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Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score

COVIDSurg Collaborative
To support the global restart of elective surgery, data from an international prospective cohort study of 8492 patients (69 countries) was analysed using artificial intelligence (machine learning techniques) to develop a predictive score for mortality in surgical patients with SARS-CoV-2. We found that patient rather than operation factors were the best predictors and used these to create the COVIDsurg Mortality Score ( Our data demonstrates that it is safe to restart a wide range of surgical services for selected patients.
PMID: 34227657
ISSN: 1365-2168
CID: 5561492

Prevalence and distribution of soil-borne zoonotic pathogens in Lahore district of Pakistan

Shabbir, Muhammad Z; Jamil, Tariq; Ali, Asad A; Ahmad, Arfan; Naeem, Muhammad; Chaudhary, Muhammad H; Bilal, Muhammad; Ali, Muhammad A; Muhammad, Khushi; Yaqub, Tahir; Bano, Asghari; Mirza, Ali I; Shabbir, Muhammad A B; McVey, Walter R; Patel, Ketan; Francesconi, Stephen; Jayarao, Bhushan M; Rabbani, Masood
A multidisciplinary, collaborative project was conducted to determine the prevalence and distribution of soil-borne zoonotic pathogens in Lahore district of Pakistan and ascertain its Public Health Significance. Using a grid-based sampling strategy, soil samples (n = 145) were collected from villages (n = 29, 5 samples/village) and examined for Bacillus anthracis, Burkholderia mallei/pseudomallei, Coxiella burnetii, Francisella tularensis, and Yersinia pestis using real time PCR assays. Chemical analysis of soil samples was also performed on these samples. The relationship between soil composition and absence or presence of the pathogen, and seven risk factors was evaluated. DNA of B. anthracis (CapB), B. mallei/pseudomallei (chromosomal gene), C. burnetii (IS1111, transposase gene), and F. tularensis (lipoprotein/outer membrane protein) was detected in 9.6, 1.4, 4.8, and 13.1% of soil samples, respectively. None of the samples were positive for protective antigen plasmid (PA) of B. anthracis and Y. pestis (plasminogen activating factor, pPla gene). The prevalence of B. anthracis (CapB) was found to be associated with organic matter, magnesium (Mg), copper (Cu), chromium (Cr), manganese (Mn), cobalt (Co), cadmium (Cd), sodium (Na), ferrous (Fe), calcium (Ca), and potassium (K). Phosphorous (P) was found to be associated with prevalence of F. tularensis while it were Mg, Co, Na, Fe, Ca, and K for C. burnetii. The odds of detecting DNA of F. tularensis were 2.7, 4.1, and 2.7 higher when soil sample sites were >1 km from animal markets, >500 m from vehicular traffic roads and animal density of < 1000 animals, respectively. While the odds of detecting DNA of C. burnetii was 32, 11.8, and 5.9 higher when soil sample sites were >500 m from vehicular traffic roads, presence of ground cover and animal density of < 1000 animals, respectively. In conclusion, the distribution pattern of the soil-borne pathogens in and around the areas of Lahore district puts both human and animal populations at a high risk of exposure. Further studies are needed to explore the genetic nature and molecular diversity of prevailing pathogens together with their seroconversion in animals and humans.
PMID: 26441860
ISSN: 1664-302x
CID: 2038272

Pharmacologic stress testing: new methods and new agents

Hendel, Robert C; Jamil, Tariq; Glover, David K
PMID: 12673185
ISSN: 1071-3581
CID: 539322