Sensitivity Analysis for Matched Observational Studies with Continuous Exposures and Binary Outcomes

Matching is one of the most widely used study designs for adjusting for measured confounders in observational studies. However, unmeasured confounding may exist and cannot be removed by matching. Therefore, a sensitivity analysis is typically needed to assess a causal conclusion's sensitivity to unmeasured confounding. Sensitivity analysis frameworks for binary exposures have been well-established for various matching designs and are commonly used in various studies. However, unlike the binary exposure case, there still lacks valid and general sensitivity analysis methods for continuous exposures, except in some special cases such as pair matching. To fill this gap in the binary outcome case, we develop a sensitivity analysis framework for general matching designs with continuous exposures and binary outcomes. First, we use probabilistic lattice theory to show our sensitivity analysis approach is finite-population-exact under Fisher's sharp null. Second, we prove a novel design sensitivity formula as a powerful tool for asymptotically evaluating the performance of our sensitivity analysis approach. Third, to allow effect heterogeneity with binary outcomes, we introduce a framework for conducting asymptotically exact inference and sensitivity analysis on generalized attributable effects with binary outcomes via mixed-integer programming. Fourth, for the continuous outcomes case, we show that conducting an asymptotically exact sensitivity analysis in matched observational studies when both the exposures and outcomes are continuous is generally NP-hard, except in some special cases such as pair matching. As a real data application, we apply our new methods to study the effect of early-life lead exposure on juvenile delinquency. We also develop a publicly available R package for implementation of the methods in this work

Molecular Detection Of Hematodinium Sp Infecting The Blue Crab, Callinectes Sapidus

Species of Hematodinium are endoparasitic dinoflagellates of crustaceans. Certain stages of the parasites can be very difficult to detect in the hemolymph of their hosts, because the trophic stages resemble hemocytes, and they can occur at relatively low densities, making diagnosis by microscopy difficult. We developed a polymerase chain reaction (PCR) assay to detect the Hernatodinium sp. infecting the blue crab, Callinectes sapidus, based on the amplification of the parasite\u27s first internal transcribed spacer region (ITS1) of the ribosomal RNA (rRNA) gene complex. The PCR assay was combined with a restriction endonucleases digestion (Bsg I) of the amplification products to differentiate between different forms of Hematodinium from different hosts. The assay had a limit of detection equivalent to 0.3 parasites per 100-mu L hemolymph. In addition, two oligonucleotide DNA probes were designed to target the 18S rRNA gene sequence of the parasite, facilitating detection in situ in crustacean tissues. These probes appear to target several, if not all species within the genus, because they labeled all isolates of Hematodinium tested in this study, whereas they were not hybridizing to other parasite species. The PCR-RFLP assay will be invaluable for future studies investigating parasite prevalence, the existence of secondary hosts or environmental reservoirs, and modes of transmission, whereas the DNA probes will be useful for confirming and localizing Hematodinium parasites in crustacean tissues

Optimal Matching with Minimal Deviation from Fine Balance in a Study of Obesity and Surgical Outcomes

In multivariate matching, fine balance constrains the marginal distributions of a nominal variable in treated and matched control groups to be identical without constraining who is matched to whom. In this way, a fine balance constraint can balance a nominal variable with many levels while focusing efforts on other more important variables when pairing individuals to minimize the total covariate distance within pairs. Fine balance is not always possible; that is, it is a constraint on an optimization problem, but the constraint is not always feasible. We propose a new algorithm that returns a minimum distance finely balanced match when one is feasible, and otherwise minimizes the total distance among all matched samples that minimize the deviation from fine balance. Perhaps we can come very close to fine balance when fine balance is not attainable; moreover, in any event, because our algorithm is guaranteed to come as close as possible to fine balance, the investigator may perform one match, and on that basis judge whether the best attainable balance is adequate or not. We also show how to incorporate an additional constraint. The algorithm is implemented in two similar ways, first as an optimal assignment problem with an augmented distance matrix, second as a minimum cost flow problem in a network. The case of knee surgery in the Obesity and Surgical Outcomes Study motivated the development of this algorithm and is used as an illustration. In that example, 2 of 47 hospitals had too few nonobese patients to permit fine balance for the nominal variable with 47 levels representing the hospital, but our new algorithm came very close to fine balance. Moreover, in that example, there was a shortage of nonobese diabetic patients, and incorporation of an additional constraint forced the match to include all of these nonobese diabetic patients, thereby coming as close as possible to balance for this important but recalcitrant covariate

Disease will limit future food supply from the global crustacean fishery and aquaculture sectors

