HVPG ≥16mmHg were independent predictors of mortality. In compensated patients the detection of APSC predicted an HVPG≥16mmHg with 92% specificity, 54% sensitivity, positive and negative likelihood ratio 7.03 and 0.50, which implies that the demonstration of APSC on ultrasound increased the probability of HVPG≥16mmHg from 58% to 91%. Conclusions. HVPG maintains an independent prognostic value in the subset of patients with cirrhosis and clinically significant portal hypertension. The presence of APSC is a specific indicator of severe portal hypertension in patients with cirrhosis. Detection of APSC on ultrasound allows the non-invasive identification of a subgroup of compensated patients with bad prognosis, avoiding the invasive measurement of HVPG.

First results from a Swiss level I trauma centre participating in the UK Trauma Audit and Research Network (TARN): Prospective cohort study

QUESTIONS UNDER STUDY: Patient characteristics and risk factors for death of Swiss trauma patients in the Trauma Audit and Research Network (TARN). METHODS: Descriptive analysis of trauma patients (≥16 years) admitted to a level I trauma centre in Switzerland (September 1, 2009 to August 31, 2010) and entered into TARN. Multivariable logistic regression analysis was used to identify predictors of 30-day mortality. RESULTS: Of 458 patients 71% were male. The median age was 50.5 years (inter-quartile range [IQR] 32.2-67.7), median Injury Severity Score (ISS) was 14 (IQR 9-20) and median Glasgow Coma Score (GCS) was 15 (IQR 14-15). The ISS was >15 for 47%, and 14% had an ISS >25. A total of 17 patients (3.7%) died within 30 days of trauma. All deaths were in patients with ISS >15. Most injuries were due to falls <2 m (35%) or road traffic accidents (29%). Injuries to the head (39%) were followed by injuries to the lower limbs (33%), spine (28%) and chest (27%). The time of admission peaked between 12:00 and 22:00, with a second peak between 00:00 and 02:00. A total of 64% of patients were admitted directly to our trauma centre. The median time to CT was 30 min (IQR 18-54 min). Using multivariable regression analysis, the predictors of mortality were older age, higher ISS and lower GCS. CONCLUSIONS: Characteristics of Swiss trauma patients derived from TARN were described for the first time, providing a detailed overview of the institutional trauma population. Based on these results, patient management and hospital resources (e.g. triage of patients, time to CT, staffing during night shifts) could be evaluated as a further step.

Near-hanging as presenting to hospitals in Queensland: Recommendations for practice

Near-hanging is an increasing presentation to hospitals in Australasia. We reviewed the clinical management and outcome of these patients as they presented to public hospitals in Queensland. A retrospective clinical record audit was made at five public hospitals between 1991 and 2000. Of 161 patients enrolled, 82% were male, 8% were Indigenous and 10% had made a previous hanging attempt. Chronic medical illnesses were documented in 11% and previous psychiatric disorders in 42%. Of the 38 patients with a Glasgow Coma Scale score (GCS) of 3 on arrival at hospital, 32% returned to independent living and 63% died. Fifty two patients received CPR, of whom 46% had an independent functional outcome. Independent predictors of mortality were a GCS on hospital arrival of 3 (AOR 150, CI 95% 12.4-1818, P

Stroke in patients with diabetes mellitus: a study from North Western Nigeria.

