Unrecoverable stent deformation in the left main: Crush it or remove it?

Serial ostial and distal left main lesions continue to be one of the most difficult tasks for the interventional cardiologist, with many potential complications occurring. We present such a high-risk percutaneous coronary intervention where immediate stent explantation was deemed necessary because the metal deformation and high radial strength of the particular stent platform would prevent an acceptable procedural result if it had been crushed to the vessel wall. The aim of this paper was to discuss left main stent deformation, debate the risks and benefits of stent explantation and finally test in-vitro our theory on “insufficient” crush with stents with high radial strength and compare it with conventional stents. Bench-testing supports our ad-hoc explantation decision showing stent underexpansion, recoil, and malapposition, obtaining an inadequate minimal stent area.     

Microsurgical nonmicrovascular flaps in forearm and hand reconstruction

Relatively new method in flap's surgery, perforator flaps tends to monopolize nowadays the surgeon's interest. The question is: could these flaps be used not only as free flaps, as were mainly used until now, but also as local or regional flaps? On the basis of our experience with 115 operated cases, we will try to demonstrate that a lot of simple or composite defects in the forearm and hand could be covered, in selected cases, by using local or regional perforator flaps. This may have as result, in the future, a dramatic decrease in the indication for free flap transfers. Because these flaps need a microsurgical dissection, but do not need microvascular sutures, they could be defined as “microsurgical nonmicrovascular flaps.” The main advantages of these flaps could be summarized as: no microsurgical sutures, no main vascular pedicles sacrifice, same surgical field, shorter hospitalization time. © 2007 Wiley‐Liss, Inc. Microsurgery, 2007.     

A randomized phase II trial of sequential gemcitabine plus vinorelbine followed by gemcitabine plus ifosfamide versus gemcitabine plus cisplatin in the treatment of chemo-naive patients with stages III and IV non-small cell lung cancer (NSCLC)

BACKGROUND: Third-generation platinum-based combinations are established as first-line treatment for advanced non-small cell lung cancer (NSCLC). Non-platinum regimens could be an alternative if they show similar efficacy with better tolerability. This randomized phase II trial compared the objective tumor response rate (ORR) of sequential gemcitabine plus vinorelbine followed by gemcitabine plus ifosfamide versus gemcitabine plus cisplatin. Secondary objectives included time to disease progression (TTP), overall survival and toxicity. METHODS: Chemo-naive patients with stages III and IV NSCLC and Karnofsky performance status >70 were assigned to receive either (a) gemcitabine 1000mg/m(2) plus vinorelbine 25mg/m(2) on days 1 and 8 for 2 cycles, followed by gemcitabine 1000mg/m(2) on days 1 and 8 plus ifosfamide 2000mg/m(2) on day 1 (GV-GI arm) for 2 cycles or (b) gemcitabine 1250mg/m(2) on days 1 and 8 with cisplatin 70mg/m(2) on day 1 (GC arm) for 4 cycles. RESULTS: Between July 2001 and January 2003, 102 patients were enrolled (50 on the GV-GI arm and 52 on the GC arm). Patient characteristics were balanced between arms (GV-GI arm: median age 59 years, 84% male, 22 stage IIIB, 24 stage IV, 4 stage IIIA; GC arm: median age 56 years, 87% male, 27 stage IIIB, 23 stage IV, 2 stage IIIA). Of the 101 patients evaluable for response, ORR was significantly higher on the GC arm than on the GV-GI arm (25% versus 6%, respectively; p=0.007). No complete responses occurred. TTP was longer on the GC arm than on the GV-GI arm (median 135 and 79 days, respectively), although this difference was not statistically significant (p=0.065). Survival was not significantly different between the arms (median 293 and 197 days, respectively; p=0.16). Although significantly more thrombocytopenia was reported on the GC arm (22% and 4%, respectively; p=0.02), it did not lead to more transfusions (15 transfusions in 5 patients versus 14 transfusions in 6 patients, respectively). There was no significant difference in other safety parameters between treatment arms. CONCLUSIONS: GC appears to produce better response in advanced NSCLC than GV-GI, with a trend towards longer TTP. Except for more thrombocytopenia with GC, similar toxicity profiles were observed.     

B(0) and B(1)-insensitive uniform T(1)-weighting for quantitative, first-pass myocardial perfusion magnetic resonance imaging.

Myocardial perfusion can be estimated, in principle, from first-pass MR images by converting the T(1)-weighted signal-time curves to contrast agent concentration-time curves. Typically, T(1) weighting is achieved by saturating the magnetization with a nonselective radiofrequency (RF) pulse prior to the imaging sequence. The accuracy of the perfusion estimate derived from the single-point T(1)-weighted signal depends on the initial residual longitudinal magnetization (RLM) produced by the saturation pulse. In this study we demonstrate that single-shot, echo-planar imaging can be used to show initial RLM resulting from incomplete saturation due to static magnetic field and RF field inhomogeneities in the heart at 1.5 T. Three saturation pulses, single, composite simple, and composite B(1)-insensitive rotation (BIR-4) were evaluated in phantom and cardiac experiments. The RLM image was calculated by normalizing the saturated image by a proton-density-weighted image. Mean RLM produced by the three saturation pulses was significantly different in noncontrast cardiac imaging (RLM(single) = 0.108 +/- 0.078; RLM(composite) = 0.051 +/- 0.052; RLM(BIR-4) = 0.011 +/- 0.009; P < 0.001; n = 20). Using a BIR-4 pulse to perform saturation of magnetization seems promising for improving the effectiveness and uniformity of T(1) weighting for first-pass perfusion imaging.     