Seafood is a highly traded food commodity. Farmed and captured crustaceans contribute a significant proportion with annual production exceeding 10 M metric tonnes with first sale value of $40bn. The sector is dominated by farmed tropical marine shrimp, the fastest growing sector of the global aquaculture industry. It is significant in supporting rural livelihoods and alleviating poverty in producing nations within Asia and Latin America while forming an increasing contribution to aquatic food supply in more developed countries. Nations with marine borders often also support important marine fisheries for crustaceans that are regionally traded as live animals and commodity products. A general separation of net producing and net consuming nations for crustacean seafood has created a truly globalised food industry. Projections for increasing global demand for seafood in the face of level or declining fisheries requires continued expansion and intensification of aquaculture while ensuring best utilisation of captured stocks. Furthermore, continued pressure from consuming nations to ensure safe products for human consumption are being augmented by additional legislative requirements for animals (and their products) to be of low disease status. As a consequence, increasing emphasis is being placed on enforcement of regulations and better governance of the sector; currently this is a challenge in light of a fragmented industry and less stringent regulations associated with animal disease within producer nations. Current estimates predict that up to 40$3bn) is lost annually, mainly due to viral pathogens for which standard preventative measures (e.g. such as vaccination) are not feasible. In light of this problem, new approaches are urgently required to enhance yield by improving broodstock and larval sourcing, promoting best management practices by farmer outreach and supporting cutting-edge research that aims to harness the natural abilities of invertebrates to mitigate assault from pathogens (e.g. the use of RNA interference therapeutics). In terms of fisheries losses associated with disease, key issues are centred on mortality and quality degradation in the post-capture phase, largely due to poor grading and handling by fishers and the industry chain. Occurrence of disease in wild crustaceans is also widely reported, with some indications that climatic changes may be increasing susceptibility to important pathogens (e.g. the parasite Hematodinium). However, despite improvements in field and laboratory diagnostics, defining population-level effects of disease in these fisheries remains elusive. Coordination of disease specialists with fisheries scientists will be required to understand current and future impacts of existing and emergent diseases on wild stocks. Overall, the increasing demand for crustacean seafood in light of these issues signals a clear warning for the future sustainability of this global industry. The linking together of global experts in the culture, capture and trading of crustaceans with pathologists, epidemiologists, ecologists, therapeutics specialists and policy makers in the field of food security will allow these issues to be better identified and addressed

Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairness

Group fairness is achieved by equalising prediction distributions between protected sub-populations; individual fairness requires treating similar individuals alike. These two objectives, however, are incompatible when a scoring model is calibrated through discontinuous probability functions, where individuals can be randomly assigned an outcome determined by a fixed probability. This procedure may provide two similar individuals from the same protected group with classification odds that are disparately different -- a clear violation of individual fairness. Assigning unique odds to each protected sub-population may also prevent members of one sub-population from ever receiving equal chances of a positive outcome to another, which we argue is another type of unfairness called individual odds. We reconcile all this by constructing continuous probability functions between group thresholds that are constrained by their Lipschitz constant. Our solution preserves the model's predictive power, individual fairness and robustness while ensuring group fairness.Comment: 23 pages, 5 figures, 2 table

Counterfactual Explanations via Locally-guided Sequential Algorithmic Recourse

Counterfactuals operationalised through algorithmic recourse have become a powerful tool to make artificial intelligence systems explainable. Conceptually, given an individual classified as y -- the factual -- we seek actions such that their prediction becomes the desired class y' -- the counterfactual. This process offers algorithmic recourse that is (1) easy to customise and interpret, and (2) directly aligned with the goals of each individual. However, the properties of a "good" counterfactual are still largely debated; it remains an open challenge to effectively locate a counterfactual along with its corresponding recourse. Some strategies use gradient-driven methods, but these offer no guarantees on the feasibility of the recourse and are open to adversarial attacks on carefully created manifolds. This can lead to unfairness and lack of robustness. Other methods are data-driven, which mostly addresses the feasibility problem at the expense of privacy, security and secrecy as they require access to the entire training data set. Here, we introduce LocalFACE, a model-agnostic technique that composes feasible and actionable counterfactual explanations using locally-acquired information at each step of the algorithmic recourse. Our explainer preserves the privacy of users by only leveraging data that it specifically requires to construct actionable algorithmic recourse, and protects the model by offering transparency solely in the regions deemed necessary for the intervention.Comment: 7 pages, 5 figures, 3 appendix page

Preoperative neutrophil-lymphocyte ratio and outcome from coronary artery bypass grafting

