Mortality benefit of primary transportation to a PCI‐capable center persists through an eight‐year follow‐up in patients with ST‐segment elevation myocardial infarction

Background

The purpose of this study was to compare long‐term outcomes of primary transport (PT) and secondary transport (ST) in patients with STEMI.

Method

We assigned consecutive 869 patients referred for STEMI during a 2‐year period (2008‐2009). The primary endpoint was to compare long‐term outcomes and mortality of PT to a catheterization laboratory and ST from regional hospitals to a catheterization laboratory. Six hundred seventy‐seven patients (77.9%) were enrolled for the final evaluation, 192 (22.1%) having been excluded.

Results

The median DBT was 34 ± 15.92 min for PT patients (n = 354) and 100 ± 28.82 min for ST patients (n = 323) (P < 0.005). One‐month mortality was 3.95% in the PT group versus 9.46% in the ST group (P = 0.002). One‐year mortality in the PT was 7.35% and 20.51% in the ST group (P < 0.005). Eight‐year mortality was in the PS 26.8% versus 32.6% in the ST group (P = 0.035). Left ventricular ejection fraction (LVEF) was 45 ± 12.14% versus 45 ± 12.48% (P = 0.21); creatine kinase (CK) was 22.78 ± 78.69 ukat/L versus 23.21 ± 82.61 ukat/L, (P = 0.58); and length of hospitalization was 4.98 ± 4.61 days in the PT group versus 5.25 ± 5.86 days in the ST group (P = 0.22). The air transport was used in the PT group (RR 0.85, 95% CI 0.63‐1.09); and ST group (RR 1.17, 95% CI 0.91‐1.40); P = 0.22). Time distribution of cardiac arrest median for PT 1432 days (n = 25) versus ST 266 (n = 31) P = 0.24.

Conclusion

The mortality benefits of PT to a PCI capable hospital persist throughout an 8‐year follow‐up.

     

Pooled testing efficiency increases with test frequency

Pooled testing increases efficiency by grouping individual samples and testing the combined sample, such that many individuals can be cleared with one negative test. This short paper demonstrates that pooled testing is particularly advantageous in the setting of pandemics, given repeated testing, rapid spread, and uncertain risk. Repeated testing mechanically lowers the infection probability at the time of the next test by removing positives from the population. This effect alone means that increasing frequency by x times only increases expected tests by around x. However, this calculation omits a further benefit of frequent testing: Removing infections from the population lowers intragroup transmission, which lowers infection probability and generates further efficiency. For this reason, increasing testing frequency can paradoxically reduce total testing cost. Our calculations are based on the assumption that infection rates are known, but predicting these rates is challenging in a fast-moving pandemic. However, given that frequent testing naturally suppresses the mean and variance of infection rates, we show that our results are very robust to uncertainty and misprediction. Finally, we note that efficiency further increases given natural sampling pools (e.g., workplaces, classrooms) that induce correlated risk via local transmission. We conclude that frequent pooled testing using natural groupings is a cost-effective way to provide consistent testing of a population to suppress infection risk in a pandemic.