Prediction of unfavorable outcomes in cryptococcal meningitis: results of the multicenter Infectious Diseases International Research Initiative (ID-IRI) cryptococcal meningitis study

Cryptococcal meningitis (CM) is mostly seen in immunocompromised patients, particularly human immunodeficiency virus (HIV)-positive patients, but CM may also occur in apparently immunocompetent individuals. Outcome analyses have been performed in such patients but, due to the high prevalence of HIV infection worldwide, CM patients today may be admitted to hospitals with unknown HIV status, particularly in underdeveloped countries. The objective of this multicenter study was to analyze all types of CM cases in an aggregate cohort to disclose unfavorable outcomes. We retrospectively reviewed the hospitalized CM patients from 2000 to 2015 in 26 medical centers from 11 countries. Demographics, clinical, microbiological, radiological, therapeutic data, and outcomes were included. Death, neurological sequelae, or relapse were unfavorable outcomes. Seventy (43.8%) out of 160 study cases were identified as unfavorable and 104 (65%) were HIV infected. On multivariate analysis, the higher Glasgow Coma Scale (GCS) scores (p?=?0.021), cerebrospinal fluid (CSF) leukocyte counts > 20 (p?=?0.038), and higher CSF glucose levels (p?=?0.048) were associated with favorable outcomes. On the other hand, malignancy (p?=?0.026) was associated with poor outcomes. Although all CM patients require prompt and rational fungal management, those with significant risks for poor outcomes need to be closely monitored.     

A Narrative Review on Thrombolytics in Advanced CKD: Is it an Evidence-Based Therapy?

Purpose

A timely pharmacoinvasive strategy consisting of thrombolytic therapy (TT) plays a pivotal role in three major scenarios: acute ischemic stroke (AIS), acute myocardial infarction (STEMI), and massive pulmonary embolism (PE). Presence of advanced chronic kidney disease (CKD) (estimated glomerular filtration rate <?30 mL/min/1.73 m2), known to disturb thrombotic/thrombolytic equilibrium, causes difficulties for clinicians in evaluating risk-benefit balance, as current guidelines do not address the relationship between TT and the advanced CKD. This narrative review aims to evaluate the most important scientific resources regarding the evidences, benefits, and risks of using thrombolytics in advanced CKD.

Methods

We searched the electronic database of PubMed for studies evaluating the relationship between renal dysfunction and TT in patients with STEMI, AIS, and massive PE. Randomized controlled trials (RCTs), observational studies including prospective or retrospective cohort studies, reviews, meta-analyses, and guidelines were included if referring to TT for one of the three scenarios in advanced CKD.

Results

Prothrombotic conditions in CKD, associated with an increased risk of hemorrhages, can affect the safety and efficacy of TT. Concerns regarding in-hospital bleeding events and poor clinical outcomes subsequent to TT in advanced CKD continue to cause underutilization or delaying routine reperfusion therapy.

Conclusions

The impact of TT on the outcomes of advanced CKD patients is poorly understood to date, with scarce data available in current guidelines and conflicting results from observational studies. Until evidence-based data from RCTs will be obtained, the clinical challenge of maximizing benefits for this high-risk subgroup lays in the hands of practicing clinicians.

     

