Objective To identify existing prediction models for the risk of development of type 2 diabetes and to externally validate them in a large independent cohort.Data sources Systematic search of ...English, German, and Dutch literature in PubMed until February 2011 to identify prediction models for diabetes.Design Performance of the models was assessed in terms of discrimination (C statistic) and calibration (calibration plots and Hosmer-Lemeshow test).The validation study was a prospective cohort study, with a case cohort study in a random subcohort. Setting Models were applied to the Dutch cohort of the European Prospective Investigation into Cancer and Nutrition cohort study (EPIC-NL). Participants 38 379 people aged 20-70 with no diabetes at baseline, 2506 of whom made up the random subcohort.Outcome measure Incident type 2 diabetes. Results The review identified 16 studies containing 25 prediction models. We considered 12 models as basic because they were based on variables that can be assessed non-invasively and 13 models as extended because they additionally included conventional biomarkers such as glucose concentration. During a median follow-up of 10.2 years there were 924 cases in the full EPIC-NL cohort and 79 in the random subcohort. The C statistic for the basic models ranged from 0.74 (95% confidence interval 0.73 to 0.75) to 0.84 (0.82 to 0.85) for risk at 7.5 years. For prediction models including biomarkers the C statistic ranged from 0.81 (0.80 to 0.83) to 0.93 (0.92 to 0.94). Most prediction models overestimated the observed risk of diabetes, particularly at higher observed risks. After adjustment for differences in incidence of diabetes, calibration improved considerably.Conclusions Most basic prediction models can identify people at high risk of developing diabetes in a time frame of five to 10 years. Models including biomarkers classified cases slightly better than basic ones. Most models overestimated the actual risk of diabetes. Existing prediction models therefore perform well to identify those at high risk, but cannot sufficiently quantify actual risk of future diabetes.
Background
A large cohort study recently reported high pain scores after caesarean section (CS). The aim of this study was to analyse how pain after CS interferes with patients' activities and to ...identify possible causes of insufficient pain treatment.
Methods
We analysed pain scores, pain‐related interferences (with movement, deep breathing, mood and sleep), analgesic techniques, analgesic consumption, adverse effects and the wish to have received more analgesics during the first 24 h after surgery. To better evaluate the severity of impairment by pain, the results of CS patients were compared with those of patients undergoing hysterectomy.
Results
CS patients (n = 811) were compared with patients undergoing abdominal, laparoscopic‐assisted vaginal or vaginal hysterectomy (n = 2406, from 54 hospitals). Pain intensity, wish for more analgesics and most interference outcomes were significantly worse after CS compared with hysterectomies. CS patients with spinal or general anaesthesia and without patient‐controlled analgesia (PCA) received significantly less opioids on the ward (62% without any opioid) compared with patients with PCA (p < 0.001). Patients with PCA reported pain‐related interference with movement and deep breathing between 49% and 52% compared with patients without PCA (between 68% and 73%; p‐values between 0.004 and 0.013; not statistically significant after correction for multiple testing).
Conclusion
In daily clinical practice, pain after CS is much higher than previously thought. Pain management was insufficient compared with patients undergoing hysterectomy. Unfavourable outcome was mainly associated with low opioid administration after CS. Contradictory pain treatment guidelines for patients undergoing CS and for breastfeeding mothers might contribute to reluctance of opioid administration in CS patients.
Aims/hypothesis
Treatment guidelines recommend the UK Prospective Diabetes Study (UKPDS) risk engine for predicting cardiovascular risk in patients with type 2 diabetes, although validation studies ...showed moderate performance. The methods used in these validation studies were diverse, however, and sometimes insufficient. Hence, we assessed the discrimination and calibration of the UKPDS risk engine to predict 4, 5, 6 and 8 year cardiovascular risk in patients with type 2 diabetes.
Methods
The cohort included 1,622 patients with type 2 diabetes. During a mean follow-up of 8 years, patients were followed for incidence of CHD and cardiovascular disease (CVD). Discrimination and calibration were assessed for 4, 5, 6 and 8 year risk. Discrimination was examined using the
c
-statistic and calibration by visually inspecting calibration plots and calculating the Hosmer–Lemeshow χ
2
statistic.
Results
The UKPDS risk engine showed moderate to poor discrimination for both CHD and CVD (
c
-statistic of 0.66 for both 5 year CHD and CVD risks), and an overestimation of the risk (224% and 112%). The calibration of the UKPDS risk engine was slightly better for patients with type 2 diabetes who had been diagnosed with diabetes more than 10 years ago compared with patients diagnosed more recently, particularly for 4 and 5 year predicted CVD and CHD risks. Discrimination for these periods was still moderate to poor.