The COVID-19 pandemic has generated a health and economic crisis not seen in more than a century. Opening businesses and schools is necessary to regain economic activity, but the potential public health costs are dramatic. One policy to circumvent this stark trade-off is to open the economy, while implementing surveillance testing that can quickly identify infected individuals—particularly those without symptoms—and prevent them from spreading the disease. Unfortunately, testing at this scale appears infeasible given the cost and capacity constraints. This paper makes a simple but essential point about these costs: When using pooling testing, frequent testing of correlated samples makes testing dramatically more efficient (and therefore less costly) than understood both by existing research and policy makers.In pooled testing (1), multiple samples are combined and tested together using one test, and the entire pool is cleared given a negative test result. Pooling is an old concept, and a large literature has emerged on optimal strategies (1–10); more recently, others have discussed how it might be used to increase COVID-19 test efficiency (11, 12). However, all of these papers focus on one-time testing of a set of samples with known and independent infection risk, which matches common use cases such as screening donated blood for infectious diseases (13–18). These environmental assumptions are violated when dealing with a novel pandemic with rapid spread. In this case, people need to be tested multiple times, testing pools are likely formed from populations with correlated infection risk, and risk levels at any time are very uncertain. How do these changes impact testing strategy?We start with the well-known observation that pooled testing is more efficient when the infection probability is lower, because the likelihood of a negative pooled test is increased. This observation has been used to conclude that pooled testing is not cost-effective for “high-risk” populations, such as health care workers or for people in areas experiencing an outbreak. While this statement is true for one-off testing, it does not hold when the population is tested repeatedly. As an extreme example, if a person in a high-risk area was just tested and determined to be negative, their probability of infection when tested an hour later is extremely low, simply because there is not much time to be infected between the tests. In other words, the infection probability at the time of testing depends both on the flow rate of infection and the timing of testing.We quantify the impact of testing frequency on infection probability and its consequent impact on pooled-testing efficiency. For example, we show that, given reasonable levels of independent risk, testing twice as often cuts the infection probability at the time of testing by (about) half, which lowers the expected number of tests at each testing round to about 70% of the original number. The savings are akin to a “quantity discount” of 30% in the cost of testing. Therefore, rather than requiring 2 times the number of tests, doubling the frequency only increases costs by a factor of 1.4. More generally, we demonstrate that testing more frequently requires fewer tests than might be naively expected: Increasing frequency by x times only uses about x as many tests, implying a quantity discount of (1−1/x).The benefits to frequency are even greater when the disease spreads within the testing population. In this case, testing more frequently has an additional benefit: By quickly removing infected individuals, infection spread is contained, future infection probabilities are lowered, and testing efficiency rises further. We analytically quantify this additional benefit as a function of the exponential-like growth path of the disease. We show that, in this case—somewhat paradoxically—the quantity discount can be so great that more frequent testing can actually reduce the total number of tests. For example, if the disease dynamics are such that doubling the testing frequency reduces the infection probability at the time of testing by more than fourfold, then doubling the frequency will require fewer tests in expectation.In our simple model, we assume that infection probabilities are known when constructing optimal pool sizes and efficiency statistics. However, the prediction of infections in a fast-changing pandemic is an extremely difficult inference problem (see, e.g., ref. 19). Given this issue, it is appropriate to worry that uncertainty and potential misprediction will make pool size choices challenging, reduce pooled testing efficiency, and render our conclusions void. For example, testing data from Massachusetts in the fall of 2020 shows high average testing positivity rates (7%) that vary widely across time and space (SD of 6%) in potentially unpredictable ways. (These data are publicly available at https://www.mass.gov/info-details/covid-19-response-reporting.) Using one-off pooled testing given this population—which has an extremely high positivity rate partially due to self-selection of people who desire a test—will be very inefficient given the high rates and the potential for misoptimization. However, as discussed above, frequent testing of a consistent population reduces the mean and variance of infection probabilities at the time of testing because there is little time between testing for mean- and variance-inducing spread to occur, and the selection issue is removed. For example, as noted in ref. 20, the town of Wellesley, MA, employed weekly testing of consistent subpopulations in the fall of 2020, and the average positivity rates stayed low (0.3%) and didn’t vary considerably (SD of 0.3%). When positivity rates have low mean and variance, we show that the efficiency of pooled testing is strongly robust to reasonably miscalibrated estimations and constant pool sizes, such that pooled testing remains very attractive. Finally, we note that better estimation of the positivity distribution is also helped by frequent testing, which naturally produces a constant stream of recent test result data from the relevant population.We note one final efficiency benefit associated with the most natural implementation of frequent testing. When frequently testing a consistent subpopulation (such as those living or working together), it is likely that the infection spreads within the subpopulation. This correlation increases the benefits of pooled testing even in a static testing environment (a finding concurrently noted in ref. 21). Intuitively, an increased correlation in a pool with fixed individual risk lowers the likelihood of a positive pooled test result, which increases efficiency.Throughout the paper, we consider a very stylized environment with a number of simplifications to present transparent results. While removing these constraints further complicates the problem and raises a number of important logistical questions, we do not believe that their inclusion changes our main insights. For example, our simple model assumes that a person who becomes infected will test positive indefinitely, whereas, in reality, they will potentially recover at some point. This does not impact our results when the time between tests is less than the recovery period, but it lowers the relative cost of pooled testing when frequency is low, because the prevalence is lower due to recoveries. However, our main qualitative conclusion—testing more frequently leads to fewer tests for each testing period—still holds in this case.Another important simplification is that we model a test with perfect sensitivity. [As noted in ref. 22, test specificity of standard protocols such as PCR appears to be very close to one. However, if specificity is a concern, the past literature (9, 23) has clear methods to optimize in the case of imperfect tests.] There are multiple ways in which pooled testing interacts with test sensitivity. First, there is a natural negative impact: Combining samples can potentially dilute the viral load below the limit of detection of the test. However, this implies that the false negatives will occur when the viral load is very low and the person is less likely to be infectious.^* Second, this dilution concern is counteracted, when testing frequently, by the large increase in overall sensitivity coming from running a larger number of tests.^† Third, as noted in ref. 22, false negatives may result from poor-quality samples. However, frequency again has benefits: By testing the same population repeatedly, subjects become better experienced with proper sampling protocols, and those who provide poor samples can be identified and corrected.Finally, we largely abstract away various practical implementation costs and constraints. First, we assume that every test, whether individual or pooled, has the same cost. However, pooled testing necessitates a more complicated setup in the laboratory, requiring more space and trained personnel (or a robotic setup) to correctly mix the samples together. While these costs are relatively moderate if spread over a long period of time, a laboratory might be reluctant to change their operations when the duration of the pandemic is very unclear. Second, we assume that there is no time delay between testing and receiving the test result. In reality, it takes time to transport samples to the laboratory and test them, and pooled testing takes more time than individual testing because it potentially requires an additional retesting step. Fortunately, the difference in these delays can be minimized when using the common “hold-out” method: Only a portion of each individual sample is used to construct the pooled sample, such that the remaining portions of the individual samples can be immediately individually tested if the pooled sample tests positive. However, even if the difference is minimized, any delay still impacts our analysis. In particular, by assuming no delay, increasing the testing frequency minimizes the likelihood of undiscovered new infections in the time between tests, such that the infection probability at the time of testing can be kept arbitrarily low. But, when there is a delay in receiving test results, it is not possible to stop infection and spread during the delay period even if testing is continuous. Therefore, it might be simply impossible to lower the infection probability below the ∼5% threshold at which the cost benefit of pooled testing is considered clear. In this extreme case, we do not recommend pooled testing. However, if the risk and spread are so extreme that 5% of a group is expected to be newly infected every few days even with very frequent testing, an alternative policy relying on isolation seems far more likely.Although we see this paper as noting a general insight of the relationship between pooled testing and testing frequency, it is useful to discuss the particular historical context in which the paper was written. The first paper draft of the paper was completed in June 2020, during the first wave of the COVID-19 pandemic. At that point, testing supply was low and prices were high because laboratories were building up testing capacity in a relatively strict regulatory environment. By early 2021, multiple organizations—such as Mirimus, Ginkgo, and the Broad—were offering frequent pooled testing at much cheaper prices than individual testing, and multiple organizations with correlated risk—such as employers, cities, and school districts—were employing these tests. For example, in February 2021, Massachusetts implemented a policy of providing universal weekly pooled testing for all K-12 students and faculty and staff.^‡ And, nationally, the Rockefeller Foundation called for use of frequent pooled testing as an essential aspect of school reopening (30).^§ The authors, based on the main insights of this paper, supported many of these policy initiatives and recommendations. Interestingly, the cost of pooled testing in Massachusetts (between $3 and $10 per student per test) is almost precisely the predicted amount using pooling in the first draft of the paper, providing a useful empirical validation of the model.The paper proceeds as follows: Pooled Testing reviews one important finding in the pooled testing literature that efficiency rises as infection probability falls; Increasing Test Frequency Interaction discusses the relationship between testing frequency and efficiency; Robustness to Uncertainty demonstrates how correlated infection leads to larger pool sizes and greater efficiency; and Conclusions concludes.     

