Epidemiology of the 2022 Mpox Outbreak in the US Veterans Health Administration.

BACKGROUND: In May 2022, mpox cases were reported in nonendemic countries, including the United States. We examined mpox infections in the Veterans Health Administration (VHA). METHODS: Mpox diagnostic and whole genome sequencing (WGS) results, demographics, risk factors, hospitalizations, exposures, deaths, and pharmacy and immunization data were obtained from VHA data sources (23 May 2022-31 May 2023). RESULTS: Of 1144 Veterans tested, 251 (21.9%) were presumptive positive for nonvariola orthopoxvirus (NVO) or confirmed positive for NVO and Monkeypox virus (MPXV). Incidence rate was 7.5 per 100 000 Veterans in care, with the highest rate observed in Veterans aged 25-34 years (13.83 cases per 100 000). Higher odds of NVO or NVO/MPXV positivity was associated with male sex; non-Hispanic Black race/ethnicity; syphilis or human immunodeficiency virus (HIV) positivity; or genital/rectal sample site, whereas older age and vaccination with JYNNEOS or vaccinia (smallpox) had lower odds. Among 209 with confirmatory testing, 90.4% reported intimate contact and/or an epidemiological link, 84.5% were men who have sex with men (MSM), 24.2% received tecovirimat, and 8.1% were hospitalized with 1 death. Eighty-six sequenced samples had evaluable WGS results. All were clade IIb, representing 10 different lineages from 20 states and the District of Columbia. CONCLUSIONS: Mpox affected younger, MSM, non-Hispanic Black, and HIV/syphilis-positive men among US Veterans. Viral diversity was noted across geographic regions. At-risk Veterans would benefit from vaccination and risk reduction strategies for mpox and other sexually transmitted infections.

Automating HIV drug resistance genotyping with RECall, a freely accessible sequence analysis tool.

Genotypic HIV drug resistance testing is routinely used to guide clinical decisions. While genotyping methods can be standardized, a slow, labor-intensive, and subjective manual sequence interpretation step is required. We therefore performed external validation of our custom software RECall, a fully automated sequence analysis pipeline. HIV-1 drug resistance genotyping was performed on 981 clinical samples at the Stanford Diagnostic Virology Laboratory. Sequencing trace files were first interpreted manually by a laboratory technician and subsequently reanalyzed by RECall, without intervention. The relative performances of the two methods were assessed by determination of the concordance of nucleotide base calls, identification of key resistance-associated substitutions, and HIV drug resistance susceptibility scoring by the Stanford Sierra algorithm. RECall is freely available at http://pssm.cfenet.ubc.ca. In total, 875 of 981 sequences were analyzed by both human and RECall interpretation. RECall analysis required minimal hands-on time and resulted in a 25-fold improvement in processing speed (∼150 technician-hours versus ∼6 computation-hours). Excellent concordance was obtained between human and automated RECall interpretation (99.7% agreement for >1,000,000 bases compared). Nearly all discordances (99.4%) were due to nucleotide mixtures being called by one method but not the other. Similarly, 98.6% of key antiretroviral resistance-associated mutations observed were identified by both methods, resulting in 98.5% concordance of resistance susceptibility interpretations. This automated sequence analysis tool provides both standardization of analysis and a significant improvement in data workflow. The time-consuming, error-prone, and dreadfully boring manual sequence analysis step is replaced with a fully automated system without compromising the accuracy of reported HIV drug resistance data.

HIV-1 integrase sequence variability in antiretroviral naïve patients and in triple-class experienced patients subsequently treated with raltegravir.

Viruses were sequenced from 75 antiretroviral therapy (ARV)-naïve and from 75 ARV-treated patients who subsequently received a raltegravir-containing regimen. No major integrase inhibitor (INI)-resistance mutations were present in the 150 integrase (IN) sequences. Four ARV-naïve (5.3%) and two ARV-treated patients (2.7%) had one of the following minor INI-resistance mutations: L74M, E157Q, G163R, and R263K but there was no association between baseline raltegravir genotype and subsequent response to raltegravir treatment. We also combined our sequences with 4170 previously published group M IN sequences from INI-naïve patients to assess IN sequence variability and compared our findings with those of a study we performed in 2008 using data from 1563 patients. The number of polymorphic IN positions increased from 40% to 41% between the two studies. However, none of the major INI-resistance mutations was found to be polymorphic in either study and there were no significant changes in the prevalence of any of the minor INI-resistance mutations.

Can olanzapine cause delirium in the elderly?

OBJECTIVE: To report a case of delirium probably caused by the atypical antipsychotic olanzapine in a 74-year-old man with dementia. CASE SUMMARY: A 74-year-old white man with a diagnosis of severe dementia of mixed etiology with behavioral disturbances was admitted to an urban teaching hospital for increasing agitation in the context of worsening dementia. Olanzapine 2.5 mg each evening was started for agitation, and the dose was titrated to 5 mg each evening with additional emergent doses. Memantine, an N-methyl-D-aspartate antagonist, was increased from the admission dose of 10 mg/day to 15 mg/day. The patient developed symptoms of delirium on hospital day 4. Neuroleptic malignant syndrome and other causes of delirium were ruled out. Discontinuation of olanzapine resulted in resolution of the delirium. DISCUSSION: Antipsychotic medications are commonly used to treat symptoms of delirium. Atypical antipsychotics are better tolerated in the elderly because of their fewer adverse reactions compared with other antipsychotics. Olanzapine has been successfully used in the treatment of delirium. However, there have been case reports of delirium associated with olanzapine, probably related to its intrinsic anticholinergic effect. Application of the Naranjo probability scale indicated a probable relationship between the onset of delirium and the use of olanzapine in this patient. As of December 1, 2005, this was the second such report of a case in the elderly. CONCLUSIONS: Although olanzapine is useful in the treatment of delirium, elderly patients treated with this drug can develop delirium and hence should be closely monitored.

Sensitivity and specificity of the ViroSeq human immunodeficiency virus type 1 (HIV-1) genotyping system for detection of HIV-1 drug resistance mutations by use of an ABI PRISM 3100 genetic analyzer.

The ViroSeq human immunodeficiency virus type 1 (HIV-1) genotyping system is an integrated system for identification of drug resistance mutations in HIV-1 protease and reverse transcriptase (RT). Reagents are included for sample preparation, reverse transcription, PCR amplification, and sequencing. Software is provided to assemble and edit sequence data and to generate a drug resistance report. We determined the sensitivity and specificity of the ViroSeq system for mutation detection using an ABI PRISM 3100 genetic analyzer with a set of clinical samples and recombinant viruses. Twenty clinical plasma samples (viral loads, 1,800 to 10,500 copies/ml) were characterized by cloning and sequencing individual viral variants. Twelve recombinant-virus samples (viral loads, approximately 2,000 to 5,000 copies/ml) were also prepared. Eleven recombinant-virus samples contained drug resistance mutations as 40% mixtures. One recombinant-virus sample contained an insertion at codon 69 in RT (100% mutant). Plasma and recombinant-virus samples were analyzed using the ViroSeq system. Each sample was analyzed on three consecutive days at each of three testing laboratories. The sensitivity of mutation detection was 99.65% for the clinical plasma samples and 99.7% for the recombinant-virus preparations. The specificity of mutation detection was 99.95% for the clinical samples and 100% for the recombinant-virus mixtures. The base calling accuracy of the 3100 instrument was 99.91%. Mutations in clinical plasma samples and recombinant-virus samples were detected with high sensitivity and specificity, including mutations present as mixtures. This report supports the use of the ViroSeq system for identification of drug resistance mutations in HIV-1 protease and RT genes.