Lege Artis Medicinae

[Bedside decision making - Prognostic functions]

VOKÓ Zoltán

DECEMBER 21, 2011

Lege Artis Medicinae - 2011;21(12)

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We aimed to investigate the association between fluoxetine use and the survival of hospitalised coronavirus disease (COVID-19) pneumonia patients. This retrospective case-control study used data extracted from the medical records of adult patients hospitalised with moderate or severe COVID-19 pneumonia at the Uzsoki Teaching Hospital of the Semmelweis University in Budapest, Hungary between 17 March and 22 April 2021. As a part of standard medical treatment, patients received anti-COVID-19 therapies as favipiravir, remdesivir, baricitinib or a combination of these drugs; and 110 of them received 20 mg fluoxetine capsules once daily as an adjuvant medication. Multivariable logistic regression was used to evaluate the association between fluoxetine use and mortality. For excluding a fluoxetine-selection bias potentially influencing our results, we compared baseline prognostic markers in the two groups treated versus not treated with fluoxetine. Out of the 269 participants, 205 (76.2%) survived and 64 (23.8%) died between days 2 and 28 after hospitalisation. Greater age (OR [95% CI] 1.08 [1.05–1.11], p<0.001), radiographic severity based on chest X-ray (OR [95% CI] 2.03 [1.27–3.25], p=0.003) and higher score of shortened National Early Warning Score (sNEWS) (OR [95% CI] 1.20 [1.01-1.43], p=0.04) were associated with higher mortality. Fluoxetine use was associated with an important (70%) decrease of mortality (OR [95% CI] 0.33 [0.16–0.68], p=0.002) compared to the non-fluoxetine group. Age, gender, LDH, CRP, and D-dimer levels, sNEWS, Chest X-ray score did not show statistical difference between the fluoxetine and non-fluoxetine groups supporting the reliability of our finding. Provisional to confirmation in randomised controlled studies, fluoxetine may be a potent treatment increasing the survival for COVID-19 pneumonia.

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[Risk of nonsteroidal antiinflammatory drugs. Focus on aceclofenac]

FARSANG Csaba

[Nonsteroidal antiinflammatory drugs (NSAIDs) are among the most frequently used pharmaceuticals. Nevertheless, a number of studies emphasized that NSAIDs were damaging not only the gastrointestinal (GI), but also the cardiovascular (CV) system, could increase the blood pressure, the frequency of coronary events (angina, myocardial infarction) and stroke incidence, as well as they might deterio­rate renal functions. The National Institute for Health and Care Excellence (NICE) did not find evidence that administering NSAIDs could increase the risk of developing COVID-19 or worsened the condition of COVID-19 patients. However, unwanted effects of specific drugs differ substantially in their occurrence and seriousness as well. It seemed to be for a long time that the NSAIDs provoked higher GI-risk was closely related to the COX1/COX2 selectivity, like the cardiovascular (CV) risk to the COX2/COX1 selectivity, however, the recent data did not prove it clearly. Based on the available literature while pondering the gastrointestinal and cardiovascular adverse events, among all NSAIDs the aceclofenac profile seemed to be the most favourable.]

Lege Artis Medicinae

[Second game, 37th move and Fourth game 78th move]

VOKÓ Zoltán

[What has Go to do with making clinical decisions? One of the greatest intellectual challenges of bedside medicine is making decisions under uncertainty. Besides the psychological traps of traditionally intuitive and heuristic medical decision making, lack of information, scarce resources and characteristics of doctor-patient relationship contribute equally to this uncertainty. Formal, mathematical model based analysis of decisions used widely in developing clinical guidelines and in health technology assessment provides a good tool in theoretical terms to avoid pitfalls of intuitive decision making. Nevertheless it can be hardly used in individual situations and most physicians dislike it as well. This method, however, has its own limitations, especially while tailoring individual decisions, under inclusion of potential lack of input data used for calculations, or its large imprecision, and the low capability of the current mathematical models to represent the full complexity and variability of processes in complex systems. Nevertheless, clinical decision support systems can be helpful in the individual decision making of physicians if they are well integrated in the health information systems, and do not break down the physicians’ autonomy of making decisions. Classical decision support systems are knowledge based and rely on system of rules and problem specific algorithms. They are utilized widely from health administration to image processing. The current information revolution created the so-called artificial intelligence by machine learning methods, i.e. machines can learn indeed. This new generation of artificial intelligence is not based on particular system of rules but on neuronal networks teaching themselves by huge databases and general learning algorithms. This type of artificial intelligence outperforms humans already in certain fields like chess, Go, or aerial combat. Its development is full of challenges and threats, while it presents a technological breakthrough, which cannot be stopped and will transform our world. Its development and application has already started also in the healthcare. Health professionals must participate in this development to steer it into the right direction. Lee Sedol, 18-times Go world champion retired three years after his historical defeat from AlphaGo artificial intelligence, be­cause “Even if I become the No. 1, there is an entity that cannot be defeated”. It is our great luck that we do not need to compete or defeat it, we must ensure instead that it would be safe and trustworthy, and in collaboration with humans this entity would make healthcare more effective and efficient. ]