Aim To quantify the cost and prediction of futile care in the Neonatal Intensive Care Unit (NICU). Methods We observed 1813 infants on 100 000 NICU bed days between 1999 and 2008 at the University of Chicago. We determined costs and assessed predictions of futility for each day the infant required mechanical ventilation. Results Only 6% of NICU expenses were spent on nonsurvivors, and in this sense, they were futile. If only money spent after predictions of death is considered, futile expenses fell to 4.5%. NICU care was preferentially directed to survivors for even the smallest infants, at the highest risk to die. Over 75% of ventilated NICU infants were correctly predicted to survive on every day of ventilation by every caretaker. However, predictions of ‘die before discharge’ were wrong more than one time in three. Attendings and neonatology fellows tended to be optimistic, while nurses and neonatal nurse practitioners tended to be pessimistic. Conclusions Criticisms of the expense of NICU care find little support in these data. Rather, NICU care is remarkably well targeted to patients who will survive, particularly when contrasted with care in adult ICUs. We continue to search for better prognostic tools for individual infants.

Objectives Errors in clinical reasoning are a major factor for delayed or flawed diagnoses and put patient safety at risk. The diagnostic process is highly dependent on dynamic team factors, local hospital organization structure and culture, and cognitive factors. In everyday decision-making, physicians engage that challenge partly by relying on heuristics – subconscious mental short-cuts that are based on intuition and experience. Without structural corrective mechanisms, clinical judgement under time pressure creates space for harms resulting from systems and cognitive errors. Based on a case-example, we outline different pitfalls and provide strategies aimed at reducing diagnostic errors in health care. Case presentation A 67-year-old male patient was referred to the neurology department by his primary-care physician with the diagnosis of exacerbation of known myasthenia gravis. He reported shortness of breath and generalized weakness, but no other symptoms. Diagnosis of respiratory distress due to a myasthenic crisis was made and immunosuppressive therapy and pyridostigmine were given and plasmapheresis was performed without clinical improvement. Two weeks into the hospital stay, the patient’s dyspnea worsened. A CT scan revealed extensive segmental and subsegmental pulmonary emboli. Conclusions Faulty data gathering and flawed data synthesis are major drivers of diagnostic errors. While there is limited evidence for individual debiasing strategies, improving team factors and structural conditions can have substantial impact on the extent of diagnostic errors. Healthcare organizations should provide the structural supports to address errors and promote a constructive culture of patient safety.

Background Diagnostic errors have been attributed to cognitive biases (reasoning shortcuts), which are thought to result from fast reasoning. Suggested solutions include slowing down the reasoning process. However, slower reasoning is not necessarily more accurate than faster reasoning. In this study, we studied the relationship between time to diagnose and diagnostic accuracy. Methods We conducted a multi-center within-subjects experiment where we prospectively induced availability bias (using Mamede et al.’s methodology) in 117 internal medicine residents. Subsequently, residents diagnosed cases that resembled those bias cases but had another correct diagnosis. We determined whether residents were correct, incorrect due to bias (i.e. they provided the diagnosis induced by availability bias) or due to other causes (i.e. they provided another incorrect diagnosis) and compared time to diagnose. Results We did not successfully induce bias: no significant effect of availability bias was found. Therefore, we compared correct diagnoses to all incorrect diagnoses. Residents reached correct diagnoses faster than incorrect diagnoses (115 s vs. 129 s, p < .001). Exploratory analyses of cases where bias was induced showed a trend of time to diagnose for bias diagnoses to be more similar to correct diagnoses (115 s vs 115 s, p = .971) than to other errors (115 s vs 136 s, p = .082). Conclusions We showed that correct diagnoses were made faster than incorrect diagnoses, even within subjects. Errors due to availability bias may be different: exploratory analyses suggest a trend that biased cases were diagnosed faster than incorrect diagnoses. The hypothesis that fast reasoning leads to diagnostic errors should be revisited, but more research into the characteristics of cognitive biases is important because they may be different from other causes of diagnostic errors.

Scientific peer review has existed for centuries and is a cornerstone of the scientific publication process. Because the number of scientific publications has rapidly increased over the past decades, so has the number of peer reviews and peer reviewers. In this paper, drawing on the relevant medical literature and our collective experience as peer reviewers, we provide a user guide to the peer review process, including discussion of the purpose and limitations of peer review, the qualities of a good peer reviewer, and a step-by-step process of how to conduct an effective peer review.

Fc receptor-like 4 (FcRL4) attenuates B-cell receptor signaling (BCR) while enhancing TLR-responsiveness. FcRL4-mediated BCR dampening is dependent on tyrosine phosphatases SHP1/2. However, regulation of FcRL4 expression and mechanisms underlying FcRL4 amplification of TLR-signaling remain unknown. We find that exposure of human B cells to TLR-2-7 -9 ligands leads to upregulated FcRL4 expression. In FcRL4 transfected B-cell lines, TLR9-induced FcRL4 upregulation was associated with increased HcK expression. Aditionally, p38 inhibition suppressed upregulation of FcRL4 and CD23 but not HcK expression. HcK is an enhancer of TLR-signaling, likely activated by SHP-1/2 and we found that HcK or SHP1/2 inhibition, significantly suppressed TLR9-induced upregulation of CD23. To determine an in vivo relevance for our findings we assessed TLR-stimulated purified FcRL4+ B cells and compared to FcRL4- B cells, FcRL4+ B cells expressed significantly higher levels of the pro-inflammatory cytokine IL-6. Evaluating B cells of HIV+ viremic subjects showed that ex vivo unstimulated FcRL4hi B cell subsets expressed high levels of IL-6. Further, FcRL4+ B cells exhibited high levels of HcK and phosphorylated MAPkinases p38 and Erk .Our data indicate that TLR-activation upregulates FcRL4 expression, and FcRL4 recruited SHP1/2 likely activates HcK thereby amplifying TLR-signaling. Finally, in HIV+ viremic subjects TLR-activated FcRL4+ B cells likely contribute to inflammation via IL-6 expression.