Background: Stroke is one of the major causes of morbidity and mortality worldwide and apart from being exceedingly harmful in diabetics, stroke is a disabling disorder. The study was undertaken to describe the clinical characteristics, outcome pattern and predictors of mortality in a cohort of diabetic patients presenting with stroke in two tertiary health facilities in North Western Nigeria. Method: Out of all stroke patients seen from June 2007 to February 2011, persons with diabetes mellitus presenting with stroke in the emergency unit of the two tertiary hospitals in Kano were consecutively recruited for the study. Classification of stroke into hemorrhagic and infarctive subtypes was based on brain computerized tomography (CT), brain magnetic resonance imaging (MRI) and World Health Organization (WHO) criteria. Follow-up period was for thirty days. Result: Out of the five hundred and thirty six stroke patients seen during the study period, 85 (15.9%) patients, comprising 48 (56.5%) males, had diabetes. Thirty eight (44.7%) of the identified diabetics were previously undiagnosed. Sixty four (75.3%) had infarctive stroke. One-month case fatality rate was 30.6%. Factors associated with death included male sex, past history of TIA, abnormal respiratory pattern, hemorrhagic stroke, aspiration pneumonitis, and worsening GCS. Aspiration pneumonitis and worsening GCS were independent predictors of one month mortality of stroke in the patients. Conclusion: In DM patients studied, infarctive stroke was more common, case fatality was 30.6%. Male gender, past history of TIA, abnormal respiratory pattern, hemorrhagic stroke, aspiration pneumonitis, and worsening Glasgow Coma Score (GCS) were associated with mortality. Aspiration pneumonitis and worsening GCS were independent predictors of one month mortality of stroke in diabetic patients.

Modelling Mortality and Reproduction Rates for Management of Sheep Flocks in Northern Australia

By quantifying the effects of climatic variability in the sheep grazing lands of north western and western Queensland, the key biological rates of mortality and reproduction can be predicted for sheep. These rates are essential components of a decision support package which can prove a useful management tool for producers, especially if they can easily obtain the necessary predictors. When the sub-models of the GRAZPLAN ruminant biology process model were re-parameterised from Queensland data along with an empirical equation predicting the probability of ewes mating added, the process model predicted the probability of pregnancy well (86% variation explained). Predicting mortality from GRAZPLAN was less successful but an empirical equation based on relative condition of the animal (a measure based on liveweight), pregnancy status and age explained 78% of the variation in mortalities. A crucial predictor in these models was liveweight which is not often recorded on producer properties. Empirical models based on climatic and pasture conditions estimated from the pasture production model GRASP, predicted marking and mortality rates for Mitchell grass (Astrebla sp.) pastures (81% and 63% of the variation explained). These prediction equations were tested against independent data from producer properties and the model successfully validated for Mitchell grass communities.

Elevated soluble cellular adhesion molecules are associated with increased mortality in a prospective cohort of renal transplant recipients

Increased plasma levels of cellular adhesion molecules (CAMs) have been shown to be predictors of all cause mortality in individuals with chronic renal failure 12 and patients with end-stage renal disease receiving haemodialysis 3. In renal transplant recipients the predictive value of CAMs has not been well characterised. The aim of this study was to assess the relationship between CAMs and all-cause mortality during prospective follow-up of a renal transplant cohort.

Survival Analysis of Patients with Heart Failure: Implications of Time-Varying Regression Effects in Modeling Mortality

Background: Several models have been designed to predict survival of patients with heart failure. These, while available and widely used for both stratifying and deciding upon different treatment options on the individual level, have several limitations. Specifically, some clinical variables that may influence prognosis may have an influence that change over time. Statistical models that include such characteristic may help in evaluating prognosis. The aim of the present study was to analyze and quantify the impact of modeling heart failure survival allowing for covariates with time-varying effects known to be independent predictors of overall mortality in this clinical setting. Methodology: Survival data from an inception cohort of five hundred patients diagnosed with heart failure functional class III and IV between 2002 and 2004 and followed-up to 2006 were analyzed by using the proportional hazards Cox model and variations of the Cox's model and also of the Aalen's additive model. Principal Findings: One-hundred and eighty eight (188) patients died during follow-up. For patients under study, age, serum sodium, hemoglobin, serum creatinine, and left ventricular ejection fraction were significantly associated with mortality. Evidence of time-varying effect was suggested for the last three. Both high hemoglobin and high LV ejection fraction were associated with a reduced risk of dying with a stronger initial effect. High creatinine, associated with an increased risk of dying, also presented an initial stronger effect. The impact of age and sodium were constant over time. Conclusions: The current study points to the importance of evaluating covariates with time-varying effects in heart failure models. The analysis performed suggests that variations of Cox and Aalen models constitute a valuable tool for identifying these variables. The implementation of covariates with time-varying effects into heart failure prognostication models may reduce bias and increase the specificity of such models.