Background: An elevated preoperative white blood cell count has been associated with a worse outcome after coronary artery bypass grafting (CABG). Leukocyte subtypes, and particularly the neutrophil-lymphocyte (N/L) ratio, may however, convey superior prognostic information. We hypothesized that the N/L ratio would predict the outcome of patients undergoing surgical revascularization. Methods: Baseline clinical details were obtained prospectively in 1938 patients undergoing CABG. The differential leukocyte was measured before surgery, and patients were followed-up 3.6 years later. The primary end point was all-cause mortality. Results: The preoperative N/L ratio was a powerful univariable predictor of mortality (hazard ratio [HR] 1.13 per unit, P 3.36). Conclusion: An elevated N/L ratio is associated with a poorer survival after CABG. This prognostic utility is independent of other recognized risk factors.Peer reviewedAuthor versio

Bacillus Coagulans GBI-30 (BC30) improves indices of Clostridium difficile-Induced colitis in mice

<p>Abstract</p> <p>Background</p> <p>Probiotics have beneficial effects in rodent models of <it>Clostridium difficile </it>(<it>C. diffiicle</it>)-induced colitis. The spore forming probiotic strain <it>Bacillus Coagulans </it>GBI-30, 6086 (BC30) has demonstrated anti-inflammatory and immune-modulating effects <it>in vitro</it>. Our goal was to determine if BC30 improved <it>C. difficile</it>-induced colitis in mice. Starting on study day 0, female C57BL/6 mice were dosed by oro-gastric gavage for 15 days with vehicle (saline) or BC30 (2 × 10⁹CFU per day). Mice in the <it>C. difficile </it>groups received an antibiotic mixture (study days 5 to 8 in the drinking water), and clindamycin (10 mg/kg, i.p., on study day 10). The <it>C. difficile </it>strain VPI 10463 was given by gavage at 10⁴CFU to induce colitis on day 11. On day 16, stools and colons were collected for further analyses.</p> <p>Results</p> <p>All mice treated with BC30 survived on study day 13, while two mice treated with vehicle did not survive. On day 12, a significant difference (p = 0.0002) in the percentage of mice with normal stools (66.7%) was found in the BC30/<it>C. difficile </it>group, as compared to the vehicle/<it>C. diffcile </it>group (13.0%). On study day 16, 23.8% of mice treated with BC30 had normal stools, while this value was 0% with vehicle treatment (p value = 0.0187). On this day, the stool consistency score for the BC30/<it>C. difficile </it>group (1.1 ± 0.2) was significantly lower (p < 0.05) than for the vehicle/<it>C. difficile </it>cohort (1.9 ± 0.2). BC30 modestly attenuated the colonic pathology (crypt damage, edema, leukocyte influx) that was present following <it>C. difficile infection</it>. Colonic MIP-2 chemokine contents (pg/2 cm colon) were: 10.2 ± 0.5 (vehicle/no <it>C. difficile</it>), 24.6 ± 9.5 (vehicle/<it>C. difficile</it>) and 16.3 ± 4.3 (BC30/<it>C. difficle</it>).</p> <p>Conclusion</p> <p>The probiotic BC30 improved some parameters of <it>C. difficile</it>-induced colitis in mice. BC30 prolonged the survival of <it>C. diffiicle </it>infected mice. Particularly, this probiotic improved the stool consistency of mice, in this infectious colitis model.</p

New insight into the transmission dynamics of the crustacean pathogen Hematodinium perezi (Dinoflagellata) using a novel sentinel methodology

Hematodinium perezi causes disease and mortality in several decapod crustaceans along the eastern seaboard and Gulf coast of the USA. The route of transmission of the parasite is unknown, but infections exhibit a sharp seasonal cycle in its primary host, the blue crab Callinectes sapidus, that indicates the possibility of a short transmission period in its life cycle. We developed a sentinel methodology based on the use of naïve, uninfected, early benthic juvenile crabs (instars C1 to C10) to investigate the transmission of H. perezi. Crabs were collected from a non-endemic site, held for a short period for evaluation, and then deployed in a highly endemic site for 14 d. Transmission of the pathogen was successful; 12.7 to 25.7% of the crabs deployed at the endemic site became infected over this period. Infections developed rapidly, with 25% of new infections developing into heavy infections during the deployment. The large number of infections that developed using the sentinel methodology allowed for the first estimates of incidence (the proportion of new infections in a population over time) in this system. Incidence varied from 0.9 to 1.8% of the resident crab population per day and accounts for the high prevalence levels observed in the endemic coastal bays of the Delmarva Peninsula. The development of this sentinel methodology has broad application for studying disease ecology in this system and in other pathogens that infect decapods