{"id":27830,"date":"2025-08-30T13:57:52","date_gmt":"2025-08-30T08:12:52","guid":{"rendered":"https:\/\/www.revoscience.com\/en\/?p=27830"},"modified":"2025-08-30T13:57:56","modified_gmt":"2025-08-30T08:12:56","slug":"new-sepsis-diagnostic-could-reduce-critical-time-to-save-patients","status":"publish","type":"post","link":"https:\/\/www.revoscience.com\/en\/new-sepsis-diagnostic-could-reduce-critical-time-to-save-patients\/","title":{"rendered":"New sepsis diagnostic could reduce critical time to save patients"},"content":{"rendered":"\n
\"\"
KTH Professor Wouter van der Wijngaart (left) and PhD student\u00a0Henar Marino Miguelez.\u00a0IMAGE: David Callahan<\/sup><\/em><\/figcaption><\/figure>\n\n\n\n

A new diagnostic method would confirm sepsis infections earlier, cutting critical hours in the \u201crace against time\u201d to save patients\u2019 lives.<\/p>\n\n\n\n

Publishing in\u00a0Nature Publishing Journal Digital Medicine<\/a><\/em>, the team from KTH Royal Institute of Technology and Uppsala University say their diagnostic process offers a speedier alternative to the bacteria culturing process hospitals routinely use to identify suspected bloodstream infections.<\/p>\n\n\n\n

The process uses a centrifuge to separate bacteria from blood cells and automatic microscopy for detection, enabling a clinic to confirm bacterial infection in as little as two hours using software trained by artificial intelligence, says Henar Marino Miguelez, a doctoral student at KTH Royal Institute of Technology. She and doctoral student Mohammad Osaid were the study\u2019s lead authors.<\/p>\n\n\n\n

By contrast, hospital labs generally need at least a day of incubation before the growth of infectious bacteria begins to reveal itself in blood cultures.<\/p>\n\n\n\n

\u201cDiagnosing sepsis is a race against time,\u201d Marino Miguelez says. \u201cWith every hour of delayed treatment of patients in septic shock, survival rates drop by 8 percent.\u201d<\/p>\n\n\n\n

By enabling prompt identification of pathogens, the appropriate antibiotic treatment can be started sooner, says Wouter van der Wijngaart, a professor at KTH Royal Institute of Technology who leads research in microfluidic and biomedical systems.<\/p>\n\n\n\n

Typically, a clinic will put a patient on a broad-spectrum antibiotic when sepsis is suspected, at least until they identify the pathogen. But that precaution carries its own risks, due to the inherent drug toxicity, attacking beneficial gut bacteria, and promoting the emergence of antibiotic-resistant strains.<\/p>\n\n\n\n

\u201cIt takes a hospital two to four days before they are sure which antibiotic to treat a bloodstream infection with,\u201d van der Wijngaart says. \u201cWe\u2019re trying to do this in four to six hours.\u201d<\/p>\n\n\n\n

In tests using blood samples spiked with bacteria, the system successfully detected E. coli<\/em>, K. pneumoniae<\/em>, and E. faecalis<\/em> at clinically relevant levels, as low as 7 to 32 bacterial colony-forming units per milliliter of blood.<\/p>\n\n\n\n

While the method proved to work well with these bacteria, it did not for Staphylococcus aureus<\/em>, which hides in blood clots. Miguelez says the researchers are working on ways to fix that.<\/p>\n\n\n\n

The technique employs a \u201csmart centrifugation,\u201d which spins blood samples on top of an agent that causes bacteria to float upwards while blood cells sediment downwards, leading to a clear, liquid layer containing bacteria but no blood cells. This liquid is then injected into a chip with microscale channels, where it flows easily.<\/p>\n\n\n\n

Miniscule traps in the chip capture the separated bacteria, and any bacterial growth quickly becomes\u00a0<\/span>visible in automated time-lapse microscopy images analyzed by the machine learning software.<\/p>\n\n\n\n

The work was a collaboration between the teams of van der Wijngaart at KTH and Johan Elf and Carolina W\u00e4hlby at Uppsala University.<\/p>\n","protected":false},"excerpt":{"rendered":"

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