Kinetics methods for clinical epidemiology problems

Calculating the probability of each possible outcome for a patient at any time in the future is currently possible only in the simplest cases: short-term prediction in acute diseases of otherwise healthy persons. This problem is to some extent analogous to predicting the concentrations of species in a reactor when knowing initial concentrations and after examining reaction rates at the individual molecule level. The existing theoretical framework behind predicting contagion and the immediate outcome of acute diseases in previously healthy individuals is largely analogous to deterministic kinetics of chemical systems consisting of one or a few reactions. We show that current statistical models commonly used in chronic disease epidemiology correspond to simple stochastic treatment of single reaction systems. The general problem corresponds to stochastic kinetics of complex reaction systems. We attempt to formulate epidemiologic problems related to chronic diseases in chemical kinetics terms. We review methods that may be adapted for use in epidemiology. We show that some reactions cannot fit into the mass-action law paradigm and solutions to these systems would frequently exhibit an antiportfolio effect. We provide a complete example application of stochastic kinetics modeling for a deductive meta-analysis of two papers on atrial fibrillation incidence, prevalence, and mortality.Much of the medical progress over the last century can be attributed to the objective assessment of the effect of treatments on the evolution of specific diseases. Treatment effect is measured as the rate of an event such as recovery in a sample of the patient population. Relatively immediate results were obtained from studies involving acute diseases, occurring in previously healthy individuals, in which recovery could be clearly identified. This resulted in the development of effective treatments for most acute diseases affecting children and younger adults and a substantial prolongation of life expectancy (1). Consequently, many acute diseases were treated effectively. This led to the current, more complex situation, in which an elderly population suffers from a combination of chronic conditions. Few older people are strictly healthy, and besides the evolution of the chronic conditions themselves, acute diseases occurring in this setting do not always evolve as in a young, healthy population. This combination of chronic conditions and risk factors amounts to the presence of more heterogenous populations. Thus, samples need to be larger to allow reproducible predictions, compared with those for acute diseases occurring in a young and previously healthy population. Predictions that are also more complex (there is no strict “recovery”) apply to a limited range of cases.The concepts used by clinicians and epidemiologists to describe the health status of individuals and their prevalence in the population, as well as the rates of change in this status and the general predictive laws, are quite analogous to the concepts used by chemists for predicting the future concentrations of species in a reactor. Early works on the spread of epidemics of communicable diseases (2, 3) made reference to this analogy, unlike later developments in mathematical epidemiology (4, 5). The purpose of current mathematical modeling of epidemiology is mostly the kinetics (or “dynamics” as it is frequently called) of the spread of a communicable disease in an acute epidemic (6), an important and pressing problem when such epidemics occur. The primary phenomenon represented in these models is contagion. The models used are typically deterministic, self-catalytic kinetic models of the whole population, with mass-action law assumption.The focus of clinical studies in chronic diseases is the risk for various possible outcomes for the patient that are usually distinct from a complete recovery and sometimes of a quantitative nature—for example, how much of the function of an organ is preserved. Kinetics-type mathematical support for this purpose is rarely available, other than a simple statement of risk or relative risk that is directly inferred from a study in a sample.Deterministic event rates are the basis of virtually all clinical judgement. A typical example is, What is the yearly risk of stroke in patients with atrial fibrillation on either of two treatments, such as warfarin or aspirin? (More individual parameters are usually taken into account when classifying each patient). A lower yearly risk rate in one of the treatment categories is an argument to choose that treatment for a particular patient. This risk rate is usually the rate of stroke that has been directly measured in a study where a sample of patients belonging to certain classes (for example, middle-aged males with atrial fibrillation and no history of stroke) has been followed for some time. The observed event rates are taken as the best estimations for the population sharing the same characteristics as the patients in the sample, a population that is presumed infinite. The event rates are inferred, however, starting from observations made in finite, small, ensembles of individuals (case series). Thus, inference is always probabilistic, as event rates in the population can be estimated only with some uncertainty, even in homogenous populations.In populations in which individuals have various combinations of underlying pathologies that may each influence the future event rates, this approach may frequently lead to unreproducible results (7, 8). Aiming to predict events that would occur in the more distant future, as needed with chronic disease, further complicates the problem: The longer the prediction time is, the higher the number of other events that may intervene and invalidate the prediction.Both epidemiology and chemical kinetics have evolved independently over the previous decades, each developing its own stochastic methods with a specific terminology that frequently refers to somewhat similar concepts. Prediction of event rates from relatively small samples, using probabilistic models, is of primary importance for epidemiology. Half a century ago, the factors influencing the recovery from acute diseases in otherwise healthy (that is, homogenous) populations were the main concern. Thus, the problem was to estimate event rates in otherwise simple systems. Models of the epidemiologic equivalent of a single reaction, with a few other parameters, were adequate for this. Probabilistic issues were mostly related to the errors associated with the limited sizes of the samples used, but the inferred rates were typically deterministic. In chemistry, at that time, model development focused on identifying the relatively complex reaction mechanisms that occur, even when only a few initial species are involved, and on describing their kinetics, typically with systems of deterministic differential equations adjusted using macroscopic measurements of species concentrations. Uncertainty due to small molecule numbers was not usually involved. Over the last 70 y, however, chemical kinetics developed new methods, such as models of more complex systems that do not rely on mass-action law (9) or models of single-molecule kinetics that might be closer to the problem of predicting clinical evolution in individual patients. Also, issues that occur in the biochemical kinetics of more complex systems, such as crowding (10), are to some extent analogous to event prediction in heterogenous populations.The development of numerical methods allows the practical approach to problems that involve systems that are both complex and stochastic and the exploration of uncertain phenomena at both individual and population levels (11). An important clinical problem that cannot, in general, be solved without such a systematic approach is to compute, for an individual, the risks for each possible disease over the next time interval (such as 1 y), given what we know about his or her health status and history and based on currently available epidemiologic data. Solving this problem would allow much more accurate planning of clinical interventions than is possible today.In this paper, we attempt to compare concepts, methods, and models that have been developed in the two fields, by reformulating the epidemiologic approaches in chemical kinetics terms, to identify chemical kinetics methods that might be adaptable for epidemiologic use. In Supporting Information, we show an example of a deductive meta-analysis of two epidemiology papers, using a stochastic kinetic system.