Experimental Investigation on the Structural Performance of Single Span Hollow Core Slab under Successive Impact Loading

In Lebanon and many other countries where structures are vulnerable to impact loads caused by accidental rock falls due to landslides, specifically bridges with hollow core slab, it is mandatory to develop safe and efficient design procedures to design such types of structures to withstand extreme cases of loading. The structural response of concrete members subjected to low velocity high falling weight raised the interest of researchers in the previous years. The effect of impact due to landslide falling rocks on reinforced concrete (RC) slabs has been investigated by many researchers, while very few studied the effect of impact loading on pre-stressed structures, noting that a recent study was conducted at Beirut Arab University which compared the dynamic behavior of reinforced concrete and post-tensioned slabs under impact loading from a 605 kg impactor freely dropped from a height of 20 m. Hollow core slabs are widely used in bridges and precast structures. Thus, studying their behavior due to such hazards becomes inevitable. This study focuses on these types of slabs. For a better understanding of the behavior, a full scale experimental program consists of testing a single span hollow core slab. The specimen has 6000 mm × 1200 mm × 200 mm dimensions with a 100 mm cast in a place topping slab. Successive free fall drops cases from 14 m height will be investigated on the prescribed slab having a span of 6000 m. This series of impacts will be held by hitting the single span hollow core slab at three different locations: center, edge, and near the support. The data from the testing program were used to assess the structural response in terms of experimental observations, maximum impact and inertia forces, structural damage/failure: type and pattern, acceleration response, and structural design recommendations. This research showed that the hollow core slab has a different dynamic behavior compared to the post tensioned and reinforced concrete slabs mentioned in the literature review section.     

