Functional outcome of total hip arthroplasty in tubercular hip arthritis: A prospective study.

Background: Total hip arthroplasty (THA) is a well-established procedure to cure tubercular hip arthritis in patients with healed tuberculosis while its role in active tuberculosis is still debatable. The aim of the study is to investigate the functional outcomes of THA in active tuberculosis with advanced hip arthritis. The reactivation of tuberculosis and complications postoperatively has also been assessed. Materials and methods: The current open-ended prospective cohort study was carried out at a tertiary center from 2018 to 2020. Twenty patients of active tubercular hip arthritis (8 females and 12 males) were taken with a follow-up period ranging from 1 year to 3 years, with a mean of 14 months.Biochemical investigations were done both preoperatively and postoperatively. Preoperative anti-tubercular therapy (ATT) regimen was administered, as per standard norms, to patients for a minimum period of 6 weeks, and postoperatively for 6 months-12 months. Postero-lateral and Hardinge approaches were employed in all cases. Clinical and radiological parameters were assessed and functional outcomes were evaluated using the Harris Hip score (HHS). Results: The mean age of patients was 37.6 ± 11.38 years. Biochemical parameters were also found to improve postoperatively (p < 0.0001). The mean flexion, extension, abduction, external and internal rotation were found to increase postoperatively (p < 0.001). The mean flexion deformity in the preoperative period was 12.35 ± 4.716, whereas none of the patients had flexion deformities post operatively. The mean shortening was 2.12 ± 0.60 and 1 ± 0 at preoperative and postoperative respectively. The Total hip arthroplasty implant was found stable in all patients. The mean Harris score increased subsequently throughout the follow-up interval and differences were statistically significant (p < 0.0001). None of the patients had reactivation of tuberculosis infection postoperatively. Conclusion: Total hip arthroplasty is a reliable option to treat active advanced tubercular hip arthritis and gives good functional outcome with proper preoperative and postoperative ATT regimen.

Utility of itraconazole and terbinafine in mucormycosis: a proof-of-concept analysis.

An epidemic of mucormycosis followed the second wave of COVID 19 in the state of Uttar Pradesh, India in May 2021. This epidemic, however, had additional challenges to offer in the form of acute shortage of all forms of amphotericin B, posaconazole and isavuconazole. It was, therefore, planned to assess the trends in minimum inhibitory concentration (MIC) of antifungal agents, viz itraconazole and terbinafine, and provide a template for personalized therapy to see whether the results could be translated clinically. This is an observational, single-center study. Samples comprising nasal swab, nasal and paranasal sinus tissue, brain tissue, brain abscess and orbital content, derived from 322 patients from northern India with mucormycosis, of whom 215 were male and 107 were female, were used for analysis. Cultures were identified both by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) and conventional methods of identification. Antifungal susceptibility was done for amphotericin B, posaconazole, isavuconazole, itraconazole and terbinafine as per Clinical Laboratory Standard Institute M38-A2. The outcome was identification of the species of mucormycosis and susceptibility to itraconazole and terbinafine besides other primary antifungal agents. Patients or the public were not involved in the design, or conduct, or reporting or in the dissemination plans of our research. Of 322 patients, 203 were culture-positive, of whom 173 were positive by both MALDI-TOF and conventional methods of identification. Final antifungal susceptibility testing was available for 150 patients. The most common Mucorales found to cause this epidemic was Rhizopus oryzae, followed by R. microsporus Amphotericin B, posaconazole and isavuconazole had low MIC values in 98.8% of all Mucorales identified. The MIC of itraconazole was species-dependent. 97.7% of Roryzae had MIC ≤2 µg/mL. However, only 36.5% of Rmicrosporus had MIC ≤2 µg/mL. For terbinafine, 85.2% of R. microsporus had MIC ≤2 µg/mL. We conclude that identification at the species level is required as antifungal susceptibilities seem to be species-dependent. Assessment of the efficacy of itraconazole and terbinafine warrants further studies with clinical assessment and therapeutic drug monitoring as they seem to be potential candidates especially when the primary agents are not available.

Skill (or lack thereof) of data-model fusion techniques to provide an early warning signal for an approaching tipping point.

Many coupled human-natural systems have the potential to exhibit a highly nonlinear threshold response to external forcings resulting in fast transitions to undesirable states (such as eutrophication in a lake). Often, there are considerable uncertainties that make identifying the threshold challenging. Thus, rapid learning is critical for guiding management actions to avoid abrupt transitions. Here, we adopt the shallow lake problem as a test case to compare the performance of four common data assimilation schemes to predict an approaching transition. In order to demonstrate the complex interactions between management strategies and the ability of the data assimilation schemes to predict eutrophication, we also analyze our results across two different management strategies governing phosphorus emissions into the shallow lake. The compared data assimilation schemes are: ensemble Kalman filtering (EnKF), particle filtering (PF), pre-calibration (PC), and Markov Chain Monte Carlo (MCMC) estimation. While differing in their core assumptions, each data assimilation scheme is based on Bayes' theorem and updates prior beliefs about a system based on new information. For large computational investments, EnKF, PF and MCMC show similar skill in capturing the observed phosphorus in the lake (measured as expected root mean squared prediction error). EnKF, followed by PF, displays the highest learning rates at low computational cost, thus providing a more reliable signal of an impending transition. MCMC approaches the true probability of eutrophication only after a strong signal of an impending transition emerges from the observations. Overall, we find that learning rates are greatest near regions of abrupt transitions, posing a challenge to early learning and preemptive management of systems with such abrupt transitions.