BNP and Admission Glucose as In-Hospital Mortality Predictors in Non-ST Elevation Myocardial Infarction

Objectives. Admission hyperglycemia and B-type natriuretic peptide (BNP) are associated with mortality in acute coronary syndromes, but no study compares their prediction in-hospital death. Methods. Patients with non-ST-elevation myocardial infarction (NSTEMI), in-hospital mortality and two-year mortality or readmission were compared for area under the curve (AUC), sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV), and accuracy (ACC) of glycemia and BNP. Results. Respectively, AUC, SEN, SPE, PPV, NPV, and ACC for prediction of in-hospital mortality were 0.815, 71.4%, 84.3%, 26.3%, 97.4%, and 83.3% for glycemia = 200 mg/dL and 0.748, 71.4%, 68.5%, 15.2%, 96.8% and 68.7% for BNP = 300 pg/mL. AUC of glycemia was similar to BNP (P = 0.411). In multivariate analysis we found glycemia >= 200mg/dL related to in-hospital death (P = 0.004). No difference was found in two-year mortality or readmission in BNP or hyperglycemic subgroups. Conclusion. Hyperglycemia was an independent risk factor for in-hospital mortality in NSTEMI and had a good ROC curve level. Hyperglycemia and BNP, although poor in-hospital predictors of unfavorable events, were independent risk factors for death or length of stay >10 days. No relation was found between hyperglycemia or BNP and long-term events.

Impact of left ventricular hypertrophy late after aortic valve replacement for aortic stenosis on cardiovascular morbidity and mortality

AIMS: The goal of this study was to assess the prevalence of left ventricular (LV) hypertrophy in patients with aortic stenosis late (>6 months) after aortic valve replacement and its impact on cardiac-related morbidity and mortality. METHODS AND RESULTS: In a single tertiary centre, echocardiographic data of LV muscle mass were collected. Detailed information of medical history and angiographic data were gathered. Ninety-nine of 213 patients (46%) had LV hypertrophy late (mean 5.8 +/- 5.4 years) after aortic valve replacement. LV hypertrophy was associated with impaired exercise capacity, higher New York Heart Association dyspnoea class, a tendency for more frequent chest pain expressed as higher Canadian Cardiovascular Society class, and more rehospitalizations. 24% of patients with normal LV mass vs. 39% of patients with LV hypertrophy reported cardiac-related morbidity (p = 0.04). In a multivariate logistic regression model, LV hypertrophy was an independent predictor of cardiac-related morbidity (odds ratio 2.31, 95% CI 1.08 to 5.41), after correction for gender, baseline ejection fraction, and coronary artery disease and its risk factors. Thirty seven deaths occurred during a total of 1959 patient years of follow-up (mean follow-up 9.6 years). Age at aortic valve replacement (hazard ratio 1.85, 95% CI 1.39 to 2.47, for every 5 years increase in age), coexisting coronary artery disease at the time of surgery (hazard ratio 3.36, 95% CI 1.31 to 8.62), and smoking (hazard ratio 4.82, 95% CI 1.72 to 13.45) were independent predictors of overall mortality late after surgery, but not LV hypertrophy. CONCLUSIONS: In patients with aortic valve replacement for isolated aortic stenosis, LV hypertrophy late after surgery is associated with increased morbidity.

Exploring race/ethnicity as a risk factor for mortality in newborns following congenital heart surgery at a center of excellence