Conclusions/interpretation
We observed that the UKPDS risk engine overestimates CHD and CVD risk. The discriminative ability of this model is moderate, irrespective of various subgroup analyses. To enhance the prediction of CVD in patients with type 2 diabetes, this model should be updated.
Objective Myocardial infarction (MI) is a frequent complication of carotid endarterectomy (CEA), yet most events are silent. Routine post-operative monitoring of cardiac troponin was implemented to ...facilitate timely recognition of MI and stratify high risk patients. The aim was to evaluate the incidence of troponin elevation after CEA and its association with adverse cardiovascular events. Methods This analysis included patients ≥60 years old who underwent CEA, whose troponin-I levels were routinely monitored post-operatively and were included in a cohort study that assessed clinical outcomes. A clinical troponin cutoff of 60 ng/L was used. The primary endpoint was the composite of MI, stroke, and cardiovascular death. Secondary endpoints were MI, stroke, coronary intervention, cardiovascular death, and all cause death. Results 225 consecutive patients were included in the analysis. Troponin elevation occurred in 34 patients (15%) and a post-operative MI was diagnosed in eight patients. After a median follow up of 1.8 years (IQR 1.0–2.6), the primary endpoint occurred in 29% of patients with troponin elevation versus 6.3% without (HR 5.6, 95% CI 2.4–13), MI in 24% versus 1.6% (HR 18.0, 95% CI 4.7–68), stroke in 5.9% versus 4.2% (HR 1.4, 95% CI 0.3–6.7), coronary intervention in 5.9% versus 2.6% (HR 2.7, 95% CI 0.5–14), cardiovascular death in 5.9% versus 0.5% (HR 11.8, 95% CI 1.1–131), and all cause death in 15% versus 5.8% (HR 3.0, 95% CI 1.0–8.7), respectively. Incidences of the primary endpoint and all cause mortality in patients with a post-operative MI versus “troponin only” were 25% versus 7.7% and 25% versus 12%, respectively. Conclusion Troponin elevation after CEA occurred in 15% of patients. The incidence of adverse cardiovascular events was significantly higher in patients with troponin elevation, which was mainly attributable to silent non-ST segment elevation MIs that occurred in the early post-operative phase.
Altered respiratory rate is one of the first symptoms of medical conditions that require timely intervention, e.g., sepsis or opioid-induced respiratory depression. To facilitate continuous ...respiratory rate monitoring on general hospital wards a contactless, non-invasive, prototype monitor was developed using frequency modulated continuous wave radar. We aimed to study whether radar can reliably measure respiratory rate in postoperative patients. In a diagnostic cross-sectional study patients were monitored with the radar and the reference monitor (pneumotachograph during mechanical ventilation and capnography during spontaneous breathing). Eight patients were included; yielding 796 min of observation time during mechanical ventilation and 521 min during spontaneous breathing. After elimination of movement artifacts the bias and 95 % limits of agreement for mechanical ventilation and spontaneous breathing were −0.12 (−1.76 to 1.51) and −0.59 (−5.82 to 4.63) breaths per minute respectively. The radar was able to accurately measure respiratory rate in mechanically ventilated patients, but the accuracy decreased during spontaneous breathing.
Various cardiovascular prediction models have been developed for patients with type 2 diabetes. Their predictive performance in new patients is mostly not investigated. This study aims to quantify ...the predictive performance of all cardiovascular prediction models developed specifically for diabetes patients.
Follow-up data of 453, 1174 and 584 type 2 diabetes patients without pre-existing cardiovascular disease (CVD) in the EPIC-NL, EPIC-Potsdam and Secondary Manifestations of ARTerial disease cohorts, respectively, were used to validate 10 prediction models to estimate risk of CVD or coronary heart disease (CHD). Discrimination was assessed by the c-statistic for time-to-event data. Calibration was assessed by calibration plots, the Hosmer-Lemeshow goodness-of-fit statistic and expected to observed ratios.
There was a large variation in performance of CVD and CHD scores between different cohorts. Discrimination was moderate for all 10 prediction models, with c-statistics ranging from 0.54 (95% CI 0.46 to 0.63) to 0.76 (95% CI 0.67 to 0.84). Calibration of the original models was poor. After simple recalibration to the disease incidence of the target populations, predicted and observed risks were close. Expected to observed ratios of the recalibrated models ranged from 1.06 (95% CI 0.81 to 1.40) to 1.55 (95% CI 0.95 to 2.54), mainly driven by an overestimation of risk in high-risk patients.