Ultrasound-guided fine-needle aspiration and thyroid disease

BACKGROUND: Fine-needle aspiration represents a critical diagnostic test in determining proper management of thyroid disease and the use of ultrasound-guided fine-needle aspiration (USGFNA) has increased over the years. METHODS: A retrospective chart review of patients undergoing USGFNA. Two hundred fifteen patients underwent 234 procedures with 362 nodules aspirated within a 2 (1/2)-year period. RESULTS: The mean ages of women and men were 51.9 and 57.8, respectively. The average size of nodules was 2.1 cm. A difficult to assess gland or nodule was the most common indication for USGFNA (33%). The sensitivity was 88.2%, specificity was 80.0%, the PPV was 65.2%, the negative predictive value was 94.1%, and the accuracy was 82.5%. The cancer yield, inadequacy, and complication rates were 44%, 10.5%, and 8.5%, respectively. CONCLUSIONS: USGFNA aspiration is a safe and effective diagnostic modality in the management of thyroid disease, especially for nodules that are difficult to palpate.     

Scleral fixation of posterior chamber intraocular lenses using fascia lata to cover the knots

BACKGROUND AND OBJECTIVE: To describe the use of fascia lata to cover the polypropylene knots of scleral fixated posterior chamber intraocular lenses (PCIOL). PATIENTS AND METHODS: Fascia lata was used to cover the knots of scleral fixated PCIOL in 5 eyes with significant scleral thinning. Four of the 5 eyes had the PCIOL insertion and the fascia lata patching in the same setting. The fifth eye previously had scleral fixated PCIOL with late suture erosion through a partial thickness scleral flap. RESULTS: There was no suture exposure or graft thinning throughout a follow-up period of 8 to 16 months. The eyes tolerated the fascia lata well with no early or late postoperative complications. CONCLUSION: Fascia lata provides an effective means to cover the knots of scleral fixated PCIOL, especially in aphakic patients with significant scleral thinning.     

Guidelines for the management of community-acquired pneumonia in Saudi Arabia: a model for the Middle East region

Worldwide, community-acquired pneumonia (CAP) is a common respiratory tract infection and is now a growing public health concern in Saudi Arabia. In an effort to simplify treatment regimens to aid the practitioner, empirical treatment guidelines for CAP have evolved across the international medical community, reducing the number of antibiotics used and improving outcomes. Saudi Arabia and the surrounding region have no such consensus guidelines and this document aims to redress this lack. The potential impacts of developing and implementing CAP treatment guidelines in Saudi Arabia, which are new to the Kingdom, will be examined. Widespread adoption of these SACAP guidelines could lead to nationwide reductions of antibiotic resistance and improvement of clinical outcomes. Ultimately, Kingdomwide uniformity of treatment algorithms provides a foundation for both database generation and valuable outcomes of research in the future.     

Immune dysregulation in major depression: a critical review of existing evidence

It is now well established that depression is associated with immune dysregulation. It is not, however, known whether this immune dysregulation plays a role in the pathophysiology of major depression or whether it increases the susceptibility of the depressed patient to immune-related disorders. This article presents a critical review of existing evidence for immune dysregulation in major depression, including changes in leucocyte trafficking, lymphocyte function, and markers of immune activation. Possible mediators of immune dysregulation in major depression are briefly discussed. Finally, the relationship between major depression and several medical conditions such as infection, allergy and autoimmune disorders, cardiovascular diseases, cancer and AIDS is critically reviewed.     

Infection control in Saudi Arabia: meeting the challenge

Hospital-acquired infection poses significant clinical and economic burden worldwide. In the Kingdom of Saudi Arabia, infection control is a young, rapidly growing specialty. An infrastructure to expedite the growth of this important discipline is fast being established. The kingdom faces unique challenges when addressing infection control, which are the subject of this review.Much of the policy-making in domestic infection control is driven by the preventive medicine concerns of the annual pilgrimage (Hajj) to Mecca, which are unparalleled. The Saudi Ministry of Health acts to contain and control public health risks at this gathering of 2 million. Infectious hazards at the Hajj include meningococcal meningitis, respiratory tract infections, bloodborne diseases, and zoonotic diseases, all of which have international ramifications as pilgrimaging Muslims return home.In the wake of the extraordinary pace of modernization in Saudi Arabia, deficiencies in infection control remain, which are slowly being redressed. This review examines the anatomy of infection control and its evolution in the kingdom. Future goals and infection control policy-making are given particular emphasis.Saudi Arabia seeks increasing international partnership in the area of infection control and preventive medicine. The Saudi health care system was formed on the basis of Western models to resounding success. Saudi Arabia is now in a position to provide experience and knowledge in return. International dialogue in the infection control arena is of mutual value. Important public health progress is afoot in this young kingdom, and these advances translate both regionally and on the international platform.