The purpose of this study was to determine if race/ethnicity was a significant risk factor for hospital mortality in children following congenital heart surgery in a contemporary sample of newborns with congenital heart disease. Unlike previous studies that utilized administrative databases, this study utilized clinical data collected at the point of care to examine racial/ethnic outcome differences in the context of the patients' clinical condition and their overall perioperative experience. A retrospective cohort design was used. The study sample consisted of 316 newborns (<31 days of age) who underwent congenital heart surgery between January 2007 through December 2009. A multivariate logistic regression model was used to determine the impact of race/ethnicity, insurance status, presence of a spatial anomaly, prenatal diagnosis, postoperative sepsis, cardiac arrest, respiratory failure, unplanned reoperation, and total length of stay in the intensive care unit on outcomes following congenital heart surgery in newborns. The study findings showed that the strongest predictors of hospital mortality following congenital heart surgery in this cohort were postoperative cardiac arrest, postoperative respiratory failure, having a spatial anomaly, and total ICU LOS. Race/ethnicity and insurance status were not significant risk factors. The institution where this study was conducted is designated as a center of excellence for congenital heart disease. These centers have state-of-the-art facilities, extensive experience in caring for children with congenital heart disease, and superior outcomes. This study suggests that optimal care delivery for newborns requiring congenital heart surgery at a center of excellence portends exceptional outcomes and this benefit is conferred upon the entire patient population despite the race/ethnicity of the patients. From a public health and health services view, this study also contributes to the overall body of knowledge on racial/ethnic disparities in children with congenital heart defects and puts forward the possibility of a relationship between quality of care and racial/ethnic disparities. Further study is required to examine the impact of race/ethnicity on the long-term outcomes of these children as they encounter the disparate components of the health care delivery system. There is also opportunity to study the role of race/ethnicity on the hospital morbidity in these patients considering current expectations for hospital survival are very high, and much of the current focus for quality improvement rests in minimizing the development of patient morbidities.^

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

The effects of ambulance ramping on Emergency Department length of stay and mortality

Background: Ambulance ramping within the Emergency Department (ED) is a common problem both internationally and in Australia. Previous research has focused on various issues associated with ambulance ramping such as access block, ED overcrowding and ambulance bypass. However, limited research has been conducted on ambulance ramping and its effects on patient outcomes. ----- ----- Methods: A case-control design was used to describe, compare and predict patient outcomes of 619 ramped (cases) vs. 1238 non-ramped (control) patients arriving to one ED via ambulance from 1 June 2007 to 31 August 2007. Cases and controls were matched (on a 1:2 basis) on age, gender and presenting problem. Outcome measures included ED length of stay and in-hospital mortality. ----- ----- Results: The median ramp time for all 1857 patients was 11 (IQR 6—21) min. Compared to nonramped patients, ramped patients had significantly longer wait time to be triaged (10 min vs. 4 min). Ramped patients also comprised significantly higher proportions of those access blocked (43% vs. 34%). No significant difference in the proportion of in-hospital deaths was identified (2%vs. 3%). Multivariate analysis revealed that the likelihood of having an ED length of stay greater than eight hours was 34% higher among patients who were ramped (OR 1.34, 95% CI 1.06—1.70, p = 0.014). In relation to in-hospital mortality age was the only significant independent predictor of mortality (p < 0.0001). ----- ----- Conclusion: Ambulance ramping is one factor that contributes to prolonged ED length of stay and adds additional strain on ED service provision. The potential for adverse patient outcomes that may occur as a result of ramping warrants close attention by health care service providers.

The impact of temperature on mortality in Tianjin, China : a case-crossover design with a distributed lag non-linear model

Background There has been increasing interest in assessing the impacts of temperature on mortality. However, few studies have used a case–crossover design to examine non-linear and distributed lag effects of temperature on mortality. Additionally, little evidence is available on the temperature-mortality relationship in China, or what temperature measure is the best predictor of mortality. Objectives To use a distributed lag non-linear model (DLNM) as a part of case–crossover design. To examine the non-linear and distributed lag effects of temperature on mortality in Tianjin, China. To explore which temperature measure is the best predictor of mortality; Methods: The DLNM was applied to a case¬−crossover design to assess the non-linear and delayed effects of temperatures (maximum, mean and minimum) on deaths (non-accidental, cardiopulmonary, cardiovascular and respiratory). Results A U-shaped relationship was consistently found between temperature and mortality. Cold effects (significantly increased mortality associated with low temperatures) were delayed by 3 days, and persisted for 10 days. Hot effects (significantly increased mortality associated with high temperatures) were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. Conclusions In Tianjin, extreme cold and hot temperatures increased the risk of mortality. Results suggest that the effects of cold last longer than the effects of heat. It is possible to combine the case−crossover design with DLNMs. This allows the case−crossover design to flexibly estimate the non-linear and delayed effects of temperature (or air pollution) whilst controlling for season.