All 10 evaluated models had a comparable and moderate discriminative ability. The recalibrated, but not the original, prediction models provided accurate risk estimates. These models can assist clinicians in identifying type 2 diabetes patients who are at low or high risk of developing CVD.
Abstract Background Extremely low birth weight (ELBW) infants are at risk of cognitive impairment and follow-up is therefore of major importance. The age at which their neurodevelopmental outcome ...(NDO) can reliably be predicted differs in the literature. Aims To describe NDO at 2, 3.5 and 5.5 years in an ELBW cohort. To examine the value of NDO at 2 years corrected age (CA) for prediction of NDO at 3.5 and 5.5 years. Study design A r etrospective cross-sectional and longitudinal cohort study. Subjects 101 children with a BW ≤ 750 g, born between 1996 and 2005, who survived NICU admission and were included in a follow-up program. Outcome measures NDO, measured with different tests for general development and intelligence, depending on age of assessment and classified as normal (Z-score ≥ − 1), mildly delayed (− 2 ≤ Z-score < − 1) or severely delayed (Z-score < − 2). Results At 2, 3.5 and 5.5 years 74.3, 82.2 and 76.2% had a normal NDO. A normal NDO at 2 years CA predicted a normal NDO at 3.5 and 5.5 years in 92% and 84% respectively. Of the children with a mildly or severely delayed NDO at 2 years CA the majority showed an improved NDO at 3.5 (69.2%) and 5.5 years (65.4%) respectively. Conclusions The majority of the children with a BW ≤ 750 g had a normal NDO at all ages. A normal NDO at 2 years CA is a good predictor for normal outcome at 3.5 and 5.5 years, whereas a delayed NDO at 2 years CA is subject to change with the majority of the children showing a better NDO at 3.5 and 5.5 years.
We present a strategy for the analysis of cell surface carbohydrate expression patterns using lectin arrays fabricated on gold surfaces. Antibody and glycoprotein binding experiments showed that the ...lectins were effectively immobilized on the surface and retained their carbohydrate-binding specificities. The approach was demonstrated in the analysis of carbohydrate expression on two mammalian cell lines.
Delirium is frequently unrecognised. EEG shows slower frequencies (i.e. below 4 Hz) during delirium, which might be useful in improving delirium recognition. We studied the discriminative performance ...of a brief single-channel EEG recording for delirium detection in an independent cohort of patients.
In this prospective, multicentre study, postoperative patients aged ≥60 yr were included (n=159). Before operation and during the first 3 postoperative days, patients underwent a 5-min EEG recording, followed by a video-recorded standardised cognitive assessment. Two or, in case of disagreement, three delirium experts classified each postoperative day based on the video and chart review. Relative delta power (1–4 Hz) was based on 1-min artifact-free EEG. The diagnostic value of the relative delta power was evaluated by the area under the receiver operating characteristic curve (AUROC), using the expert classification as the gold standard.
Experts classified 84 (23.3%) postoperative days as either delirium or possible delirium, and 276 (76.7%) non-delirium days. The AUROC of the relative EEG delta power was 0.75 95% confidence interval (CI) 0.69–0.82. Exploratory analysis showed that relative power from 1 to 6 Hz had significantly higher AUROC (0.78, 95% CI 0.72–0.84, P=0.014).
Delirium/possible delirium can be detected in older postoperative patients based on a single-channel EEG recording that can be automatically analysed. This objective detection method with a continuous scale instead of a dichotomised outcome is a promising approach for routine detection of delirium.
NCT02404181.
Chemistry is described for the fabrication of DNA arrays on gold surfaces. Alkanethiols modified with terminal aldehyde groups are used to prepare a self-assembled monolayer (SAM). The aldehyde ...groups of the monolayer may be reacted with amine-modified oligonucleotides or other amine-bearing biomolecules to form a Schiff base, which may then be reduced to a stable secondary amine by treatment with sodium cyanoborohydride. The surface modifications and reactions are characterized by polarization modulation Fourier transform infrared reflection absorption spectroscopy (PM-FTIRRAS), and the accessibility, binding specificity, and stability of the DNA-modified surfaces are demonstrated in hybridization experiments.
PDF
